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Aligning educational resources and strategies to improve student learning: effective practices using an evidence-based model

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ALIGNING EDUCATIONAL RESOURCES AND STRATEGIES TO IMPROVE
STUDENT LEARNING:
EFFECTIVE PRACTICES USING AN EVIDENCE-BASED MODEL

by

Andrew Phillip Pulver

A Dissertation Presented to the
FACULTY OF THE USC ROSSIER SCHOOL OF EDUCATION
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF EDUCATION

May 2011

Copyright 2011 Andrew Phillip Pulver
ii

DEDICATION
“To mom and dad!”
This dissertation is dedicated to my loving and supportive mom and dad who continue to
watch over me from heaven above. I was fortunate to grow up in a loving, nurturing and
supportive family. As the thirteenth child of fifteen, I learned the value of hard work,
sacrifice, collaboration and diversity. My parents believed in education and the impact it
makes on the lives of individuals and society. Both my parents came from simple
beginnings, my father, the son of a small business owner and my mother growing up on
farm. Education and perseverance was the great equalizer for them as although they
struggled in grammar school, they both persevered and graduated college. My mother
graduated nursing school and my dad received both his bachelor’s and master’s degree
from Marquette after serving in the US Army. My parents instilled a strong sense of
integrity, honesty, compassion, charity and faith within all fifteen of their children and
taught us by example the value of commitment and a strong work ethic. Their labor of
love, sacrifice and service to others has made me the man I am today. This dissertation is
further dedicated to my fourteen brothers and sisters as they have always been both a
source of support and inspiration throughout my life. To Darwin for your patience and
support every step of the way along this incredible journey.

iii

ACKNOWLEDGEMENTS
I would like to thank my Dissertation Chair, Dr. Lawrence O. Picus, for his ongoing
support, feedback and encouragement throughout this process. Dr. Picus’ incredible
knowledge, positive attitude, and dedication to students greatly contributed to my success
in this program. I would also like to thank the other dissertation committee members, Dr.
Hentschke and Dr. Nelson for their guidance, encouragement and time. Five principals
graciously shared their time and participated in this study. Many thanks are in order for
them. In each case, I learned from a gracious school leader who was willing to share
both their successes and pitfalls to improve the level of education we provide our young
students. Thank you to my Superintendent, Dr. Gregory Franklin, for his constant
encouragement to join the USC family and pursue this doctoral program. It truly has been
life changing. Thank you Dr. Sherry Kropp, Assistant Superintendent of Educational
Services, for your constant support throughout this endeavor. Thank you to the incredible
staff, students and parents at Lee Elementary School for their unwavering support
throughout this journey. I have never worked alongside a more collaborative and
compassionate group of individuals who were passionate about using research to improve
student learning. Finally, I am so appreciative of my fellow graduate students with whom
I was fortunate to navigate the waters of USC. I have been blessed by the support and
life-long friendships made through this dynamic OC Cohort. I have learned much from
all of you and am thrilled to be part of such a dedicated and talented group of educators.
Your passion for excellence, compassion for students and dedication to improving
student learning is both infectious and inspiring!
iv

TABLE OF CONTENTS
Dedication ii

Acknowledgements iii

List of Tables vii

List of Figures ix

Abstract xii

Chapter 1 – Introduction 1
Background of the Problem 1
Federal Role in Education Funding and Accountability 4
Education Funding in California 5
Evolution of Equity to Adequacy 7
Student Achievement in California and Funding Resources 10
Beating the Odds 12
Statement of the Problem 14
Purpose of the Study 15
Importance of the Study 17
Research Design 18
Definitions 21

Chapter 2 – Literature Review 27
Overview of California Student Demographics, Achievement and Resources 28
California Educational Resource Allocation 36
Federal Resource Allocations Targeted to Improve Student Performance 48
Evolution of Educational Equity to Adequacy 59
Using Educational Resources More Effectively to Improve Student Performance 75
Evidence-Based Model 102
Summary 115

Chapter 3 – Methods 118
Research Questions 119
Design 119
Sample and Population 121
Data Collection 125
Case Studies 129
Ethical Considerations 130
Data Analysis 131

v

Chapter 4 – Results 133
School Demographics and Data 134
Key Elements & Themes of the Improvement Process 151
Change the curriculum program and create a new instructional vision 158
Formative assessments and data-based decision making 161
Comparison of School Resources to the Evidence-Based Model 176
Summary & Lessons Learned 189

Chapter 5 – Discussion 193
Summary of Findings 195
Lessons Learned 197
Limitations 204
Implications for Future Research 205
Conclusion 207

References 210

Appendices
Appendix A – IRB Approval 228
Appendix B – Quantitative Data Collection 229
Appendix C – Qualitative Data Collection 239
Appendix D – Pine Elementary 241
Background on School and District 241
Key Elements and Themes of the Improvement Process 246
Comparison of School Resources to the Evidence-Based Model 256
Summary and Lessons Learned 259
Future Considerations 261
Appendix E – Elm Elementary 263
Background on School and District 263
Key Elements and Themes of the Improvement Process 268
Comparison of School Resources to the Evidence-Based Model 282
Summary and Lessons Learned 285
Future Considerations 286
Appendix F – Orangewood Elementary 288
Background on School and District 288
Key Elements and Themes of the Improvement Process 293
Comparison of School Resources to the Evidence-Based Model 312
Summary and Lessons Learned 316
Future Considerations 318

vi

Appendix G – Greenwood Elementary 320
Background on School and District 320
Key Elements and Themes of the Improvement Process 325
Comparison of School Resources to the Evidence-Based Model 340
Summary and Lessons Learned 343
Future Considerations 345
Appendix H – Redwood Elementary 347
Background on School and District 347
Key Elements and Themes of the Improvement Process 351
Comparison of School Resources to the Evidence-Based Model 365
Summary and Lessons Learned 368
Future Considerations 370

vii

LIST OF TABLES
Table 2.1 California Public K-12 Student Demographic Population 4 Year Trend 29
Table 2. 2 U.S. Rankings of California 31
Table 2.3 Number of Schools in Program Improvement in California in 2009-2010 34
Table 2.4 County Tax Rates and School Expenditures Level Comparisons in 1968-69 38
Table 2.5: Instructional Strategies That Affect Student Achievement 93
Table 2.6: The Taxonomy Table (Taxonomy for Learning, Teaching & Assessing) 94
Table 2.7: Adequate Resources for a Prototypical Elementary School 106
Table 3.1: School Sample Demographics 122
Table 3.2: Academic Performance Index (API) Scores and Growth 123
Table 3.3 California State Rank and Similar Schools Rank (Scale of 1-10) 123
Table 3.4: AYP Percent Proficient and Advance and PI Status 2008-2010 124
Table 4.1: Summary of Case Studies Demographics, 2009-2010 136
Table 4.2 Similar School & Statewide Ranking of the Sample Schools 139
Table 4.3: Summary of Case Studies PI and API Status, 2010 AYP Report 141
Table 4.4: Summary of Case Studies ELA –Proficient & Above Trend 143
Table 4.5: School Sample Mathematics – Proficient & Above Trend 147
Table 4.6: Summary of Case Studies Performance of Evidence-Based Strategies 153
Table 4.7: Average Case Study EBM Resource Allocation Comparison 179
Table 4.8: Basic School Elements Performance of Evidence-Based Strategies 181
Table 4.9: Administrative Support Performance of Evidence-Based Strategies FTE 183
Table 4.10: General Personnel Resources of Evidence-Based Strategies FTE 185
viii

Table 4.11: Extended Support of Evidence-Based Strategies FTE 187
Table 4.12: Other Staffing Resources of Evidence-Based Strategies FTE 188
Table D.1: Pine Elementary Demographic Comparison 2009-10 241
Table D.2: Pine Elementary Evidence-Based Model Comparison 258
Table D.3: Pine Elementary Performance of Evidence-Based Strategies 261
Table E.1: Elm Elementary Demographic Comparison 2009-10 263
Table E.2: Elm Elementary Evidence-Based Model Comparison 284
Table E.3: Elm Elementary Performance of Evidence-Based Strategies 286
Table F.1: Orangewood Elementary Demographic Comparison 20009-10 288
Table F.2: Orangewood Elementary Evidence-Based Model Comparison 315
Table F.3: Orangewood Elementary Performance of Evidence-Based Strategies 318
Table G.1: Greenwood Elementary Demographic Comparison 2009-10 320
Table G.2: Greenwood Elementary Evidence-Based Model Comparison 342
Table G.3: Greenwood Elementary Performance of Evidence-Based Strategies 345
Table H.1: Redwood Elementary Demographic Comparison 2009-10 347
Table H.2: Redwood Elementary Evidence-Based Model Comparison 367
Table H.3: Redwood Elementary Performance of Evidence-Based Strategies 370

ix

LIST OF FIGURES
Figure 2.1 K-12 Enrollment for the 5 Largest States in the United States 2005-06 28
Figure 2.2 Percent Proficient or Advanced in ELA by Subgroups, 2008-09 32
Figure 2.3 Percent Proficient or Advanced in Math by Subgroups, 2008-09 33
Figure 2.4: California’s School Finance System 43
Figure 2.5: K-12 Proposition 98 Funding Fluctuation from 2007 to 2010 45
Figure 2.6: The Evidence Based Model 114
Figure 3.1: School Expenditure Structure and Resource Indicators 128
Figure 4.1: 2009-10 Case Studies Percent of Students by Significant Subgroup 137
Figure 4.2: Change in API of Sample Schools Between 2006-2010 138
Figure 4.3: Summary of Case Studies ELA – Proficient & Above Trend 143
Figure 4.4: Case Studies Hispanic Subgroup ELA –Proficient & Above Trend 145
Figure 4.5 Case Studies EL Subgroup ELA –Proficient & Above Trend 145
Figure 4.6: Case Studies SED Subgroup ELA –Proficient & Above Trend 146
Figure 4.7: Summary of Case Studies Mathematics – Proficient & Above Trend 148
Figure 4.8: Case Studies Hispanic Subgroup Math – Proficient & Above Trend 149
Figure 4.9: Case Studies EL Subgroup Math –Proficient & Above Trend 149
Figure 4.10: Case Studies SED Subgroup Math –Proficient & Above Trend 150
Figure 4.11: Case Studies Implementation: Understanding the Performance Challenge 155
Figure 4.12: Case Studies Implementation: Setting Ambitious Goals 157
Figure 4.13: Case Studies Implementation:Changing the Curriculum Program 160
Figure 4.14: Case Studies Implementation: Data-Based Decision Making 162
x

Figure 4.15: Case Studies Implementation: Professional Development 165
Figure 4.16: Case Studies Implementation: Using Time Efficiently and Effectively 168
Figure 4.17: Case Studies Implementation: Extended Learning 170
Figure 4.18: Case Studies Implementation: Collaborative and Distributed Leadership 173
Figure 4.19: Case Studies Implementation: Professional and Best Practices 176
Figure D.1 School Demographics Percentage for Pine Elementary 242
Figure D.2 Pine Elementary School’s Yearly API Trend 243
Figure D.3 Pine Elementary ELA - Percent Proficient or Above Trend 245
Figure D.4 Pine Elementary Math Percent Proficient or Above 246
Figure E.1 School Demographics Percentage for Elm Elementary 265
Figure E.2 Elm Elementary School’s Yearly API Trend 266
Figure E.3 Elm Elementary ELA - Percent Proficient or Above Trend 267
Figure E.4 Elm Elementary Math Percent Proficient or Above 268
Figure F.1 School Demographics Percentage for Orangewood Elementary 290
Figure F.2 Orangewood Elementary School’s Yearly API Trend 291
Figure F.3 Orangewood Elementary ELA - Percent Proficient or Above Trend 292
Figure F.4 Orangewood Elementary Math Percent Proficient or Above 293
Figure G.1 School Demographics Percentage for Greenwood Elementary 321
Figure G.2 Greenwood Elementary School’s Yearly API Trend 322
Figure G.3 Greenwood Elementary ELA - Percent Proficient or Above Trend 324
Figure G.4 Greenwood Elementary Math Percent Proficient or Above 324
Figure H.1 School Demographics Percentage for Redwood Elementary 349
xi

Figure H.2 Redwood Elementary School’s Yearly API Trend 349
Figure H.3 Redwood Elementary ELA - Percent Proficient or Above Trend 350
Figure H.4 Redwood Elementary Math Percent Proficient or Above 351

xii

ABSTRACT
This study analyzes effective research-based educational elements that have led to
improved student learning. Odden and Archibald (2009) outline ten core elements
successful schools and districts implement to dramatically improve student performance.
In addition to the framework and strategies outlined by Odden and Archibald (2009), the
Evidence-Based Model (Odden & Picus, 2008) of resource allocation was utilized to
examine the alignment between how schools use their allocated resources along with
research-based strategies to improve student performance. Case studies of five diverse
elementary schools include interviews and analysis of student performance data and
resource allocations. The findings were compared with a prototypical school using the
Evidence Based Model. Although each of the case study schools demonstrated the
application of all ten evidence-based strategies, many were not implemented to the level
and intensity research suggests is needed to make substantial gains in student
performance. The common theme interwoven throughout the most successful schools
was the sense of intense urgency and personal responsibility to improve student
proficiency for all students. The results of this study support the current research on the
effectiveness of setting lofty goals, providing targeted interventions and extended
learning opportunities for struggling students coupled with frequent progress monitoring,
and a commitment to improving student performance by improving instruction through
intense and ongoing professional development.

1
CHAPTER 1 – INTRODUCTION
Background of the Problem
The importance of education in America, American life and the prosperity of our
future cannot be understated. In an ideal setting, education is a great equalizer in society
and for many it is the key to experiencing the “American Dream.” The future of America
depends on America’s youth. Addressing the nation’s youth at the start of their 2009-10
school year, President Barak Obama reminded American K-12 students how what they
make of their education will “decide nothing less than the future of this country (Obama,
2009). President Obama, (2009) reiterated to students, “What you’re learning in school
today will determine whether we as a nation can meet our greatest challenges in the
future.”
For the better part of the twentieth century, the United States led the world in
providing education for all its citizens while the country garnered huge benefits from a
well-educated workforce (Hanushek & Lindseth, 2009). As a result, many Americans
have enjoyed a standard of living that is envious to many countries abroad. Currently, the
United States spends more money educating its children than most other developed
countries in the world. Yet, despite a massive financial commitment to K-12 education
over the past four decades, from both a federal and state level, our education system has
been failing us in important ways, especially when it comes to our nation’s poorest and
most vulnerable students (Hanushek & Rivkin, 1997; Hanushek & Lindseth, 2009;
Friedman, 2005).
2
Since the 1950’s, the United States public education system has been under closer
scrutiny and sparked ongoing public concern that continues unabated to this day. The
1954 ruling of Brown v. Board of Education of Topeka (1954) initiated the courts active
role in education with the desegregation of schools and raising awareness about the
disparity in educational performance of minority students in the nation’s public schools.
Soon after, the launch of Sputnik in 1957, acerbated the scrutiny causing the American
public to question the rigor and effectiveness of U.S. schools relative to other
industrialized nations (Gallimore & Golberg, 2001; Hanushek & Lindseth, 2009;
Marzano, 2003). From the time Brown started to take effect until about 1990, there was a
dramatic reduction in the gap between blacks and whites in educational attainment and
academic achievement (Neal, 2006; Raudenbush, 2009). However, by all credible
accounts, the process of convergence ended around 1990 (Raudenbush, 2009). By 1983,
the National Commission on Excellence in Education’s (1983) report titled A Nation at
Risk ignited the public’s outcry for improved student outcomes and set the stage for
improved educational reforms. Regrettably, not even the standards-based movement in
the 1990’s nor the current No Child Left Behind (NCLB) Act of 2002 have silenced the
public’s concern of American schools.
From 1960 to 2005, K-12 educational spending in the United States rose
significantly; adjusting for inflation, per pupil expenditures nearly quadrupled (Hanushek
& Lindseth, 2009). Hanushek and Lindseth (2009) assert that the problem is that we are
not getting much in return for our massive financial commitment. Since the late 1950s,
numerous federal and state education laws have been approved. Additionally, countless
3
reform measures have been initiated and a myriad of court cases have been rendered to
improve student outcomes and minimize the achievement gap among minority and white
students. While educational spending quadrupled over the past four decades, student
achievement in reading, math, and science has remained relatively flat with large
numbers of students performing at basic levels through the twelfth grade (Hanushek &
Lindseth, 2009). Consequently, U.S. students no longer lead the world and are no longer
as competitive when compared to their global counterparts (Friedman, 2005; Hanushek &
Lindseth, 2009; Loeb, Bryk, & Hanushek, 2007; Odden, Monk, Nakib & Picus, 1995;
Schneider, 2008; Stecher, Hamilton, and Gonzalez, 2003).
Friedman (2005) argues that the United States is in a slow but steady crisis. The
crisis is described as a quiet crisis as it involves the steady erosion of America’s
mathematical, scientific and engineering base. As the world becomes increasingly flat
with a global economy and technological advances, America will soon find itself falling
behind other countries in its capacity for scientific discovery, innovation and economic
development. The crisis is a national one, and the failure to find effective solutions
threatens not only individual well-being, but our country’s leadership in the global
community as well. The continued spotlight of accountability on public schools coupled
with a renewed sense of urgency to improve student performance for all students cannot
be dimed by the current fiscal constraints throughout the nation. Instead, the fiscal
constraints magnify the need to focus on effective allocations of resources to improve
student performance. This study analyzed resource allocation strategies in diverse schools
4
that were resulting in significant gains in student outcomes, compared with schools
whose student outcomes have dropped dramatically.
Federal Role in Education Funding and Accountability
In 1964, the Gardner Task Force laid the groundwork for federal investment in
public education and proposed the framework for Lyndon Johnson’s Elementary and
Secondary Education Act (ESEA) and Title I (Cross, 2004). The focus of this massive
federal funding was to provide aid to poor and disadvantaged students. The thought was
that by providing funds for impoverished students, student achievement would improve
and the achievement gap would narrow. By the end of the century more than 150 billion
dollars were spent on Title I, with little to show in terms of closing the achievement gap
(Cross, 2004 Hanushek & Lindseth, 2009). The passage of ESEA set the stage for further
federal involvement in public education and increased federal accountability, something
previously delegated primarily to each state. This shift ultimately led to President George
W. Bush’s 2002, reauthorization of ESEA under the No Child Left Behind Act (NCLB).
Federal and state education policies over the years have had profound impact on
America’s classrooms. In 2002, the federal government implemented NCLB. The
passage of NCLB occurred during a fertile period of time when outrage was growing
about the educational inequalities while a larger influence of global economic shifts
continued to demand a more educated and highly skilled workforce than school systems
were providing (Weiss, 2007). NCLB sought to hold states, local education agencies
(LEAs), and individual schools accountable for ensuring all students are proficient in
English Language Arts (ELA) and mathematics by 2014. NCLB measures growth in
5
school performance against fixed standards, all in hope to help narrow the achievement
discrepancies between whites and various minority or underrepresented groups
(Edsource, 2008). Weiss (2007) describes how NCLB dramatically changed federal
educational funding metrics as it shifted the focus from inputs (number of students
served, dollars spent per pupil, number of certified teachers) to outcomes (student
achievement levels, value added by teachers, cost to achieve proficiency). In addition, it
disaggregated outcome metrics by district, school, grade level, and subject, making
transparent both the inputs and outputs occurring inside classrooms (Weiss, 2007). NCLB
coupled with state standards and accountability systems have harnessed momentum
around improving outcomes for all students, especially those who in the past have
traditionally been underserved. Despite the momentum to improve student outcomes for
all students, one of the biggest complaints against NCLB is its failure to provide the
necessary funding to adequately secure the desired performance results.
Education Funding in California
In addition to laws and inducements directed by the federal government, public
education funding in California has been impacted by a variety of state legislative
reforms, laws and court rulings. Over the past 40 years, a combination of court rulings,
legislative enactments and voter initiatives have made profound changes in the landscape
of educational finance and governance (Timar, 2004, 2004). The landmark California
Supreme Court ruling Serrano v. Priest (1971, 1976) required the state to “equalize”
funding among districts from property tax (Odden & Picus, 2008; Timar, 2006, 2004;
Edsource, 2000). The Serrano case highlighted that “low wealth” districts taxed
6
themselves at higher rates compared to “high wealth” districts in order to generate
revenue to support educational needs. The court’s ruling in Serrano found that wealth
related disparities were unconstitutional. Responding to the Serrano court decision,
Assembly Bill 65 of 1977, attempted to equalize revenue limits for districts by adjusting
for inflation overtime.
Proposition 13 passed in 1978, addressed the tax inequalities in the Serrano case
by attempting to end further disparities of the unequal share of property tax revenue that
school districts receive from local property tax (Edsource, 2000). Proposition 13 capped
the property tax rate at 1% for all homeowners resulting in a dramatic reduction in
property tax dollars and reducing the amount of property taxes available for local district
control (Edsource, 2000; Timar, 2006, 2004). According to Timar (2004), Proposition
13’s main feature shifted school finance decision making from districts to the state.
Proposition 13 dramatically altered the effect local districts and municipalities had on
educational funding and revenues (Kirst, 2006; Loeb et al., 2007; Picus, 2006). This shift
put California education funding at the whim of economic cycles that are much less
stable over time, cycles that swing from deficit spending to accumulating large reserves.
In an effort to stabilize education funding in California, voters approved in 1988,
Proposition 98. Proposition 98 resulted in minimum state funding levels for K-12 and
community colleges by constitutionally protecting a portion of the state budget
(Edsource, 2000; Odden & Picus, 2008; PACE, 2006; Timar, 2006, 2004). Timar (2004)
argues that while Proposition 98 guarantees 40% of the state’s general revenue are
apportioned to K-12 districts and community colleges, its major impact has been to use
7
the state budget as a policy tool. Since policy makers know that 40% of general revenue
dollars must be spent on K-12 and community colleges and because they do not know
how much money will be available for the following year’s budget, there is often a last
minute rush to spend money on measures policymakers want more direct control over
(Timar, 2006, 2004).
According to Timar (2004), rather than putting money into general revenues for
schools, policymakers increasingly target funds for special purposes in the form of
categorical grants. Since the passage of Proposition 98, the growth rate of categorical
programs expanded exponentially. Although a number of bills and measures passed in
California have attempted to reduce the inequities among districts, high wealth districts
are still able to generate a higher amount of revenue (PACE, 2006; Timar, 2006, 2004).
The inequity among students in different districts, especially among California’s most
vulnerable students, still persists and the funding for most students in California
continues to be far from adequate.
Evolution of Equity to Adequacy
Over the past two decades, the focus on education funding has evolved from
equity to adequacy (Odden, 2003; Odden & Picus, 2008: Rebell, 2007). Various court
cases like Brown (1954), Serrano (1971) and others have focused largely on the equitable
distribution of funding, yet failed to address the issue of equitable student performance
outcomes (Clune, 1994; Odden 2003; Hanushek & Lindseth, 2009). Overtime, concern
evolved from fiscal equity differences to differences in student achievement between
high socio-economic status (SES) students and those living in low SES. The failure to
8
diminish the achievement gap across the nation led to further lawsuits sprouting up across
federal and state courtrooms, asserting the education finance systems were
unconstitutional (Hanushek & Lindseth, 2009). Rebell (2007) states that nearly seventy-
five percent of these lawsuits were successful because courts found that states failed to
identify the necessary cost associated to adequately educate all students to a similar
performance target.
The equity based funding model attempts to ensure all students receive the same
amount of resources to support student leaning. According to Hanushek and Lindseth
(2009), proponents of equity cases assumed equalization would occur simply by
narrowing the disparity gap between low-SES and high-SES districts. However, equity
based methods did not always narrow the disparity gap and in some cases further
aggravated the inequity problem (Evers & Clopton, 2006; Hanushek, 1996; McNeil,
2010; Rebell, Wolff, & Yaverbaum, 2010; Timar, 1996, 2004). Meanwhile, the
adequacy model of funding sets out to determine the level of resources for students based
on their individual needs and the amount of resources necessary for them to achieve an
agreed upon performance benchmark (Hanushek & Lindseth, 2009; Odden, 2003, Rebell,
2007). The court cases were extremely successful because close scrutiny of states
education finance systems uncovered that few states attempted to determine objectively
the amount of resources required to meet desired learning requirements (Rebell, 2007).
The standards-based reform movement has been a critical focus of education
policy for over 20 years. Standards-based education reform seeks to educate all students
to high levels of achievement and clearly identifies target benchmarks for student
9
performance. Implied in this goal is both an element of equity and excellence (Odden,
2003). According to Odden, (2003) the goal is outcome oriented (student performance)
and focuses on the results of the education system as a whole by dramatically diminishing
the “achievement gap.” As school accountability shifted focus to student performance
outcomes, school finance litigation began to evolve from equity to adequacy models
(Clune, 1994; Odden, 2003; Hanushek & Lindseth, 2009; Odden & Picus, 2008; Rebell,
2007). The outcomes of various adequacy cases have led to four main approaches in
resolving educational adequacy concerns within states’ constitutions that guarantee an
adequate education to all students.
Four main approaches have emerged to determine an adequate funding level. All
four adequacy approaches seek to determine the level of funding necessary to produce
benchmark proficiency standards for all students. While all four approaches have levels
of merit, they have also been subject to scrutiny and criticism which will be further
addressed in the next chapter (Hanushek & Lindseth, 2009; PACE, 2006; Rebell, 2007).
Currently, no single approach is dominant throughout the country. Each approach
outlined can produce varying dollar amounts and often produce substantial increases to
funding beyond current educational funding levels (Odden, 2003). The following are
brief explanations of these four adequacy approaches (Odden, 2003; Hanushek &
Lindseth, 2009; Odden & Picus, 2008; Rebell, 2007).
1) Successful District Model: This model identifies successful school districts, as defined
by student test scores, that are meeting standards and uses their cost as an estimate of
adequacy.
10
2) Cost Function Model: This approach relies on current spending and achievement
patterns across all schools in a state to predict optimum spending solutions. The cost
function model uses advanced statistical techniques like regression analysis, to determine
what resources are required for students to reach a certain performance level.
3) Professional Judgment Model: In this approach, a group of educational experts
(teachers, principals, superintendents and others) identify effective educational strategies
for a particular level and then determine the adequate expenditure for students based on
effective educational strategies.
4) Evidence Based Model: This model identifies a comprehensive set of school-level
elements identified through empirical research that are necessary to deliver a high-quality
comprehensive instructional program. After the research-based elements are identified,
this model determines an adequate expenditure level by assigning a price to each element
and aggregating it to a total cost. The evidence based approach employs current
educational research to determine what resources are needed to reach proficiency.
Student Achievement in California and Funding Resources
Despite the development of challenging education standards and sustained
attention to school improvement over the past ten years, California continues to lag
behind its counterparts on various measures of student achievement (Loeb et al., 2007).
The 2007 National Assessment of Education Progress (NEAP) reflects California fourth
grade students 48
th
in reading and 47
th
in math compared to students from all fifty states.
Student achievement in 8
th
grade is equally alarming; California ranked 7
th
lowest in
eighth grade math (Loeb et al., 2007; NCES, 2009c). As students move to high school,
11
the grim story continues. California’s graduation rate is now below 70% and only 52% of
California schools met NCLB’s AYP requirement in 2008 (Edsource, 2009d). Significant
progress will require fundamental and comprehensive change throughout the system.
Despite being one of the largest economies in the world, California has
historically lagged behind many other states in terms of educational funding. Between
1996 and 2008, California ranked anywhere between thirty-sixth and forty-first in per-
pupil spending, while continually ranking below the national average (EdData, 2008,
Edsource, 2010b; Loeb et al., 2007). While California continues to fund education below
the national average, it is responsible for educating some of the largest percent of
minority, EL and low-SES students, most of which require additional educational
resources to help them meet proficiency standards (Loeb et al., 2007; Hanushek, 2006a;
Picus, 2006, Odden, 2009; Odden & Picus, 2008). Compounding the funding problem is
the fact that California’s cost are higher than those in most other states primarily due to
the higher wages of a college-educated labor force (Loeb et al., 2007; PACE, 2006;
Timar, 2004). The lower spending in California is reflected in a high student-to-staff
ratio, including fewer teachers and administrators per pupil (Loeb et al., 2007; PACE,
2006).
The low achievement of California’s students will likely hurt their economic
outcomes later in life and be detrimental to the state as a whole (Loeb et al., 2007). There
is growing evidence that educational quality, measured by proficiency in test scores, is
highly related to economic growth and directly related to future individual earnings
(Brewer, Hentschke, & Eide, 2008; Hanushek & Lindseth, 2009; Loeb et al., 2007). In a
12
global knowledge economy, the economic growth of regions and nations is often affected
by the skills of its workers, which in turn are directly related to student learning outcomes
(Brewer et al., 2008; Loeb et al., 2007).
As increased educational funding in the near future appears dismissal, the focus
should shift on how successful schools are demonstrating academic growth by aligning
research and best practices to the allocation of scarce fiscal resources. California school
demographics are changing with increasing minority, EL and low income students
entering the system who often require additional resources to help them attain
proficiency. School administrators and district staff must decide how to allocate resources
to serve a diverse student population with a broad range of needs. Often, these needs
compete against each other for the equity of resources allocated. In times of limited
resources and fiscal constraints, utilizing an effective resource allocation model that is
supported by research and connected to improved student outcomes is imperative.
Beating the Odds
Many schools with similar student populations and resources have been
successful in closing the achievement gap and improving overall student performance
(Odden, 2009; Odden & Archibald, 2009; Reeves, 2000; Marzano, 2003; Perez, Parish,
Anand, Speroni, Esra, Socias, et al., 2007; Williams, Kirst, Haertel et al., 2005). Williams
et al. (2005) conducted a comprehensive study on California elementary schools serving
similar student populations with a majority of low socio-economically disadvantaged
(SED) students coupled with a significant percentage of English Learners. The study
suggests successful schools serving these populations are incorporating a variety of
13
educational strategies that are fostering the academic success of their students. Strategies
employed include: adopting new curriculum text series, using assessment data,
implementing standards-based curriculum and implementing effective professional
development opportunities for staff. A similar study by Perez et al., (2007) indicates
many “beating the odds” schools perform better than their peers while allocating similar
levels of spending. “Beating the odds” schools employed high quality teachers who were
responsible and accountable for the content their students learned. In addition, these
schools implemented increased: staff development, interventions for struggling students
during the school day, and teacher collaboration (Perez et al., 2007). Finally, these
“beating the odds” schools had stronger and more experienced site administrators while
also having significantly lower ratios of tenured teachers than low performing schools
(Perez et al., 2007).
Reeves, (2000) coined the phrase “90/90/90” schools. In his work, he identified
schools where 90% of the students were eligible for free and reduced lunch, 90% of the
students were from ethnic minorities and 90% of the school’s population was achieving
high academic standards. Reeves (2000) found the following common characteristics
within the “90/90/90 schools:
• A focus on academic achievement
• Clear curriculum choices
• Frequent assessment of student progress and multiple opportunities for
improvement
• An emphasis on nonfiction writing
• Collaborative scoring of student work
Marzano (2003) highlights the importance and integration of school-level, student-level
and teacher-level factors that lead to improved student outcomes, especially for low
14
performing students and schools. There is a wealth of research that expresses how under-
performing students and under-performing schools have beaten the odds and improved
student outcomes to high academic levels (Odden, 2009; Odden & Archibald, 2009;
Reeves, 2000; Perez et al., 2007; Williams et al., 2005). However, there is a need for
further research in the area of how school-site resource allocation strategies are employed
to improve student academic proficiency.
Statement of the Problem
The future of America depends on America’s educated youth. What American
students learn in school today will decide whether we as a nation can meet our greatest
challenges tomorrow (Obama, 2009). Since the late 1950’s numerous federal and state
education laws have been approved, countless reform measures have been initiated and a
myriad of court cases have been rendered to improve student outcomes and minimize the
achievement gap among minority and white students. Increases in educational funding
were necessary to connect these reform efforts with the desired student performance
outcomes. Despite a massive financial investment to K-12 education over the past four
decades, from both a federal and state level, student achievement has remained relatively
flat (Hanushek & Rivkin, 1997; Hanushek & Lindseth, 2009). Consequently, American
students no longer lead the world and are less competitive when compared to their global
counterparts (Friedman, 2005; Hanushek & Lindseth, 2009; Loeb et al., 2007; Odden et
al., 1995; Schneider, 2008; Stecher et al., 2003). As the world becomes increasingly more
flat with a global economy and technological advances, America will soon find itself
15
falling behind other countries in its capacity for scientific discovery, innovation and
economic development (Friedman, 2005; Slavin, 2005).
School sites must address the challenge of adequately educating an increasingly
diverse student population with fewer resources and less decision rights on how to
effectively allocate resources to improve student outcomes. The evolution of educational
funding from equity to adequacy has propelled policymakers and public schools to
identify what encompasses an adequate education and how to secure it for all students.
The continued spotlight of accountability on public schools coupled with a renewed sense
of urgency to improve student performance for all students must not be dimed by the
current fiscal constraints throughout the nation. Instead, the fiscal constraints magnify the
need to focus on effective allocations of resources to improve student performance
effectively and efficiently. Schools must be strategic in how educational resources are
allocated to ensure improved student achievement. While research on the implementation
of various adequacy models have been performed in various states, site level adequacy
research is limited (Hartman, Bolton, & Monk, 2001). Research on how schools align and
allocate diminishing resources without diminishing returns is imperative.
Purpose of the Study
The purpose of this study was to analyze site level resource allocation strategies
in diverse schools that were resulting in significant growth in their Academic
Performance Index (API), compared with schools who’s API dropped dramatically. The
conceptual frameworks for this study was by Odden (2009) and Odden and Archibald’s
(2009) work on doubling student performance as well the Evidence-Based Model (Odden
16
& Picus, 2008) dealing with research based strategies for school improvement. Six
elementary schools in Southern California were selected to participate in this study based
upon similar student demographics. All six schools had a student population of at least
60% SED, 50% Hispanic, and 40% EL students who either significantly improved their
2009 API score by forty or more points or experienced a dramatic drop in their 2009 API
score by at least 17 points. School level analysis resulted from this study contributes to
the discussion on how an evidence-based adequacy model can help identify effective
educational strategies for improving our schools. Data collection and analysis provides
educational practitioners, policymakers and the academic community with an expanded
knowledge base on school level resource allocations and which allocation patterns, if any,
have implications for improved student outcomes.
Research Questions. The following research questions were used to guide this
study:
1. What are the current instructional vision and improvement strategies at the
school level?
2. How are resources at the school and district used to implement the school’s
instructional improvement plan?
3. How did the allocation and use of resources at the school change in response
to the recent budget adjustments including overall funding reductions and
changes in the use of categorical funds?
17
4. How are the actual resource use patterns at the school sites aligned with or
different from the resource use strategies used in Odden and Picus’ (2008)
Evidence-Based Model?
Importance of the Study
There is growing evidence that educational quality, measured by proficiency in
test scores, is highly related to economic growth and directly related to future individual
earnings (Hanushek & Lindseth, 2009; Loeb et al., 2007;). California continues to lag
behind its counterparts on various measures of student achievement and ranks among the
worst on the NAEP in the United States (Loeb et al., 2007; Edsource, 2007, 2008, 2009b,
2009c). The low achievement of California’s students will likely hurt their economic
outcomes later in life and be detrimental to the state as a whole (Loeb et al., 2007).
Despite being one of the largest economies in the world, California continues to fund
education below the national average. California schools have been hit with substantial
budget reductions over the past few years and are facing additional budget reductions
which will directly impact services and programs.
Educating a massive, diverse student population like California makes the
allocation of resources a daunting task especially in times of unprecedented budget
reductions. As educational leaders are faced with the overwhelming responsibility to
determine which services and programs should be cut while re-aligning remaining
resources to continue to meet the demands of improved student performance, successful
resource allocation strategies that improve student learning must be identified.
Understanding how resources are allocated at the school level to successfully improve the
18
achievement of all students, while simultaneously narrowing the achievement gap, is
critical. However, this skill and vision is often lacking at the school site.
In times of limited resources and fiscal constraints, utilizing an effective resource
allocation model that is supported by research and connected to improved student
outcomes is imperative. Although similar schools within the same school district often
receive the same amount of funding, student achievement can vary greatly (EdSource,
2007). Some schools effectively raise the achievement levels while others do not. Many
schools with similar student populations and resources have been successful in closing
the achievement gap and improving overall student performance (Odden, 2009; Odden &
Archibald, 2009; Reeves, 2000; Marzano, 2003; Perez, et al., 2007; Williams, et al.,
2005). Using the Evidence Based Model developed by Odden and Picus (2008) provides
local educators and state policymakers within California greater insight of how
disadvantaged schools can utilize their resources effectively to beat the odds and promote
change. Conducting analysis on how successful schools are demonstrating academic
growth by aligning research and best practices to the allocation of scarce fiscal resources
contributes further to the academic literature on educational adequacy and resource
allocation.
Research Design
The research design implemented to investigate the research questions above
utilized a multiple methods design incorporating a combination of both quantitative and
qualitative forms of data (Patton, 2002). The study examined the resource allocation
practices at the school level to support student achievement. Data was obtained from
19
DataQuest (California Department of Education, 2010) in order to identify six elementary
schools within Orange County that during the 2009 assessment year were identified as
either significantly improving student learning through a significant gain in their API
score or experienced a dramatic decline in student achievement outcomes through a
significant drop in their API score. A purposeful sample of the elementary schools
ensured the student populations of the six elementary schools included at least 60% SED,
50% Hispanic, and 40% EL students. Utilizing the evidence-Based Model (Odden &
Picus, 2008) primarily as a quantitative framework and Odden (2009) and Odden and
Archibald’s (2009) work on doubling student performance for the qualitative framework
for comparison, case studies of each school were analyzed (See Appendices D-H). Cross-
case comparisons provide comparisons of effective and ineffective school level resource
allocation models that can be gleaned for future implementation at other schools. Due to
the studies multiple methods approach and use of interviews as primary source data, this
study relied upon the honesty of the participants to portray an accurate depiction of
resource allocation and educational strategies being implemented at the individual school
level. Furthermore, the findings of this study assume there will not be an increase in state
or federal funding in the near future. Based on these assumptions, there were five
limitations and four delimitations indentified with this study.
Limitations. Comparing the school level resource allocation practices of six
elementary schools in Southern California to the Evidence-Based Model has several
limitations. Due to the small sample size of the study, the findings cannot be generalized
to many other schools or student populations. While the methodology used was a
20
multiple methods approach, the schools chosen for this study were not randomly selected.
Second, the study relied on selection criteria and events that occurred 14 months prior to
the implementation of data collection. Thus, it is difficult to assess if success growth in
API was due to the allocation models being described by site level administration, or
other factors beyond the schools’ control. Third, due to individual district policies
restricting research access coupled with site level principal’s willingness to participate in
the study, not all of the elementary schools the met the original selection criteria within
Orange County were studied. Fourth, both the Evidence-Based Model (Odden & Picus,
2008) and the Ten Strategies for Doubling Student Performance (Odden, 2009; Odden &
Archibald, 2009) framework used for this study assumes site level control of resource
allocation and freedom to implement identified educational strategies. However, due to
variation of district centralization and control regarding funding resources, what may
have actually been studied was district level allocation of resources as opposed to school
site level as intended. Finally, the American Recovery and Reinvestment Act (ARRA)
was enacted in February 2009. School districts across the nation received one-time
additional federal funding that will be required to be spent by June 30, 2010. The
outcome of this study may be skewed as a result of the various ways in which districts
and schools allocate the additional one-time funds.
Delimitations. Given the limitations described above, the following systematic
investigations did not commence as part of this research study. Given the limited
resources of the researcher, a sample size was not selected outside the Orange County
area. Second, the study was directed to the elementary school level within Orange County
21
of schools who during the 2009 assessment year were identified as either significantly
improving student learning through a significant gain in their API score or experienced a
decline in student achievement outcomes through a significant drop in their API score.
Six of those elementary schools were selected based on the following similar student
demographics: 1) at least 60% SED student population; 2) at least 50% Hispanic
population; and 3) at least 40% identified as EL. Third, the study focused on school level
resource allocation for the 2009-2010 school year only. Lastly, no analysis was
performed to verify if the growth or decline demonstrated by the schools were
significantly significant when compared to similar schools within California.
Definitions
1. Academic Performance Index (API): A number designated by California
Department of Education (2009b) that ranges from 200 to 1000 and is calculated
from student results on statewide assessments. California has set a target score of
800 for all schools to meet, and those that do not achieve a score of 800 are
required to meet annual growth targets set forth by the state.
2. Achievement Gap: A difference in scores on student achievement tests between
groups of students.
3. Add-ons: A funding source that is typically considered as adding to the LEA’s
general purpose revenue outside of local property taxes and state aid (Timar,
2006).
4. Adequacy: Framed and interpreted within each individual state constitution,
adequate educational funding is defined as the level of funding that would allow
22
each LEA to provide a range of instructional strategies and educational programs
so that each student is afforded an equal opportunity to achieve to the state’s
education performance standards (Odden & Archibald, 2009; Odden & Picus,
2008).
5. Adequate Yearly Progress (AYP): A report required by the federal No Child Left
Behind (NCLB) Act of 2002 and is used to measure how well individual schools
and districts are doing in meeting the following requirements: (a) student
participation rates on statewide tests; (b) percentage of students scoring at the
proficient level or above in English-language arts and mathematics on statewide
tests; (c) in California only, API growth; and (d) graduation rate (California
Department of Education, 2009b).
6. American Recovery and Reinvestment Act (ARRA): The federal stimulus
package enacted by the U.S. Congress and President Obama in March, 2009 that
allocated additional, one-time funds to school districts across the United States.
The act provided more than $100 billion for prekindergarten through 12th grade
schools nationwide, and nearly $8 billion for California. It was a one-time
infusion for the 2008-09 and 2009-10 school years (Edsource, 2010a)
7. Average Daily Attendance (ADA): The number of students present on each
school day throughout the year, divided by the total number of school days in a
year (Edsource, 2010a)
8. Base Revenue Limits: Is the amount of general purpose funding per ADA that a
LEA receives in state aid and local property taxes to pay for the basic cost of
23
educating a student regardless of special classifications or categories (EdSource,
2009a). In California the base revenue limit equals the state aid to the LEA + local
property tax collected by the LEA (Timar, 2006).
9. California Standards Tests (CSTs): A series of tests that measure student’s
achievement of California’s content standards in the areas of English-language
arts, mathematics, science, and history-social sciences (California Department of
Education, 2009a).
10. Categorical Funding: Funds that are targeted to support specific groups and/or
class of students, such as students with special needs, low-income, or English
learners. There are four types of categorically funded programs: entitlement,
incentive, discretionary grants, and mandated cost reimbursement (Timar, 2006).
11. Economic Impact Aid (EIA) Funds: California state categorical funds made
available to school districts to support the education of low income students and
those learning English (Edsource, 2010a).
12. English Learner (EL): Indicates a person who has a first language other than
English and is in the process of acquiring English.
13. Equity: Within education, the term is used to measure (1) horizontal equity, or the
equal access of education from individual to individual; and (2) vertical equity, or
the appropriate treatment of each individual based on their unique needs (Bhatt &
Wraight, 2009).
14. Evidence Based Model (EBM): An educational funding approach based on
identifying individual, school-based programs and educational strategies that
24
research has shown to improve student learning (Odden & Archibald, 2009;
Odden & Picus, 2008).
15. Excess Taxes: Considered an add-on in California, LEAs are allowed to keep any
excess taxes that they generate beyond their revenue limits and is calculated by
determining the difference between a LEAs revenue limit and property tax
revenues (Timar, 2006).
16. Expenditures: For elementary and secondary schools, all charges incurred , both
paid and unpaid and debt, applied to the current fiscal year (National Center for
Edcuation Statistics, 2010a). Expenditures types include current expenditures,
instructional expenditures, and expenditures per student.
17. Fulltime Equivalent (FTE): The ratio derived by dividing the number of work
hours required in a part-time position by the number of work hours required in a
corresponding full-time position.
18. General Fund: Federal and state funds that are non-categorical and not restricted
or required to be spent on specific student populations or programs.
19. General Purpose Funding: In California, general purpose funding equals the base
revenue limits + revenue limit add-ons + excess local property taxes (Timar,
2006).
20. Local Education Agency (LEA): An educational agency at the local governmental
level that operates schools or contracts for educational services. LEAs can be as
small as single school districts and as large as county offices of education.
25
21. Program Improvement (PI): A formal designation required under NCLB (2002)
for Title I funded LEAs and schools that fail to make AYP for two consecutive
years (California Department of Education, 2009c). While a LEA or school is
under PI status, they are obligated to implement certain federal and state
requirements.
22. Significant Subgroups: Each significant subgroup within a school must make
AYP. For purposes of participation rate, a subgroup is considered numerically
significant if 100 or more students are enrolled on the first day or testing or if 50
or more students enrolled on the first day of testing make up at least 15 percent of
the total population. For purposes of percent proficient, a subgroup is considered
numerically significant if there are 100 or more students with valid scores or if
there are 50 or more students with valid scores who make up at least 15 percent of
the total valid scores (California Department of Education, 2009d).
23. Similar Schools Rank: The similar schools rank indicates the decile rank of a
school’s API compared with the API scores of 100 other schools with similar
demographic characteristics. The similar schools ranks allow schools to look at
their academic performance compared to other schools with similar student
populations (California Department of Education, 2009e).
24. Socio-economic Status (SES): A measure of an individual or family's relative
economic and social ranking (National Center for Edcuation Statistics, 2010a)
26
25. Title I: A federal program that provides financial assistance to LEAs and schools
with high numbers and percentages of poor children in order to help all children
meet state adopted academic standards (U.S. Department of Education, 2010).

27
CHAPTER 2 – LITERATURE REVIEW
Providing an adequate education and connecting it with a funding structure that
supports all students reaching academic proficiency has been an enduring goal of
educators (Odden & Picus, 2008). California school demographics are changing with
increasing minority, EL and low income students entering the system who often require
additional resources to help them attain proficiency (Loeb et al., 2007; Hanushek, 2006a;
Picus, 2006, Odden, 2009; Odden & Picus, 2008). School administrators and district staff
must decide how to allocate resources to serve a diverse student population with a broad
range of needs. Often, these needs compete against each other for the equity of resources
allocated. Understanding how resources are allocated at the school level to successfully
improve the achievement level of all students, while simultaneously narrowing the
achievement gap, is critical. However, this skill and vision is often lacking at the school
site. Determining the allocation of resources based on student needs at the school level
involves issues of equity and adequacy. This chapter will seek to provide further insight
into how resources may be utilized by aligning them with evidence-based strategies
shown to be effective for improving student achievement. The literature will be
synthesized and organized by the following six sections: (1) overview of California
student demographics, achievement and resources, (2) educational resource allocation
within California, (3) federal resource allocations targeted to improve student
performance, (4) evolution of educational equity and adequacy (5) evidence-based
strategies for using educational resources more effectively, and (6) the use of an
evidence-based model to guide effective resource use.
28
Overview of California Student Demographics, Achievement and Resources
California serves over 6.2 million students, the largest K-12 student population in
the nation. As seen in Figure 2.1, comparing California’s student population with the
country’s four other most populous states underscores it size (Edsource, 2008). California
has nearly 2 million more students than Texas, the next largest state and 1.4 million more
students than both New York and Florida combined (Edsource, 2008).
Figure 2.1 K-12 Enrollment for the 5 Largest States in the United States 2005-06
Source: Edsource, (2008).

Table 2.1 shows, California’s student demographics are changing as more and
more students are classified into various subgroups while its white student population is
declining. Ironically, the overall student population in California public schools is
decreasing, but the number of students in disadvantaged subgroups, particularly
socioeconomically disadvantaged (SED) and Hispanic students are on the rise (Edsource,
0
1,000,000
2,000,000
3,000,000
4,000,000
5,000,000
6,000,000
7,000,000
California Texas New York Florida Illionois
K‐12 Enrollment for 5 Largest States in 2005‐
06
29
2010c). As seen Table 2.1, California’s SED population is 53.7%, Hispanic population is
49% and its English Learner (EL) population is 24.2%.
Table 2.1 California Public K-12 Student Demographic Population 4 Year Trend
2004-05 2005-06 2006-07 2007-08 2008-09
Hispanic 2,961,104
(46.8%)
3,003,716
(47.6%)
3,026,956
(48.1%)
3,056,616
(48.7%)
3,064,614
(49.0%)
White 1,981,547
(31.3%)
1,915,491
(30.3%)
1,849,078
(29.4%)
1,790,513
(28.5%)
1,741,664
(27.9%)
Asian/Pacific
Islander
550,083
(8.7%)
557,558
(8.8%)
549,232
(8.7%)
555,946
(8.9%)
526,403
(8.4%)
African
American
505,221
(8.0%)
495,017
(7.8%)
477,776
(7.6%)
466,141
(7.4%)
454,781
(7.3%)
Filipino 163,151
(2.6%)
165,572
(2.6%)
165,480
(2.6%)
167,385
(2.7%)
168,112
(2.7%)
Native
American/
Alaskan
51,821
(0.8%)
50,758
(0.8%)
48,383
(0.8%)
47,543
(0.8%)
46,446
(0.7%)
Multiple/No
Response
109,214
(1.7%)
124,324
(2.0%)
170,038
(2.7%)
191,325
(3.0%)
210,501
(3.4%)
Total
Enrollment
6,322,141 6,312,436 6,286,943 6,275,469 6,252,031
LARGEST SIGNIFICANT SUBGROUPS IN CALIFORNIA
Socio-
Economically
Disadvantaged
(SED)
3,127,202
(49.9%)
3,164,384
(51.1%)
3,149,361
(50.8%)
3,118,053
(50.9%)
3,284,120
(53.7%)
Hispanic 2,961,104
(46.8%)
3,003,716
(47.6%)
3,026,956
(48.1%)
3,056,616
(48.7%)
3,064,614
(49.0%)
White 1,981,547
(31.3%)
1,915,491
(30.3%)
1,849,078
(29.4%)
1,790,513
(28.5%)
1,741,664
(27.9%)
English
Learners
(EL)
1,591,525
(25.2%)
1,570,424
(24.9%)
1,568,738
(25.0%)
1,553,091
(24.7%)
1,515,074
(24.2%)
Special
Education
(Age 0-22)
681,969
(10.8%)
683,178
(10.8%)
679,648
(10.8%)
677,875
(10.8%)
678,105
(10.8%)
Source: EdSource (2010b).
California has more students who speak English as a second language and
educates more than one-third of the nation’s EL students (Edsource, 2008). Furthermore,
as shown in Table 2.2, comparing California to the rest of the nation, California has the
30
highest population of students living with a parent who does not have a high school
degree and is proportionally among the top of children living in low income families
(Edsource, 2008, 2010c). Educating a massive, diverse student population like California
makes the allocation of resources a daunting task. Despite the development of
challenging education standards and sustained attention to school improvement over the
past ten years, California continues to lag behind its counterparts on various measures of
student achievement (Loeb et al., 2007). The 2009 National Assessment of Education
Progress (NEAP) reflects California’s fourth grade students 48
th
in reading and 45
th
in
math compared to students from all fifty states (see Table 2.2).
Table 2.2 further illustrates the student achievement in 8
th
grade is equally
alarming; California ranked 46
th
in eighth grade math and 49
th
in 8
th
grade reading
(NCES, 2009a, 2009b). As students move to high school, the grim story continues.
California’s graduation rate is now below 70% and only 52% of California schools met
NCLB’s AYP requirement in 2008 (Edsource, 2009d). While some suggest California’s
educational achievement standing simply reflects the large minority populations in the
state, student achievement data appears to negate this (Loeb et al., 2007). Loeb et al.,
(2007) assert that California schools as a whole do not do well for any subgroup,
including white and non-Hispanic students.

31
Table 2.2 U.S. Rankings of California

CA
Rank
CA
Average
U.S.
Average Highest Lowest
Teacher Salaries
(2007-08)
1 $65,808 52,800 65,808/CA 36,674/South
Dakota

Expenditures per
Pupil (2007-08)
41 $8,586 9,934 17,109/District
of Columbia

5,685/Arizona
Public School
Revenue (2006-07)
per 1,000 Personal
Income in 2007

22 $47 $46 $60/Vermont $24/District of
Columbia

Per Capita Personal
Income (2007)
9 $43,221 $39,430 63,881/District
of Columbia

$29,549/
Mississippi
Percentage of
Children in
Households in
Which the
Household Head
Has Not Completed
High School (2008)

1 26% 16% 26%/California 5%/Maine
Percentage of
Children Who
Speak a Language
Other Than English
at Home (2008)
1 44% 21% 44%/California 3%/Mississippi
& Virginia
4
th
Grade NAEP
Reading*
48 210 Scaled
Score (23%
Prof/Adv)
220 Scaled
Score (31%
Prof/ Adv.)

234 Scaled
Score (57 %
Prof/Adv.)
Massachusetts
207 Scaled
Score
(18 %
Prof/Adv.)
Louisiana
8
th
Grade NAEP
Reading*
49 253 Scaled
Score
(22 %
Prof/Adv.)
262 Scaled
Score
(30 % Prof/
Adv.)

274 Scaled
Score
(42 % Pro/Adv)
Massachusetts

251 Scaled
Score
(19 %
Prof/Adv)
Louisiana
4
th
Grade NAEP
Math*
45 232 Scaled
Score (30%
Prof/Adv)
239 Scaled
Score (39%
Prof/Adv)

252 Scaled
Score (57%
Prof/Adv)
Massachusetts

227 Scaled
Score (23%
Prof or Adv.)
Mississippi
8
th
Grade NAEP
Math*
46 270 Scaled
Score
(23%
Prof/Adv)
282 Scaled
Score
(32% (Prof/
Adv)

299 Scaled
Score (51%
Prof/Adv.)
Massachusetts
265 Scaled
Score (16%
Prof/Adv.)
Mississippi
Note: Adapted from: EdSource (2010b) and NCES (2009a, 2009b).
*These numbers does not include DoDEA and the District of Columbia
32
Under NCLB, all students are expected to be proficient in reading and math by
2010-14. Figure 2.2 portrays California’s proficiency rate by student groups in English
Language Arts (ELA) for the 2008-09 academic school year. As seen in Figure 2.2, just
over half of all California students are proficient in ELA and even California’s highest
achieving demographic group, Asian, leaves slightly more than one in four students not
meeting proficiency standards (California Department of Education, 2010). Across
California, EL, Hispanic, SED, African-American, and students with disabilities are all
below 40% proficiency in ELA.
Figure 2.2 Percent Proficient or Advanced in ELA by Subgroups, 2008-09

Source: California Department of Education, (2010).
Meanwhile, Figure 2.3 shows how California students fair in mathematics
proficiency. While on a whole California students scored two points higher on
mathematics than on ELA, (54.2% in math compared to 52.2% proficiency in ELA),
white, and African-American students actually scored lower on mathematics than they
did on ELA. California’s largest significant subgroup comprised of nearly 54% of the
total population, SED students, scored 38.4% in ELA and 43.6% in mathematics. More
33
than 45% of California students are not proficient in math and ELA (California
Department of Education, 2010).
Figure 2.3 Percent Proficient or Advanced in Math by Subgroups, 2008-09

Source: California Department of Education, (2010).
California’s poor academic performance is also earmarked by the number of
schools in Program Improvement (PI). Schools that receive federal Title I funds through
NCLB are placed in PI if they fail to meet the adequate yearly progress (AYP)
performance targets in the same content area or on the same indicator for two consecutive
years in a row (Edsource, 2010b; Stecher, Hamilton, & Gonzalez, 2003; Weiss, 2007).
According to Edsource, (2010b) 69% of elementary, 59% of middle, and 43% of high
schools received Title I funding for the 2009-10 academic year. Table 2.3 shows
California has 2,783 schools in PI in the 2009-10 school year. That equates to almost
49% of all Title I schools and 28% of every school in California being enrolled in PI.
35% of California schools in PI have been in PI for five or more years.

34
Table 2.3 Number of Schools in Program Improvement in California in 2009-2010
2009-10 Elementary Middle High Total
Number of
Schools
5,998 1,466 2,453 9,917
Number of Title
I Schools
4,139 859 1,067 6,065
Title I Schools in Program Improvement
Year 1 493 88 167 748
Year 2 186 50 73 309
Year 3 227 39 57 323
Year 4 208 60 60 328
Year 5 601 371 103 1,075
Total 1,715 608 460 2,783
Source: EdSource (2010b).
Many associate California’s dismal student achievement outcomes to a lack of
adequate funding by the state. In 2008, California had the tenth largest economy in the
world with a gross state product over 1.84 trillion dollars (California State Assembly,
2010). Despite being one of the largest economies in the world, California has
historically lagged behind many other states in terms of educational funding. Between
1996 and 2007, California ranked anywhere between thirty-six (See Table 2.2) and forty-
first in per-pupil spending, while continually ranking below the national average
(EdData, 2008, Edsource, 2010b; Loeb et al., 2007). In 2005, California ranked thirtieth
in the country, or forty-sixth in the nation when adjusted for regional cost (Hanushek &
Lindseth, 2009). As shown in Table 2.2, California ranks twenty-second in the nation for
public school revenue and ninth in the nation for per-capita income. According to
Edsource, (2010b), public school revenue per $1,000 personal income is used to measure
a state’s effort to support education, while per capita personal income is used to assess
the capacity of residents to support education. California ranked 9
th
in the nation in
personal income (capacity) yet, only 22
nd
in public effort for education. As California
35
continues to fund education below the national average, it is responsible for educating
some of the largest percent of minority, EL and SED students, most of which require
additional educational resources to help them meet proficiency standards (Loeb et al.,
2007; Hanushek, 2006a; Picus, 2006, Odden, 2009; Odden & Picus, 2008).
Compounding the funding problem is the fact that California’s cost are higher than those
in most other states primarily due to the higher wages of a college-educated labor force
(Edsource, 2010; Loeb et al., 2007; PACE, 2006; Timar, 2004). Table 2.2 shows
California ranking number one in the nation for teacher salaries (Edsource, 2010b). The
lower spending in California is reflected in a high student-to-staff ratio, including fewer
teachers and administrators per pupil (Loeb et al., 2007; PACE, 2006).
The low achievement of California’s students will likely hurt their economic
outcomes later in life and be detrimental to the state as a whole (Loeb et al., 2007). There
is growing evidence that educational quality, measured by proficiency in test scores, is
highly related to economic growth and directly related to future individual earnings
(Brewer, Hentschke, & Eide, 2008; Hanushek & Lindseth, 2009; Loeb et al., 2007).
According to Loeb et al., (2007) in a global knowledge economy, the economic growth of
regions and nations is often affected by the skills of its workers, which in turn are directly
related to student learning outcomes. California’s school finance and governance system
are fundamentally flawed (Loeb et al., 2007; Kirst, 2006; PACE, 2006; Timar, 2004). As
a result, California students perform far lower on achievement test than do students in
other states (Loeb et al., 2007). The next section reviews how California’s educational
36
funding system has been influenced throughout the political process and how policy and
case law has systematically changed California’s resource allocations to schools.
California Educational Resource Allocation
Analyzing the current performance levels across students in California and the
vast disparities in achievement among student groups engenders the blunt realization that
California’s academic student performance needs improvement. Improving student
academic proficiency requires reforming California schools and its educational system.
One cannot assess our ability to target reforms without clearly understanding how we
allocate and use educational resources (Picus, 2006). Such an assessment leads to the
connection of finance and to what extent California’s educational funding system is
aligned with improving student performance. The magnitude of both the total
commitment and the per-pupil level of educational resources devoted to educating
California’s school children is significant (Picus, 2006). California’s current education
budget exceeds $56 billion dollars (Edsource, 2010b). Despite this, some argue that K-12
education funding levels are neither equitable nor adequate, especially considering
California’s schools include the largest and most diverse student population in the nation
(Picus, 2006; Woody & Henne, 2006). Regardless of educational funding levels, there is
growing concern that California’s school finance system is unnecessarily complex and
disjointed (Kirst, 2006; Loeb et al., 2007; Picus, 2006; Timar, 2004, 2006). There are
three major events that shape the current structure of California school finance, the
Serrano decision, Proposition 13, and Proposition 98. Picus (2006) argues that the
37
educational reform options facing today’s state policymakers are dramatically limited by
these and other past events.
Serrano v. Priest. Over the past 40 years, a combination of court rulings,
legislative enactments and voter initiatives have made profound changes in the landscape
of educational finance and governance (Timar, 2004, 2006). The landmark California
Supreme Court ruling Serrano v. Priest (1971, 1976) required the state to “equalize”
funding among districts from property tax (Kirst, 2006; Odden & Picus, 2008; Picus,
2006; Timar, 2006, 2004; Edsource, 2000). The Serrano case highlighted that “low
wealth” districts taxed themselves at higher rates compared to “high-wealth” districts in
order to generate revenue to support educational needs. Even then, low-wealth districts
were unable to raise as much revenue as “high-wealth” districts as shown in Table 2.4.
Table 2.4 demonstrates the differences between two districts within the same county
based upon their abilities to generate tax revenue under the pre-1970 funding system
(Timar, 2006). As illustrated, Newark Unified School District was forced to institute a
higher tax rate of $6.65 per $1,000 of the assessed property value, which provided the
district an expenditure level of $616 per ADA. However, Emery Unified School District
was able to institute a lower tax rate of $2.57 per $1,000 of the assessed property value,
allowing them to garner an expenditure level of $2,223 per ADA (Timar, 2006).

38

Table 2.4 County Tax Rates and School Expenditures Level Comparisons in 1968-69
County ADA Assessed Value
per ADA
Tax Rate
($)
Expenditure per
ADA ($)
Alameda
Emery Unified
586 $100,187 2.57 $2,223
Newark Unified
8,638 $6,042 6.65 $616
Kern
Rio Bravo Elem.
122 $136,271 1.05 $1,545
Lamont Elem
1847 $5,971 3.06 $533
Los Angeles
Beverly Hills Unified
5,542 $50,885 2.38 $1,232
Baldwin Park Unified
13,108 $3,706 5.48 $577
Note: Adapted from Timar (2006) p.34.
Newark’s tax rate was more than twice as much as Emery’s yet it provided 3.5
times less revenues per ADA. The California Supreme Court stated that school district
revenues were so reliant on local property tax revenues that students in “low-wealth
districts,” districts with low assessed property valuation, were denied equal educational
opportunities and violated the “Equal Protection” clause of California’s Constitution.
Responding to the Serrano court decision, Assembly Bill 65 of 1977, attempted to
equalize revenue limits for districts by adjusting for inflation overtime.
The court’s ruling in Serrano found that wealth related disparities were
unconstitutional. However, the legislature chose to respond to the Serrano ruling through
equal general revenue spending limits and categorical programs (Timar, 2004).
According to Kirst (2006), the courts suggested several alternatives for remedy, but the
legislature chose to focus solely on spending disparities among districts’ general
unrestricted revenue. The Court maintained categorical funds were not subject to
Serrano’s equalization provisions since by their nature, categorical funds target special
needs populations (Timar, 2004). In essence, the Court permitted that schools could be
39
funded by two streams, general purpose funds and special purpose funds. Serrano’s
primal concern with district spending differences does not allow California’s finance
system to take into account regional cost differences, and thus implies an assumption that
it costs as much to operate a rural school district as it does a large urban district (Kirst,
2006). Kirst (2006) asserts that the legislative response to Serrano’s focus of equal
district spending has not created an effective finance system overall, and is not attuned to
a focus on student outcomes.
Proposition 13. Proposition 13 passed in 1978, addressed the tax inequalities in
the Serrano case by attempting to end the further disparities of the unequal share of
property tax revenue that school districts receive from local property tax (Edsource,
2000). Proposition 13 capped the property tax rate at 1% for all homeowners resulting in
a dramatic reduction in property tax dollars and reducing the amount of property taxes
available for local district control (Edsource, 2000; Kirst, 2006; Picus, 2006; Timar,
2004, 2006). In addition to lowering property taxes, Proposition 13 required a two-thirds
majority vote by both legislative houses for future state tax increases, while also requiring
a two-thirds majority in local elections on ballot measures to raise additional tax dollars.
According to Timar (2004), Proposition 13’s main feature shifted school finance decision
making from local districts to the state. Proposition 13 dramatically altered the effect
LEAs and municipalities had on educational funding and revenues while also severely
limiting local school districts ability of raising revenue (Kirst, 2006; Loeb et al., 2007;
Picus, 2006). After passage of Proposition 13, how much money schools would receive
and what strings would be attached to those monies was determined by the state
40
(Edsource, 2000; Odden & Picus, 2008; Picus 2006; Timar, 2004, 2006). Proposition 13
shifted California’s education revenue source, largely from local property tax to general
state revenue and sales tax. It also took away the local ability to adjust to these swings by
eliminating their ability to ask taxpayers for more property tax revenue. This shift put
California education funding at the whim of economic cycles that are much less stable
over time, cycles that swing from deficit spending to accumulating large reserves. In
1970, prior to proposition 13, only nine states spent more on education than California
(Hanushek & Lindseth, 2009). By 2005, California ranked thirtieth in the country or
forty-sixth in the nation when costs are adjusted for regional cost (Hanushek & Lindseth,
2009).
Proposition 98. Both the Serrano decision and the passage of Proposition 13
continued to influence control away from LEAs to state policymakers as to how much
money schools receive and what strings would be attached to those monies (Timar,
2004). California voters went back to the ballot box in 1988, in an attempt to take back
some control of educational spending. In an effort to stabilize education funding in
California, voters approved in 1988, Proposition 98. Proposition 98 resulted in minimum
state funding levels for K-12 and community colleges by constitutionally protecting a
portion of the state budget (Edsource, 2000; Odden & Picus, 2008; Picus, 2006; Timar,
2004, 2006). Its purpose was to provide schools and community colleges with a
guaranteed funding source that grows over time with the economy and student
enrollment. Timar (2004) argues that while Proposition 98 guarantees 40% of the state’s
general revenue are apportioned to K-12 districts and community colleges, its major
41
impact has been to use the state budget as a policy tool. Since policymakers know that
40% of general revenue dollars must be spent on K-12 and community colleges and
because they do not know how much money will be available for the following year’s
budget, there is often a last minute rush to spend money on measures policymakers want
more direct control over (Timar 2004). According to Picus, (2006) Proposition 98
provides a theoretical floor for educational spending, but it has also served as a ceiling for
educational spending by limiting policymakers’ flexibility in budget decisions.
Politicization of categorical grants in California’s resource allocation. The use
of categorical funding through specific educational grants is not new to California.
According to Timar, (2006) there are four types of categorically funded programs:
entitlements, inducements, discretionary and mandated cost reimbursements. However,
since the Serrano decision, there has been a dramatic shift in resource allocation between
unrestricted and restricted (categorical) funds (Timar, 2004, 2006; Picus, 2006). Timar
(2004) asserts categorical funding for schools has generated political controversy since its
inception. There are deep ideological divisions between advocates and opponents of
compensatory aid, especially aid for low-income or disadvantaged students and
accountability measures tied to such aid (Timar, 2004). Over the last three decades, a
growing proportion of state funding for education has been provided through categorical
programs which are not subject to the Serrano requirements (PACE, 2006; Timar, 2004).
According to Timar, (2004) rather than putting money into general revenues for schools,
policymakers increasingly target funds for special purposes in the form of categorical
grants.
42
Since the passage of Proposition 98, the growth rate of categorical programs has
expanded exponentially. The desire to keep additional educational dollars, especially
those protected under Proposition 98, from going to teachers’ salaries was largely
responsible for legislative targeting of school programs into protected categorical
programs (Timar 2006, 2004). The legislature responded to legal and political demands
by shifting more revenue to categorical programs. Timar (2004) argues that categorical
programs tend to respond to perceived or real educational problems in “ad hoc”, gradual
fashion; as problems increase, so do categorical programs.
Recent state budgets have included over 100 different educational categorical
programs with considerable and programmatic overlap (PACE, 2006; Timar, 2006,
2004). Although recent attempts have been made to consolidate overlapping categorical
programs with duplicative goals, California continues to allocate nearly one-third of state
educational funding (over $14 billion) through almost 80 different categorical grants
(Edsource, 2010b, 2009d; PACE, 2006). Figure 2.4 demonstrates how federal, state,
parcel taxes, and other miscellaneous dollars are distributed to LEAs for both categorical
and general purpose. The column on the left in Figure 2.4 shows the five sources of
funds California schools use for operating. As of January 2009, funding sources for
California schools could be broken down into the following four categories: almost 10%
provided by the federal government, nearly 60% from state generated taxes, slightly less
than 23% from property taxes, approximately 2% from state lottery, and 5% from other
miscellaneous sources such as parcel taxes (EdSource, 2009a). The column on the right
43
of Figure 2.4 exhibits that about two-thirds of the money allocated to schools is for
general purposes while almost one-third is intended for categorical funding.

Figure 2.4: California’s School Finance System

Source: Edsource, (2009a)
Problems with California’s current resource allocation. Although a number of
bills and measures passed in California have attempted to reduce the inequities among
districts, high wealth districts are still able to generate a higher amount of revenue
(PACE, 2006; Timar, 2006. 2004). Timar (2004) reported that 53.8% of students in the
state that are in the bottom quartile of need are also in the bottom quartile of funding.
44
Recent literature (PACE, 2006; Timar, 2004, 2006) suggests that the relationship between
student need and the distribution of resources from categorical grants is weak at best and
regressive at worst. Loeb et al., (2007) further support the notion of inequities in
California’s education funding, finding that similar districts can receive substantially
different revenues per pupil. The result is wide variation in spending across school
districts. The difference in total expenditures, excluding capital outlays, in a district at the
25
th
percentile of spending and a district in the 75
th
percentile of per pupil spending is
more than $1000 per student (Loeb et al., 2007). In addition, the source of school
funding is unstable both in terms of revenue fluctuations and the lateness of the budgeting
process, severely limiting school districts’ ability to plan and react in a timely and
appropriate manner (Edsource, 2010c; Loeb et al, 2007; Timar, 2004). As illustrated in
Figure 2.5, over the past three years, K-12 Proposition 98 funding has fluctuated from
over $51 billion to $44 billion dollars with districts often facing mid-year reductions. In
the 2008-09 school year, Proposition 98 funding was cut nearly $7.2 billion dollars. The
Proposition 98 spending requirement has dropped sharply, and policymakers have used
its minimum guarantee as a funding ceiling (Edsource, 2010c).
The inequity among students in different districts, especially among the state’s
most vulnerable students, still persists and funding for most students in California
continues to be far from adequate. California’s resource allocation structure to schools
targets its goal as equalization without regard to adequacy or academic standards (Timar,
2006). California’s educational finance structure has never been updated to align with the
state’s accountability system nor redesigned to help local officials meet student
45
performance targets (Loeb et al, 2007; PACE, 2006; Timar 2006, 2004). California’s
school reform efforts to improve student performance have focused on standards-based
accountability. California’s Academic Performance Index provides a clear description of
what students need to know and sets desired performance levels for all students.
However, what is missing is a clear system of funding that is tied to strategies the will
lead to the improved student outcomes outlined by the state’s API (Loeb et al., 2007;
PACE, 2006; Timar, 2006, 2004).
Figure 2.5: K-12 Proposition 98 Funding Fluctuation from 2007 to 2010

Source: Edsource, (2010c).
There is growing consensus that while holding schools accountable for improved
student performance, the legislature has done little to provide schools with the autonomy
and flexibility to achieve improved student outcomes (Loeb et al., 2007; PACE, 2006;
46
Timar, 2006, 2004). According to Loeb et al., (2007) California prescribes at the state
level more of how funds should be spent than other states. Schools have little control over
resource allocations, but are expected to produce outcomes as thought they did (PACE
2006; Timar, 2006, 2004). There is some evidence that districts use of state-prescribed
categorical aid is less effective for improving student outcomes than general, unrestricted
aid (Loeb et al, 2007). These findings along with others suggest that California school
districts can allocate resources more effectively when given flexibility than when the
allocation is determined solely by the state (Loeb et al., 2007; PACE, 2006; Timar, 2006,
2004).
Complexity in tiers. In February, 2009, lawmakers made significant changes to
almost half of the state’s categorical programs, giving districts greater flexibility
(Edsource 2010b, 2010c). The state provided this flexibility for 5 years (retroactive to
2008-09 through 20012-13) largely to help districts deal with significant educational cuts
(Edsource 2010b, 2010c). The already complex and unpredictable state educational
funding structure added further complexity by breaking up the various categorical grants
into three tiers, each with different rule sets and timelines. The three tiers differentiate
both flexibility and cuts compared to the previous year: (a) Tier 1 categorical programs
represent more than 20 programs that were neither substantially cut nor given any type of
flexibility; (b) Tier 2 categorical programs represent about 11 programs that were cut by
20% without flexibility; and (c) Tier 3 categorical programs represent nearly 40 programs
that were cut 20% but given flexibility (Edsource, 2010b, 2010c). Adding to the
complexity, the K-3 class size reduction program was listed as a Tier 1 program, but
47
policymakers substantially loosened its penalty structure. The temporary structure allows
districts to raise class size beyond the 20 to 1 categorical restrictions up to 30 to 1 or
more through the 2011-12 school year (Edsource, 2010c).
Picus (2006) states that the heart of the problem for California school finance
today is that we do not have a clear picture of how much money we need to educate
students to the state’s desired performance levels. California’s school finance system
remains a confusing system with little relationship between identified student needs and
the targeting of resources to meet those needs (Picus, 2006). While California’s diverse
student population includes large numbers of students who require additional services to
succeed, it employs a school resource allocation system that is entirely dependent on the
fluctuating condition of the state budget (Loeb et al, 2007; Picus, 2006; Timar, 2004).
While the state has established high standards and performance outcomes that California
students must attain, it lacks a clear strategy to adequately allocate the resources
necessary to ensure all students meet these outcomes (PACE, 2006; Timar, 2006; Timar
2004). California schools must address the challenge of adequately educating an
increasingly diverse student population with fewer resources and less decision rights on
how to effectively allocate and align resources to evidence-based educational strategies to
improve student outcomes. Given the parameters of California’s school finance structure,
it is important to understand how these limited and often restricted resources can be
integrated more effectively.

48

Federal Resource Allocations Targeted to Improve Student Performance
Since the second half of the twentieth century, local control over public schools
has dramatically eroded and shifted the balance of control to state and federal control due
to a variety of factors including: court rulings, federal regulations, state mandates and
ballot initiatives (Hanushek & Lindseth, 2009; Hanushek & Rivkin, 1997; Kirst, 2004;
Lindseth, 2006; Odden & Picus, 2008; Wirt & Kirst, 2005; Rebell, 2007; Ryan, 2009).
Since the late 1950s, numerous federal and state education efforts have been initiated and
a myriad of court cases have been rendered to improve student outcomes and minimize
the achievement gap between minority and white students. Increases in educational
funding evolved in an effort to connect these reform efforts with desired student
performance outcomes. From 1960 to 2005, K-12 educational spending in the United
States rose significantly; adjusting for inflation, per pupil expenditures nearly quadrupled
(Hanushek & Lindseth, 2009). While educational spending quadrupled over the past four
decades, student achievement in reading, math, and science has remained relatively flat
with large numbers of students performing at basic levels through the twelfth grade
(Hanushek & Lindseth, 2009). Consequently, U.S. students no longer lead the world and
are no longer as competitive when compared to their global counterparts (Friedman,
2005; Hanushek & Lindseth, 2009; Loeb et al., 2007; Odden et al., 1995; Schneider,
2008; Stecher et al., 2003). As the world becomes increasingly more flat with a global
economy and technological advances, America will soon find itself falling behind other
countries in its capacity for scientific discovery, innovation and economic development.
49
The crisis is a national one, and the failure to find effective solutions and adequate
resources threatens not only individual well-being, but our country’s leadership in the
global community as well. Public scrutiny of American schools has been the impetus for
further federal involvement and financial support in public education and the further
erosion of local educational control.
Relationship between poverty, EL and student achievement. The link between
poverty and lower student achievement has been present for several decades. Research
has indicated that students’ academic outcomes are related to their socioeconomic status
(SES) (Berliner, 2006; Blossfeld & Shavit, 1993; Bradley & Corwyn, 2002; Brooks-
Gunn & Duncan, 1977; Chatterji 2006; Carbonaro, 2005; Coleman, et al., 1966; Sirin,
2005). Beginning with the Coleman Report in 1966, researchers have reported the
impact of a student’s background on his or her chances for success in school (Coleman, et
al., 1966; Woody & Henne, 2006). The National Center for Education Statistics (NCES)
consistently reports a negative correlation among poverty and student achievement, as
measured by reading and math performance on the National Assessment of Educational
Progress, or NAEP, (NCES, 2009a, 2009b, 2009c, 2005; Woody & Henne, 2006). Sirin,
(2005) did a comprehensive review of research on socioeconomic status and academic
achievement between 1990-2000 and found that parents’ location along the
socioeconomic structure has a profound impact on a child’s academic achievement.
Children from high poverty environments enter school less ready to learn while their
ability to use language to solve problems lags behind their more affluent counterparts
50
(Val, 2004). Historically students of low SES have performed lower on standards-based
tests than their non-economically disadvantaged counterparts (Berliner, 2006).
Brooks-Gunn and Duncan (1997) examined how the timing of poverty in one’s
life affects academic outcomes. Students whose SES were below the poverty line in
preschool and early elementary had lower rates of school completion and adverse effects
on cognitive development than their non-economically disadvantaged peers, as well as
students who were exposed to poverty in the middle and later stages of their schooling.
According to Blossfeld and Shavit (1993), there appears to be a greater impact on
educational attainment in the early years of one’s educational journey as the economic
factors related to one’s family seems to have greater influence earlier than later during
educational transitions. The effects of socioeconomic factors on one’s educational
attainment seems to decrease later in life as older students are less likely to be dependent
on the family’s financing of education. Therefore, advocates state interventions are
critical, especially in early education (Blossfeld & Shavit, 1993; Brooks-Gunn & Duncan,
1997; Carbonaro, 2005; Chatterji, 2006).
According to Woody and Henne, (2006) California mirrors national trends with
the disparity in achievement between socioeconomically disadvantaged students and their
more affluent counterparts. Low-income students are on average 30% less likely to reach
proficiency on the California Standards Test (CST) in both ELA and math (Woody &
Henne, 2006). The relationship between poverty and English Learner (EL) students
causes further concern. Recently, 32% of Title I students in California were also
identified as EL. Gandara and Rumberger (2007) studied the resource needs of
51
California’s English Learners. They suggest that all disadvantaged students, including
poor and linguistic minority students, require additional resources to help them attain the
same academic standards as their more advantaged peers (Gandara & Rumberger, 2007).
Achievement data suggest that students who are both poor and linguistic minorities need
more resources because they have the furthest to catch up (Gandara & Rumberger, 2007;
Odden & Picus, 2008; Woody & Henne, 2006).
Evolution of ESEA and Title 1. During the formation and early days of the
republic, Americans had a distrust of a distant, national form of government and wanted
important decisions made close to home, especially those regarding education (Writ &
Kirst, 2005). Since the U.S. Constitution fails to mention the right of public education or
schooling, control of public education has been relegated to states. As the thinking spread
that schooling will produce a more informed, literate, numerate and moral citizenry, local
governments started investing and exercising more control over schools (Odden & Picus,
2008; Kirst, 2004; Wirt & Kirst, 2005). Throughout the early twentieth century, states
adopted various efforts to minimize the resource disparity among different school
districts, while still maintaining local control of education (Odden & Picus, 2008).
However, the measures taken were insufficient in eradicating such inequalities and thus,
local control of education began to erode (Hanushek & Lindseth, 2009; Odden & Picus,
2008; Wirt & Kirst, 2005; Kirst, 2004). Over the course of a century, between 1862 and
1963, the U.S. Congress considered unrestricted general financial support to schools
thirty-six times and rejected all thirty-six occurrences (Kirst, 2004; Wirt & Kirst, 2005).
Opponents had long argued successfully that since the Tenth Amendment to the
52
Constitution delegated control of schools to the states, the federal government had no
constitutional right to meddle in education (Kirst, 2004; Wirt & Kirst, 2005).
The 1954, ruling of Brown v. Board of Education of Topeka (1954) initiated the
courts active role in education with the desegregation of schools and raising awareness
about the disparity in educational performance of minority students in the nation’s public
schools (Hanushek & Lindseth, 2009; Kirst, 2004; Lindseth, 2006; Ryan, 2009; Wirt &
Kirst, 2005; Zirkel, 2001). In 1955, in what is known as Brown II, the Supreme Court
delegated the task of carrying out school desegregation to district courts with orders that
desegregation occur "with all deliberate speed (Hanushek & Lindseth, 2009; Rosenberg,
1991). The Brown rulings brought national attention to educational inequalities and
public scrutiny on conditions of public education while setting the stage for the further
federal involvement in education.
Soon after the Brown (1954, 1955) rulings, the U.S. Congress entertained policies
to mitigate a variety of social inequalities (Cross, 2004; Kirst, 2004; Ravitch, 1983; Wirt
& Kirst, 2005). Wirt and Kirst (2005) assert the Brown rulings set in motion the federal
government’s quest to reduce unequal educational opportunities that were tolerated by
state and local policymakers. Over the past decades, several federal and state policies
have attempted to address the needs of low-income students. Most notable is Title I, a
hallmark of the federal Elementary and Secondary Education Act (ESEA) signed into law
in 1965. In the early 1960’s, the Kennedy administration began discussion about
providing substantial federal dollars for K-12 public schools. The focus of this massive
federal funding of public schools shifted to provide targeted federal aid to poor and
53
disadvantaged students. Rather than pursuing unrestricted general aid that the slain
President Kennedy sought unsuccessfully, President Johnson attempted to tie federal
education money to special-needs categories, schools with low-income students and low-
achieving pupils (Cross, 2004; Hanushek & Lindseth, 2009; Kirst, 2004; Wirt & Kirst,
2005). The thought was that by providing funds for impoverished students, student
achievement would improve and the achievement gap would narrow. The passage of
ESEA set the stage for further federal involvement in public education and increased
federal accountability, something previously delegated primarily to each state. Since
Johnson’s initial passage of the ESEA Act in 1965, nearly every preceding President has
also sought to reauthorize ESEA during their tenure (Kirst, 2004; Wirt & Kirst, 2005).
While Title I funds were directed toward disadvantaged children, the federal
government failed to specify the types of services schools should provide with the
additional resources (Jennings, 2000; Kirst, 2004; Wirt & Kirst, 2005; Woody & Henne,
2006). Instead, states and local districts were in charge of allocating the targeted
resources. Originally, Title I was primarily used to fund supplemental programs, allowing
schools to incorporate targeted strategies to support the lowest-performing students
(Farkas & Hall, 2000). The program fell under sharp attack during the late 1960s when
mounting evidence revealed states and districts were using Title I funds contrary to its
intent (Jennings, 2000). As a result, federal policymakers enacted two additional
provisions to govern the allocation and distribution of Title I funds. The first provision
required that Title I schools receive comparable funding to the funding received by other
schools (Roza et al., 2005; Woody & Henne, 2006). The second provision required that
54
Title I funds do not replace state and local funding; the targeted funds must supplement,
not supplant resources (Jennings, 2000; Kirst, 2004; Roza, et al., 2005; Wirt & Kirst,
2005; Woody & Henne, 2006).
Title I faced further scrutiny during the 1980s. The report, A Nation at Risk (1983)
caused lawmakers to grow increasingly frustrated with the policy’s lack of articulated
guidelines to measure student achievement (Jennings, 2000; Woody & Henne, 2006). As
a result, the 1988 reauthorization incorporated significant changes and stipulations. First,
states were mandated to define levels of achievement for targeted students. Second, states
were required to identify schools that failed to meet adequate progress towards these
goals. Lastly, responding to a lack of flexibility inherent in the use of Title I funds,
targeted funds no longer were solely designated for specific services, but also gave
schools the flexibility to offer schoolwide programs targeted to improve student
outcomes (Jennings, 2000; Wirt & Kirst, 2005; Woody & Henne, 2006). Under the new
schoolwide program option, Title I schools with 75% or more of its students in poverty
could use the targeted funds for resources that would benefit the entire school. Woody
and Henne (2006) describe the intent of this change was to help schools with a high
percentage of high-poverty students improve the overall instructional school program.
According to Frank and Hall, (2000) the reason for this 75% threshold being so high was
to ensure that Title I funds supported the neediest students.
During the Clinton administration’s reauthorization of ESEA, Title I required
states to have academic standards, define levels of student proficiency and assess student
achievement (Jennings, 2000; Woody & Henne, 2006). In addition, the poverty threshold
55
for schoolwide programs was lowered from 75% to 50%. This adjustment was a dramatic
shift and resulted in a growing number of schools targeting Title I funds to support a
schoolwide improvement effort (Farkas & Hall, 2000; Woody & Henne, 2006).
NCLB and Race to the Top. During the 1980s and 1990s, much of the
educational reform efforts were driven at the state level with an increasing gubernatorial
influence and shifting more local control to the states (Kirst, 2004; Wirt & Kirst, 2005a).
The standards-based reform movement swept the nation state by state with governors,
business executives, policymakers and curriculum specialist calling for all students to
have equal access to a guaranteed curriculum (Kirst, 2004; Marzano, 2003; Weiss, 2007;
Wirt & Kirst, 2005). The-standards-based reform movement got the attention of the
federal government and eventually paved the road to the passage of the No Child Left
Behind (NCLB) Act of 2002. The federal government’s reauthorization of the ESEA
dramatically altered the implementation and requirements of Title I by passing NCLB
(Woody and Henne, 2006). The passage of NCLB occurred during a fertile period of time
when outrage was growing about the educational inequalities while a larger influence of
global economic shifts continued to demand a more educated and highly skilled
workforce than school systems were providing (Weiss, 2007).
Since 2002, NCLB has taken the notion of accountability and sanctions in public
education to a level unseen in any previous policy or regulation. NCLB holds states,
LEAs, and individual schools receiving targeted Title I funds accountable for ensuring all
students are proficient in English Language Arts (ELA) and mathematics by 2014 by
placing mandates on the federal educational inducements. NCLB measures growth in
56
school performance against fixed standards, all in hope to help narrow the achievement
discrepancies between whites and various minority or underrepresented groups
(Edsource, 2008; Kirst, 2004; Wirt & Kirst, 2005; Woody and Henne, 2006). Under
NCLB, schools that receive Title I funds and fail to meet Adequate Yearly Progress
(AYP) for two consecutive years are subject to sanctions under Program Improvement
(PI). In 2009-10, 69% of elementary, 59% of middle and 43% of high schools received
federal Title I funding (Edsource, 2010b). Under PI, Title I schools face numerous
sanctions including setting aside additional resources for professional development,
providing students with school choice, restructuring the school and replacing
administration and school staff (Edsource, 2008; Kirst, 2004; Wirt & Kirst, 2005; Woody
and Henne, 2006). As previously mentioned, Table 2.3 shows California has a total of
2,783 schools currently in PI (Edsource, 2010b). While NCLB has created momentum
around accountability and improving student learning outcomes for all students,
significant achievement gaps still persist (Weiss, 2007). The public’s scrutiny on the
quality of American schools remains as the federal government continues to pressure
states to reform education through various policy inducements, including the federal
government’s most recent attempt through the American Recovery and Reinvestment Act
(ARRA) of 2009.
Federal stimulus: Race to the Top. The education component of the American
Recovery and Reinvestment Act (2009), also known as the federal stimulus, has been
described as the nation’s largest investment in education (Edsource, 2009c). It provided
more than $100 billion for prekindergarten through 12
th
grade to schools across the
57
nation, and nearly $8 billion for California (Edsource, 2009c). In addition, it established
$4.5 billion to be allocated by the U.S. Department of Education through a completive
grant called Race to the Top (RTT) (Peterson & Rothstein, 2010, Edsource, 2009c). In
order to qualify for most of the federal stimulus funds, including RTT, states had to
commit to pursuing reform in the following four areas:
1. Increasing teacher and principal effectiveness and equitable distribution of
effective staff;
2. Establish data systems and use data for improvement
3. Adopt rigorous college-and career-ready standards and high quality
assessments; and
4. Turn around the lowest performing schools (Edsource, 2009c).
Given California’s fiscal crisis, state policymakers felt the incentives were too much to
ignore and thus felt pressure to align state policy with the new federal initiatives
(Edsource, 2009c). The new initiatives are likely to be similar to ones called for in the
reauthorization of ESEA. The stimulus package’s education components come in the
form of three different groups: (1) large, formula-driven pots of money distributed
quickly to save jobs; (2) supplement smaller existing programs; and (3) a group of
competitive grants (Edsource, 2009c).
The largest competitive grant program is RTT. RTT provides over $4 billion
dollars to a handful of states that have created conditions for bold, comprehensive action
in the four reform areas mentioned above (Edsource, 2009c). The RTT program is the
largest program ever to be under the discretion of the U.S. Department of Education. The
58
department planned to make large grants to a few states rather than spreading the money
across several reform states. Forty states applied to participate in RTT, but only Delaware
and Tennessee emerged on top and won the first round of Race to the Top (Edsource,
2009c; Peterson & Rothstein, 2010) While some researchers question the reliability and
validity of the department’s ranking system for RTT (Peterson & Rothstein, 2010), the
U.S. Department of Education assures other states that they if they did not win in round
one, they could win a competitive grant in round two (Edsource, 2009c; Peterson &
Rothstein, 2010;). Time will tell what impact the federal stimulus and the RTT program
will have on improving student outcomes and reforming school systems, especially those
most failing struggling students.
Any direct link between Title I funds and improved student outcomes remains in
question (Stullich, Eisner, McCrary, & Roney, 2006; Woody and Henne, 2006). The
achievement gap between socioeconomic status continues to persist both nationally and
within California, despite policy and educational efforts to target the needs of low-
income students (Woody & Henne, 2006). While it may be difficult to ascertain the
impact on student achievement of particular policies such as targeting additional funds
for low-income students, research suggest certain school and classroom strategies are
effective for improving student outcomes. A review of the relevant research of specific
strategies using educational resources more effectively to improve student performance
will be discussed later in the fifth section of this chapter. The next section addresses the
evolution of educational equity to adequacy in terms of resource allocation.

59

Evolution of Educational Equity to Adequacy
Over the past two decades, the focus on education funding has evolved from
equity to adequacy (Odden, 2003; Odden & Picus, 2008: Rebell, 2007). Various court
cases like Brown (1954), Serrano (1971) and numerous others focused largely on the
equitable distribution of funding, yet they failed to address the issue of equitable student
performance outcomes (Clune, 1994; Odden 2003; Hanushek & Lindseth, 2009). Over
time, concern evolved from fiscal equity differences to differences in student
achievement between high socio-economic status (SES) students and those living in low
SES. Federal legislation such as ESEA and IDEA targeted resources to mitigate the
growing achievement gap concerns. The failure to diminish the achievement gap across
the nation led to further lawsuits across federal and state courtrooms, asserting the
education finance systems were unconstitutional (Hanushek & Lindseth, 2009). Rebell
(2007) states that nearly seventy-five percent of these lawsuits were successful because
the courts found that states failed to identify the necessary cost associated to adequately
educate all students to a similar performance target. This section will summarize the
difference between equity and adequacy, adequacy court cases, and describe the four
adequacy models that have emerged as a result of federal and state court rulings and
legislative action.
Equity vs. adequacy. The equity based funding model attempts to ensure all
students receive the same amount of resources to support student leaning. Since the
1950’s, equity became a focus and goal of school finance (Odden & Picus, 2008; Picus,
60
2006; Rebell, 2007). Equity required designing state funding systems that mitigated
inequities in property wealth and expenditures across school districts; resulting in many
states adopting “foundation” funding programs (Lindseth, 2007; Picus, 2006; Rebell,
2007). Foundation programs involved designing school finance structures that provided
state aid in inverse relationships to the property wealth of the various school districts in
the state (Picus, 2006). States shifted from providing equal grants to districts based on the
number students toward providing a minimum “foundation level” of funding using tax
revenues with the state providing additional funds to poorer districts. Such funding
programs helped level the playing field and provided property poor districts additional
revenues than the prior funding system (Odden and Picus, 2008; Picus, 2006). According
to Rebell (2007) little research was done to determine an appropriate foundation level of
funding. Instead of being based on actual educational costs or needs, it was a purely
political process that was dependent on the amount of state funds available (Rebell,
2007).
School finance experts began pushing toward addressing the concept of vertical
equity as it became commonly recognized that children and the communities in which
they were serviced varied widely in both need and wealth (Chambers & Levin, 2006). At
the state level, vertical equity examines relationships between district property wealth and
state level funding (Odden & Picus, 2008; Roza & Hill, 2004). Various state educational
systems embraced this concept and treated children and taxpayers of varying need and
wealth in systematically different ways (Chamber & Levin, 2006). Within districts,
vertical equity examines relationships between resource allocation and pupil
61
characteristics such as race, ethnicity, or socio-economic status (Chamber & Levin, 2006;
Odden & Picus, 2008; Roza & Hill, 2004). According to Hanushek and Lindseth (2009),
proponents of equity cases assumed equalization would occur simply by narrowing the
disparity gap between low-SES and high-SES districts. However, equity based methods
did not always narrow the disparity gap and in some cases further aggravated the inequity
problem (Evers & Clopton, 2006; Hanushek, 1996; McNeil, 2010; Rebell, 2007; Timar,
1996, 2004).
Chambers and Levin, (2006) along with Clune (1994) argue that it is within the
context of vertical equity that we find the concept of adequacy emerge as the following
questions are asked:
• How much differently do we need to treat children with varied educational
needs?
• How differently do we need to treat the various types of communities in which
these children are served?
By the 1990’s, considerable emphasis was placed on understanding the relationship
between money and student performance (Picus, 2006). During this time period, two key
factors continued to shift the focus of school finance from equity to adequacy. The first
was the question of: Does money matter? Do differences in dollars spent equate in
substantive differences in educational opportunities or student learning? The second
factor was that the answer to the question above requires linking dollars to results in a
standards-based educational environment (Odden, 2003)
62
Ultimately, the adequacy movement emerged largely from the standards-based
movement and shifted school finance away from equity to an outcome oriented model of
adequacy (Baker, 2007; Odden, 2003, Odden & Picus, 2008; PACE, 2006; Rebell, 2007).
The adequacy movement asks a simple question: How much money is needed to ensure
all students meet a state’s identified performance standard? An adequacy model of
funding sets out to determine the level of resources for students based on their individual
needs and the amount of resources necessary for them to achieve an agreed upon
performance benchmark (Hanushek & Lindseth, 2009; Odden, 2003, Pace, 2006; Odden
& Picus, 2008; Rebell, 2007). Unfortunately, economists and statisticians have not been
able to consistently identify the nature of that relationship, nor quantify it in an
appropriate and predictable manner so that policymakers can provide funds in ways that
ensure desired results for all students (Picus, 2006).
Improving student performance is the hallmark of educational policy today. The
standards-based reform movement has been a cornerstone of education policy for over 20
years. Standards-based education reform seeks to educate all students to high levels of
achievement and clearly identifies target benchmarks for student performance. Implied
in this goal is both an element of equity and excellence (Odden, 2003). According to
Odden, (2003) the goal is outcome oriented (student performance) and focuses on the
results of the education system as a whole by dramatically diminishing the “achievement
gap.” The passage of NCLB (2002) requires every state to adopt academic outcome
standards and ensure that all students, with limited exceptions, meet benchmark
proficiency standards by the year 2014 (Edsource, 2008; Hanushek & Lindseth, 2009;
63
Hentschke &Wohlstetter, 2004; Weiss, 2007). NCLB’s demands that all students reach
targeted performance levels puts further demands on state’s educational finance systems
to provide adequate funding levels to ensure such results are achieved. As school
accountability shifted focus to student performance outcomes, school finance litigation
began to evolve from equity to adequacy models (Clune, 1994; Odden, 2003; Hanushek
& Lindseth, 2009; Odden & Picus, 2008; Rebell, 2007).
Adequacy is an approach various groups used when challenging state educational
funding systems in court. According to Picus, (2006) court cases shifted from equity to
adequacy following the Kentucky Supreme Court’s ruling in 1989, that Kentucky’s
education funding system was unconstitutional. The court ruled that all children should
be able to meet certain minimum performance standards and that resources provided by
the state were inadequate to ensure that possibility (Lindseth, 2007; Picus, 2006). The
Kentucky legislature responded by appropriating an additional billion dollars a year for
education and established an extensive testing and accountability system (Picus, 2006).
Since the Kentucky adequacy case, nearly forty-four other states have been to court to
litigate the issue of what is an appropriate education (Chambers & Levin, 2006). The
majority of the court cases have been successful because close scrutiny of states
education finance systems has shown few states have attempted to determine objectively
the amount of resources required to meet desired learning requirements (Rebell, 2007).
Adequacy and the courts. The judicial focus on the level of funding needed to
provide an adequate education, coupled with the nationwide movement to raise
educational standards, has resulted in an explosion of “costing-out” studies that aim to
64
determine objectively the amount of funding necessary to provide all students with a
meaningful opportunity for an adequate education (Rebell, 2007). According to
Hanushek and Lindseth, (2009) adequacy cases are fundamentally different than equity
cases. Equity cases typically involve federal and state equal protection clauses, while
adequacy cases are grounded in educational clauses within states’ constitutions. While
the United States Constitution does not explicitly call on the federal government to
educate its children, nearly every state constitution requires either vaguely or explicitly,
that the state or its legislature provide a form of free public education to the children of
the state (Hanushek & Lindseth, 2009). Hanushek and Lindseth (2009) spell out the
components courts must factor in when ruling on adequacy suits: (1) what level of
education is required within the state constitution; (2) whether the state is or is not
providing that level of education; (3) if not, what ought to be done to remedy the
situation. Often, the courts are asked to decide whether state K-12 education funding
levels are sufficient to provide an “adequate” system and if not, how much more funding
is needed (Clune, 1994; Odden, 2003; Hanushek & Lindseth, 2009; Odden & Picus,
2008; Rebell, 2007).
Adequacy studies and lawsuits typically expand the amount of resources allotted
to education (Baker et al., 2008; Hanushek & Lindseth, 2009; Lindseth, 2006; Odden et
al., 2003; Picus, 2006; Taylor et al., 2005) instead of merely redistributing educational
dollars from one LEA to another as is typical with equity lawsuits (Hanushek & Lindseth,
2009; Lindseth, 2006). Thus, adequacy suits have become increasingly more popular than
equity lawsuits among powerful segments of the educational community, including union
65
leaders, education coalitions and parent advocacy groups since adequacy can be a winner
for all schools (Hanushek & Lindseth, 2009). The outcomes of various adequacy cases
have led to four main approaches used in resolving educational adequacy concerns within
states’ constitutions that guarantee an adequate education to all students. When applied,
these approaches are often referred to as adequacy studies or costing out studies
requested by various state legislatures or policymakers, often responding to prior court
decisions (Baker, 2005; Bhatt & Wraight, 2009; Baker et al., 2008; Hanushek, 2006a;
Hanushek & Lindseth, 2009; Imazeki, 2008; Odden et at. 2003, PACE, 2006; Rebell,
2007).
Hanushek (2006a) views the courts involvement in the school finance adequacy
debate as a result of the poor decisions they have made. He argues that courts have at
times overstepped their jurisdiction by mandating a move toward adequacy, and are in
effect dictating policy as opposed to defending the constitution (Hanushek, 2006a;
Hanushek, 2006b; Hanushek & Lindseth, 2009). Hanushek believes that the various
costing out studies conducted in response to court decisions are flawed in both design and
execution (Hanushek, 2006b). He argues that adequacy studies do not always relate to
improved student outcomes and that such studies ought to be interpreted at political
documents, not scientific studies (Hanushek, 2006b). In Courting Failure: How School
Finance Lawsuits Exploit Judges’ Good intentions and Harm or Children, Hanushek
(2006a) argues that courts have moved into an arena in which they are unprepared as they
lack the relevant expertise in school funding. Furthermore, he views the various adequacy
66
studies commissioned by policymakers as political reactions lacking scientific designs
and reliability across various states (Hanushek, 2006a).
While Hanushek views various adequacy studies as possibly harming children
(Hanushek, 2006b), Rebell (2007) maintains that adequacy studies are a key part of
school reform and represent a vast improvement over how school policy has traditionally
been carried out in the past. Baker (2005) echoes Rebell’s sentiments and demonstrates
that it is possible for states to use cost analysis procedures to estimate the resources
necessary to support all students reaching designated performance standards and
improved student outcomes. Baker (2005) argues that the courts will be necessary agents
in the process of moving toward adequate funding systems and in effect improving
schools
Adequacy models seek to provide districts and schools with the resources
necessary to achieve specific educational outcomes (Odden et al., 2003; Odden & Picus,
2008; PACE 2006). Alexander, (2004) describes state accountability programs and
NCLB as requiring educators to “do more” without providing any additional resources or
direction as to how to improve student achievement. He continues by stating it is vital
these outcomes (in the form of standards and benchmark proficiency standards) do not
become watered-down over time and argues that the best way to prevent standards from
gravitating toward “minimal expectations” is to ensure schools are adequately funded
(Alexander, 2004).
Four approaches to adequacy. Adequacy of funding refers to the amount of
funding required to accomplish the goals set forth by an education system (Bhatt &
67
Wraight, 2009). Four main approaches have emerged to help determine an adequate
funding level necessary to achieve desired student outcomes: (1) the successful school
district approach; (2) the cost function approach; (3) the professional judgment approach
and; (4) the evidence-based approach (Baker, 2005; Bhatt & Wraight, 2009; Baker et al.,
2008; Hanushek, 2006a; Hanushek & Lindseth, 2009; Imazeki, 2008; Odden et at. 2003,
PACE, 2006; Rebell, 2007). According to Odden, (2003) designing an adequate school
finance system requires states to identify both adequate expenditure levels for the typical
student in the typical district while accounting for sufficient adjustments for different
student needs. Currently, no single approach is dominant throughout the country. Each
approach outlined can produce varying dollar amounts and often produce substantial
increases to funding beyond current educational funding levels (Baker et al., 2008;
Imazeki, 2008; Odden, 2003; PACE, 2006). Details about each approach are described
below.
The successful school district approach. The successful school district approach
identifies districts that have been successful in achieving student outcomes meeting state
performance standards and then sets the adequacy level at the weighted average of the
expenditure per pupil of those districts (Baker et al, 2008; Bhatt & Wraight, 2009;
Hanushek & Lindseth, 2009; Odden, 2003; Odden & Picus, 2008; Picus, 2006; Rebell,
2007). Developed by John Augenblick and John Myers, the successful school district
model identifies school districts that are meeting the established goals of the state
standards and uses their expenditure level as a baseline estimate of the cost to provide an
68
adequate education (Rebell, 2007).The key to this model is being able to determine the
differences in how successful and unsuccessful districts spend their money.
This model is easy to explain to policymakers and ultimately the public.
Successful school district studies can be completed relatively quickly and are
comparatively less expensive to conduct (Rebell, 2007). However, they often only use
homogenous demographics and spending patterns that are below the state average, often
excluding both small rural and large urban districts into the estimate (Odden, 2003;
Odden & Picus, 2008; Rebell, 2007). The successful school district approach has
difficulty determining how to calculate the extra resources needed to educate students
with special needs (Odden and Picus, 2008; Rebell, 2007). Further problems with this
approach include that each districts’ identified definition of success results in
considerable variation in the amount of resources called for to eliminate the achievement
gap (Rebell, 2007). Odden and Picus (2008) indicate that successful district studies tend
to be generalizable to average sized, suburban districts that serve homogenous
populations; thus they are difficult to apply to large, diverse, urban school districts.
In California, Perez et al. (2007) used a successful school district approach to
study several schools identified as “Beating the Odds” (BTO) and compared them with
“Low Performing” (LP) schools. This study was part of the Getting Down to Facts
project that was a major part of the Governor’s Committee on Education Excellence and
incorporated a successful school district approach by comparing the spending levels
between LP and BTO schools. The researchers found it difficult to identify BTO and LP
schools due to test score instability over the years. Perez et al (2007) found that high
69
poverty schools in both groups spent more per pupil than average, but that high poverty
BTO schools spent slightly more per pupil. The data revealed there was little relationship
between school resources and academic success. They conclude that resources only make
a difference if they are utilized properly by qualified people and are focused on
improving student achievement (Perez et al., 2007). Although the study identified a few
factors related to increased student performance, it lacks specificity on exactly what the
BTO schools are doing differently with roughly the same amount of resources as other
schools to have earned the Beating the Odds designation. Successful school district
adequacy approaches have been conducted and/or used by policymakers in several
additional states including Illinois, Maryland, Mississippi, Ohio and California (Odden,
2003; Perez et al., 2007).
The cost function approach. The cost function approach relies on current
spending and achievement patterns across all schools in a state to predict optimum
spending solutions. The cost function model uses advanced statistical techniques like
regression analysis, to determine what resources are required for students to reach a
certain performance level (Baker et al, 2008; Bhatt & Wraight, 2009; Hanushek &
Lindseth, 2009; Odden, 2003; Odden & Picus, 2008; Picus, 2006; Rebell, 2007).
Applying complex econometric models used in other industries, cost function studies
attempt to determine how spending levels affect various outcomes with varying student
characteristics. It requires more rigorous analysis than the successful schools approach
and it goes a step further by trying to determine costs for different student groups (Baker
et al., 2008; Rebell, 2007). Cost function analyses require large data sets on both
70
spending and achievement in order to estimate appropriate resource allocation patterns
(Baker et al., 2008; Imazeki, 2007; Odden and Picus, 2008, Rebell, 2007). According to
Baker et al. (2008), cost function’s analysis strength is that it is specifically designed to
measure district by district differences in cost associated with the geographic price
variations, economies of scale and variations in student needs. Thus, it can provide both a
basic level of spending while making cost adjustments that can be applied to the base
given different scenarios.
Cost function approaches are limited to the amount and quality of data available
to them. In addition, cost functions analysis assumes that schools and districts organize
their resources in order to maximize student performance; it assumes resources are
utilized effectively and efficiently (Baker et al., 2008; Imazeki, 2007; Odden and Picus,
2008, Rebell, 2007). Cost function approaches typically fail to identify what schools
should do with resource allocations to improve student learning (Baker et al., 2008;
Odden, 2003). Critics argue that cost function studies fail to provide usable information
about the resources and strategies necessary to help a given student achieve a set outcome
(Baker et al., 2008; Hanushek, 2006a; Hanushek & Lindseth, 2009; Odden, 2003).
As part of California’s Getting Down to Facts project, Imazeki (2007) conducted
an econometric cost function analysis to quantify the relationship between student
outcomes and costs for districts with a variety of characteristics. The study utilized
spending data based upon per pupil general fund expenditures, student demographics,
enrollment data, and achievement data in the form of district Academic Performance
Index scores and California Standards Test results in English Language Arts and
71
mathematics. Although every study within the various Getting Down to Facts adequacy
study found that additional resources were necessary in order to make California’s
educational resource allocation adequate, the cost function approach called for the least
amount (Imazeki, 2007). The cost function approach estimates that California districts
would need an additional $1.7 billion in order for all of them to reach an API score of
800 (Imazeki, 2007). Imazeki (2007) found that California significantly underfunds
districts with the highest concentrations of students in most need of additional help and
resources.
Professional judgment approach. The professional judgment approach asks a
group of educational experts to identify effective educational strategies for all grade
levels and for students with various special needs (Baker et al, 2008; Bhatt & Wraight,
2009; Hanushek & Lindseth, 2009; Odden, 2003; Odden & Picus, 2008; Picus, 2006;
Rebell, 2007). The experts delineate the ingredients required for each, assign a price tag
to each ingredient and sum everything up to obtain a total expenditure per pupil (Odden,
2003; Odden & Picus, 2008). This strategy can be adjusted for differences in price
points due to geographical regions, district size, differences in student needs and more.
An advantage of this approach is that it identifies what is required to produce the desired
student outcomes. According to Rebell (2007), the major advantage of the professional
judgment studies are that they; (1) pool the collective wisdom of a group of highly
qualified education professionals, and (2) the groups can more properly assess the
desired outcomes of school that are not easily measured by standardized test scores.
Unlike the successful school district approach and the cost function approach, the
72
professional judgment approach lacks a direct connection to student performance
(Odden, 2003). The composition of the educational experts determines the reliability of
other estimates and the accuracy of their recommendations. Also problematic with the
professional judgment approach is that panel experts can vary from panel to panel and
the recommendations made by the panel can be subjective and inconsistent (Rebell,
2007). Professional judgment studies have been used in many states including, Kansas,
Maryland, Oregon, and Wyoming.
Chambers, Levin, and DeLancey (2007) conducted a professional judgment
study in California as part of California’s Getting Down to Facts project. Two panels of
educators were developed, each consisting of a superintendent of schools, principals
from each school-level, teachers, and specialist. The panels were charged with the task
of identifying what programs and resources would be necessary for a “typical”
California school to achieve the identified performance outcomes by all students within
that school. Both panels were informed to modify their initial plans to accommodate for
schools serving large populations of diverse students (EL students, low-SED students,
students with disabilities etc.). The researchers then assigned a cost to each program
that the panels specified. Chambers et al., (2007) adequacy study found that per-pupil
spending would need to be increased between 53% and 71% to meet a level of adequacy
for all students within California. This increase would require an additional expenditure
of $24 to $32 billion dollars and ranges from $22.3 to $30.3 billion more than the cost
function approach also studied in the Getting Down to Facts project (Chambers et al.,
2007; Imazeki, 2007).
73
Evidence-based approach. The evidence-based approach, also known as the
Evidence-Based Model (EBM), identifies a comprehensive set of school-level elements
identified through empirical research that are necessary to deliver a high-quality
comprehensive instructional program (Baker et al, 2008; Bhatt & Wraight, 2009;
Hanushek & Lindseth, 2009; Odden, 2003; Odden & Picus, 2008; Picus, 2006; Rebell,
2007). The evidence-based approach incorporates evidence from the following three
resources:
1) Research with randomized assignment to the treatment;
2) Research with other types of controls and procedures that can help separate the
impact of the treatment;
3) Best practices either as codified in a comprehensive school design or from studies
of impact at the local district or school-level.
This approach attempts to provide schools with specific details about educational
strategies shown by research to be effective in raising student achievement. Additionally,
it aims to provide schools with clear information about what resources should be used to
implement those strategies (Odden & Picus, 2008; Odden et al., 2005). After the
research-based elements are identified, this model determines an adequate expenditure
level by assigning a price to each element and aggregating it to a total cost. The evidence-
based approach, developed by Lawrence Picus and Allan Odden, has been used to
evaluate and develop adequacy studies in Kentucky, Arkansas, Arizona, South Dakota,
Wyoming and Washington (Odden & Archibald, 2009; Odden & Picus, 2008). Strangely,
the evidence-based approach was the only of the four major adequacy models not applied
74
to California’s Getting Down the Facts project. However, the evidence-based approach
was the primary framework used throughout this investigation of six California schools.
Since the Evidence-Based Model was a primary framework utilized for this study, section
six of this chapter will further examine Odden and Picus’ (2008) Evidence Based Model
in greater depth.
Hanushek is a harsh critic of the evidence-based approach to adequacy, stating
that this model is designed to maximize expenditures, not student outcomes (Hanushek,
2006b; Hanushek & Lindseth, 2009). He argues that consultants of the Evidence-Based
Model fail to provide an explicit projection of how achievement would improve with
their model schools (Hanushek, 2006b). Hanushek further states that it is difficult to
measure the effectiveness of the various expenditures since an entire district or site must
adopt the model and also questions the research used to back the various strategies the
model advocates (Hanushek, 2006b, Hanushek & Lindseth, 2009). According to
Hanushek, (2006b) there is a substantial body of work across decades of research that
shows, contrary to widely help popular beliefs, a consistent relation between school
resources and student achievement is lacking.
Archibald, (2006) provides evidence to counter Hanushek’s premise that
resources are not related to school achievement. In a study conducted in Nevada,
Archibald (2006) indicates that increases in per pupil spending led to positive
achievement in both mathematics and reading, with results in reading being statistically
significant. The increases were not just a result of simply providing schools with more
money; instead, increases in student performance were a result of using resources more
75
thoughtfully and purposefully (Archibald, 2006). Additional resources were used to
increase teacher training, focus on improving weak academic areas, and developing ways
to mitigate certain student characteristics such as poverty (Archibald, 2006). Slavin
(1999) acknowledges that while increased dollars do not magically transform themselves
into greater learning, it is evident that money can make a difference if spent on specific
programs or other investments known to be effective. Evidence across research studies
seems to conclude that what matters more than adding additional resources to improve
student outcomes , is how resources are combined with educational strategies that have a
clear focus on how to improve student achievement and how the resources are used more
effectively to increase the academic proficiency of all students (Archibald, 2006;
Hanushek, 2006a; Hanushek & Lindseth, 2009; Loeb et al., 2007; Odden, 2009, Odden &
Archibald, 2009; Odden and Picus, 2008; PACE, 2006; Hanushek, 1996, 1997, 2006a;
Hanushek & Lindseth, 2009; Hanushek & Rivkin, 1997; Marzano, 2003; Loeb et al.,
2007; Odden, 2003, 2009; Odden & Archibald, 2009, 2000; Odden et al., 2008; Odden et
al., 2007; Odden et al., 2005; Odden & Picus, 2008; PACE, 2006; Picus et al., 1996a;
Perez et al., 2007; Rebell, 2007; Slavin, 1999, 2005; Williams et al., 2005).
Using Educational Resources More Effectively to Improve Student Performance
As previously outlined, California’s academic performance has yet to ensure all
students master rigorous standards and perform at high achievement levels. According to
Odden, (2009) the primary goal of education in the twenty-first century is to educate the
vast majority of all children to rigorous performance standards, including children from
low-income, minority and other disadvantaged groups. This goal includes having children
76
learn to “world class” performance standards where they are adept at problem solving,
thinking critically and communicating (Odden & Archibald, 2009). There is growing
knowledge about what can be done by schools and districts to dramatically improve
student learning. Reeves, (2006) argues that there is a tremendous amount of things
educators can do to improve student achievement and to mitigate some of the student
characteristics that influence poor student performance. The education system will need
to implement multiple and complex changes in order to meet these lofty goals (Hanushek,
2006a; Hanushek & Lindseth, 2009; Loeb et al., 2007; Odden, 2009, Odden & Archibald,
2009; Odden and Picus, 2008; PACE, 2006; Reeves, 2006). Often, the critical question is
not about the risk of change, but instead, the risk associated if the system fails to change
(Reeves, 2006). Changes will be necessary in school and classroom organization,
curricular programs, assessment practices, pedagogy, professional development, learning
time, technology, recruitment and retention of quality personnel, and incentives that
encourage continuous improvement (Loeb et al., 2007; Odden, 2009, Odden &
Archibald, 2009; Odden and Picus, 2008; PACE, 2006; Reeves, 2006; Weiss, 2007).
Equally important, the education system will need to use its resources more
productively and effectively (Archibald, 2006; Hanushek, 2006a; Hanushek & Lindseth,
2009; Karoly, 2001; Loeb et al., 2007; Odden, 2009, Odden & Archibald, 2009; Odden
and Picus, 2008; PACE, 2006). According to McEwan and McEwan (2003), thoughtful
consideration of cost is essential to making good, research-based educational decisions.
The purpose of any cost analysis is to determine if the program or intervention is
worthwhile; is it cost-feasible and is it cost-effective. Educators need to invest in what
77
has proven to demonstrate success and utilize a set of core research-based strategies
(Clark & Estes, 2002; Odden, 2009, Odden & Archibald, 2009; Odden and Picus, 2008;
Tucker, 1996). The purpose of this section is to review effective research-based
educational elements that have led to improved student learning. Given the breathe of
research in this area, frameworks by Odden (2009) and Odden and Archibald (2009) on
how various schools and districts across the nation doubled student performance were
adapted and compiled as a framework to synthesize the literature. The change process
will require educators to align resources more effectively with proven educational
strategies to improve student performance. Before policymakers are willing to allocate
additional resources into the education system, they will likely want to ensure that
educators are using current resources more effectively and in ways that efficiently
produce increased student achievement (Odden & Archibald, 2009). The following six
evidence-based strategies have been used to structure effective resource allocation
practices in schools and will be addressed in this section: (1) setting high expectations for
student learning, (2) data-based decision making, (3) professional development, (4)
effective instruction, (5) extending learning opportunities for struggling learners, and (6)
creating a culture of collaborative and distributive leadership.
Goal setting and high expectations for student learning. Setting high and
ambitious goals, regardless of a school’s current performance level or student
demographics has been an effective strategy various schools have employed to
dramatically improve student outcomes (Odden, 2009; Odden & Archibald, 2009; Duke,
2006; Hattie, 2009; Marzano, 2003; Marzano, Waters & McNulty, 2005; Reeves, 2000;
78
Weiss, 2007). A key aspect of schools and districts that make a difference in student
performance is that they set goals beyond the marginal or even reasonable level and
instead set goals to make large differences in student performance (Odden, 2009; Odden
& Archibald, 2009; Reeves, 2000). Setting ambitious goals go beyond setting “stretch
goals” or getting the “bubble” kids over the proficiency bar, instead ambitious goals
focus on educating all students to proficiency, focusing on educating a large portion of
students to advanced levels of performance, or having all students pass end-of-course
examinations. In order to make such goals come to fruition, teachers and administrators
must truly believe that all children can learn at high levels (Blankstein, 2004; DuFour et
al., 2006; Duke, 2006; Odden, 2009; Odden & Archibald 2009; Marzano, 2003, 2007;
Weinstein, 2002; Weiss, 2007). However, there is much research that shows teachers and
other school staff often place lower expectations on students who have traditionally
performed poor in the past, including minority, low SED and EL students (Cotton, 1989;
Odden, 2009; Odden & Archibald, 2009; Marzano, 2007; Weinstein, 2002). The result of
such action is it usually perpetuates continued poor academic performance and a
widening of the achievement gap between their more advantaged peers.
Effect of teacher expectations. A teacher’s beliefs about students’ chances of
success in school influence the teacher’s interactions with students, which in turn
influences students’ academic achievement. The effect of teacher expectations on student
achievement is one of the most well-researched aspects of classroom instruction (Cotton,
1989; Marzano, 2007; Weinstein, 2002). Research supports teachers form opinions or
expectations of student performance early on in the school year. Based on these
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expectations, teachers often treat high-expectation students differently from low
expectation students (Cotton, 1989; Marzano, 2007; Weinstein, 2002). Teacher behavior
differs among high and low expectation students in both the teacher’s affective tone and
quality interactions with students. Students interpret these encoded messages as signals
for how they are expected to perform and behave in class (Marzano, 2007; Weinstein,
2002). High-expectation students usually achieve at or near their potential, while low-
expectation students do not gain as much as they could have gained if they were taught
differently. Once a teacher has developed low expectations for a student, it is very
difficult for the teacher to change his or her behavior toward the student (Cotton, 1989;
Marzano, 2007; Weinstein, 2002).
Goal setting and feedback. According to Odden, (2009) schools that doubled
student performance not only believed that all children can learn to high levels, including
minority, low SED and EL students; they also set high goals for student achievement and
educated all students to high performance levels. Schools that dramatically improve
student outcomes to high levels of achievement view their mission as teaching their
students to high levels, and setting high goals for student performance regardless of the
socio-demographic conditions within in their school and community (Blankstein, 2004;
Duke, 2006; Hattie, 2009; Odden, 2009; Odden & Archibald, 2009; Marzano, 2003;
Reeves, 2000; Walberg, 2006; Woody & Henne, 2006). Schools and districts that set high
goals and do not meet them in one year do not blame the students or their home-life,
instead they take responsibility themselves, modify the curriculum program and seek to
reverse the drop next year (Blankstein, 2004; Odden, 2009, Odden & Archibald, 2009;
80
Reeves, 2000; Walberg, 2006; Woody & Henne, 2006). Instead, they believe they can
attain these goals and they work relentlessly to attain them without excuses.
In addition to defining student expectations, teachers must provide timely and
effective feedback to students along the way and encourage students to establish and
monitor their own learning goals (Marzano, 200, 2007). Setting and maintaining high
academic standards must be a continuous process and communicated throughout the
school community (Odden, 2009). The standards must articulate clearly defined student
expectations if student achievement is to be improved (Resnick & Hall, 2005). Marzano
(2003, 2007) reviewed various research studies on the effects of goal setting in classroom
instruction. An analysis of the results showed that the average score in classes where
goals setting was effectively employed was almost twenty-one percentile points higher
than the average score in classes where goal setting was not incorporated (Marzano,
2003, 2007). Additionally, a meta-analysis of eleven studies on the impact of goal setting
on student achievement conducted by Hattie (2009) found a strong relationship between
goal setting and improved student learning. Marzano, (2007) further reported that goal
setting and feedback used in tandem was more powerful than either of them used alone.
Effective feedback is specific and formative in nature (Marzano, 2003, 2007). Providing
feedback to students and using the feedback to inform instruction involves the integration
of data-based decision making. The next section describes how data-based decision
making can be used to promote improved student performance.
Data-based decision making. According to Stecher and Kirby (2004), setting
goals for desired levels of student performance combined with using assessments for
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measuring goal attainment enables school systems to more accurately judge success.
Stiggins (2002) defines assessment, at least in part, as the process of gathering
information to inform instructional decisions. Unless a school employs assessments that
are specific to the curriculum taught, it cannot accurately determine how well its students
are learning (Marzano, 2003). Odden (2009) argues that while the popular trend in
education circles is to complain about the amount of testing in schools, schools that are
doubling student performance and experiencing dramatic improvements in student
outcomes are actually adding additional layers of assessments. High performing schools,
especially high-performing, low-poverty schools are immersed in a culture of continuous
improvement, incorporating multiple strategies to make decisions based on data rather
than on intuition (Blankstein, 2004; Datnow, et al., 2007; DuFour, et al., 2006; Stiggins,
2002; Stiggins & DuFour, 2009; Walberg, 2006; Woody & Henne, 2006; Williams et al.,
2005; Supovitz & Taylor, 2003;Togneri & Anderson, 2003). As a continuous
improvement educational system, both student knowledge and student performance needs
to be measured often and utilized to improve practice.
Johnson, (2002) emphasizes the importance of using relevant data as the basis for
making appropriate decisions to improve student achievement. Data-based decision
making involves the systematic collection and analysis of various types of data to guide
decisions that promote student achievement. Data can help schools identify strategies
that are working, solve problems and identify the best use of resources (Johnson, 2002).
However, teachers and administrators must know how to appropriately use and interpret
the data to make appropriate decisions. Using data-driven decision making can be a
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difficult task and requires a commitment from school and district leadership (Blink,
2007). With the multitude of data sources available to schools, the principal, along with a
data leadership team should decide what types of useful data to collect and should receive
training on proper data analysis and use (Johnson, 2002). Research indicates that data-
based decision making is effective if it incorporates professional development as part of a
systematic reform strategy teaching educators how to utilize data effectively and
purposefully (Datnow, Park, & Wholstetter, 2007; Feldman, Lucey, Goodrich, & Frazee,
2003; Fullan, 2003, 2005, 2007; Johnson, 2002; Mohrman, 1994;Stiggins, 2002).
Formative assessments. Formative assessments represents one of the most
powerful instructional tools available to a teacher for promoting student achievement
(Black & Williams, 1998; DuFour et al., 2006; Odden, 2009; Odden & Archibald, 2009;
Marzano, 2003; Marzano, 2007; Stiggins & DuFour, 2009). Formative assessments are
typically more diagnostic in nature and given at periods within a nine week instructional
period (Odden, 2009). When teachers have detailed data through formative assessments,
they are better equipped to design instructional strategies and pedagogy that are in tune to
the exact learning status of the students in their own classroom and school (Odden, 2009;
Reeves, 2006; Stiggins, 2002). As a result of synthesizing more than 250 studies, Black
and William (1998) state the following about the power of formative assessments: “The
research reported here shows conclusively that formative assessment does improve
learning. The gains in achievement appear to be quite considerable, and as noted earlier,
amongst the largest ever reported for educational interventions (p.61).” Furthermore,
while examining over 800 meta-analysis research studies on factors that influence student
83
learning, Hattie (2009) found that a teacher’s use of data to determine future instruction
was strongly related (effect size of 0.90 standard deviation) to improving student
achievement. Stiggins (2002) argues that assessments can contribute to the development
of effective schools in ways that have largely been ignored in the evolution of standards,
assessment and accountability. He makes the distinction between assessment of learning
and using assessment for learning. Additionally, Marzano (2007) found that the
frequency of formative assessments is related to improved student outcomes. Research
found that two formative assessments per week resulted in an effect size of 0.85 or a
percentile gain of thirty points (Marzano, 2007). According to Stiggins and DuFour,
(2009) teachers and schools can use formative assessments to:
• Identify student understanding
• Clarify what comes next in their learning
• Trigger and become part of an effective part of intervention for struggling
students
• Inform and improve the instructional practice of individual teachers or
teams
• Help students track their own progress toward standard mastery
• Motivate students by building confidence in themselves as learners
• Fuel continuous improvement processes across staff by driving a school’s
transformation.
Building teacher capacity for effective data use seems to go hand-in-hand with
building instructional knowledge and skills. Although the use of data could pinpoint areas
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for improvement and areas of strength, data alone cannot improve student learning
(Datnow et al., 2007; Johnson, 2002; Stiggins & DuFour, 2009). Professional
development is needed for teachers and administrators to develop the skills necessary to
take the information gleaned from both benchmark and formative assessments and design
instructional strategies that target the varying needs of the students in their classrooms.
Without professional development to build instructional knowledge for re-teaching,
differentiating instruction, and scaffolding students, teachers lack the tools to utilize data
to make improvements (Datnow et al., 2007). The next section outlines the critical role of
professional development and it’s implication on improving student performance by
improving instruction.
Professional development. Improving instruction by improving professional
learning for educators is one of the most important factors that leads to improved student
learning (Wei, Darling-Hammond, Andree, Richardson, & Orphanos, 2009; Elmore,
2000; Odden, 2009; Odden & Archibald, 2009; Odden et al., 2007; Odden and Picus,
2008; Reeves, 2010). In order to improve student achievement, educational organizations
must continuously strengthen their instructional core by increasing teachers’ skills and
knowledge, engaging students in learning and ensuring the curriculum taught challenges
students academically (Childress, Elmore & Grossman, 2006; Clarke & Estes, 2002). A
school’s success is critically dependent on their ability to provide intensive and ongoing
professional development for both its teachers and principals (Elmore, 2000). The
National Staff Development Council recently analyzed numerous research studies on
professional development and identified several key findings necessary for professional
85
development to be effective (Darling-Hammond et. al, 2009). Effective professional
development should be intensive, ongoing, connected to practice, focused in on teaching
and learning of specific academic content, and connected to other school goals.
Wei et al. (2009) discovered that it takes teachers nearly eighty hours or more of
professional learning each year to improve their skills, change their practice and
ultimately improve their students’ academic achievement. Studies of professional
development that lasted fourteen or fewer hours showed no impact on student learning.
The largest effects were found when professional development programs offered between
thirty and one hundred hours spread out over a six to nine month period of time (Wei et
al., 2009). According to Datnow (2005), any change is only considered institutionalized
after it becomes second nature to the staff and is no longer thought of as a special project
or an effort for improvement. Therefore, staff development programs should be
systematic and attempt to bring about deliberate change; change in the classroom, change
in beliefs and attitudes, and change in student learning outcomes (Elmore & Burney,
1999; Guskey, 1986; Reeves, 2010).
A literature review of various studies on professional development by Odden
(2009) and Odden and Picus (2008) have led to the identification of six structural features
of effective professional development programs:
1. Professional development should be school based, job embedded, and focused
on the curriculum taught over an ongoing period of time (Darling-Hammond
& McLaughlin, 1999; Elmore & Burney, 1999).
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2. The duration of the professional development cannot be a one-time workshop,
and should take place over at least 100 hours and closer to 200 hours (Birman,
et al., 2000; Corcoran, 1995; Desimone, Porter, Garet, Yoon, & Birman, 2002;
Odden & Picus, 2008; Reeves, 2010).
3. Research suggests (Birman, et al., 2000; Elmore, 2002) that effective
professional development should be organized to include collective
participation of teachers from the same school, department or grade level.
Effective professional development should be organized around groups of
teachers that would over time include the entire faculty.
4. Effective professional development should have a content focus which leads
to teachers expanding their own content knowledge as well as understanding
how students learn that particular content. As academic curriculum standards
as expanded the scope and complexity of content, teachers (especially
multiple-subject elementary teachers) require deeper content knowledge
(Corcoran, 1995; Darling-Hammond & McLaughlin, 1999; Elmore, 2002;
Reeves, 2010).
5. The professional development should provide teachers the opportunity to
actively engage in the meaningful analysis of teaching and learning (Birman,
et al., 2000; Corcoran, 1995). Professional development is most effective
when it includes opportunities for teachers to work directly on incorporating
the new techniques into their classroom instruction with the help of
instructional coaches (Birman et al., 2000; Corcoran; Reeves, 2010).
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6. The professional development should be clearly aligned with key parts of the
educational system such as student content, performance standards, school or
district goals, and the development of a professional community (Corcoran,
1995; Darling-Hammond & McLaughlin, 1999; Desimone et al., 2002;
Reeves, 2002).
Each of these six structural features involves resource requirements and resource
allocation. Organizing effective professional development requires a considerable amount
of time and money; thus it is critical to determine how to effectively implement
professional development given limited resources (Odden, 2009; Odden & Picus, 2008).
Odden’s (2009) review of the literature identifies three effective strategies.
Instructional coaches. Research demonstrates there is strong evidence that
professional development through coaching promotes student learning in schools and
builds a school’s capacity for transformation (Creasy & Paterson, 2005; Wei et al., 2009;
Fermanich, 2002; Knight, 2006; Reeves, 2010). Teachers who receive coaching are more
likely to incorporate the desired instructional practices and apply them more
appropriately than are teachers whose professional development involved more
traditional settings (Wei et al., 2009). Coaching involves a collaborative union in which
one person supports another to further develop their understanding and practice in an area
defined by individual need and interest. Coaching focuses on in-depth development of
specific knowledge, skills and strategies and is informed by evidence and ongoing
feedback (Wei et al., 2009; Knight, 2006). Just as ongoing, timely and specific feedback
is critical for students to improve performance (Marzano, 2003, 2007), ongoing and
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specific feedback to teachers is vital toward improving instruction and pedagogy (Wei et
al., 2006; Odden, 2009; Reeves, 2010). Creasy and Paterson (2005) describe effective
coaching as dependent on the learner’s willingness to: (1) understand their own learning
needs; (2) reflect on their current practice; (3) take an increasingly more active role
(personal ownership) in their learning; and (4) act on the strategies learned to improve
student learning. According to Knight (2006), schools must (1) provide coaches sufficient
time to work with teachers; (2) continue to use proven research-based interventions; (3)
allow coaches to build trust with teachers as well as principles; and (4) provide on-going
professional development to the coaches as well. Effective staff development models
ought to involve intensive opportunities in specific content areas for professional
learning, coupled with coaching support that ensures the learning translates into effective
instructional implementation; ultimately improving student outcomes (Creasy &
Paterson, 2005; Wei et al., 2009; Knight, 2006; Odden, 2009; Odden & Picus, 2008;
Reeves, 2010).
Pupil-free days. As discussed by Odden, (2009) teachers require student-free
days to receive professional development. This can be accomplished in two ways: (1) hire
substitute teachers and provide professional development during the normal school year,
or (2) extending the school year for teachers to include pupil-free days. The latter strategy
is more popular in the successful schools outlined by Odden (2009) as it avoids
disruption of the instructional time. Both options have potential benefits and drawbacks,
but the cost remains relatively the same (Archibald & Gallagher, 2002; Gallagher, 2002;
Miles, Odden, Fermanich, Archibald, & Gallagher, 2004; Odden, 2009; Odden,
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Archibald, Fermanich, & Gallagher, 2002). Best practices by schools dramatically
improving student outcomes reveals the practice of extending teachers school year by
approximately ten days devoted solely for professional development purposes (Miles et
al., 2004; Odden, 2009; Odden & Archibald, 2009; Archibald & Gallagher, 2002; Odden
et al., 2002; Odden & Picus, 2008).
Collaborative time during the regular school day. The primary way to provide
job-embedded professional development is to provide a portion of the instructional day
for planning and preparation (Odden, 2009; Odden & Picus, 2008). When looking at
successful, high achieving countries, a common characteristic found is that professional
learning is built into the teacher’s regular workday (Wei et al., 2009). This is the time
when teacher teams analyze formative assessments, create instructional units, plan
interventions, meet with instructional coaches and reflect on the success of the
instructional lessons taught (DuFour et al., 2006; Odden, 2009; Odden & Picus, 2008).
Providing time during the school day for teachers to engage in purposeful collaboration
with a focus on learning to improve practice and student performance is critical to a
learning organization (DuFour et al., 2006). The primary purpose of any professional
development program is to improve student learning by improving instruction. The next
section outlines relevant literature on effective instruction.
Effective instruction. Togneri and Anderson (2003) studied various high
performing schools and found that one of the major factors essential for school
improvement involves putting in place a system-wide approach to improving instruction.
Successful schools put in place system-wide approaches to improving instruction that
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articulate content and provide instructional support while promoting greater internal, as
opposed to external, accountability (Elmore, 2003; Togneri & Anderson, 2003). The
standards-based reform movement infers that the goal to raising student achievement is
through effective instruction and a guaranteed curriculum to all students. (Birman et al.,
2000; Marzano, 2003). Marzano (2003) describes curriculum and instruction as all
possible learning opportunities provided by a school or community. Mayer (2008)
describes effective instruction that is focused on a learner-centered approach in which the
learner is at the heart of all learning. There are two overarching goals in a learning
centered approach: (1) to understand the cognitive process and knowledge used by
learners in carrying out academic task, and (2) to understand how to help students
develop the cognitive processes used by skilled practitioners to perform academic task
(Mayer, 2008). According to Mayer (2008) instruction refers to the teacher’s construction
of environments for the student, where such environments are intended to facilitate
change in the learner’s knowledge base. Learning refers to lasting changes in the
learner’s knowledge based upon the person’s experience (Mayer, 2008). Most
breakdowns in student learning are often the result of poor instruction and curricular
design (Anderson & Krathwohl, 2001; Marzano, 2003; Mayer, 2008).
Guaranteed and viable curriculum. Marzano (2003) ranks having a guaranteed
and viable curriculum as the single most influential school level factor on student
achievement. Simply teaching state standards does not ensure a guaranteed and viable
curriculum for all students as often there is a discrepancy between the intended
curriculum (state standards), the implemented curriculum (what is actually taught) and
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the attained curriculum (what students actually learn) (Marzano, 2003). Viability
requires educators ensuring the articulated curriculum can be adequately learned in the
time available. However, there is not enough time during the instructional year for
teachers to adequately address the breathe of content prescribed in the state standards
(Marzano, 2003). Successful schools that have dramatically improved student outcomes
have worked tirelessly to create both a guaranteed and viable curriculum by using a laser
like focus on identifying the essential learning students must master in a given subject
and at a given grade level (DuFour et al., 2006; Odden, 2009; Odden & Archibald, 2009;
Marzano, 2003, Reeves, 2002; Williams et al., 2005; Woody and Heene, 2006). This
process requires educators to examine the relative significance of each standard to decide
which components of the standards are critical for student mastery. Reeves, (2002)
provides a series of three reflective questions to facilitate this process: (1) Does it have
endurance? Will we expect students to retain the knowledge and skill over time? (2) Does
it have leverage? Will proficiency in this standard help students in other areas of the
curriculum? (3) Does it develop students’ readiness for success at the nest level? Is it
essential for success in the next unit or grade level? Integrating the findings of Marzano
(2003) and Langer (1999), curricular an instructional best practices implemented at the
school level should also include: (1) clearly stated learning objectives for each lesson or
course; (2) multiple exposure of skills and knowledge which are then repeatedly
introduced in a variety of lessons across a variety of curricular areas; and (3) structured
learning that leads to transfer of knowledge through strategies for thinking.
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Effective instructional strategies. Marzano Pickering and Pollock (2001) outline
specific instructional strategies that research have shown over the years to improve
student achievement. Through their analysis, they identify nine instructional categories
shown to improve student achievement along with the effect size for each category. Table
2.5 provides an overview of the nine categories and includes specific teacher behaviors
associated with each category. As illustrated in Table 2.5, having students engage in
complex thinking by identifying similarities and differences had the largest impact on
improved student learning with an effect size of 1.61. The effect size reports how many
standard deviations the average score in the experimental group (the group that received
the instructional strategy) is above the average score in the control group. Hattie (1992)
did a meat-analysis of over 6000 studies on eight different instructional strategies.
Tutoring and mastery learning were the instructional strategies found by Hattie (1992)
that had the strongest impact on student achievement, both with an effect size of 0.50 or a
percentile gain of nineteen.

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Table 2.5: Instructional Strategies That Affect Student Achievement
Note: Adapted from Marzano Pickering, & Pollock (2001).
Instructional
Category
Average
Effect Size
Specific Behaviors
Identifying similarities
and differences
1.61
• In-class assignments and homework involving
comparison and classification, and metaphors and
analogies
Summarizing and note-
taking
1.0
• Asking students to do the following:
o Generate verbal and written summaries
o Take effective and useful notes
o Revise their notes, correcting errors, and
adding information
Reinforcing effort and
providing recognition
0.80
• Recognize and celebrate learning progress throughout a
unit
• Recognize and reinforce the significance of effort
• Recognize and celebrate learning at the end of a unit
Homework and practice 0.77
• Provide specific feedback
• Assign homework for the purpose of reinforcing the
skills focused on during instruction
Nonlinguistic
representations
0.75
• Asking students to do the following:
o Generate mental images representing content
o Draw pictures or pictograms representing
content
o Construct graphic organizers
o Make physical models of content
o Revise their aforementioned representations of
content
Cooperative learning 0.73
• Organizing students into groups (either mixed-ability
or same-ability as appropriate)
Setting objectives and
providing feedback
0.61
• Setting specific learning goals and the beginning of
each unit
• Asking students to set their own learning goals and the
beginning of each unit
• Asking students to monitor their own progress
throughout a unit
• Proving summative feedback at the end of a unit
Generating and testing
hypotheses
0.61
• Engaging students in generating and testing hypotheses
through the following ways:
o Problem-solving tasks
o Decision-making tasks
o Investigation tasks
o Experimental inquiry tasks
o Systems analysis tasks
o Inventions tasks
Questions, cues, and
advance organizers
0.59
• Activate prior knowledge before presenting new
content
• Provide ways for students to organize new learning
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While research-based instructional strategies and the specific behaviors related to
the strategy provide useful suggestions to classroom teachers, effective instruction also
involves the need for effective instructional planning and lesson design. Classroom
instruction is driven by lesson objectives and standards. Anderson and Krathwohl (2001)
created a taxonomy table to provide teachers with an organizational framework for
planning and designing lesson objectives called: A Taxonomy for Learning, Teaching
and Assessing, otherwise known as the Taxonomy Table. The Taxonomy Table extends
Blooms Taxonomy (or levels of thinking) into a two-dimensional framework including
both cognitive process and knowledge (Anderson & Krathwohl, 2001).
Table 2.6: The Taxonomy Table (Taxonomy for Learning, Teaching & Assessing)
The
Knowledge
Dimension
The Cognitive Process Dimension
Remember Understand Apply Analyze Evaluate Create
Factual
Knowledge

Conceptual
Knowledge

Procedural
Knowledge

Meta-
Cognitive
Knowledge

Source: Anderson & Krathwohl (2001).
As seen in Table 2.6, the cognitive process dimension contains six categories,
with each level increasing in cognitive complexity: (1) Remember, (2) Understand, (3)
Apply, (4) Analyze, (5) Evaluate, and (6) Create. The knowledge dimension contains four
categories or types of knowledge: (1) Factual, (2) Conceptual, (3) Procedural, and (4)
Metacognitive. The knowledge categories move along a continuum from concrete
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(Factual) to abstract (Metacognitive) (Anderson & Krathwohl, 2001). Different types of
objectives require different instructional approaches, different learning activities,
different curricular materials and varying roles of both the teacher and students. The
Taxonomy Table (Anderson & Krathwohl, 2001) allows teachers to align the cognitive
processes and type of knowledge within an objective to both their instruction and the
assessments offered to their students (Anderson & Krathwohl, 2001).
The Taxonomy Table (Anderson & Krathwohl, 2001) can be used with any
instructional framework or instructional delivery model, including best practices of the
Gradual Release of Responsibility (Fisher & Frey, 2007) and Madeline Hunter’s (1984)
Lesson Design. Implementing a school-wide effective approach to instruction through the
lens of a common instructional framework that utilizes research-based instructional
strategies has been shown to improve student achievement (Anderson & Krathwohl,
2001; Birman, et al., 2000; Elmore, 2003; Fisher & Frey, 2007; Hattie, 1982; Hattie,
2009; Langer, 1999; Marzano, 2003; Marzano et al., 2001; Odden, 2009; Odden &
Archibald, 2009; Reeves, 2002; Togneri & Smith, 2003; Williams et al., 2005; Woody
and Heene, 2006). Inevitably, even the most effective schools and teachers utilizing
research-based instructional strategies will encounter students who are not achieving at
the desired performance level. When this happens, schools who are driven to ensure all
students receive an adequate education turn to further evidence-based educational
strategies by providing additional opportunities for struggling students to reach
proficiency.
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Extend learning opportunities for struggling students. Reeves (2006) argues
that while it is true that certain student characteristics influence student proficiency, it is
unfounded that student characteristics influence the opportunity for educators to influence
gains in student achievement. Various reform efforts, educational strategies and resource
allocations have been directed toward mitigating the achievement gap between groups of
students. The standards based reform movement and NCLB’s requirement that all
students be taught to the same level of expected proficiency has forced schools to
investigate successful strategies to extend the learning opportunities for struggling
students. Research suggests that improving the quality of instructional time is as
important as increasing the quantity of time in school and much less costly (Marzano,
2003). High quality teaching is of added benefit to disadvantaged groups of students who
have little opportunity to learn outside of school (Silva, 2007). However, regardless of the
quality of a school’s instructional program, most schools will have some students that
need more than the instruction already provided by the regular classroom teacher (Odden
2009).
In addition to putting the most effective teachers with the highest need students
(Blankstein, 2004; Reeves, 2006; Williams et al., 2005; Woody and Heene, 2006; Odden,
2009; Odden & Archibald, 2009; Slavin, 2005) schools that have dramatically improved
student learning and narrowed the achievement gap provided multiple strategies to help
struggling students achieve or exceed proficiency (Odden, 2009; Odden & Archibald,
2009). Typically, extra help strategies are supported from targeted categorical programs
focused on struggling students such as the federal Title I and other similar state programs
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directed to schools with students from low-SES backgrounds, students with disabilities
and EL students (Odden 2009). Odden’s (2009) review of literature and best practice on
extra help strategies for struggling students identifies three strategies that have been
shown to improve student achievement. These extra help strategies reflect a long-
recognized theory that given sufficient time, most students can learn to high standards
(Bransford, Brown, & Cocking, 1999; Odden, 2009).
Tutoring. The most intensive extra-help strategy (and often the most expensive)
provided during the school day is tutoring (Odden, 2009). In a meta-analysis of over 125
studies on effective instructional practices, Hattie (1992, 2009) found tutoring to have
one of the largest effect size (effect size of 0.50 standard deviation) on improving student
achievement. Research continues to support that individual and very small group tutoring
is one of the most effective extra-help strategies (Cohen, Kulik, & Kulik, 1982; Cohen,
Raudenbush & Ball, 2002; Hattie, 1992, 2009; Odden 2009; Odden & Archibald, 2009;
Odden & Picus, 2008; Torgeson, 2004). The strategy of tutoring is to intervene
immediately and intensively for struggling learners in the area of reading or math while
they are initially learning the concept instead of waiting and providing remedial support
after poor performance (Odden, 2009; Odden & Archibald, 2009; Odden and Picus,
2008). The success of tutoring, as is with all instruction, is dependent upon the quality of
the person providing the instruction (Odden & Picus, 2008; Rebora, 2008). According to
the research, highly-qualified certificated teachers should be the individuals providing the
additional tutoring. Instructional aides can be used only if the aid was selected according
to rigorous literacy criteria and was trained in a specific reading or math tutoring program
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(Farkas, 1998; Odden, 2008; Odden & Archibald, 2009; Odden & Picus, 2008). Richard
Arlington, Professor of education at the University of Tennessee states in an interview for
Teacher Magazine that tutoring and other Response to Instruction (RtI) models ought to
be taught by the school’s teaching staff that have the most comprehensive training on
teaching reading and literacy. He argues that instead schools often send students for RtI
or other interventions to the special education teachers whom are often the most limited
on reading instruction expertise (Rebora, 2010). Quality tutoring that will significantly
impact the achievement of struggling learners ought to be explicitly tied to the identified
learning problem, aligned to the regular instructional program and taught by a highly
skilled educator with expertise in the specific targeted area (Cohen et al., 1982; Cohen et
al., 2002; Farkas, 1998; Odden 2009; Odden & Archibald, 2009; Odden & Picus, 2008;
Torgeson, 2004; Rebora, 2010).
Extended day and extended year programs. The other two extra-help strategies to
provide struggling students with additional learning opportunities outlined by Odden
(2009) include providing academic support outside the regular school day. The first
involves extending learning beyond the normal school day. Such programs can be offered
before school, after school and on weekends (Odden, 2009). Gabrieli (2010) states that
greatest opportunity expanding learning time offers for improving academic proficiency
comes from being able to better individualize instruction by putting the right teachers
with the right students while targeting specific skills. Dobbie and Fryer (2009) studied
schools in New York City’s Harlem Promise Academies and found schools that extended
the school day and offered tutoring on Saturdays and in the summer provided fifty
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percent more time for all students and doubled the learning time for those who struggle
the most. The study found significant student achievement gains especially in students
who previously struggled (Dobbie & Fryer, 2009). However, Gabrieli (2010) argues that
modest amount of increased time will not help schools reach significant improvements in
achievement. Instead, he says schools must add a minimum of three hundred hours a
year, or an additional forty-five minutes a day while integrating the expanded time into
an overall redesign of the school schedule in order to experience the substantial benefits
of expanded time.
The second strategy for expanding time and providing additional learning
opportunities for struggling students is through providing summer school (Odden, 2009).
Summer breaks have a larger negative impact on at risk (low-SES and minority) students’
reading and mathematics achievement than for their more affluent peers (Cooper, Nye,
Charlton, Lindsay, & Greathouse, 1996; Gladwell, 2008). Studies suggest the effects of
summer school on improved student achievement is largest for elementary students when
the programs emphasize reading and mathematics and for high school students when
programs focus on courses students failed in the prior school year (Odden, 2009; Odden
& Archibald, 2009; Odden & Picus, 2008). However, Hattie (2009) reviewed various
studies on the effect summer school has on student achievement but found summer
school programs had only a slight effect (an effect size of 0.23 standard deviation) on
student achievement. Regardless, if implementing a summer school program, Borman
and Dowling (2006) have summarized six critical components to an effective summer
school program: (1) early intervention during elementary school, (2) a full six to eight
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week summer school program, (3) a clear focus on reading and math, (4) parent
involvement and participation, (5) monitoring to ensure fidelity to effective instructional
delivery in reading and math, and (6) monitoring of student attendance. While schools
have incorporated additional learning opportunities for struggling students as a strategy to
improve learning, one of the most accepted educational strategies to improve academic
achievement, especially in low-performing schools is through the creation of a
collaborative culture and distributed leadership (DuFour et al., 2006; Duke, 2006;
Blankstein, 2004; Fullan, 2003; Mandinach & Honey, 2008; Odden, 2009; Odden &
Archibald, 2009; Odden & Picus, 2008; Marzano, 2003; Reeves, 2006; Schmoker, 2006;
Stiggins & DuFour, 2009; Walberg, 2006; Williams et al., 2005; Woody & Henne, 2006).
Collaborative culture and distributed leadership. School leadership, high-
quality teaching and collaborative adult actions to improve the quality of planning,
monitoring and implementation of instruction can make a difference in student
achievement (Reeves, 2006). Effective leaders believe in holistic accountability; they
review data, make midcourse corrections and focus decision making on the aspects that
have the most leverage (Bolman & Deal, 2006; Reeves, 2006; Blankstein, 2004; DuFour
et al., 2006; Reeves, 2006). Leadership is best distributed and supported by a team with
complementary strengths working on a common vision or goal (Bolman & Deal, 2006;
Reeves, 2006). Odden (2009) found schools that doubled student performance created a
culture of shared leadership, shared accountability and a spirit of collaboration. The
essential conditions for collaboration are focused on goals and structured around data,
where teachers teach one another about effective instructional practices (Schmoker, 2004;
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Symonds, 2004). In such schools, when students did not achieve desired proficiency
levels, teachers and administration looked internally and changed their practice instead of
blaming students (Duke, 2006; Blankstein, 2004; Odden, 2009, Odden & Archibald,
2009; Reeves, 2000; Reeves, 2006; Woody & Henne, 2006). While research clearly
supports the need for schools to have strong principal leadership who put instruction and
improved practice at the cornerstone of their daily actions, (Hallinger & Heck, 2003;
Fullan, 2005, 2003, 2002; Marzano, 2003; Marzano et al., 2005; Reeves, 2006), it also
recognizes the transformational effect creating a Professional Learning Community
(PLC) can have on improving teacher effectiveness and student learning (DuFour et al.,
2006, Stiggins & DuFour, 2009; Fullan, 2003; Odden, 2009; Odden & Archibald, 2009;
Odden & Picus, 2008; Marzano, 2003; Reeves, 2006).
Mandinach and Honey (2008) found in their work with schools that PLC’s have
been one of the most significant tools in facilitating positive change toward improving
student performance at the site level. Schmoker (2006) supports this finding by stating
that, PLC’s have emerged as arguably one of the best, most agreed upon means by which
schools can strive toward continuously improving instruction and student performance.
However, the term professional learning community has become commonplace and used
to describe virtually any loose coupling of individuals sharing a common interest or
working in teams. This lack of clarity can be an obstacle when schools are trying to
implement PLC tenets (DuFour et al., 2006; Schmoker, 2006). According to DuFour et
al. (2006), PLC’s are focused and committed to the learning of each student and are
comprised of teams whose members work independently to achieve common goals
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established by the team. The rationale for any strategy for building a learning
organization centers on the notion that such organizations will produce dramatically
improved results (Senge, 1994). There are six major tenets of PLC’s: (1) a focus on
learning, (2) a collaborative culture with a focus on learning for all, (3) engagement in
collective inquiry into best practices and current reality, (4) members are action oriented,
moving quickly to turn aspirations into action, (5) a relentless commitment to continuous
improvement, and (6) results oriented. When combined within a culture of distributed
leadership, these tenets can produce dramatic improvements in student learning and
proficiency for all students (DuFour et al., 2006, Stiggins & DuFour, 2009; Fullan, 2003;
Odden, 2009; Odden & Archibald, 2009; Odden & Picus, 2008; Marzano, 2003; Reeves,
2006). Understanding educational strategies illustrated by research to improve student
learning is critical in the reform process. Equally important is aligning resource
allocations with these effective elements. The next section studies Odden and Picus’
(2008) Evidence-Based Model in greater depth and highlights how resource allocations
are aligned with the strategies shown to improve student learning outcomes.
Evidence-Based Model
According to Hirsh, (2006) the infusion of more money into poorly performing
school systems typically yields disappointing results. While meaningful reform will
likely require additional money, simply allocating more funds into poor performing
school systems is unlikely to result in substantial student learning outcome increases
(Firestone, Goertz, Nagle, B & Smelkinson, 1994; Hirsch, 2006; Loeb et al., 2007;
Hanushek, 2006a; Hanushek &Lindseth, 2009; Odden & Archibald, 2009; Odden &
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Picus, 2008). Hirsh (2006) calls for educational adequacy to move beyond the adequacy
of inputs (money and resources) into ensuring adequacy of outputs (student
performance). Money alone is not the cure and adding additional resources without
embedded reform and accountability can be disastrous. Researchers on educational
reform agree that reform efforts must address how existing resources are combined with
educational strategies that have a clear focus on how to improve student achievement and
how both current and new resources are utilized more effectively to increase student
outcomes (Archibald, 2006; Hanushek, 1996, 1997; Hanushek, 2006a; Hanushek &
Lindseth, 2009; Hanushek & Rivkin, 1997; Marzano, 2003; Loeb et al., 2007; Odden,
2003; Odden, 2009; Odden & Archibald, 2009; Odden & Archibald, 2000; Odden et al.,
2008; Odden et al., 2007; Odden et al., 2005; Odden & Picus, 2008; PACE, 2006; Picus
et al., 1996a; Perez et al., 2007; Rebell, 2007; Slavin, 1999, 2005; Williams et al., 2005).
What sets an evidence-based model apart from other adequacy approaches is that
the model is aligned with reform efforts and educational elements supported by research
and best practices toward improving student outcomes (Odden & Archibald, 2009; Odden
& Picus, 2008, Picus et al., 2008; Rebell, 2007). Odden and Picus’ (2008) Evidence-
Based Model is a framework that identifies effective, researched-based strategies and
allocates resources that are aligned with the strategies to deliver a comprehensive and
high-quality instructional program for all students within a school. Odden and Archibald,
(2009) acknowledge that the rigor of evidence supporting the effectiveness of the various
recommendations embedded within the Evidence-Based Model varies; however, the
model only includes recommendations that are supported by sound research evidence or
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best practices. As mentioned previously, the Evidence-Based Model (Odden & Picus,
2008) is based on evidence on from the following three sources: (1) research with
randomized assignment to the treatment; (2) research with other types of controls or
statistical procedures to break down the impact of the treatment; and (3) identified best
practices either as codified in a comprehensive school design or derived from studies of
impact at the local district or school level (Odden & Picus, 2008; Picus et al., 2008). The
evidence is compiled and used to identify a comprehensive set of adequate resources to
create a prototypical school. Although the degree of effectiveness of any of the individual
recommendations within the prototypical school can be debated, as can the sum total of
all the recommendations, the Evidence-Based Model (Odden & Picus, 2008) includes
many strategies that both education researchers and practitioners argue should be part of
any high performing school (Odden & Archibald, 2009).
The prior section outlined several research-based elements and best practices to
improve student performance while providing a high-quality instructional program to all
students. The Evidence-based Model (Odden & Picus, 2008) integrates many of these
elements into both the resource allocation patterns and the design of a prototypical
elementary school. Table 2.7 summarizes the elements included in the prototypical
elementary school. Actual schools vary and thus are prorated proportionally based upon
the student population and demographics of the school. The following recommendations
are specific to the Evidence Based Model (EBM) for a prototypical elementary school:
School and class size. Research suggest elementary school size in the range of
400-500 students are most effective and efficient (Andrews, Duncombe & Yinger, 2002;
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Lee & Smith, 1997; Raywid, 1998). Thus, the prototypical elementary school is based on
a K-5 model of 432 students. According to the Tennessee STAR study (Finn, Gerber,
Achilles, & Boyd-Zacharias, 2001), a large scale randomized study, students in small
classes of 15 to 1 in primary grades experienced improved academic achievement when
compared to students in regular classes. The impact of small class sizes is even larger for
students from low-income and minority backgrounds (Odden & Picus, 2008). Therefore,
the EBM recommends K-3 class size of 15 to 1. Evidence on the effect of class size for
grades 4-12 is not fully established (Biddle and Berliner, 2002), thus the EBM sets the
best practice recommendation to 25 to 1 in core subjects for grades four and above. In
many schools, less than 50% of educational resources are directly allocated to core
academic areas (Odden et al., 1995). Furthermore, from 1950 to 1995, the proportion of
core classroom teachers to certificated staff fell from 70% to 52% (Odden & Picus,
2008). Given the demands of holding all students accountable to the same performance
standards in core subject areas, the EBM allocates a majority of instructional dollars to
core instruction. Thus, the EBM protects the encroachment of elective and other non-core
classes to no more than 20% (Odden & Picus, 2008).

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Table 2.7: Adequate Resources for a Prototypical Elementary School
School Element Evidence-Based Model
School Size K-5; 432 Students
Class Size K-3: 15; 4-5: 25
Instructional Days 200, includes 10 days for intensive PD training
Kindergarten Full-day kindergarten
Administrative Support
Principal 1.0 FTE
School Site Secretary 1.0 Secretary and 1.0 Clerical
General Personnel Resources
Core Teachers 24 FTE
Specialist Teachers 20% of core teachers
Instructional Facilitators/Mentors 2.2 FTE
Extended Support
Tutors for struggling students One for every 100 poverty students: 2.16
Teachers for EL students An additional 1.0 FTE teacher for every 100 EL students
Extended Day 1.8 FTE
Summer School 1.8 FTE
Special Education Personnel
Learning & mild disabled students Additional 3.0 professional teacher positions
Severely disabled students 100% state reimbursement minus federal funds
Other Staffing Resources
Substitutes 5% of personnel resources and special education personnel
Pupil support staff 1.0 FTE for every 100 poverty students
Non-Instructional Aides 2.0 FTE
Librarians/media specialists 1.0 FTE
Resources for gifted students $25 per student
Technology $250 per pupil
Instructional Materials $140 per pupil
Student Activities $200 per pupil
Professional Development
$100 per pupil for other PD expenses - trainers,
conferences, travel, etc. not included above
Note: Adapted from Odden & Picus (2008).

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Specialist Teachers/Planning Time for Collaborative Development. Specialist
teachers are provided by the EBM to enrich student education through art, music, library
skills, and physical education while providing release time for teachers for collaborative
planning, job-embedded professional development, and ongoing curricular development
(Odden & Picus, 2008). In order to provide this planning time, 20% additional staff is
necessary for elementary schools and would allow teachers to have 45-60 minutes daily
of preparation time. The EBM formula allots 20% of the total core instructional teachers
to constitute the total number of additional staff.
Kindergarten. Numerous studies have highlighted the positive impact providing
a full-day kindergarten has on developing basic skills and pre- literacy skills, especially
for those students from low-income backgrounds (Cannon, Jacknowitz, & Painter, 2006;
H. Cooper, Allen, Patall, & Dent, 2010; Fusaro, 1997; Gullo, 2000; Lee, Burkam, Ready,
Honigman, & Meisels, 2006; Villegas, 2005). Villegas, (2005) in a WestEd study,
analyzed seven experimental- design studies comparing full-day and half-day
kindergarten programs and concluded that full-day kindergarten programs led to higher
student achievement, increased attendance rates, improved literacy and language
development, and improved social and emotional behavior. Extending classroom time to
full-day programs provides an opportunity for additional individual instruction and
decreases the amount of large-group or teacher-directed activities (Clark & Kirk, 2000;
Villegas, 2005). Furthermore, a longer day better prepares children for the transition to
first grade and literacy readiness (Clark & Kirk, 2000; Lee, et al., 2006; Villegas, 2005).
Some studies showed higher reading achievement persisting through third grade and in
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some cases, through seventh grade (Villegas, 2005). Recently there have been several
policy initiatives to require full-day offerings of kindergarten (Cannon, et al., 2006;
Villegas, 2005). All fifty states now allow an extended kindergarten program, yet as of
recently, only ten states provided additional funding for LEAs to offer full-day
kindergarten programs (Villegas, 2005). LEAs residing in states that do not fund full-day
programs can make the switch only if the LEA is able to generate local funds to cover the
additional cost associated with providing a full-day program. Given the effectiveness of
full-day kindergarten on student achievement is well-established, the EBM recommends
providing resources for a full-day program option (Odden and Picus, 2008). Odden and
Picus (2008) recommend that students who attend a full-day kindergarten be counted as
full 1.0 student in the funding formula as opposed to the common practice of counting
kindergarten students as 0.5 student in the funding formula.
Administrative support. Often it is assumed that every school needs a principal.
The EBM recommends one full time equivalent administrator for each prototypical
school of 432 students or one part time (0.5 FTE) administrator for every 216 students.
Instead of allocating funds for an assistant principal, the EBM provides resources for
instructional coaches to help facilitate the instructional program more effectively.
Additional administrative support is provided for secretarial, clerical and administrative
assistance to administrators and teachers. The EBM provides 1.0 FTE senior secretary
and 1.0 FTE clerk at the elementary level (Odden & Picus, 2008).
Staff and resources for extra student needs. Regardless of the quality of a
school’s instructional program, most schools will have some students that need more than
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the instruction already provided by the regular classroom teacher (Odden 2009). Schools
must provide additional effective strategies to help struggling learners reach proficiency.
As previously discussed, several of these evidence-based strategies, such as tutoring and
expanded learning time are provided for in the EBM. The model provides tutors to
support struggling students with immediate, intensive assistance during the regular school
day to support content mastery. One credentialed teacher is allotted under the EBM for
every 100 low-SES students (Odden & Picus, 2008). A suggested use of this tutor to is
provide instruction for one student every twenty minutes or three students per hour; thus
one tutor position would service 18 students per day. In order to increase the number of
tutoring sessions, the at-risk tutor should teach small groups of one to three students for
30 minute sessions or three to five students for 45 minute sessions.
English Learners. English Language Learners also have additional assistance
embedded into the EBM. Research shows that ELs from lower-income and less educated
backgrounds often struggle in school and require additional help (Gandara & Rumberger,
2007; Odden & Picus, 2008). As with low-SES students, the EBM provides EL students
an additional 1.0 FTE fully credentialed teacher for every 100 EL students enrolled in the
school. The additional support allows schools to offer support to ELs through
combinations of smaller classes, professional development for teachers to teach
“sheltered English lessons” and “reception” centers for districts with large numbers of EL
students that enter the school system at different times during the school year (Odden &
Picus, 2008). The EBM also provides special education classes for severely disabled
students with special education aides.
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Extended Day. After school programs are created to provide students with
academic support and a safe location after school. Odden and Picus (2008) provide this
additional assistance for struggling students in the EBM to achieve proficiency on
academic standards. Since not all students will need to attend this program, the model
suggests only 50% of the free and reduced lunch program pupil count, and for every 15
students, one 1.0 FTE be provided. The EBM recommends a two hour after school
program five days per week with teachers providing at least one hour of homework
assistance or tutoring during that time (Odden & Picus, 2008).
Summer School. Odden and Picus (2008) included funding for a summer school
program in the EBM to support all students in the rigorous California state standards. The
funding formula includes a provision of 50% of all free and reduced lunch program for a
recommended session of eight weeks, six hours per day, and a class size of no more than
15 students to provide much needed additional instructional time to meet state standards.
The EBM recommends the qualities of a summer school program match the findings of
Borman and Dowling (2006) mentioned previously.
Student Support. Student support in the Evidence Based Model includes
counselors, nurses, psychologists, and social workers (Odden & Picus, 2008). Schools are
enhanced with student support and family outreach embedded into the school culture,
particularly for schools with disadvantaged students. The EBM provides one licensed
professional for every 100 low-SES students, with a minimum of 1.0 FTE for each
prototypical elementary school of 432 students. The recommendation enables school
districts and individual schools to allocate the FTE across guidance counselors, social
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workers, nurses, and other student support professionals in a way that best fits the need of
the school.
Instructional Aides. The Evidence Based Model does not recommend nor fund
instructional aides. The model identifies the need for supervisory aides and recommends
2.0 FTE for a school of 400-500 students.
Intensive Professional Development. Professional development is an essential
component to improving student achievement through teacher practice (Supovich &
Turner, 2000; Desimone et al., 2002, Fermanich et al., 2006, Marzano, 2003). Effective
professional development is one of the most important strategies provided for in the
Evidence Based Model. It is the primary method through which teachers transform
practice into high quality instruction which is the key to improving student learning
(Marzano, 2003). Odden and Picus (2008) recommend the following strategies for
professional development based on their review of the literature:
• Time during the summer for intensive training institutes, most easily
accomplished by ensuring that approximately 10 days for teachers’ work year is
dedicated to professional development. The EBM recommends augmentation of
the work year with an additional 10 days to include staff development.
• On-site coaching for all teachers to assist with the incorporation of research-based
strategies into teachers’ instructional repertoire.
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• Collaborative work with teachers during the school day with planning and
preparation periods to improve the curricular and instructional program, requiring
clever scheduling of the school day to allow this time.
• Funds for summer and ongoing training during the school year are allotted for
approximately $100 per pupil under the EBM, thus including money for the
trainer and assorted professional development costs.
Instructional Facilitators. Instructional facilitators are provided in the prototypical
school of at a ratio of 1.0 FTE for every 200 students. These individuals are responsible
for coordinating the instructional program of the school and provide necessary coaching
and mentoring required for effective professional development. The majority of the
instructional facilitator’s role is to provide in-classroom support, modeling lessons and
provide constructive feedback to teachers in order to improve the instructional program
(Odden & Picus, 2008).
Additional staffing and resources. In addition to core and other school elements
discussed above, the EBM (Odden & Picus, 2008) also provides resources for: (a)
substitute teachers, (b) pupil support staff, (c) non-instructional aides, (d)
librarians/media specialists, (e) resources for gifted students, (f) instructional materials,
(g) student activities, and (h) technology. Figure 2.6 list these resources along with other
elements outside the core as these components provide support to the core instructional
program offered to students.
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The primary goal of the Evidence-based Model is to provide adequacy both in terms
of resources and student proficiency outcomes, through proficiency in state academic
standards. As shown in Figure 2.6, the model starts at the core with an emphasis on core
instruction in mathematics, language arts, science and social studies and expands outward
to support specialized instruction (Picus, et al, 2008). The concentric circles in Figure 2.6
exhibits how the EBM expands core instruction to account for all learners, including
struggling learners by providing additional resources for extended learning, tutors, EL
support and summer school. Furthermore, the EBM recognizes the critical role
professional development plays on ensuring all students receive a high-quality
instructional program.

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Figure 2.6: The Evidence Based Model
Instructional Materials
Gifted
Tutors and pupil support:
1 per 100 at risk
Elem
20%
K-3: 15 to 1
4-5: 25 to 1
ELL
1 per
100
Technology
Site-Based Leadership

Note: Adapted from Did increased flexibility in the use of categorical grants help California schools and
community colleges improve student performance? A thematic dissertation proposal by Picus (2009).
Adapted with permission.

As demonstrated by Figure 2.6 above, improving student performance by improving
instruction should include every teacher at all levels of support by focusing on student
proficiency in core subject areas. The EBM supports a strong focus on intensive, on-
going, and job-embedded professional development (Odden & Picus, 2008). The EBM
provides a spectrum of resources for various educational elements including pre-school,
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full-day kindergarten, gifted and special needs programs, summer school and technology.
It also recognizes the critical role site-based leadership has on the total school program.
Regardless of resources available, without an effective leader and the efficient use of
those resources, instructional change will not take place (Fullan, 2005). Effective
instructional leaders believe all students can master rigorous curriculum, believe in
holistic accountability, review data, make midcourse corrections and focus decision
making and alignment of resources on the greatest points of leverage (Fullan, 2003, 2005;
Reeves, 2006; Schmoker, 2006).
Summary
The hallmark of educational reform is academic proficiency for all students and
ensuring schools teach all students to rigorous performance standards. As outlined by the
research, it is imperative that schools have clarity on successful educational strategies so
that they can restructure themselves around a more powerful instructional improvement
process (Odden, 2009). After decades of research on the relationship of resources and
student achievement, researchers continue to offer evidence with differing conclusions.
The evidence neither says that resources never matter nor that resources could not matter
(Hanushek, 2006b). Some researchers argue that until evidence is able to desegregate
resources on an individual student basis by school, it is unlikely that research will be able
to fully measure the impact additional resources have on student achievement (Picus,
2006; Picus & Robillard, 2000). However, evidence across studies seems to conclude
that what matters more than adding additional resources to improve student outcomes , is
how resources are combined with educational strategies that have a clear focus on how to
116
improve student achievement and how the resources are used more effectively to increase
the academic proficiency of all students (Archibald, 2006; Hanushek, 1996, 1997, 2006a;
Hanushek & Lindseth, 2009; Hanushek & Rivkin, 1997; Marzano, 2003; Loeb et al.,
2007; Odden, 2003, 2009; Odden & Archibald, 2009, 2000; Odden et al., 2008; Odden et
al., 2007; Odden et al., 2005; Odden & Picus, 2008; PACE, 2006; Picus et al., 1996a;
Perez et al., 2007; Rebell, 2007; Slavin, 1999, 2005; Williams et al., 2005).
Educating a massive, diverse student population like California makes the
allocation of resources a daunting task. Despite the development of challenging
education standards and sustained attention to school improvement over the past ten
years, California continues to lag behind its counterparts on various measures of student
achievement (Loeb et al., 2007). California’s economic future is dependent upon the
skills and strength of its workers. If California students are going to participate fully in its
future development, they will need quality schools that are competitive with other states
and nations (Brewer et al., 2008; Loeb et al., 2007). The research presented suggests that
California’s school finance system and educational governance is fundamentally flawed.
While the state has established high standards and performance outcomes, it lacks a clear
strategy to adequately allocate the resources necessary to ensure all students meet these
outcomes. California schools must address the challenge of adequately educating an
increasingly diverse student population with fewer resources and less decision rights on
how to effectively allocate resources and align them to evidence-based educational
strategies to improve student outcomes.
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The literature review in this chapter has: outlined California’s student
demographics achievement and resource allocation patterns over the years; presented the
reader with how the federal government has targeted resources to special needs students
to improve student performance; highlighted the evolution of school equity to adequacy;
presented evidence on several effective evidence-based strategies and; outlined a model
that aligns resource allocations at the school level to evidence-based strategies. As
increased educational funding in the near future appears dismissal, the focus should shift
on how successful schools are demonstrating academic growth by aligning research and
best practices to the allocation of scarce fiscal resources. Regardless of economic
prosperity or despair, empirical and scientific data ought to guide decisions determining
effective allocation of resources to deliver a high quality comprehensive instructional
program to all students. The purpose of this study was to analyze site level resource
allocation strategies in diverse schools that are resulting in significant growth in their
Academic Performance Index (API), compared with schools who’s API dropped
dramatically. Utilizing the Evidence Based Model, (Odden & Picus, 2008) this study
seeks to provide local educators and state policymakers better insight on how
disadvantaged schools can utilize their resources effectively to beat the odds and institute
change. Conducting analysis on how successful schools are demonstrating academic
growth by aligning research and best practices to the allocation of scarce resources will
contribute further to the academic literature on educational adequacy and resource
allocation.

118
CHAPTER 3 – METHODS
In times of limited resources and fiscal constraints, utilizing an effective resource
allocation model that is supported by research and connected to improved student
outcomes is imperative. Although similar schools within the same school district often
receive the same amount of funding, student achievement can vary greatly (Edsource,
2007). Some schools effectively raise the achievement levels while others do not. The
purpose of this study was to analyze site level resource allocation strategies in diverse
schools with similar student demographics that were resulting in significant growth in
their Academic Performance Index (API) score, compared with schools whose API score
dropped dramatically. Many schools with similar student populations and resources have
been successful in closing the achievement gap and improving overall student
performance (Odden, 2009; Odden & Archibald, 2009; Reeves, 2000; Marzano, 2003;
Perez, et al., 2007; Williams, et al., 2005).
This study utilized Odden and Picus’ (2008) Evidence-Based Model in
conjunction with Odden (2009) and Odden and Archibald’s (2009) work on doubling
student performance as frameworks. Conducting analysis on how successful schools are
demonstrating academic growth by aligning research and best practices to the allocation
of scarce fiscal resources is timely and prudent in today’s educational climate. Using the
Evidence Based Model developed by Odden and Picus (2008) provides local educators
and policymakers within California greater insight on how disadvantaged schools can
utilize their resources effectively to beat the odds and promote change. School level
analysis resulted from this study contributes to the discussion on how an evidence-based
119
adequacy model can help identify effective educational strategies for improving our
schools. Data collection and analysis provides educational practitioners, policymakers
and the academic community with an expanded knowledge base on school level resource
allocations and which allocation patterns, if any, have implications for improved student
outcomes. This chapter outlines the research study design, participants, data collection,
instrumentation, ethical considerations and data analysis.
Research Questions
The following research questions will be used to guide this study:
1. What are the current instructional vision and improvement strategies at the
school level?
2. How are resources at the school and district used to implement the school’s
instructional improvement plan?
3. How did the allocation and use of resources at the school change in response
to the recent budget adjustments including overall funding reductions and
changes in the use of categorical funds?
4. How are the actual resource use patterns at the school sites aligned with or
different from the resource use strategies used in Odden and Picus’ (2008)
Evidence-Based Model?
Design
Analyzing how schools allocate resources to improve student learning is a
dynamic process that requires the integration of various types of data. The design
methodology implemented for this study used a multiple-methods, case study design
120
incorporating both quantitative and qualitative data. The multiple methods design, paired
with methodological triangulation, enhances the study by illustrating a comprehensive
picture to the research questions (Morse, 2003; Patton, 2002). According to Patton,
(2002) triangulation can strengthen a study by combining methods while methodological
triangulation uses multiple methods to study a single problem.
Using a purposeful sampling approach based on criterion, intensity and
convenience sampling, quantitative data was garnered to provide comparisons of
effective and ineffective allocations of school level resources that demonstrate improved
student achievement outcomes. To help educational leaders improve practice and inform
decision making, qualitative data was collected, to provide in-depth comparisons of the
effective and ineffective educational strategies implemented in schools (Morse, 2003;
Patton, 2002). Qualitative analysis within the case studies portrayed which schools were
demonstrating academic growth by aligning research-based educational strategies and
best practices to local decisions made at the school level and how scarce fiscal resources
were allocated.
Odden and Picus’ (2008) Evidence-Based Model and Odden’s (2009) Ten
Strategies for Doubling Student Performance was used as frameworks for data collection
and analysis within this study. The Evidence-Based Model (Odden & Picus, 2008)
framework generated comparisons between actual resources available at each school site
and the level of resources the Evidence-Based Model would generate for each individual
school. The Ten Strategies for Doubling Student Performance (Odden, 2009; Odden &
Archibald, 2009) framework provided comparisons between the ten educational strategies
121
for improving student performance outlined and the actual educational strategies
implemented within each individual school.
Sample and Population
In an effort to provide information rich cases with greater in-depth analysis, this
study will use a purposeful sampling approach. Data was obtained from DataQuest
(California Department of Education, 2010) in order to first identify elementary schools
within Orange County that during the 2009 assessment year were identified as either
significantly improving student learning through a significant gain in their API score or
experienced a dramatic decline in student achievement outcomes through a significant
drop in their API score. The average API growth and standard deviation was calculated
for all 397 elementary schools within Orange County (M = 18.5, SD = 19.5). Next, data
were examined to identify either K-5 or K-6 elementary schools with student
demographic populations that included at least 60% SED, 50% Hispanic, and 40% EL.
The specifics of the purposeful sampling using criterion and intensity-based approaches
for this study narrowed the population of elementary schools available to select. Thus,
given the purposeful sampling parameters established above, schools improving their API
score by at least 42 points (1.3 standard deviations above the mean API score for all
Orange County elementary schools) and schools declining in API score by at least 17
points (1.75 standard deviations below the mean API score for all elementary schools in
Orange County) with student demographic populations that included at least 60% SED,
50% Hispanic, and 40% EL were identified as possible candidates for this study. Out of
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nearly 400 elementary school in Orange County, thirty-seven schools met both the API
and student demographic criteria.
Six elementary schools in Orange County with grades kindergarten through fifth
and/or sixth grade were selected to participate in this study based upon similar student
demographics. As illustrated in Table 3.1 and 3.2, all six schools had a student
population of at least 60% SED, 50% Hispanic, and 40% EL students who either
significantly improved their 2009 API score by forty or more points or experienced a
dramatic drop in their 2009 API score by at least 17 points. Table 3.1 includes a summary
of the student demographics for the schools selected within this study.
Table 3.1: School Sample Demographics
School Grades Enrollment
%
Hispanic
%
White % ELL
%
(SED)
Pine Elementary K-5 375 50 35 44 61
Elm Elementary K-6 586 83 2 72 84
Orangewood Elementary K-6 695 85 9 56 78
Greenwood Elementary K-6 669 75 5 57 79
Redwood Elementary K-6 710 97 2 77 99
Sequoia Elementary K-5 478 68 19 60 73
Orange County Average - - 44.7 32.8 27.9 43.1
State Average - - 49.0 27.9 24.2 53.7
Note: Adapted from California Department of Education, (2010).
In addition to API growth each year, Table 3.2 includes each school’s API scores
from 2007 to 2010. The API scores ranged from 822-693. Furthermore, Table 3.3
includes each school’s State Ranks and Similar Schools Rank over the past three reported
years. The 2009 API growth among the six schools ranged from an increase of sixty-three
123
points to a drop of twenty-four points. Two of the six schools, Elm and Greenwood
Elementary School, have experienced growth each of the last three years on their API
scores.
Table 3.2: Academic Performance Index (API) Scores and Growth
School 2007
API
Score
2007
API
Growth
2008
API
Score
2008
API
Growth
2009
API
Score
2009
API
Growth
2010
API
Score
2010
API
Growth
Pine Elementary 786 -19 763 -40 813 63 800 -13
Elm
Elementary
687 23 713 15 767 55 764 -3
Orangewood
Elementary
717 2 695 -20 745 50 798 54
Greenwood
Elementary
650 6 745 98 787 42 780 -4
Redwood
Elementary
701 29 715 6 693 -17 712 21
Sequoia
Elementary
819 110 844 16 822 -24 806 -16
Note: Adapted from California Department of Education, (2010).

Table 3.3 California State Rank and Similar Schools Rank (Scale of 1-10)
School 2007
State
Rank
2007
Similar
Schools
Rank
2008
State
Rank
2008
Similar
Schools
Rank
2009
State
Rank
2009
Similar
Schools
Rank
Pine 7 7 4 3 6 7
Elm 2 4 2 3 4 8
Orangewood 3 5 2 2 3 4
Greenwood 1 2 4 5 5 8
Redwood 3 9 2 8 1 5
Sequoia 8 10 8 10 7 10
Note: Adapted from California Department of Education, (2010).

Table 3.4 includes AYP scores that reflect the percentage of students who scored
proficient or advanced during the 2009 and 2010 STAR administration. Table 3.4 also
identifies what year, if any, the school was in Program Improvement (PI). The schools in
this study range from year 5 of PI to not being in PI at all. One school, Greenwood
Elementary School has been in year five of program improvement for the past two years,
even though it’s API has improved over one hundred-forty points over the past three
124
years. In order to protect the identity and privacy of all students and staff involved in this
study, pseudonyms were used in place of the actual school names.
Table 3.4: AYP Percent Proficient and Advance and PI Status 2008-2010
School Subgroup 2008
ELA
%
Prof
or
Adv
2008
Math
%
Prof
or
Adv
2008
PI
2009
ELA
%
Prof
or
Adv
2009
Math
%
Prof
or
Adv
2009
PI

2010
ELA
%
Prof
or
Adv
2010
Math
%
Prof
or
Adv
2010
PI
Pine
Elementary
All 46.6 55.2 Not
in PI
59.3 62.5 Not
in PI
57.7 54.9 Not
in PI
Hispanic 34.4 38.7 - 44.2 54.8 - 43.8 41.5 -
EL 27.9 38.2 - 41.7 52.1 - 44.3 45.1 -
SED 32.1 45 - 48.1 54.8 - 49.4 48.8 -
Elm
Elementary
All 29.8 50 Year
1
38.6 66.8 Year
2
42.7 67.2 Year
3
Hispanic 23.7 46.3 - 34.3 64.4 - 38.5 63.6 -
EL 28.2 49.5 - 35.8 65.8 - 33.6 62.4 -
SED 27.8 48.5 - 35.4 63.6 - 37.8 64.3 -
Orangewood
Elementary
All 33.8 40.9 Year
4
43.1 50.9 Year
4
50.6 59.9 Not
in PI
Hispanic 28 36.3 - 40.4 47 - 46.3 58.1 -
EL 30 36 - 37.1 45.7 - 43.7 58.9 -
SED 31.4 38.2 - 42.4 49.6 - 48.4 60.3 -
Greenwood
Elementary
All 39.3 46.7 Year
5
44.4 63.8 Year
5
41.8 62.1 Year
5
Hispanic 31.8 39.8 - 36.6 58.6 - 36.3 58.4 -
EL 35.9 43.1 - 39.3 63.2 - 36.4 61.8 -
SED 35.4 43.3 - 38.8 60.6 - 38.6 60.0 -
Redwood
Elementary
All 32.8 38.9 Year
3
35.2 35.6 Year
4
34.9 38.9 Year
5
Hispanic 32.9 39.1 - 34.4 34.8 - 34.7 38.8 -
EL 28.9 36 - 32.6 32.2 - 30.6 35.2 -
SED 32.9 38.8 - 35.2 35.6 - 34.9 38.9 -
Sequoia
Elementary
All 57 73.2 Not
in PI
59.4 69.3 Not
in PI
51.7 62.2 Not
in PI
Hispanic 49.6 69.4 - 53.4 63.5 - 43.6 57.2 -
EL 48 71 - 49.7 63.6 - 43.1 57.5 -
SED 47.7 67.3 - 53.8 64.3 - 46.3 58.5 -
Note: Adapted from California Department of Education, (2010).

125
Data Collection
As part of a thematic dissertation group at the University of Southern California,
this study was one of 12 other similar studies that took place in the fall of 2010. This
research study built upon two years worth of adequate resource allocation studies
previously conducted at the University of Southern California. In order to create a
standardized data collection process among the twelve researchers, eight hours of training
was provided by Dr. Lawrence Picus during the month of March 2010. The full day
training included informed consent protocols, quantitative and qualitative data collection
protocols, data collection coding, case study analysis, the university’s Institutional
Review Board (IRB) requirements, and methods for making appropriate school contacts
for the purposes of this study. Follow up training to reinforce and review standardization
of data collection was conducted during the month of August 2010 prior to the
researchers data collection from the schools studied. School site principals were
contacted via phone and email to obtain consent to participate in the study. Upon consent
and commitment from site principals to participate in the study, an interview appointment
was scheduled.
Using a structured interview protocol (see Appendix B and C), the various
interviews took place over several days and lasted approximately two hours per school.
Prior to the in-person interview, a series of pre-interview documents were requested and
analyzed by the researcher to help inform and prepare the semi-structured interviews.
Once the pre-interview documents were analyzed, a semi-structured interview was
conducted between the researcher and the school site principal allowing for detailed
126
discussions as to how the educational strategies and resources allocation practices at the
school site level improved student performance. After each school site visit and interview
was completed, information ascertained from the interview was entered into a secured
online database provided by Lawrence O. Picus and Associates. Information uploaded on
the secured database was extrapolated and analyzed into a case study write-up for each
school site studied. Six K-6 elementary schools from four local educational agencies
(LEAs) within Orange County agreed to participate in this study based upon the criteria
mentioned prior. However, of those, five elementary schools from four LAEs participated
fully and are indicated in per their assigned pseudonym (UP-IRB IIR0000701). Sequoia
Elementary school did not fully participate in the study due to lack of responsiveness
from the principal when it came time to conduct the interviews.
Quantitative data collection. The quantitative data collected for this study was
based upon Odden and Picus’ (2008) Evidence-Based Model along with the school
expenditure structure and resource indicators and educational service strategies
developed by Odden, Archibald, Fermanich and Gross (2003). A representation of the
structure developed by Odden et al, (2003) is illustrated below in Figure 3.1. The
quantitative information collected as identified and articulated prior to the study and
outlined in a data collection code book (see Appendix B). The topics of the coding
scheme developed to guide the quantitative analysis of this study were as follows: (a)
school profile data and contacts, (b) district profile data and contacts, (c) school resource
indicators, (d) core academic teachers, (e) specialist and elective teachers, (f) library staff
127
(g) extra-help staff, (e) other instructional staff, (f) professional development staff and
costs, (g) student services staff, (e) administrative staff, and (f) elementary class size.

128
Figure 3.1: School Expenditure Structure and Resource Indicators
School Resource Indicators
School Building Size
School Unit Size
Percent Low Income
Percent Special Education
Percent ESL/LEP
Expenditures Per pupil
Professional Development
Expenditures Per Teacher
Special Academic Focus of School/Unit
Length of Instructional Day
Length of Class Periods

Length of Reading Class (Elementary)
Length of Mathematics Class (Elementary)
Reading Class Size (Elementary)
Mathematics Class Size (Elementary)
Regular Class Size (Elementary)
Length of Core* Class Periods (Secondary)
Core Class Size (Secondary)

Non-Core Class Size (Secondary)
Percent Core Teachers

*Math, English/LA, Science, & Social Studies
School Expenditure Structure
Instructional 1. Core Academic Teachers
- English/ Reading/ Language Arts
- History & Social Studies
- Math & Science
2. Specialist and Elective Teachers/Planning and Preparation
- Art, music, physical education. etc.
- Academic Focus with or without Special Funding
- Vocational
- Drivers Education
- Librarians
3. Extra Help
- Tutors
- Extra Help Laboratories
- Resource Rooms (Title 1. special education or other part-day pullout
programs)
- Inclusion Teachers
- English as a second language classes
- Special Education self-contained classes for severely disabled students
(Including aides)
- Extended Day and Summer School
- District-Initiated Alternative Programs
4. Professional Development
- Teacher Time - Substitutes and Stipends
- Trainers and Coaches
- Administration
- Materials, Equipment and Facilities
- Travel & Transportation
- Tuition and Conference Fees
5. Other Non-Classroom Instructional Staff
- Coordinators and Teachers on Special Assignment
- Building Substitutes and Other Substitutes
- Instructional Aides
6. Instructional Materials and Equipment
- Supplies, Materials and Equipment
- Computers (hardware, software, peripherals)
7. Student Support
- Counselors
- Nurses
- Psychologists
- Social Workers
- Extra-Curricular and Athletics
Non-Instructional 8. Administration
9. Operations and Maintenance
- Custodial
- Utilities
- Security
- Food Service
Source: Figure reprinted from Odden, et al., 2003.
129
Qualitative data collection. Qualitative data using an open-ended semi-
structured data collection protocol (see Appendix C) was used to capture descriptive
understandings of the schools (a) curriculum and instructional vision, (b) resource
allocation, (c) instructional leadership, and (d) accountability. The protocols used were
adapted from similar adequacy studies conducted by Lawrence O. Picus and Associates
(Odden, et al., 2007; Odden, et al., 2005; Picus, et al., 2008). Using a semi-structured
interview protocol provided greater reliability in the information gathered among each
school site, while also allowing for flexibility of emergent topics that the principal or
researcher found relevant to discuss. Discussions regarding how resources were allocated
to improve student outcomes along with specific strategies implemented were discussed
during the interviews. Using principals at the main informants was critical to this study as
principals are typically aware and knowledgeable about their schools and provided the
researcher shrewd understanding into what and why something was occurring in terms of
instructional strategies, site level resource allocations and student performance.
Case Studies
The purpose of incorporating a case study approach was to provide important
context and in-depth information regarding resource allocation and educational strategies
being implemented at the individual school level (Morse, 2003; Patton, 2002). Data was
organized, classified and condensed in a written, descriptive manner that portrayed a
story about each school (Patton, 2002). The case studies depicted which schools were
demonstrating academic growth by aligning research-based educational strategies and
best practices to local decisions made at the school level and how scarce fiscal resources
130
were allocated. Qualitative analysis of each school provided comparisons of effective and
ineffective school level resource allocation models and the educational strategies
implemented to improve student performance.
Ethical Considerations
Prior to conducting the study, the researcher along with the eleven other
researchers conducting similar studies submitted an application to the University Park
Institutional Review Board (UPIRB) to ensure an independent third party would monitor
and protect the rights and welfare of research subjects. Based on the low-risk associated
with this study and previous findings of the UPIRB on similar studies, the UPIRB
determined the study as Not Human Subjects Research (NHSR) and thus exempted this
study from further IRB protocols. Interested participants in this study chose to participate
in this study and were not pressured to participate if they declined. As stated earlier,
Sequoia decided to no longer participate in this inquiry study. A consent form for each
participant was provided prior to participating in the study and participants were assured
their input would be kept strictly confidential. In order to protect the identity and privacy
of all participants involved in this study, pseudonyms were used in place of the actual
school names and the data was maintained on a secure database. Finally, as the study
relies on participants’ honest and accurate portrayals of strategies implemented and
resource allocation patterns at the school level, any school that resided in the district that
the researcher was employed in was not included in this study.

131
Data Analysis
The multiple methods design, paired with methodological triangulation, enhanced
the study by illustrating a comprehensive picture to the research questions (Morse, 2003;
Patton, 2002). The quantitative data was collected, analyzed and compared to Evidence-
Based Model (Odden & Picus, 2008). Both qualitative and quantitative data garnered
from the principal interviews was compared to the Evidence-Based Model (Odden &
Picus, 2008) and the Ten Strategies for Doubling Student Performance (Odden, 2009;
Odden & Archibald, 2009) and then written into individual case studies for each school
studied. Any gaps in research identified were followed up by additional contact with the
participants and added to the findings. Data analysis incorporated descriptive statistics
including ranges, averages, ratios and standard deviations. Charts, graphs, trend
comparison and document analysis was used to illustrate findings and identify effective
and ineffective resource allocation patterns at the school level. This data helped make a
determination as to how the strategies and resource allocation practices at each school
influenced student performance.
Qualitative and quantitative analysis of each school was developed in order to
provide comparisons of effective and ineffective school level educational strategies and
resource allocation models that could be gleaned for future implementation at other
schools. Data collection and analysis provided educational practitioners, policymakers
and the academic community with an expanded knowledge base on school level resource
allocations and which allocation patterns, if any, have implications for improved student
outcomes. California schools have been hit with substantial budget reductions over the
132
past few years and are facing additional budget reductions which will directly impact
services and programs. In times of limited resources and fiscal constraints, conducting
analysis on how successful schools are demonstrating academic growth by aligning
research and best practices to the allocation of scarce fiscal resources is imperative.
Utilizing the Evidence Based Model developed by Odden and Picus (2008) and the Ten
Strategies for Doubling Student Performance (Odden & Archibald, 2009) provides local
educators and state policymakers greater insight on how disadvantaged schools can
utilize their resources effectively and inform decision making to beat the odds by
promoting improved student outcomes.

133
CHAPTER 4 – RESULTS
Utilizing the Evidence-Based Model (Odden & Picus, 2008) as a resource
allocation framework, the purpose of this study was to examine school level resource
allocation strategies that resulted in significant growth in the Academic Performance
Index (API) scores of a diverse group of schools, and to compare that with schools where
the API dropped dramatically. By conducting analysis at the school level, this study
contributes to the overall discussion on how successful schools are demonstrating
academic growth by aligning research and best practices to the allocation of scarce fiscal
resources. This chapter summarizes the research study findings that were obtained by
examining the case studies of five elementary schools in Orange County (Appendices D-
H). The reason for using a multiple-methods, case study approach was to illustrate
comprehensively a picture of the resource allocation strategies applied at the site level
(Morse, 2003; Patton, 2002). The analysis of these findings include inductive analysis
involving comparisons and themes of effective and ineffective educational strategies
implemented in schools, as well as deductive analysis in which data was analyzed
through the lens of existing frameworks (Morse, 2003; Patton, 2002). The conceptual
framework for this study was by Odden (2009) and Odden and Archibald’s (2009) work
on doubling student performance as well the Evidence-Based Model (Odden & Picus,
2008) dealing with research based strategies for school improvement.
The case study findings are summarized in this chapter to enhance the
understanding of: (1) the demographic and academic data within the schools; (2) key
elements and themes of the improvement process in each school; and (3) how the use of
134
an evidence-based model can guide effective resource allocation. The findings will be
summarized and a discussion of lessons learned throughout the case studies will be
addressed. The following research questions were used to guide this analysis:
1. What are the current instructional vision and improvement strategies at the
school level?
2. How are resources at the school and district used to implement the school’s
instructional improvement plan?
3. How did the allocation and use of resources at the school change in response
to the recent budget adjustments including overall funding reductions and
changes in the use of categorical funds?
4. How are the actual resource use patterns at the school sites aligned with or
different from the resources use strategies used in Odden and Picus’ (2008)
Evidence-Based Model?
This chapter explores the findings of these questions for each elementary school studied.
School Demographics and Data
In an effort to provide information rich cases to enhance the analysis, this study
used a purposeful sampling approach. Data were obtained from DataQuest (California
Department of Education, 2010) to first identify elementary schools within Orange
County that were identified as either significantly improving student learning through a
significant gain in their API score or experienced a dramatic decline in student
achievement outcomes through a significant drop in their API score during the 2009
assessment year. The average API growth and standard deviation was calculated for all
135
397 elementary schools within Orange County (M = 18.5, SD = 19.5). The data were
further examined to identify either K-5 or K-6 elementary schools with student
demographic populations that included at least 60% SED, 50% Hispanic, and 40% EL.
The specifics of the purposeful sampling criterion and intensity-based approaches for this
study narrowed the population of elementary schools available for further study. Given
the purposeful sampling parameters established above, schools improving their 2009, API
score by at least 42 points (1.3 standard deviations above the mean API score for all
elementary schools in Orange County) and schools declining in API score by at least 17
points (1.75 standard deviations below the mean API score for elementary schools in
Orange County) with student demographic populations that included at least 60% SED,
50% Hispanic, and 40% EL were identified as possible candidates for this study. Out of
nearly 400 elementary schools in Orange County, thirty-seven schools met both the API
and student demographic criteria. Six K-6 elementary schools from four local educational
agencies (LEAs) within Orange County agreed to participate in this study based upon the
criteria above. Of those, five elementary schools from four LAEs participated fully and
are indicated per their assigned pseudonym (UP-IRB IIR0000701) in Table 4.1 below.
Sequoia Elementary school, listed previously in the first three chapters, did not fully
participate in the study due to lack of responsiveness from the principal when it came
time to conduct the interviews. The five schools that fully participated in the study are
listed below in Table 4.1 along with their corresponding enrollment and demographic
data.

136
Table 4.1: Summary of Case Studies Demographics, 2009-2010
School Grades Enrollment
%
Hispanic % White
%
ELL
%
(SED)
Pine Elementary K-6 425 50 29 44 68
Elm Elementary K-6 560 83 2 72 84
Orangewood Elementary K-6 694 81 8 56 67
Greenwood Elementary K-6 700 75 4 60 86
Redwood Elementary K-6 600 97 2 73 100
Orange County Average - - 44.7 32.8 27.9 43.1
State Average - - 49.0 27.9 24.2 53.7
Case Study Average K-6 596 77.2 9 61.8 80.8
Case Study Median - 600 81 4 60 84
Note: Adapted from DataQuest by California Department of Education (2010a).

As described in Table 4.1, each of the schools selected were K-6 elementary
schools during the 2009-10 school year. However, Pine and Redwood Elementary (RE)
recently converted from a K-3 structure (Pine) and a 4-6 structure (RE) into a K-6 model.
The majority of the sample schools were large elementary schools with the average case
study size of 596. Pine was the smallest school with 425 students and Greenwood was the
largest with 700 students. Each of the schools Hispanic, English Learners (EL) and socio-
economically disadvantaged (SED) student populations were above both the state and
county average. As illustrated in Figure 4.1, RE had the highest Hispanic, EL and SED
student population among the case studies while Pine was the only school with a White
subgroup of more than ten percent. Four of the five schools were made up of over 80%
Hispanic students, three of the schools served 60% or more EL students while all of them
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served a range of 67-100% low-poverty students identified as SED. Each of the schools
served a minimum of 40% EL, 50% Hispanic, and 60% SED student population.
Figure 4.1: 2009-10 Case Studies Percent of Students by Significant Subgroup
Note: Adapted from DataQuest by California Department of Education (2010a).
Assessment data. As shown in Figure 4.2 below, over the past five years, student
achievement has increased at all but one of the schools in this study (Pine). According to
the California Department of Education (2009), the statewide performance target for all
schools in California is an Academic Performance Index (API) score of 800 points.
Schools that do not meet this criterion and are required to demonstrate annual growth of
at least five index points from year-to year, based on results of statewide testing
(California Department of Education, 2009). While Pine met the 800 API target, it is the
only school that experienced a drop in API between 2006 and 2010 and that was only by
two points. Over the five year period Pine’s EL and SED student population grew and it
transitioned from a K-3 school to a K-6.
Pine Elm Orangewood Greenwood Redwood
Hispanic 50 83 84 81 97
White 29 284 2.0
EL 44 66 56 60.0 73
SED 68 75 67 86 100
0
10
20
30
40
50
60
70
80
90
100
Percentile
138
Figure 4.2 below indicates Greenwood Elementary (GE) had the largest API
growth over the past five years, with an API cumulative growth of nearly 140 points.
Over the past five years Elm experienced a 99 point API growth while Orangewood (OE)
and Redwood experienced an 84 and 44 API growth respectively. The average level of
improvement for the five schools included in this study was 72.6 API points. Although
four of the case study schools had increases in achievement over the five year period,
three of them (GE, Elm, & OE) experienced growth above the sample average.
Figure 4.2: Change in API of Sample Schools Between 2006-2010
Note: Adapted from DataQuest by California Department of Education (2010a).

According to the California Department of Education (CDE), all of the schools in
this study had a state decile ranking between 1 and 6 in 2009. RE was in the bottom
decile ranking and has seen its state ranking decline over the past four years. As depicted
in Table 4.2, over the last four years, two of the schools (Elm, & GE) have maintained or
668
642
714
665
802
712
780
798
764
800
600 650 700 750 800 850
Redwood
Green
wood
Orange
wood
Elm
Pine
201
0
200
6
139
improved their state decile ranking while Pine’s, OE’s and RE’s decile ranking has
declined. Interestingly, two of the three schools whose state decile ranking has dropped
over the past four years are from the same district and are both schools that underwent a
structural change from a K-3 or 4-6 grade structure to a K-6 model. GE has improved its
decile ranking by four levels while Elm improved its decile ranking by two levels over
the past four years. The 2010, decile ranking will not be reported until May, however,
OE’s ranking is likely to improve as it has experienced two consecutive years of 50
points or more growth in their API and is the only sample school to have exited PI in
2010.
Table 4.2 Similar School & Statewide Ranking of the Sample Schools

Pine Elm Orangewood Greenwood Redwood
2006 2009 2006 2009 2006 2009 2006 2009 2006 2009
State-wide
Ranking 7 6 2 4 4 3 1 5 2 1
Similar
School
Ranking 8 7 4 8 5 4 2 8 6 5
Note: Adapted from DataQuest by California Department of Education (2010a).
In addition to receiving a state decile ranking each year, the CDE also assigns
each school a similar schools ranking (SSR). SSRs are rankings that compare each
school’s achievement data to that of one-hundred other elementary schools in California
that serve a similar demographic. The SSR allows schools to compare themselves to
other schools that face similar challenges. In 2009, each of the schools included in this
study earned a higher SSR compared to their state ranking. Both Elm and GE earned the
highest similar school ranking of all the schools with an SSR of 8 in 2009, meaning they
were within the top 20% of schools serving similar demographics.
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Table 4.3 below summarizes the 2009-10 API growth for the case study schools
within the study. At the start of the study, four of the five schools were selected because
they had made substantial growth in their 2009 API score, more than 42 points, 1.3
standard deviations above the API mean for all elementary schools in Orange County.
However, in 2010, only one of those schools (OE) continued its substantial growth,
growing an additional 54 points from 2009 to 2010. Over the past two years, OE’s API
has grown 104 points. RE was originally selected to participate in this study because in
2009, it experienced a substantial decline in its API score; a decline of 17 points, 1.75
standard deviations below the API mean for all elementary schools in Orange County.
However, in 2010, it rebounded with a 21-point API gain. The average of all five case
study schools’ API growth from 2009 to 2010 was eleven points with the median
expressing a four point decline. The average growth was skewed by OE’s large API
growth in 2010, while three of the four schools experienced a dip in their API score from
the previous year. The original purpose to compare schools that experienced substantial
growth to schools that experienced substantial decline was problematic as the schools
were inconsistent with their academic progress over the past several years. However
cross-case comparisons were examined using the frameworks of this study to identify
both the effective and ineffective educational elements the various schools in the study
implemented as they attempted to improve student proficiency levels at their site.

141
Table 4.3: Summary of Case Studies PI and API Status, 2010 AYP Report
School
2009 PI
Status
Year
2010 PI
Status
Year
2009 API
Growth
Score
2009 Base
API Score
2010 API
Growth
Score
2009-10
API
Growth
a

Pine Elementary - - 810 813 800 (13)
Elm Elementary 2 3 767 767 764 (3)
Orangewood Elementary 4 - 745 744 798 54
Greenwood Elementary 5 5 787 784 780 (4)
Redwood Elementary 4 5 693 691 712 21
Case Study Average 3 2.6 760 -- 771 11
Case Study Median 4 3 767 -- 780 (3)
Note: Adapted from DataQuest by California Department of Education (2010a).
a
There are two API reports: (l) the Base API that is released to schools in the spring and (2) the Growth API
that is released in the fall. These two reports show results from two different school years. The Growth API
is compared to the prior year Base API to show how much a school improved from one year to the next.
The change figures displayed here compare the 2009 Base API Score to the 2010 API Growth score as the
2009 Growth API and the 2010 Growth API score don’t always appear to add correctly. Most schools
publicize and compare the Growth API Scores.

In addition to API, Adequate Yearly Progress (AYP) goals are another indicator
of a school’s academic success for all students. States and their schools are required to
meet a series of annual performance goals established under the No Child Left Behind
Act (2002). Schools that receive federal Title I funds through NCLB are placed in
Program Improvement (PI) if they fail to meet the AYP annual measurable objective
(AMO) performance targets in the same content area or on the same indicator for two
consecutive years (Edsource, 2010b; Stecher, Hamilton, & Gonzalez, 2003; Weiss,
2007). A school can exit PI only after meeting all AYP criteria for two consecutive years
(California Department of Education, 2010b). Table 4.3 shows four of the five sample
schools were in PI at the start of this study ranging from Year 2 to Year 5. Pine was the
142
only school not in PI. By 2010, OE was the only school in the study that started in PI and
successfully exited PI; OE went from Year 4 of PI in 2009 to no longer in PI in 2010.
Currently, GE and RE are in Year 5 of PI while Elm is in Year 3.
English language arts. As indicated below in Table 4.4, between 2006 and 2010,
on average each school demonstrated a 42.4 percentage point increase in the number of
students reaching proficiency or above on the statewide ELA California Standardized
Tests (CSTs). Analysis of the AYP results in ELA over the last five years ranges from
14.7 to 73.6 percentage points increase in proficient and advanced levels across the
schools. While both Elm and OE grew 18 points in ELA over the five year period, Elm
had the highest percent change of 73.6% as it started with the lowest achievement level of
24.6 percent. Three schools, Elm, OE and GE had a percentage increase in ELA
proficient and advanced above 40%, resulting in total growth of 12 or more points. Pine
and RE had the lowest point growth over the years growing little more than 7 points
between 2006 and 2010. Figure 4.3 below illustrates the ELA percent proficient and
above trend school wide from 2007 to 2010. Figure 4.3 shows that although every school
in the study increased their overall ELA proficiency in the focal year of the study, only
OE and Elm were able to build upon the previous year’s success. In fact, Elm and OE
were the only schools that experienced consistent growth in ELA percent proficient and
advanced across the four years depicted in Figure 4.3. Nearly two-thirds of RE’s students
did not reach proficiency in ELA by 2010 while the AYP AMO’s was 56.8% proficiency.

143
Table 4.4: Summary of Case Studies ELA –Proficient & Above Trend
Percent of students Proficient and Above
School 2006 2007 2008 2009 2010
%
Change
Pine Elementary 50.3 54 46.6 59.3 57.7 14.7
Elm Elementary 24.6 28.1 29.8 38.6 42.7 73.6
Orangewood Elementary 32.6 61.6 33.8 43.1 50.6 55.2
Greenwood Elementary 29.1 28.8 39.3 44.4 41.8 43.6
Redwood Elementary 27.9 30.8 32.8 35.2 34.9 25.1
Case Study Average 32.9 40.7 36.5 44.1 45.5 42.4
Case Study Median 29.1 30.8 33.8 43.1 42.7 43.6
Note: Adapted from DataQuest by California Department of Education (2010a).

Figure 4.3: Summary of Case Studies ELA – Proficient & Above Trend

Note: Adapted from DataQuest by California Department of Education (2010a).

Pine Elm Orangewood Greenwood Redwood
2007 54 28.1 31.6 28.8 30.8
2008 46.6 29.8 33.8 39.3 32.8
2009 59.3 38.6 43.1 44.4 35.2
2010 57.7 42.7 50.6 41.8 34.9
0
5
10
15
20
25
30
35
40
45
50
55
60
Percentile
144
Below, Figures 4.4, 4.5 and 4.6 further disaggregate the ELA data over the past
four years by the significant student subgroups selected in this study. Disaggregating the
data further shows some schools within the study have improved the percent proficient
and advanced of certain groups of students better than other schools. Figure 4.4 illustrates
the percent proficient and above in ELA for Hispanic students in all five schools. OE was
the most successful at improving the ELA proficiency for Hispanic students, with an 88%
increase in the percent proficient and advanced in proficiency from 2007 to 2010. OE
was the only school among the sample schools to experience consistent growth for their
Hispanic students across the past four years. None of the schools were able to reach 50%
proficiency or higher for any of the Hispanic, EL or SED subgroups. OE was the only
school that was able to build on the prior years’ ELA percent proficient and advanced for
all subgroups over the four-year period and had the largest percentage of growth for
Hispanic, EL and SED students in ELA with 88%, 64% and 74% growth respectively.
GE had the second largest ELA growth for subgroups with 68% growth for Hispanics,
57% growth for EL and 61% growth for SED students. While Elm had the highest ELA
growth overall, it had the third highest ELA growth for its subgroups with 52% growth
for Hispanics, 22% growth for EL and 39% growth for SED students. Pine had a higher
percent growth for EL students than Elm with 25% growth over the four years. RE had
the lowest percent growth for all subgroups over the four year period with 10% growth
for EL and SED students and 15% growth for Hispanic students.

145
Figure 4.4: Case Studies Hispanic Subgroup ELA –Proficient & Above Trend
Note: Adapted from DataQuest by California Department of Education (2010a).

Figure 4.5 Case Studies EL Subgroup ELA –Proficient & Above Trend
Note: Adapted from DataQuest by California Department of Education (2010a).

Pine Elm Orangewood Greenwood Redwood
2007 37.3 25.2 24.6 21.6 30.2
2008 34.4 23.7 28 31.8 32.9
2009 44.2 34.3 40.4 36.6 34.4
2010 43.8 38.5 46.3 36.3 34.7
0
5
10
15
20
25
30
35
40
45
50
Percentile
Pine Elm Orangewood Greenwood Redwood
2007 35.4 27.5 26.6 23.1 27.7
2008 27.9 28.2 30 35.9 28.9
2009 41.7 35.8 37.1 39.3 32.6
2010 44.3 33.6 43.7 36.4 30.6
0
5
10
15
20
25
30
35
40
45
50
Percentile
146
Figure 4.6: Case Studies SED Subgroup ELA –Proficient & Above Trend

Note: Adapted from DataQuest by California Department of Education (2010a).

Mathematics. Examination of Table 4.5 below reveals that between 2006 and
2010, the schools demonstrated on average a 45.5 percentage point increase in the
number of students scoring proficient and above on statewide Math CST. Every school
but Pine’s math percent proficient or advanced was higher than their overall ELA
proficiency across the years. Analysis of the AYP results in math over the last five years
ranges from -23.8 to 116.4 percentage increase in student proficient and advanced levels
across the schools. Greenwood more than doubled their students’ math proficient and
advanced scores over the five-year period from 28.7 percent proficient and advanced to
62.1 percent proficient and advanced. GE’s and RE’s math percent proficient and
advanced were similar in 2006 with fewer than 30% of their students proficient or
advanced. However by 2010, 62% of GE students were proficient and above while only
Pine Elm Orangewood Greenwood Redwood
2007 41.2 27.2 27.8 23.9 31.2
2008 32.1 27.8 31.4 35.4 32.9
2009 48.1 35.4 42.4 38.8 35.2
2010 49.4 37.8 48.4 38.6 34.9
0
5
10
15
20
25
30
35
40
45
50
55
Percentile
147
38.9% of RE’s students were proficient and above. Elm had the highest overall math
proficiency of all the schools in the study and experienced over sixteen points in growth
in 2009; the same year the school piloted the district’s new math initiative. Elm, OE and
GE all experienced at least two years of double-digit growth within the past five years.
Similar to ELA proficiency, RE and Pine had the lowest math point gains with 9.7 points
increase for RE, while Pine experienced a 17.1 point decline. Figure 4.7 illustrates the
Math percent proficient and above trend school wide from 2007 to 2010. Figure 4.7
shows that although every school in the study increased their math percent proficient and
advanced in the focal year of the study, only Elm was able to build upon the previous
year’s success across the four-year span. By 2010, three of the five schools (Elm, OE and
GE) surpassed the AYP AMO target of 58% proficiency for math.
Table 4.5: School Sample Mathematics – Proficient & Above Trend
Percent of students Proficient and Above
School 2006 2007 2008 2009 2010
%
Change
Pine Elementary 72.0 67.6 55.2 62.5 54.9 (23.8)
Elm Elementary 39.4 40.6 50.0 66.8 67.2 70.6
Orangewood Elementary 45.7 45.5 40.9 50.9 59.9 31.1
Greenwood Elementary 28.7 31.8 46.7 63.8 62.1 116.4
Redwood Elementary 29.2 37.0 38.9 35.6 38.9 33.2
Case Study Average 43.0 44.5 46.3 55.9 56.6 45.5
Case Study Median 39.4 40.6 46.7 62.5 59.9 33.2
Note: Adapted from DataQuest by California Department of Education (2010a).

148
Figure 4.7: Summary of Case Studies Mathematics – Proficient & Above Trend

Note: Adapted from DataQuest by California Department of Education (2010a).

Figures 4.8, 4.9 and 4.10 further disaggregate the Math data over the past four
years by the significant student subgroups selected in this study. By disaggregating the
data further we are able to get a clearer picture at how the schools support their subgroups
overall proficiency progress. GE and Elm were the most successful at improving the
math percent proficient and advanced levels for Hispanic students, with a 136% change
in overall proficiency from 2007 to 2010 for GE and an 80% change for Elm. None of the
schools were able to build or maintain on the prior years’ math percent proficient and
advanced scores for every subgroup over the four year period.

Pine Elm Orangewood Greenwood Redwood
2007 67.6 40.6 45.5 31.8 37
2008 55.2 50 40.9 46.7 38.9
2009 62.5 66.8 50.9 63.8 35.6
2010 54.9 67.2 59.9 62.1 38.9
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
Percentile
149
Figure 4.8: Case Studies Hispanic Subgroup Math – Proficient & Above Trend
Note: Adapted from DataQuest by California Department of Education (2010a).

Figure 4.9: Case Studies EL Subgroup Math –Proficient & Above Trend
Note: Adapted from DataQuest by California Department of Education (2010a).

Pine Elm Orangewood Greenwood Redwood
2007 49.2 35.3 40.7 24.7 36.8
2008 38.7 46.3 36.3 39.8 39.1
2009 54.8 64.4 47 58.6 34.8
2010 41.5 63.6 58.1 58.4 38.8
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
Percentile
Pine Elm Orangewood Greenwood Redwood
2007 50 38.5 41.8 28.1 35.2
2008 38.2 49.5 36 43.1 36.0
2009 52.1 65.8 45.7 63.2 32.2
2010 45.1 62.4 58.9 61.8 34.7
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
Percentile
150
Figure 4.10: Case Studies SED Subgroup Math –Proficient & Above Trend

Note: Adapted from DataQuest by California Department of Education (2010a).

As further illustrated above in Figures 4.8, 4.9 and 4.10 above, GE had the largest
percentage of growth for Hispanic, EL and SED students in math with 139%, 120% and
119% growth respectively. Elm had the second largest math growth for subgroups with
80% growth for Hispanics, 62% growth for EL and 72% growth for SED students. OE
was able to produce over 40% growth in each of its Hispanic, EL and SED subgroups
math proficient and advanced levels over the four-year period. Meanwhile, both Pine and
RE’s EL students’ math percent proficient and advanced declined over the four-year
period. Pine saw the largest drop in its math percent proficient and advanced levels for all
of its subgroups, but over the four years, the number of minority students they serve also
increased. RE’s subgroup math percent proficient and advanced levels hovered between
35 and 39 percent over the four-year period for all its subgroups. GE’s school wide math
percent proficient and advanced started off lower than RE, but over the four year period
increased over 33 points while RE grew less than ten.
Pine Elm Orangewood Greenwood Redwood
2007 52.9 37.4 41.6 27.4 37.1
2008 45 48.5 38.2 43.3 38.8
2009 54.8 63.6 49.6 60.6 35.6
2010 48.8 64.3 60.3 60 38.9
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
Percentile
151
Key Elements & Themes of the Improvement Process
The schools in this study are responsible for educating some of the largest percent
of minority, EL and SED students. Each case study’s Hispanic, EL and SED student
population all were well above the average compared to the state and county. California
school demographics are changing with increasing minority, EL and low-income students
entering the system who often require additional resources to help them attain proficiency
standards (Loeb et al., 2007; Hanushek, 2006a; Picus, 2006, Odden, 2009; Odden &
Picus, 2008). Many schools with similar student populations and resources have been
successful in closing the achievement gap and improving overall student performance
(Odden, 2009; Odden & Archibald, 2009; Reeves, 2000; Marzano, 2003; Perez, Parish,
Anand, Speroni, Esra, Socias, et al., 2007; Williams, Kirst, Haertel et al., 2005).
Improving student proficiency for all students should be the primary mission of all
schools and can be one of the most overwhelming challenges any school undertakes
(Reeves, 2005). However, research continues to provide growing evidence that schools
have much more control over student performance and other school related problems than
many choose to believe (Darling-Hammond, 1997; Marzano 2003, Odden 2009, Odden
& Archibald, 2009; Schmoker, 1999).
The purpose of this section is to analyze effective research-based educational
elements that have led to improved student learning. Odden and Archibald (2009) outline
ten core elements successful schools and districts implement to dramatically improve
student performance. In addition to the framework and strategies outlined by Odden and
Archibald (2009), the Evidence-Based Model (Odden & Picus, 2008) of resource
152
allocation was utilized to examine the alignment between how schools use their allocated
resources along with research-based strategies to improve student performance. In
addition to categorizing and summarizing the occurrence of the ten educational strategies
outlined by Odden and Archibald (2009) each elementary school that participated in the
study was ranked regarding its implementation of each evidence-based strategy on an
ordinal scale (Glass & Hopkins, 1996; Odden & Archibald, 2009). The summary of each
case study’s performance ranking is illustrated in Table 4.6 below. Schools were ranked
on a five point scale from weak to strong on how they implemented the evidence-based
strategies at their site. The numbers in Table 4.6 below represent the number of schools
who scored the particular ranking for each evidence-based strategy.

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Table 4.6: Summary of Case Studies Performance of Evidence-Based Strategies
Evidence-Based Strategy Weak
Below
Average Average
Above
Average Strong
Understanding the Performance Problem and
Challenge
2
1
2
Setting Ambitious Goals 2 1 2
Change the Curriculum Program and Create a
New Instructional Vision
1
3
1
Formative Assessments and Data-Based Decision
Making
1
3
1
Ongoing, intensive Professional Development 2 2 1
Using time Efficiently and Effectively 2 1 2
Extend Learning Opportunities for Struggling
Students
2
1 2

Collaborative Culture and Distributed Leadership 1 2 1 1
Professional and Best Practices 3 2
Note: Adapted from Doubling student performance:…and finding the resources to do it by Odden and
Archibald (2009). Copyright 2009 by Corwin Press.

Although each of the case study schools demonstrated the application of all ten
evidence-based strategies outlined within the nine categories in Table 4.6 above, many
were not implemented to the level and intensity research suggests is needed to make
substantial gains in student performance. Table 4.6 summarizes each school’s educational
reform efforts compared to the ten evidence-based strategies supported by research and
recommended by Odden and Archibald (2009) for doubling student performance. The
greatest variability among the sample schools was found in the first strategy,
understanding the performance problem and challenge. Furthermore, the evidence
revealed that 80% of the schools were above average or strong in two of the ten strategies
(change the curriculum program and create a new instructional vision; and formative
154
assessments and data-based decision making). Surprisingly, despite the fact that all of the
schools were Title I schools with additional funds available for staff development,
ongoing, intensive professional development was below average or average at 80% of the
sample schools. Four of the five schools were in PI during the focal year of the study
which mandates the school spend 10% of their Title I budget on staff development.
However, only one of the schools targeted professional development near the level
recommended by the Evidence-based Model (Odden & Picus, 2008). Although the
summaries above alone provide intrigue, a more in depth cross-comparison analysis of
each evidence-based element across the case studies provides for greater triangulation
and supporting evidence regarding the quality of implementation (Patton, 2002).
Understanding the performance problem and challenge. Teachers, principals,
and school leaders must fully understand the performance challenge and have a strong
desire to want to address student performance (Odden & Archibald, 2009). Stakeholders
must feel a sense of urgency to change student performance levels and use this urgency to
drive the instructional improvement process. The schools studied varied across the
spectrum of how they implemented an understanding of the performance challenge and
the degree to which they instilled a sense of urgency to improve student learning
throughout their schools. As illustrated in Figure 4.11, two of the schools (OE and GE)
instilled a strong sense of urgency across the school to improve the current performance
challenge. For example, the principal at OE was new to the school and district during the
focal year of the study and intentionally wanted to work at the lowest performing school
in a district; she stated she likes to turn things around and see tangible growth. When
155
meeting with grade level teams she would challenge staff who did not share her sense of
urgency to improve student proficiency stating, “I don’t know if we share the same sense
of urgency. These kids don’t have three years for us to figure it out.”
Figure 4.11: Case Studies Implementation:Understanding the Performance Challenge

Note: Adapted from Doubling student performance:…and finding the resources to do it by Odden and
Archibald (2009). Copyright 2009 by Corwin Press.

Greenwood was once the lowest performing school in its district. When the
opportunity presented itself to assign a new principal to the school, the district placed
their previous Director of School Improvement to their lowest performing school within
the district. The principal, previously a curriculum specialist in the area of math,
strategically chose to address the area of math with her staff as she knew they could
experience success early on and planned to harness that success into ELA in the
following year. GE’s math scores improved over 116% in five years. This sense of
understanding the performance problem is contrasted with Redwood. The superintendent
placed a new principal that had the least knowledge and experience with elementary
instruction at RE, the lowest performing school in the district with the most challenging
Weak:
2 schools
Below Average, 0
Average:
1 school
Above Average, 0
Strong:
2 schools
Above Average &
Strong:
2 schools
156
student demographic population. At the time, the school was an upper grade school with
only third through sixth grade but within in a year the district changed course,
transitioning all elementary schools into a K-6 structure. Instead of understanding the
performance problems plaguing the lowest performing school in the district, district
administration allowed the other elementary schools to grow into the additional grade
each year, while RE was forced to house the neighboring upper grade students. This
decision resulted in a disproportionate number of upper grade classrooms at RE and only
one classroom each at the primary level. RE was not only the lowest performing school in
the district in both ELA and math; it was also the lowest performing school among the
case studies.
Set ambitious goals. One of the most significant things any school can do to
improve student performance is to set specific, yet ambitious goals for student
performance (Odden, 2009; Odden & Archibald, 2009). According to Odden, (2009)
schools that doubled student performance not only believed that all children can learn to
high levels, including minority, low-SED and EL students; they also set high goals for
student achievement and educated all students to high performance levels. Schools that
dramatically improve student outcomes to high levels of achievement view their mission
as teaching their students to high levels, and setting high goals for student performance
regardless of the socio-demographic conditions within in their school and community
(Blankstein, 2004; Duke, 2006; Hattie, 2009; Odden, 2009; Odden & Archibald, 2009;
Marzano, 2003; Reeves, 2000; Walberg, 2006; Woody & Henne, 2006). The
accountability measures that are a part of the federal NCLB Act (2002) require schools to
157
meet the AYP targets not only for their entire student body, but for each significant
subgroup as well. The federal AYP AMO requirements have provided greater clarity for
schools to set goals and achievement targets.
Figure 4.12: Case Studies Implementation: Setting Ambitious Goals

Note: Adapted from Doubling student performance:…and finding the resources to do it by Odden and
Archibald (2009). Copyright 2009 by Corwin Press.

Surprisingly, as depicted in Figure 4.12 above, even with federal and state
achievement targets, three of the case study schools were average or below at setting
ambitious goals. The majority of the schools in the study did not set their goals beyond
the federal or state targets and most stated their goal was simply to get out of Program
improvement. Goal setting seemed more about getting out of the sanctions and
accountability structures set in place for PI, rather than setting site specific ambitious and
lofty goals for student proficiency across each subgroup. For example, Elm, Pine, and RE
all shared similar goals that were largely set by the district and based upon federal and
state mandates. On average, the goals for these three schools were as follows: students in
second grade are expected to score proficient or advanced on the CST. Students in
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grades three through sixth are expected to make at least one proficiency band growth on
the CST in both English Language Arts and Math. This growth is expected to take place
until they are able to maintain proficiency or advanced status. Along with goals for the
CST, all English Learner students are expected to make one band’s growth each year on
the California English Language Development Test (CELDT) until they become English
language proficient. None of the schools set strong, specific numerical goals for student
achievement. However, the above example of goal setting is contrasted with GE and OE.
Instead of talking about having students move one CST band each year, GE and OE set
their goal and expectation for all students on mastery learning and expected every student
to be a scholar.
Change the curriculum program and create a new instructional vision. The
third strategy addresses the core educational issues the educators have direct control over
and can change. It involves the curriculum and overall instructional program delivered to
students which are the driving engines of all educational programs (Odden, 2009).
According to Odden and Archibald (2009), schools and districts that produce high levels
of student performance focus on what they can affect, the largest being the curriculum
and instructional programs. The ideology behind the standards-based reform movement is
that the path to raising academic achievement for all students is through effective
instruction (Birman, Desimone, Porter, & Garet, 2000; Odden & Archibald, 2000b). This
ideology is based on research that suggests an effective system-wide approach to
curriculum and learning leads to an increase in student achievement (Langer, 1999;
Marzano, 2003; Togneri & Anderson, 2003). In general, the schools studied
159
demonstrated above average implementation of this strategy as indicted in Figure 4.14
below. Figure 4.14 shows that four of the five schools implemented changing the
curriculum and setting a new instructional vision above average or strong. They all
implemented a state-approved and district-adopted curriculum for all the core subjects
that were linked to standards and all used Houghton Mifflin (HM) as their adopted ELA
curriculum. RE, GE, OE, and Elm transitioned beyond the adopted standards-based
curriculum and began focusing more on standards instruction. These schools broke away
from program fidelity to their HM ELA curriculum as they found the level of rigor asked
of students in their HM ELA series did not match the level or rigor students were
expected to master on state CSTs. Principals at the four schools conducted similar
activities with their staff. For example, they conducted a Bloom’s Taxonomy (taxonomy
of thinking levels from lowest to highest using action verbs) activity with teachers.
Principals had their teachers do an alignment with CST blue prints, Bloom’s Taxonomy
and the HM series. Teachers discovered the CST blue prints and standards had a higher
thinking level in Bloom’s Taxonomy then what the ELA HM series was asking students
to perform. Upon this revelation, contrary to each district’s HM programmatic focus,
principals led their staff to unpack the standards and worked collectively to address any
misalignments by focusing more directly on the standard and the level of rigor necessary
for mastery.

160
Figure 4.13: Case Studies Implementation:Changing the Curriculum Program
Note: Adapted from Doubling student performance:…and finding the resources to do it by Odden and
Archibald (2009). Copyright 2009 by Corwin Press.
OE showed the strongest level of implementation of changing the curriculum and
creating a new instructional vision as they also changed the ELD curriculum and adopted
an intense ELA curriculum for fourth through sixth grade students who were two or more
years below grade level. OE purchased Systematic ELD published by EL Achieve and
authored by Susana Dutro. Systematic ELD breaks ELD instruction into various levels
and has various units for each level. According to the OE principal, Susana Dutro is one
of the leading authorities on ELD instruction and provides professional development and
consulting to districts across the nation. She stated the curriculum was not cheap, but it
was the best ELD curriculum she found and thus aligned resources to provide this for her
staff. Additionally, OE identified over 90 students in grades four through sixth who were
two or more years below grade level. They adopted Gateways created by Action Learning
Systems. Gateways is an intensive ELA curriculum with ELD instruction embedded
within it for grades four and above who are two or more years below grade level. It
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replaced the standard HM ELA program. Both teachers and the principal received a one-
week training on the new series prior to its implementation.
Formative assessments and data-based decision making. According to Stecher
and Kirby (2004), setting goals for desired levels of student performance combined with
using assessments for measuring goal attainment enables school systems to more
accurately judge success. Stiggins (2008) defines assessment, at least in part, as the
process of gathering information to inform instructional decisions. Unless a school
employs assessments that are specific to the curriculum taught, it cannot accurately
determine how well its students are learning (Marzano, 2003). High performing schools,
especially high-performing, low-poverty schools are immersed in a culture of continuous
improvement, incorporating multiple strategies to make decisions based on data rather
than on intuition (Blankstein, 2004; Datnow, et al., 2007; DuFour, et al., 2006; Stiggins,
2002; Stiggins & DuFour, 2009; Walberg, 2006; Woody & Henne, 2006; Williams et al.,
2005; Supovitz & Taylor, 2003;Togneri & Anderson, 2003). Examining how the case
study schools implemented formative assessments and data-based decision making,
Figure 4.14 reveals four schools addressed this strategy above average. Each school
administered ELA and math district benchmarks three to six times a year. Three of the
five schools (Pine, Elm, and RE) based their district benchmarks off the HM ELA
summative test and reported their third HM summative test was correlated to the CST. In
addition to the district benchmarks, these three schools expected teachers to give
formative assessments using the HM ELA Theme Skills Test and along with math
chapter test. Every district utilized some sort of data management system where teachers
162
and administrators could pull various reports to help facilitate data analysis and
desegregate data to respond and target various groups of students.
Figure 4.14: Case Studies Implementation: Data-Based Decision Making
Note: Adapted from Doubling student performance:…and finding the resources to do it by Odden and
Archibald (2009). Copyright 2009 by Corwin Press.

What set some schools apart from others was the amount and types of formative
assessments utilized at the site. For example, as the RE staff shifted their teaching away
from HM program fidelity to a stronger standards focus, they found district benchmarks
were not as standards based as they would like and were not as validating or useful when
it came to what they were doing in the classroom. All five schools released teachers for
“data days” after district benchmark one and two were administered to work
collaboratively along with a site teacher on special assignment (TOSA) or an
administrator to analyze the assessment results and compare it to the standards already
taught. During “data days” teachers compared student results to target instruction and
provide additional support for students not meeting expectations. At RE, teachers began
creating a five question formative assessment for each standard taught in ELA and used it
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as a pre-post assessment within a four to five week cycle. At the third to fourth week, the
five question assessment was given. Students with less than 80% mastery would spend
the next week with re-teaching opportunities while those with 80% mastery and above
received enrichment opportunities.
At GE, as teachers were identifying power standards, and unpacking them,
teachers were committed to coming up with various formative assessments to determine
whether or not their instruction worked; whether their scholars truly earned mastery. The
formative assessments were created in Professional Learning Communities (PLC) grade
level teams along with TOSA support. As teachers began implementing the common
formative assessments, teachers felt the need to do both a mid-month as well as an end of
the month formative assessment. Teachers found the end of the month was too late and
thus planned interventions based upon the scholars who did not meet mastery. In
response, teachers created a teaming system for a small portion of the day where some
scholars were provided enrichment, some scholars received additional help on pre-
requisite skills and other scholars were receiving additional help with the specific
standard they did not master. OE implemented a similar strategy as described by GE
above. Elm and Pine were the only two schools that did not have teachers create their
own common formative assessments within grade level teams. Instead, they utilized all
formative assessments directly from their adopted ELA and math series.
Ongoing, intensive professional development. Improving instruction by
improving professional learning for educators is one of the most important factors that
leads to improved student learning (Wei, Darling-Hammond, Andree, Richardson, &
164
Orphanos, 2009; Elmore, 2000; Odden, 2009; Odden & Archibald, 2009; Odden et al.,
2007; Odden and Picus, 2008; Reeves, 2010). In order to improve student achievement,
educational organizations must continuously strengthen their instructional core by
increasing teachers’ skills and knowledge, engaging students in learning and ensuring the
curriculum taught challenges students academically (Childress, Elmore & Grossman,
2006; Clarke & Estes, 2002). A key strategy to improve student performance is to
improve the knowledge and skills of teachers through providing ongoing, systematic and
intensive professional development (Odden, 2009, Odden & Archibald, 2009).
Surprisingly, despite the fact that all of the schools were Title I schools with additional
funds available for staff development, ongoing, intensive professional development was
below average or average at four of the sample schools as illustrated in Figure 4.15
below.

165
Figure 4.15: Case Studies Implementation: Professional Development
Note: Adapted from Doubling student performance:…and finding the resources to do it by Odden and
Archibald (2009). Copyright 2009 by Corwin Press.

Some of the most effective professional development activities are those that
relate directly to the instructional content and material teachers must use, and take place
in their own schools and classrooms with coaching and ongoing feedback (Miles et al.,
2004). All five schools utilized coaching to some degree as part of their professional
development plan. Some used outside consultants, some used district curriculum
specialists while others used site TOSA support. The amount of coaching opportunities
varied widely across the schools with OE at the peak offering nearly six different
coaching opportunities for staff. OE was the only school within the study that earned a
strong mark for professional development as the level of professional development
offered to its teachers was near the Evidence-Based Model’s (Odden & Picus, 2008)
recommendation. Orangewood had a $40,000 contract with Action Learning Systems for
the 2009-10 school year for professional development and allocated an additional
$40,000 to release teachers for professional development. In 2009-10, each teacher
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received approximately ten days of professional development during the school year.
Action Learning Systems main focus with staff was on question strategies. Teachers
received training and coaching on how to ask deeper level types of questions, questions
that would promote more opened ended response and require students to think critically.
Budget cuts and teacher furlough days further impacted the amount of
professional development principals could offer at the site as many of the first furlough
days to be implemented were staff development days. Greenwood’s principal got creative
and held a professional development day on the Saturday before school started. She paid
teachers to attend the day through her staff development budget. Elm’s district offered
five days of professional development the week before school started, calling it Super
Week. While Super Week was not mandatory for teachers, Elm’s principal reported the
majority of his staff attended Super Week.
Using time efficiently and effectively. Class size reduction is a strategy designed
to help educators use time more efficiently (Odden, 2009; Odden & Archibald, 2009;
Odden & Picus, 2008). According to Odden and Archibald (2009), schools that were
successful at doubling student performance used their fixed resource, instructional time
during the regular school day, more effectively and efficiently. Figure 4.16 below
highlights how the schools implemented using time efficiently and effectively. As
presented in Figure 4.16, three of the schools implemented instructional time effectively
or efficiently at the average or above-average level. While all the schools utilized some
form of class size reduction in the primary grades, it varied greatly which grades
benefited from it and to what extent the class size was reduced. OE was the only school
167
in the study who received the Quality Education Investment Act (QEIA) grant. The QEIA
Grant provides approximately $3 billion to schools authorizing school districts and other
local educational agencies to apply for funding to allocate to elementary, secondary and
charter schools that are ranked in either decile 1 or 2 as determined by the 2005 API base
(California Department of Education, 2010). The QEIA grant is intended to lower class
size to 20: 1 in kindergarten through third grade and between 24 and 25 to 1 in fourth
through sixth grade. Orangewood received funding for the QEIA grant since the 2007-08
school year and it will expire at the end of the 2012-13 school year.
All of the schools except RE mentioned they protected instructional time for core
elementary subjects, particularly ELA and provided ninety minutes of uninterrupted time
for ELA instruction. Pine ensured all student assemblies were scheduled in the afternoon
and did not interrupt morning ELA instruction. Another way schools (OE, Elm, GE and
RE) used time more effectively and efficiently was by grouping students by instructional
level for some portion of the instructional week. Each school leveled students depending
upon the various needs of their students and the agreements made with their grade level
teams. After analyzing student results on formative assessments, teachers formed various
groups to level students for more specific targeted instruction and intervention. Some of
the schools implemented this strategy more intensely than others. The principal at GE
implemented time efficiently and effectively by altering the work hours of her
intervention TOSAs. The principal had a late start for the intervention TOSAs, having
their work hours start a little more than an hour after the school day. This strategy
resulted in building into their contracted teaching day, opportunities to provide after
168
school tutoring for students needing extended learning support. Since the first half hour
block of instruction in the morning was ELD instruction and students would not be pulled
for intervention during ELD instruction, she had the TOSA’s come in later and thus stay
later. It provided primary students with an additional thirty minutes of tutoring after
school and upper grade students an additional hour of tutoring after school.

Figure 4.16: Case Studies Implementation: Using Time Efficiently and Effectively
Note: Adapted from Doubling student performance:…and finding the resources to do it by Odden and
Archibald (2009). Copyright 2009 by Corwin Press.
Extending learning opportunities for struggling students. Reeves (2006)
argues that while it is true that certain student characteristics influence student
proficiency, it is unfounded that student characteristics influence the opportunity for
educators to influence gains in student achievement. In addition to putting the most
effective teachers with the highest need students (Blankstein, 2004; Reeves, 2006;
Williams et al., 2005; Woody and Heene, 2006; Odden, 2009; Odden & Archibald, 2009;
Slavin, 2005) schools that have dramatically improved student learning and narrowed the
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achievement gap provided multiple strategies to help struggling students achieve or
exceed proficiency (Odden, 2009; Odden & Archibald, 2009). Providing multiple-extra
help strategies for students struggling to achieve proficiency is a critical component to
improving the learning outcomes for struggling students (Odden, 2009, Odden &
Archibald, 2009). Only two schools (GE and OE) implemented extended learning
opportunities for struggling students at an above average level and none of them provided
the level of intense support that the Evidence-Based Model (Odden & Picus, 2008)
recommends. As documented in Figure 4.17 below, three of the sample schools scored
average or below average when providing extended learning opportunities for struggling
students. Due to funding and budget cuts the past couple of years, none of the schools
offered an extended school year or summer school program for students not reaching
proficiency in ELA and math. All five schools leveled students during some part of the
school day, dividing students into various homogeneous instructional groups to better
target individual needs. However, the intensity and frequency of this practice varied
across the schools. Three of the schools, Pine, Elm and RE utilized instructional aides,
especially in classes with larger class sizes. However, the instructional aides provided
less instructional support to students and served more clerical or prep work for the
classroom teacher.

170
Figure 4.17: Case Studies Implementation: Extended Learning
Note: Adapted from Doubling student performance:…and finding the resources to do it by Odden and
Archibald (2009). Copyright 2009 by Corwin Press.
While all the schools provided some level of tutoring or intervention support
during or after the school day, only one school had an elaborate extended day program
designed to help struggling students reach proficiency. The success of tutoring, as is with
all instruction, is dependent upon the quality of the person providing the instruction
(Odden & Picus, 2008; Rebora, 2008). Orangewood created a systematic and intensive
extended day program beginning in January of 2010 and serving one hundred-eighty
students. Teachers in grades two through sixth identified two groups of students. The first
group involved students who were their bubble kids, students who were at basic or low
proficient on the CSTs. These students attended the extended day program three days a
week on Mondays, Wednesdays and Fridays. The second group was students who were
far below basic and below basic on CSTs. These students attended the same extended day
program two days a week on Tuesdays and Thursday. OE hired eight part-time non-
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certificated tutors to work in the extended school day program and trained them for two
weeks prior to implementation of the program.
The tutors worked three hours a day, from 2 to 5 PM. Between 2 and 2:40, the
tutors pulled kindergarten and first grade students providing tutoring support for twenty-
one kinder students and twenty-four first grade students in a small group setting of about
five or six to one. During the extended day program, second though sixth grade students
would go into the multi-purpose room. OE worked with nutrition services and provided a
snack to each child attending the extended day program. From there, students were
broken into two groups; group A and group B. Students in group A, went directly to the
tutors for the first hour. Students in group B went directly to the homework side where
volunteers helped students with their homework for an hour. The volunteers on the
homework side were provided through a partnership with a local church in the area.
When working with the tutors, students were working in a small group setting of five or
six to one. The curriculum created was based upon grade level standards, CST blue prints
and CST released questions. After the first hour, group A would go to the homework
side and group B would go to the tutoring side.
At GE, third and fourth grade teachers offered math support through MIND’s ST
Math computer-based program after school two days a week for forty minutes for every
third and fourth grade student. The intervention TOSAs had a late start so they too could
provide extended learning opportunities for students beyond the normal school day. The
principal at GE made arrangements with transportation so bus riders would not miss out
on these additional learning opportunities. As mentioned earlier, the intervention TOSAs
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at GE offered tutoring for thirty minutes a day, five days a week for their primary
scholars and sixty minutes a day, five days a week for the upper grade scholars. Elm
offered a less elaborate extended day program to struggling students. Elm provided
extended day opportunities for struggling students in ELA and math for thirty minutes
four days a week with eight teachers working with up to ten students at a time. However,
the list of students served varied by those that could stay after each day.
Additionally, as Title I schools in PI, Elm, GE, RE and OE were required to
provide supplemental educational services in the form of tutoring to low-income students.
Outside tutoring was provided to several students by private companies using district
funds for about for one hour a day, one to two days a week. However, at Elm and RE, the
tutoring efforts lacked coordination efforts with the school, other than to invite parents to
utilize this service. Beyond hosting a parent night, the tutors did not interact with the
school nor classroom teachers to find out specifically how they could best support the
individual learner.
Collaborative and distributed leadership. Powerful and effective instructional
systems require strong instructional leadership provided by principals, teachers, and
central office staff collaborating purposefully toward utilizing shared instructional
strategies and using common assessment tools (Odden 2009; Raudenbush, 2009). In
professional literature, this often referred to as creating a collaborative and professional
culture with leadership distributed across the organization to enhance effectiveness
(Odden, 2009; Odden & Archibald, 2009; Raudenbush, 2009) and is the eighth and ninth
step in Odden’s (2009) ten strategies to doubling student performance. Examining Figure
173
4.18 indicates only one of the schools in the study (Elm) was below average at instilling a
collaborative culture with distributed leadership. This is in large part because Elm is in a
highly centralized school district that dictates much of the instructional improvements
efforts from the district office to the sites. Teachers are given little latitude in the
instructional program they deliver and do not meet in professional learning teams.
Figure 4.18: Case Studies Implementation: Collaborative and Distributed Leadership
Note: Adapted from Doubling student performance:…and finding the resources to do it by Odden and
Archibald (2009). Copyright 2009 by Corwin Press.
The remaining schools in the study implement PLCs to some degree but they
varied in how much, if any, time was allotted for teachers to meet in collaborative teams.
All five schools’ schedule provided an early out day for students once a week, providing
time for teachers with additional time to meet, plan and receive professional
development. Some schools had restrictions on how they could use this time, but most
principals were given discretion on up to 75% of the early out time to use as they saw fit
for their particular school. Most principals decided to use the bulk of time afforded from
the early out day to teachers to meet in PLC teams. However, the principal at RE decided
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to use the early out day options she controlled for staff meetings and professional
development opportunities instead of providing teachers time to meet as a PLC. Thus, the
teachers lacked common time where they could meet as a PLC. OE was the only school
that allocated resources intentionally to provide teachers with 100 minutes a week during
the regular school day to meet in PLC teams. The school made this a powerful aspect of
their improvement process and hired a PE teacher and two recreational aides to provide
release time for grade levels to meet. Teachers were required to be looking at student data
and submit a report each week to the principal about the students they were monitoring
and the conversations discussed at the PLC meeting. Both OE and GE built in high levels
of accountability within the collaborative time offered to teachers.
Every school in the study created a leadership team made up of grade level
representatives from each grade level. The leadership team members were selected by the
principal to ensure the members on the leadership team would be productive members
who would help move the instructional vision of the school forward. Additionally, every
school reported they received central office support when needed and often used district
curriculum specialist to help provide specific training or professional development to
staff.
Professional and best practices. Odden and Archibald (2009) argue that
exemplary schools use evidence from research, advice from experts and work
collaboratively together to significantly improve student performance. Throughout the
curricular change process, the principals within each case study sample spent time and
resources on training teachers on best instructional practices. In general, Figure 4.19
175
indicates the schools studied demonstrated average to above average implementation of
professional and best practices. Teachers at Pine and RE received specialized training in
SDAIE instructional strategies, training and coaching on differentiation, critical thinking
and student engagement. Additionally, teachers conducted visits at other schools to glean
best practices observed and engaged in classroom walkthroughs to observe engagement
strategies and implementation of data walls. The principal at Elm along with the site
TOSA spent time working with staff during release days to plan direct instruction
lessons, backwards plan, and backwards map ELA instruction.
Four areas GE focused on were standards alignment, scholarly engagement,
parental involvement and helping their scholars create a sense of belongingness to their
school. The GE principal, site coach and intervention teachers spent much time working
with staff at staff meetings on scholarly engagement, checking for understanding and
higher-level thinking. Meanwhile, teachers at GE conducted classroom walkthroughs to
analyze the level of scholarly engagement and share best practices. Teachers at OE
received intensive and on-going professional development in ELA and ELD instruction
throughout the year and were provided with demo-lessons and coaching. OE adopted a
new ELD curriculum along with an ELA curriculum for students in grades four through
six who were two or more years below grade level. The community liaisons at OE taught
a newcomer program to EL students brand new to the country for 20 minutes a day
focusing on English survival skills. Lastly, the majority of the schools in the case study
utilized community liaisons or parent education TOSAs to provided training and
workshops to parents, including the Ten Commandments of Parenting.
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Figure 4.19: Case Studies Implementation: Professional and Best Practices
Note: Adapted from Doubling student performance:…and finding the resources to do it by Odden and
Archibald (2009). Copyright 2009 by Corwin Press.
Comparison of School Resources to the Evidence-Based Model
As previously discussed in the review of the literature, researchers on educational
reform agree that reform efforts must address how existing resources are combined with
educational strategies that have a clear focus on how to improve student achievement and
how both current and new resources are utilized more effectively to increase student
outcomes (Archibald, 2006; Hanushek, 1996, 1997; Hanushek, 2006a; Hanushek &
Lindseth, 2009; Hanushek & Rivkin, 1997; Marzano, 2003; Loeb et al., 2007; Odden,
2003; Odden, 2009; Odden & Archibald, 2009; Odden & Archibald, 2000; Odden et al.,
2008; Odden et al., 2007; Odden et al., 2005; Odden & Picus, 2008; PACE, 2006; Picus
et al., 1996a; Perez et al., 2007; Rebell, 2007; Slavin, 1999, 2005; Williams et al., 2005).
Case studies have supported the value of using an evidence-based model to determine
school-level expenditure structures (Brinson & Mellor, 2005). What sets an evidence-
based model apart from other adequacy approaches is that the model is aligned with
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reform efforts and educational elements supported by research and best practices toward
improving student outcomes (Odden & Archibald, 2009; Odden & Picus, 2008, Picus et
al., 2008; Rebell, 2007). Odden and Picus’ (2008) Evidence-Based Model is a framework
that identifies effective, researched-based strategies and allocates resources that are
aligned with the strategies to deliver a comprehensive and high-quality instructional
program for all students within a school. Odden and Archibald, (2009) acknowledge that
the rigor of evidence supporting the effectiveness of the various recommendations
embedded within the Evidence-Based Model varies; however, the model only includes
recommendations that are supported by sound research, evidence or best practices.
The Evidence-Based Model is based on evidence from the following three
sources: (1) research with randomized assignment to the treatment; (2) research with
other types of controls or statistical procedures to break down the impact of the treatment;
and (3) identified best practices either as codified in a comprehensive school design or
derived from studies of impact at the local district or school level (Odden & Picus, 2008;
Picus et al., 2008). The evidence is compiled and used to identify a comprehensive set of
adequate resources to create a prototypical school (Odden & Picus, 2008). The Evidence-
Based Model includes many strategies that both education researchers and practitioners
argue should be part of any high performing school (Odden & Archibald, 2009). Table
4.7 below summarizes the average findings of the individual case studies (Appendices D-
H) and compares it to the Evidence-Based Model’s (Odden & Picus, 2008) resource
allocation recommendations for a prototypical school. Table 4.7 further compares the
average resource allocations of all the sample schools if the schools were aligned to the
178
Evidence-based Model (Odden & Picus, 2008). As expressed below, on average the
sample schools utilized for this study were about 38% larger than the prototypical school
while allocating less resources for administrative support, general personnel resources,
extended support, other staffing resources and professional development. Resource
allocation information on special education personnel, non-instructional aides, gifted
students, technology, instructional materials and student activities were unable to be
accurately obtained from all the case study schools; therefore these calculations were not
included. What remained were the core elements of the Evidence-Based Model (Odden &
Picus, 2008), which emphasizes that all students receive effective instruction and
extended opportunities for struggling students in the core subject areas of ELA,
mathematics, science and social studies (Picus, et al., 2008).

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Table 4.7: Average Case Study EBM Resource Allocation Comparison
School Element
Evidence-Based
Model
Average Allocation
Average Allocation
Based on EBM
Prototypical Model
School Size K-5; 432 Students K-6; 596 Students 38% Larger
Class Size
K-3: 15
4-5: 25
K-3: 23
4-6: 28.1
K-3: 23.5 57% larger
4-6: 32.2 28% larger
Instructional Days 190, + 10 PD days
179.2 + 1.4PD & 3.6
prep days
10.8 less student days, +
8.6 less PD days
Kindergarten Full-day kindergarten 0.75 day kindergarten
Full Day Kindergarten
Administrative Support
Principal 1.0 FTE 1.4 FTE 1.38 FTE
School Site Secretary 1.0 FTE 1.0 FTE 1.0 FTE
School Site Clerical 1.0 FTE 0.67 FTE 1.38 FTE
General Personnel Resources
Core Teachers 24 FTE 23.1 FTE 32.7 FTE
Specialist Teachers 20% of core teachers
1 FTE (4.3% of core
teachers)
6.54 FTE
Instructional
Facilitators/Mentors
2.2 FTE
0.42 FTE 3 FTE
Extended Support
Tutors for struggling
students
1.0 FTE : 100 low
SES
1.0 FTE 4.77 FTE
Teachers for EL
students
1.0 FTE : 100 ELs
0.26 FTE 3.75 FTE
Extended Day 1.8 FTE 1.1 FTE 2.5 FTE
Summer School 1.8 FTE 0 FTE 2.5 FTE
Special Education Personnel
Learning & mild
disabled students
Additional 3.0 FTE
— —
Severely disabled
students
100% reimbursement
— —

180
Table 4.7, Continued
Other Staffing Resources
Substitutes
5% of personnel
resources
5.4% of personnel
resources
5% of Personnel
Pupil support staff
1.0 FTE : 100 low
SES
1.36 FTE 5.0 FTE
Non-Instructional Aides 2.0 FTE — 2.76 FTE
Librarians/media
specialists
1.0 FTE
0.93 FTE 1.38 FTE
Resources for gifted
students
$25 per student
— —
Technology $250 per pupil — —
Instructional Materials $140 per pupil — —
Student Activities $200 per pupil — —
Professional Development $100 per pupil $36,372 $59,580
Note: Adapted from School finance: A policy perspective (4
th
ed.) by Odden and Picus (2008), pp. 132-133.
Copyright 2008 by McGraw-Hill. Adapted with permission.
Basic School Configuration. Research suggest elementary school size in the
range of 400-500 students are most effective and efficient (Andrews, Duncombe &
Yinger, 2002; Lee & Smith, 1997; Raywid, 1998). Thus, the Evidence-Based Model’s
(Odden & Picus, 2008) prototypical elementary school is based on a K-5 model of 432
students. As depicted in Table 4.8 below, all but one of the case study schools were larger
than the recommended size and all were K-6 configurations. Pine and RE previously
were a K-3 and a 4-6 configuration respectively but the district reconfigured its
elementary structure changing to a K-6 configuration. By 2009-10, both Pine and RE
became a K-6 structure. Research evidence and a review of best practices also indicate
that class size of 15 to 1 in grades K-3 and 25 to 1 in grades 4-6 demonstrated a positive
impact on students’ academic achievement (Finn, et al., 2001; Odden & Picus, 2008).
The impact of small class sizes is even larger for students from low-income and minority
181
backgrounds (Odden & Picus, 2008). As indicated in Table 4.8, every school but OE
exceeded these averages in both the primary and upper grades. OE was the only school in
this study that received funds from the QEIA grant which stipulated class size to 20 to 1
in primary grades and 24 or 25 to 1 (depending upon the grade level) for grades four
through six. As stated earlier, the QEIA grant will expire in 2012-13. At that time, OE
will go back to the class size ratios in its district which is currently 31 to 1 in grades K-3
and 35 to 1 in grades 4-6.
Table 4.8: Basic School Elements Performance of Evidence-Based Strategies
School
School
Size K-3 4-6

Instructional
Days
Contractual
PD/Prep
Days
Full
Day K
Pine Elementary 425 22 36 180 2PD, 4Prep Yes
a

Elm Elementary 560 23.1
b
32 180 0PD
c
, 5Prep No
Orangewood Elementary 694 20 25 176 2PD, 2Prep Yes
Greenwood Elementary 700 27.7
d
32 180 1PD, 3Prep No
Redwood Elementary 600 24 36 180 2PD, 4Prep Yes
a

Prototypical EBM School 432 15 25 190 10PD Yes
Note: Adapted from School finance: A policy perspective (4
th
ed.) by Odden and Picus (2008), pp. 132-133.
Copyright 2008 by McGraw-Hill. Adapted with permission.
a
Kindergarten is one hour less than grades 1-6 at the school which = 85% of day.
b
Class size was 34 to 1 at
Kinder, and 20 to 1in 1
st
-3
rd
grade.
c
Teachers are given 15 hours of PD rate during the year to cash in and
the district offers 5 optional PD days before start of school.
d
Class size was 32 to 1 at Kinder and 3
rd
grade
and 24 to 1 in 1
st
& 2
nd
grade

The Evidence-Based Model (Odden & Picus, 2008) allocates resources providing
190 instructional days and ten days for professional development before the start of the
school year. As portrayed in the table above, all five schools provided 10-14 less
instructional days and 8-10 less professional development days than the model. OE lost
182
four instructional days in 2009-10 due to budget cuts and employee furlough days. In the
coming year, the majority of the sample schools are facing up to nine furlough days,
including the loss of up to five instructional days. OE was the only school that provided
ten professional development days, but it was offered throughout the year and pulled
teachers from their classrooms. Lastly, although numerous studies demonstrate the
effectiveness of providing a full-day kindergarten (Cannon, et al., 2006; H. Cooper, et al.,
2010; Denton, et al., 2003; Flanagan, et al., 2004; Fusaro, 1997; Gullo, 2000; Lee, et al.,
2006), only Pine, OE and RE allocated the resources to implement this evidence-based
strategy.
Administrative support resources. The Evidence-Based Model (Odden & Picus,
2008) recommends one full time equivalent (FTE) administrator for each prototypical
school of 432 students or one part time (0.5 FTE) administrator for every 216 students.
Instead of allocating funds for an assistant principal, the model provides resources for
instructional coaches to help facilitate the instructional program more effectively. The
examination of Table 4.9 below indicates two schools, GE and OE allocated two
administrators but these were also the only two schools with a student population at or
near 700. Additional administrative support is provided for secretarial, clerical and
administrative assistance to administrators and teachers. The Evidence-Based Model
(Odden & Picus, 2008) provides 1.0 FTE senior secretary and 1.0 FTE clerk at the
elementary level. Table 4.9 reveals all of the schools in the study had 1.0 FTE school
secretary but none provided the level of clerical support suggested by the Evidence-Based
Model (Odden & Picus, 2008). GE reported the 2010-11 school year will reduce their
183
assistant principal to half-time due to budget reductions while OE is losing its program
specialist.
Table 4.9: Administrative Support Performance of Evidence-Based Strategies FTE
School
Principal/
Administrator EBM
School
Site
Secretary EBM
School
Site
Clerical EBM
Pine 1.0 1.0 1.0 1.15 0.5 1.0
Elm 1.0 1.3 1.0 1.3 0.38 1.3
Orangewood 2.0 1.61 1.0 1.61 0.75 1.61
Greenwood 2.0 1.62 1.0 1.62 1.2 1.62
Redwood 1.0 1.39 1.0 1.39 0.5 1.39
Average Relative
Percent Change
- 19.76 - 28.07 - 52.83
Note: Adapted from School finance: A policy perspective (4
th
ed.) by Odden and Picus (2008), pp. 132-133.
Copyright 2008 by McGraw-Hill. Adapted with permission.
In order to compare the results of the case studies (Appendices D-H) with other
schools, the average relative percent change was calculated. The percent change was
used to compare the experimental case studies, E, with the theoretical, T, Evidence-Based
Model (Odden & Picus, 2008). The percent change calculated is the absolute value of the
difference divided by the theoretical value times 100:
% 100
As demonstrated above in Table 4.9, the average prototypical school would have
allocated 19.76 percent more administrative resources, 28.07 percent more secretarial
support, and 52.83 percent more clerical support.
General personnel resources. In many schools, less than 50% of educational
resources are directly allocated to core academic areas (Odden et al., 1995). Furthermore,
184
from 1950 to 1995, the proportion of core classroom teachers to certificated staff fell
from 70% to 52% (Odden & Picus, 2008). Given the demands of holding all students
accountable to the same performance standards in core subject areas, the Evidence-Based
Model (Odden & Picus, 2008) allocates a majority of instructional dollars to core
instruction. Thus, the Evidence-Based Model (Odden & Picus, 2008) protects the
encroachment of elective and other non-core classes to no more than 20%. For an
elementary school, the model recommends 24 core instructors based on class size
research outlined above in the literature review. Additionally, specialist teachers are
provided by the Evidence-Based Model (Odden & Picus, 2008) to enrich student
education through art, music, library skills, and physical education while providing
release time for teachers for collaborative planning, job-embedded professional
development, and ongoing curricular development. In order to provide this planning time,
the Evidence-Based Model (Odden & Picus, 2008) allocates 20% additional staff to
elementary schools to provide teachers with 45-60 minutes daily for preparation and
collaborative time.
As illustrated in Table 4.10, all five schools allocated less resources for both core
instruction and specialist teachers than what the Evidence-Based Model (Odden & Picus,
2008) would provide. While according to Table 4.10, OE was the only school that did not
allocate resources for instructional facilitators, OE provided instructional coaching to
staff through their professional development contract with Action Learning Systems. The
majority of the schools indicated the loss of their instructional coaches and facilitators in
the 2010-11 school year due to budget cuts. Additionally, all but OE will be raising class
185
size in every grade between 2-8 students in 2010-11 due to budget reductions. As
indicated in Table 4.10 below, the average prototypical school would have allocated
29.71 percent more core teachers, 83.05 percent more specialist teachers, and 85.62
percent more instructional support.
Table 4.10: General Personnel Resources of Evidence-Based Strategies FTE
School
Core
Teachers EBM
Specialist
Teachers
EBM
20% of
Core
Instructional
Facilitators EBM
Pine 15.0 21.89 1.1 (7% of core) 4.38 0.4 2.2
Elm 24.0 33.9
0.4 (1.7% of
core)
6.78 0.2
2.86
Orangewood 32.0 39.0
1.5 (4.7% of
core)
7.8 0.0
3.54
Greenwood 25.0 39.8 0 (0% of core) 7.96 0.5 3.56
Redwood 19.5 29.0 2.0 (10% of core) 5.8 1.0 3.06
Average Relative
Percent Change
- 29.71 - 83.05 - 85.62
Note: Adapted from School finance: A policy perspective (4
th
ed.) by Odden and Picus (2008), pp. 132-133.
Copyright 2008 by McGraw-Hill. Adapted with permission.
Extended support resources. Regardless of the quality of a school’s
instructional program, most schools will have some students that need more than the
instruction already provided by the regular classroom teacher (Odden 2009). Odden and
Picus (2008) accounts for the fact that not all students will master the performance
standards within the core instructional program, and that a school must design additional
effective strategies to support proficiency for struggling learners. The model provides
tutors to support struggling students with immediate, intensive assistance during the
regular school day to support content mastery. One credentialed teacher is allotted under
186
the Evidence-Based Model (Odden & Picus, 2008) for every 100 low-social-economical
status (SES) students. Research also shows that ELs from lower-income and less
educated backgrounds often struggle in school and require additional help (Gandara &
Rumberger, 2007; Odden & Picus, 2008). As with low-SES students, the Evidence-Based
Model (Odden & Picus, 2008) provides EL students an additional 1.0 FTE fully
credentialed teacher for every 100 EL students enrolled in the school. The model also
accounts for extended support resources for extended day programs and extended school
year to help struggling students reach proficiency. The Evidence-Based Model (Odden &
Picus, 2008) provides 1.8 FTE in a prototypical school for both extended-day and
summer school opportunities. As examination of Table 4.11 indicates, all of the schools
no longer provide a summer school program to help struggling students reach proficiency
in ELA and math. The majority of the case study schools cut summer school as part of
their district’s operating budget in the 2009-10 school year given the reductions in
revenue from the state.
Only three schools (Elm, OE and GE) allocated resources to provided extended
learning opportunities for struggling students beyond the regular school day. OE had the
most elaborate and systematic extended day program and served the most number of
students in their extended day program. OE allocated the equivalent of 3 FTE to serve
180 students after school; however, their tutors were not certificated teachers. As
depicted above, the average prototypical school would have allocated 79.97 percent more
tutors for low-SES students, 89.16 percent more teachers for EL students, 61.67 percent
187
more extended day instructors, and the equivalent of 100.0 percent more FTE for the
implementation of summer school.
Table 4.11: Extended Support of Evidence-Based Strategies FTE
School Tutors EBM
Teacher
for ELs EBM
Extended
Day EBM
Summer
School EBM
Pine 0.4 2.89 0.8 1.87 0.0 1.80 0.0 1.80
Elm 0.5 4.2 0.0 3.7 1.83 2.34 0.0 2.34
Orangewood 0.0 5.62 0.0 3.88 3.0
1
2.9 0.0 2.9
Greenwood 3.5 6.02 0.0 4.2 0.5 2.9 0.0 2.9
Redwood 1.0 6.0 0.5 4.38 0.0 2.5 0.0 2.5
Average Relative
Percent Change
- 79.89 - 89.16 - 61.67 - 100
Note: Adapted from School finance: A policy perspective (4
th
ed.) by Odden and Picus (2008), pp. 132-133.
Copyright 2008 by McGraw-Hill. Adapted with permission.
1
Tutors provided were non-certificated tutors. EBM calls for certificated tutors
Other staffing resources. In addition to the school elements already outlined
above, the Evidence-Based Model (Odden & Picus, 2008) also accounts for substitute
teachers, librarians/media specialists, pupil support staff and professional development
resources. According to Odden and Picus (2008), schools are enhanced with student
support and family outreach embedded into the school culture, particularly for schools
with disadvantaged students. The Evidence-Based Model (Odden & Picus, 2008)
provides one licensed professional for every 100 low-SES students, with a minimum of
1.0 FTE for each prototypical elementary school of 432 students. The recommendation
enables school districts and individual schools to allocate the FTE across guidance
counselors, social workers, nurses, and other student support professionals in a way that
best fits the need of the school. As demonstrated in Table 4.12 below, every school in the
188
study employed some form of pupil support staff, usually in the form of a community
liaison and health aide. GE was the only school that piloted a model of a half-time
certificated teacher as a parent TOSA. However, none of the schools allocated resources
for pupil support staff near the model’s recommendations. As shown in Table 4.12 below,
the average prototypical school would have allocated 29.86 percent more resources for
librarians and/or media specialist, 73.01 percent more pupil support staff and nearly 50
percent more towards professional development. The majority of the schools report
budget reductions in 2010-11 has resulted in cutting community liaisons and health aides.
GE’s half-time parent education TOSA will also no longer be funded in 2010-11. Each
school will face nearly a 40% cut in professional development resources and will see a
sharp increase in cost of substitutes due to layoff rights of probationary and permanent
employees.
Table 4.12: Other Staffing Resources of Evidence-Based Strategies FTE
School
Librarians
/Media
Specialist EBM I.A EBM
Pupil
Support
Staff
EBM
1
FTE
per
100
SED
Professional
Development EBM
Pine 1.0 1.0 0.43 0.0 0.74 2.89 $13,200 $42,500
Elm 0.94 1.30 2.25 0.0 1.36 4.7 $31,662 $56,000
Orangewood 0.72 1.61 0.0 0.0 1.53 5.62 $83,000 $69,400
Greenwood 1.0 1.62 0.0 0.0 1.48 6.02 $33,000 $70,000
Redwood 1.0 1.39 2.0 0.0 1.7 5.94 $21,000 $60,000
Average Relative
Percent Change
- 29.86 - - - 73.01 - 49.97
Note: Adapted from School finance: A policy perspective (4
th
ed.) by Odden and Picus (2008), pp. 132-133.
Copyright 2008 by McGraw-Hill. Adapted with permission.
189
Summary & Lessons Learned
Providing an adequate education and connecting it with a funding structure that
supports all students reaching academic proficiency has been an enduring goal of
educators (Odden & Picus, 2008). California school demographics are changing with
increasing minority, EL and low income students entering the system who often require
additional resources to help them attain proficiency. School administrators and district
staff must decide how to allocate resources to serve a diverse student population with a
broad range of needs. Often, these needs compete against each other for the equity of
resources allocated. Understanding how resources are allocated at the school level to
successfully improve the achievement level of all students, while simultaneously
narrowing the achievement gap, is critical. However, this skill and vision is often lacking
at the school site. Determining the allocation of resources based on student needs at the
school level involves issues of equity and adequacy. Utilizing the Evidence-Based Model
(Odden & Picus, 2008) as a resource allocation framework, this chapter examined and
summarized the findings of individual case studies (Appendices D-H). The case study
findings were summarized to provide descriptive cross-case comparisons so that one may
further enhance the understanding of: (1) the demographic and academic data within the
schools; (2) key elements and themes of the improvement process; and (3) how the use of
an evidence-based model can guide effective resource allocations.
The purpose of this study was to analyze site level resource allocation strategies
in diverse schools that are resulting in significant growth in their Academic Performance
Index (API), compared with schools who’s API dropped dramatically. Purposeful
190
sampling using criterion and intensity-based approaches for this study selected schools
improving their 2009, API score by at least 42 points and schools declining in API score
by at least 17 points with student demographic populations that included at least 60%
SED, 50% Hispanic, and 40% EL. The schools in this study are responsible for educating
some of the largest percent of minority, EL and SED students. Each case study’s
Hispanic, EL and SED student population all were well above the average compared to
the state and county.
In addition to categorizing and summarizing the occurrence of the ten educational
strategies outlined by Odden and Archibald (2009) each elementary school that
participated in the study were ranked regarding their implementation of each evidence-
based strategy on an ordinal scale (Glass & Hopkins, 1996; Odden & Archibald, 2009). A
cross-comparison examination of the interviews indicated that schools that participated in
this study implemented a number of strategies to change the curriculum and create a new
instructional program along with employing formative assessments and data-based
decision making. How schools used formative assessments and data-based decision
making to guide their instruction and implement various additional learning opportunities
for students not reaching mastery seemed paramount to the school’s overall academic
success. The greatest variability among the sample schools was found in how the overall
school culture understood the performance problem and challenge. Schools with a greater
sense of urgency to improve student proficiency embedded this sense of urgency
throughout the school culture and used it as the driving engine in their reform efforts.
191
Although each of the case study schools demonstrated the application of all ten evidence-
based strategies, their implementation and intensity varied.
As previously discussed in the review of the literature, researchers on educational
reform agree that reform efforts must address how existing resources are combined with
educational strategies that have a clear focus on how to improve student achievement and
how both current and new resources are utilized more effectively to increase student
outcomes (Archibald, 2006; Hanushek, 1996, 1997; Hanushek, 2006a; Hanushek &
Lindseth, 2009; Hanushek & Rivkin, 1997; Marzano, 2003; Loeb et al., 2007; Odden,
2003; Odden, 2009; Odden & Archibald, 2009; Odden & Archibald, 2000; Odden et al.,
2008; Odden et al., 2007; Odden et al., 2005; Odden & Picus, 2008; PACE, 2006; Picus
et al., 1996a; Perez et al., 2007; Rebell, 2007; Slavin, 1999, 2005; Williams et al., 2005).
An evidence-based model approach strives to identify a set of effective educational
procedures based on proven research strategies in order to deliver an adequate and
comprehensive instructional program for all students at the school site level (Odden &
Archibald, 2009; Odden & Picus, 2008, Picus et al., 2008; Rebell, 2007). Odden and
Picus’ (2008) Evidence-Based Model is a framework that identifies effective, researched-
based strategies and allocates resources that are aligned with the strategies to deliver a
comprehensive and high-quality instructional program for all students within a school.
Case studies have supported the value of using an evidence-based model to determine
school-level expenditure structures (Brinson & Mellor, 2005). Based on the average
findings of the individual case studies (Appendices D-H), the schools utilized for this
study were about 38% larger than the prototypical school while at the same time allocated
192
less resources for administrative support, general personnel resources, extended support,
other staffing resources and professional development. Although the summaries and
analysis above provide interesting findings, further in-depth cross-comparison analysis of
each evidence-based strategy across the numerous case studies (Appendices D-H)
provides for greater triangulation and supporting evidence regarding the quality of
implementation (Patton, 2002).

193
CHAPTER 5 – DISCUSSION
There is growing evidence that educational quality, measured by proficiency in
test scores, is highly related to economic growth and directly related to future individual
earnings (Hanushek & Lindseth, 2009; Loeb et al., 2007;). Despite the development of
challenging education standards and sustained attention to school improvement over the
past ten years, California continues to lag behind its counterparts on various measures of
student achievement (Loeb et al., 2007; Edsource, 2007, 2008, 2009b, 2009c). The low
achievement of California’s students will likely hurt their economic outcomes later in life
and be detrimental to the state as a whole (Loeb et al., 2007). Despite being one of the
largest economies in the world, California continues to fund education below the national
average. California schools have been hit with substantial budget reductions over the past
few years and are facing additional budget reductions which will directly impact services
and programs offered to support student learning. Given the economic situation today,
coupled with the fact that educational funding is experiencing severe budget reductions
over the past few years, it has become paramount that educators and policymakers
analyze the efficiency and efficacy of how scarce resources are allocated.
California school demographics are changing with increasing numbers of
minority, English Learners (EL) and low-income students entering the system – students
who often require additional resources to help them attain proficiency (Loeb et al., 2007;
Hanushek, 2006a; Picus, 2006, Odden, 2009; Odden & Picus, 2008). Educating a
massive, diverse student population like California makes the allocation of resources a
daunting task especially in times of unprecedented budget reductions. As educational
194
leaders are faced with the overwhelming responsibility to determine which services and
programs should be cut while re-aligning remaining resources to continue to meet the
demands of improved student performance, successful resource allocation strategies that
improve student learning must be identified. Understanding how resources are allocated
at the school level to successfully improve the achievement of all students, while
simultaneously narrowing the achievement gap, is critical.
An adequacy model of funding sets out to determine the level of resources for
students based on their individual needs and the amount of resources necessary for them
to achieve an agreed upon performance benchmark (Bhatt & Wraight, 2009; Hanushek &
Lindseth, 2009; Odden, 2003, Pace, 2006; Odden & Picus, 2008; Rebell, 2007). An
evidence-based approach to school funding identifies a comprehensive set of school-level
elements identified through empirical research and best practices that are necessary to
deliver a high-quality comprehensive instructional program (Baker et al, 2008; Bhatt &
Wraight, 2009; Hanushek & Lindseth, 2009; Odden, 2003; Odden & Picus, 2008; Picus,
2006; Rebell, 2007). Using the Evidence Based Model (Odden & Picus, 2008), this study
seeks to provide local educators and policymakers within California greater insight into
how disadvantaged schools can utilize their resources effectively to defy the odds and
promote change. This chapter summarizes the study’s research findings gleaned from the
case studies of five elementary schools (Appendices D-H); examines lessons learned
through the triangulation of multiple data sources; addresses additional limitations
identified through the inquiry process; and discusses the implications for future research
considerations based upon the results of this study.
195
Summary of Findings
Many schools with similar student populations and resources have been
successful in closing the achievement gap and improving overall student performance
(Odden, 2009; Odden & Archibald, 2009; Reeves, 2000; Marzano, 2003; Perez, Parish,
Anand, Speroni, Esra, Socias, et al., 2007; Williams, Kirst, Haertel et al., 2005). It is
imperative schools have clarity on successful educational strategies so that they can
restructure themselves around a more powerful instructional improvement process
(Odden, 2009). The purpose of this study was to analyze site level resource allocation
strategies in diverse schools that result in significant growth in their Academic
Performance Index (API), compared with schools where the API dropped dramatically.
Purposeful sampling using criterion and intensity-based approaches for this study
selected schools improving their 2009, API score by at least 42 points and schools
declining in API score by at least 17 points with student demographic populations that
included at least 60% Social-economically disadvantaged (SED), 50% Hispanic, and 40%
EL. The schools in this study are responsible for educating some of the largest percent of
minority, EL and high-poverty students. Each case study’s Hispanic, EL and SED student
population were well above the state and county averages.
Frameworks developed by Odden (2009) and Odden and Archibald (2009) on
how schools can double student performance were utilized as a lens throughout this study
to establish a common set of core educational elements schools used during their reform
efforts. In addition to categorizing and summarizing the occurrence of the ten educational
strategies outlined by Odden and Archibald (2009) each elementary school that
196
participated in the study was ranked regarding their implementation of each evidence-
based strategy on an ordinal scale (Glass & Hopkins, 1996; Odden & Archibald, 2009).
Cross-comparative analysis of the individual case studies (Appendices D-H) indicated
that schools that participated in this study implemented a number of strategies to change
the curriculum and create a new instructional program along with employing formative
assessments and data-based decision making. How schools used formative assessments
and data-based decision making to guide their instruction and implement various
additional learning opportunities for students not reaching mastery seemed paramount to
the school’s overall academic success. The greatest variability among the sample schools
was found in how the overall school culture understood the performance problem and
challenge. Schools with a greater sense of urgency to improve student proficiency
embedded this sense of urgency throughout the school culture and used it as the driving
engine in their reform efforts. Although each of the case study schools demonstrated the
application of all ten evidence-based strategies, their implementation and intensity varied.
In addition to effective strategies, this study also analyzed resource allocation
patterns at the sample schools using the Evidence-Based Model (Odden & Picus, 2008).
This approach attempts to provide schools with specific details about educational
strategies shown by research to be effective in raising student achievement; strategies that
both education researchers and practitioners argue should be part of any high performing
school (Odden & Archibald, 2009). The Evidence-Based Model (Odden & Picus, 2008)
compiles the educational elements and generates the necessary resources to create a
prototypical school. The Evidence-Based Model’s (Odden & Picus, 2008) prototypical
197
elementary school was used to compare the resource allocation strategies implemented by
the schools within this study. Predicated on the average findings of the individual case
studies (Appendices D-H), the schools utilized for this study were 38% larger than the
prototypical school while allocating less resources for administrative support, general
personnel resources, extended support, other staffing resources and professional
development.
Lessons Learned
Improving student proficiency for all students should be the primary mission of
all schools and can be one of the most overwhelming challenges any school undertakes
(Reeves, 2005). Research continues to provide growing evidence that schools have
much more control over student performance and other school related problems than
many choose to believe (Darling-Hammond, 1997; Marzano 2003, Odden 2009, Odden
& Archibald, 2009; Schmoker, 1999). Many schools with similar student populations and
resources have been successful in closing the achievement gap and improving overall
student performance (Odden, 2009; Odden & Archibald, 2009; Reeves, 2000; Marzano,
2003; Perez, Parish, Anand, Speroni, Esra, Socias, et al., 2007; Williams, Kirst, Haertel et
al., 2005). Providing an adequate education and connecting it with a funding structure
that supports all students reaching academic proficiency has been an enduring goal of
educators (Odden & Picus, 2008). Case studies of similar schools have supported the
value of using an evidence-based model to determine school-level expenditure structures
and how to target the resources effectively to improve student proficiency (Brinson &
Mellor, 2005).
198
The purpose of using a multiple-method, case study approach for this inquiry was
to illustrate a comprehensive picture of the resource allocation strategies applied at the
site level through garnering systematic and in-depth information (Morse, 2003; Patton,
2002). Descriptive cross-case comparisons helped identify lessons learned through
multiple case studies. The purpose of the lessons learned outlined below is to help
practitioners identify successful strategies that can be adapted and applied to other similar
settings to improve student learning (Patton, 2002). Utilizing the Evidence-Based Model
(Odden & Picus, 2008) and Odden’s (2009) strategies to improve student performance,
the purpose of this study was to analyze site level resource allocation strategies in diverse
schools that resulted in significant growth in their Academic Performance Index (API),
compared with schools who’s API dropped dramatically. School level analysis resulting
from this study contributes to the discussion on how an evidence-based adequacy model
can help identify effective educational strategies for improving our schools. Site level
analysis further provides educators insight on the wisdom and merits of the lessons
learned through the triangulation of multiple methods and sources used throughout this
inquiry (Patton, 2002).
Instructional vision and improvement strategies. The first research question
addressed identifying the current instructional vision and improvement strategies at the
school level. Teachers, principals, and school leaders must fully understand the
performance challenge and have a strong desire to want to address student performance
(Odden & Archibald, 2009). Bold improvement moves beyond duplicating or refining
existing practices and instead transforms the school’s culture by shedding ineffective
199
practices and creating a mission that all students can achieve to high levels of learning
(Odden, 1998). Although each of the case study schools (Appendices D-H) demonstrated
the application of all ten evidence-based strategies, their implementation and intensity
varied. The greatest variability among the sample schools was found in how the overall
school culture understood the performance problem and challenge coupled with how
schools set goals to mitigate these performance challenges. The common theme
interwoven throughout the most successful schools was the sense of intense urgency and
personal responsibility to improve student proficiency for all students. The foundation for
this urgency appeared to be an unwavering belief that all students, (often referred to as
scholars), including minority, EL and low-SES students, can learn at high levels and
reach mastery.
Schools with a greater sense of urgency to improve student proficiency embedded
this sense of urgency throughout the school culture and used it as the driving engine in
their reform efforts. Often, the critical question is not about the risk of change, but
instead, the risk associated if the system fails to change (Reeves, 2006). The urgency to
improve student proficiency was supported by district leadership but was organic in
nature in how it was generated first at the site level in large part by the relentless pursuit
of the site principal. Effective leaders believe in holistic accountability; they review data,
make midcourse corrections and focus decision making on the aspects that have the most
leverage (Bolman & Deal, 2006; Reeves, 2006; Blankstein, 2004; DuFour et al., 2006;
Reeves, 2006). With a strong sense of urgency to improve student proficiency, schools
200
seemed to align collaborative time for teachers and support staff to plan response
strategies to support struggling students.
Schools that harnessed the sense of urgency to improve student proficiency set
their goals beyond the federal or state targets, beyond getting out of the sanctions and
accountability structures set in place by Program Improvement. The urgency and
expectation that all students could reach mastery propelled these schools to set ambitious,
site-specific goals for student proficiency across each subgroup. Schools that
dramatically improve student outcomes to high levels of achievement view their mission
as teaching their students to high levels, and setting high goals for student performance
regardless of the socio-demographic conditions within in their school and community
(Blankstein, 2004; Duke, 2006; Hattie, 2009; Odden, 2009; Odden & Archibald, 2009;
Marzano, 2003; Reeves, 2000; Walberg, 2006; Woody & Henne, 2006). Setting
ambitious goals goes beyond setting “stretch goals” or getting the “bubble” kids over the
proficiency bar, instead ambitious goals focus on educating all students to proficiency,
focusing on educating a large portion of students to advanced levels of performance
(Odden, 2009). Schools that set high goals and do not meet them in one year do not
blame the students or their home-life, instead they take responsibility themselves, modify
the curriculum program and seek to reverse the drop next year (Blankstein, 2004; Odden,
2009, Odden & Archibald, 2009; Reeves, 2000; Walberg, 2006; Woody & Henne, 2006).
They believe they can attain these goals and work relentlessly to attain them without
excuses.
201
Resource allocations that supported the improvement plan. The second
research question looked at how resources at the school and district were used to
implement the school’s instructional improvement plan. Slavin (1999) acknowledges that
while increased dollars do not magically transform themselves into greater learning, it is
evident that money can make a difference if spent on specific programs or other
investments known to be effective. Evidence across research studies seems to conclude
that what matters more than adding additional resources to improve student outcomes, is
how resources are combined with educational strategies that have a clear focus on how to
improve student achievement and how the resources are used more effectively to increase
the academic proficiency of all students (Archibald, 2006; Hanushek, 2006a; Hanushek
& Lindseth, 2009; Loeb et al., 2007; Odden, 2009, Odden & Archibald, 2009; Odden and
Picus, 2008; PACE, 2006; Hanushek, 1996, 1997, 2006a; Hanushek & Lindseth, 2009;
Hanushek & Rivkin, 1997; Marzano, 2003; Loeb et al., 2007; Odden, 2003, 2009; Odden
& Archibald, 2009, 2000; Odden et al., 2008; Odden et al., 2007; Odden et al., 2005;
Odden & Picus, 2008; PACE, 2006; Picus et al., 1996a; Perez et al., 2007; Rebell, 2007;
Slavin, 1999, 2005; Williams et al., 2005). Schools that have dramatically improved
student learning and narrowed the achievement gap aligned resources to provide multiple
strategies to help struggling students achieve or exceed proficiency (Odden, 2009; Odden
& Archibald, 2009).
The culture of urgency and personal responsibility for student performance drove
these schools to implement various support mechanisms tailored to the needs of their
students. These schools aligned resources with their mission that while all students can
202
learn at high levels and reach mastery, some require additional support and extended
learning opportunities to reach mastery. A common theme interwoven among the
successful schools was their ability to utilize time effectively and more efficiently to
provide extended learning opportunities for struggling students. Schools that were
successful at helping all students reach scholarly mastery created systematic and
intensive extended day programs designed to help struggling students reach proficiency.
Between restructuring the work hours of intervention teachers to provide tutoring both
during the school day and after school or using trained tutors to provide intense after
school programs connected to grade level standards and homework support, successful
schools transformed their practice and aligned scare resources to support their driving
mission. Additionally, these schools believed strongly in improving student performance
by improving instruction and dedicated the resources to improve instruction through
intense and ongoing professional development. Even though many of the schools in the
studies lost professional development days due to negotiated furlough days, successful
schools did not let that deter them from finding creative ways to improve the knowledge
and skills of their teaching practice.
Response to budget shortfalls and adjustments. The third research question
examined how the allocation and use of resources at the school changed in response to
recent budget adjustments including overall funding reductions and changes in the use of
categorical funds. Given the fact that nearly 85% of district spending in California goes
toward employee salaries and benefits (Edsource, 2010d), the majority of schools
responded to budget shortfalls by reducing employee cost through a combination of
203
layoffs, salary reductions and furlough days. Although all the schools had significant
portions of their student population not meeting proficiency, the majority of them were
faced with having to cut up to five instructional days within the normal school year, while
all of them no longer offer a summer school program for struggling students. Similar to
the findings by Edsource (2010d) which surveyed California school districts’ responses
to the budget shortfalls, all of the schools took advantage of the increased flexibility in
helping them manage their budgets. In particular, districts tended to shift funds away
from adult education, deferred maintenance, professional development, art, music, gifted
education, supplemental instruction, counseling and community liaisons and aligned
available funds into core K-12 instruction (EdSource, 2010d).
Resource alignment with the Evidence-Based Model. The final research
question sought to compare how the actual resource use patterns at the school sites were
aligned with or different from the resources use strategies used in Odden and Picus’
(2008) Evidence-Based Model. While the Evidence-Based Model (Odden & Picus, 2008)
allocates resources for summer school programs for struggling students, recent budget
reductions have caused the schools within the study to cancel this vital support strategy
The average relative percent change was calculated to compare the experimental case
studies with Odden and Picus’ (2008) Evidence-Based Model. While all the schools
utilized fewer resources than the prototypical model, the greatest discrepancies in
resources allocated were resources targeted to support struggling students, SED and EL
students. Schools that mitigated the discrepancies between the resources recommended
by the Evidence-Based Model (Odden & Picus, 2008) with the actual resources targeted
204
for intervention and extended learning opportunities the most, experienced larger gains in
student achievement. The average prototypical school would have allocated 89.16% more
teachers for EL students; 85.62% more instructional coaches; 83.05% more specialist to
provide collaborative time for teachers to plan response strategies and interventions; 80%
more instructional tutors for struggling students; 73% more pupil support staff; and
61.67% more staff to provide extended day programs for struggling students.
Limitations
Comparing the school level resource allocation practices of five elementary
schools in Southern California to the Evidence-Based Model (Odden & Picus, 2008) had
several limitations. Due to the small sample size of the study, the findings cannot be
generalized to many other schools or student populations. While the methodology used
was a multiple methods approach, the schools chosen for this study were not randomly
selected. Second, the study relied on selection criteria and events that occurred 14
months prior to the implementation of data collection. Thus, it is difficult to assess if
success growth in API was due to the allocation models being described by site level
administration, or other factors beyond the schools’ control. Third, due to individual
district policies restricting research access coupled with site level principal’s willingness
to participate in the study, not all of the elementary schools that met the original selection
criteria within Orange County were studied. Fourth, both the Evidence-Based Model
(Odden & Picus, 2008) and the Ten Strategies for Doubling Student Performance
(Odden, 2009; Odden & Archibald, 2009) frameworks used for this study assume site
level control of resource allocation and freedom to implement identified educational
205
strategies. However, due to variation of district centralization and control regarding
funding resources, what may have actually been studied was district level allocation of
resources as opposed to school site level as intended. Fifth, the American Recovery and
Reinvestment Act (ARRA) was enacted in February 2009. School districts across the
nation received one-time additional federal funding that will be required to be spent by
June 30, 2010. The outcome of this study may be skewed as a result of the various ways
in which districts and schools allocate the additional one-time funds. Finally, the original
purpose to compare schools that experienced substantial growth to schools that
experienced substantial decline became problematic as the schools were inconsistent with
their academic progress over the years. However cross-case comparisons were examined
within the frameworks of this study to identify effective and ineffective educational
elements utilized by the sample schools to improve student proficiency.
Implications for Future Research
Conducting additional analysis on how successful schools with different student
populations are demonstrating academic growth by aligning research and best practices to
the allocation of scarce fiscal resources will contribute further to the academic literature
and enhance site level application. One cannot assess our ability to target reforms without
clearly understanding how we allocate and use educational resources (Picus, 2006). In
order to help schools successfully and adequately align resource allocations to effective
strategies that generate consistent improvement in student learning, additional research is
needed. While there is a tremendous amount of research on strategies to address the
needs of struggling students, there is a shortage in the literature on how successful
206
schools actually allocate resources to improve student learning. The results from this
study found wide variations in the resource allocation strategies used throughout the five
case study schools. As increased educational funding in the near future appears dismissal,
the focus should shift on how successful schools are demonstrating academic growth by
aligning research and best practices to the allocation of scarce fiscal resources. Further
research on the Evidence-Based Model (Odden & Picus, 2008) that identifies the effect-
size of the various strategies recommended by the model could help practitioners with
limited resources determine which strategies to focus on if they cannot afford to
implement the entire model. For example, would it be more effective to provide
instructional coaches and tutors than to reduce class size to the recommended levels? As
budget shortfalls appear to be on the horizon and California seems unlikely to be able to
sustain the revenue streams necessary to support the Evidence-Based Model (Odden &
Picus, 2008), understanding which components on average produce larger gains in
student proficiency would help educators align their limited resources more effectively.
Future research is recommended to determine the how some schools in various
settings instill an intense sense of urgency and personal responsibility to improve student
proficiency for all students and how schools permeate this urgency throughout the school
culture. Many schools seem to lose the sense of urgency to improve student learning after
they have reached a certain threshold of performance. Additional research is
recommended to study how schools with a strong sense of urgency to improve student
performance maintain a critical sense of urgency even after several years of continuous
improvement. Lastly, further inquiry is recommended in how successful schools establish
207
a myriad of extended learning opportunities for struggling students and establish
successful extended day programs. Educational practitioners need further insight into best
practices on extended day programs, programs that move beyond homework help and
tutoring disconnected to the grade level standards taught during the normal instructional
day. Inquiry on the components, planning, and sustainability of systematic extended day
programs could provide other schools with a general road map on things to include,
pitfalls to avoid and best practices implemented.
Conclusion
Improving student performance is the hallmark of educational policy today. The
standards-based reform movement has been a cornerstone of education policy for over 20
years. Standards-based education reform seeks to educate all students to high levels of
achievement and clearly identifies target benchmarks for student performance. Implied
in this goal is both an element of equity and excellence (Odden, 2003). The future of
America depends on America’s educated youth. What American students learn in school
today will decide whether we as a nation can meet our greatest challenges tomorrow
(Obama, 2009). Since the late 1950’s numerous federal and state education laws have
been approved, countless reform measures have been initiated and a myriad of court
cases have been rendered to improve student outcomes and minimize the achievement
gap among minority and white students. Despite a massive financial investment to K-12
education over the past four decades, from both a federal and state level, student
achievement has remained relatively flat (Hanushek & Rivkin, 1997; Hanushek &
Lindseth, 2009). In times of limited resources and fiscal constraints, utilizing an effective
208
resource allocation model that is supported by research and connected to improved
student outcomes is imperative. Although similar schools within the same school district
often receive the same amount of funding, student achievement can vary greatly
(EdSource, 2007).
School sites must address the challenge of adequately educating an increasingly
diverse student population with fewer resources and less decision rights on how to
effectively allocate resources to improve student outcomes. The evolution of educational
funding from equity to adequacy has propelled policymakers and public schools to
identify what encompasses an adequate education and how to secure it for all students.
Before policymakers are willing to allocate additional resources into the education
system, they will likely want to ensure that educators are using current resources more
effectively and in ways that efficiently produce increased student achievement (Odden &
Archibald, 2009). While meaningful reform will likely require additional money, simply
allocating more funds into poor performing school systems is unlikely to result in
substantial student learning outcome increases (Firestone, Goertz, Nagle, B &
Smelkinson, 1994; Hirsch, 2006; Loeb et al., 2007; Hanushek, 2006a; Hanushek
&Lindseth, 2009; Odden & Archibald, 2009; Odden & Picus, 2008; PACE, 2006; Picus,
1996a). Schools must be strategic in how educational resources are allocated to ensure
improved student achievement. The continued spotlight of accountability on public
schools coupled with a renewed sense of urgency to improve student performance for all
students must not be dimed by the current fiscal constraints throughout the nation.
Instead, the fiscal constraints magnify both the need and level of urgency necessary to
209
effectively and efficiently align resource allocations with evidence-based strategies that
result in improved student performance. Regardless of economic prosperity or despair,
empirical and scientific data ought to guide decisions determining effective allocation of
resources to deliver a high quality comprehensive instructional program to all students.

210
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APPENDIX A – IRB APPROVAL

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APPENDIX B – QUANTITATIVE DATA COLLECTION
This Codebook is intended to be used solely for EDUC 790 and 792 (Picus) – School
Resource Use and Instructional Improvement Strategies. It identifies data collection items
and their definitions. This document is organized according to the corresponding Data
Collection Protocol and the web portal for data entry (www.lopassociates.com).

I. School Profile
Each data item has a place for notes. This section is meant to be used for any
notations that you would like to record as a personal reminder. Notes fields will
not be used in data analysis.

A. School Name: In your training binder, there will be a group of schools for
which you are responsible. The school name and contact information are
located under the Schools tab.
B. School State ID: This is the identification number that the state has assigned
the school. You do not need to enter this; it has been entered for you.
C. Address Line 1: Street address of the school
D. Address Line 2: (optional) Second line of street address of the school
E. City: City of the school
F. State: “CA” is automatically entered for you.
G. Zip: Postal zip code of the school
H. Phone: Main office phone number for the school
I. Fax: Main office fax number for the school
J. Website: School’s official website

II. School Contacts
This section is for recording the contact people at the school. This will include the
principal, and most likely the secretary. Anyone else you interview should also be
recorded here. Any notes you’d like to make about this person (E.g. phonetic
spelling of their name) should go in the notes sections, as well as what the data
source is.

A. Title: The job title of the person who you interview from the school.
B. Honorific: Mr., Mrs., Ms., Dr., Rev., etc.
C. First Name: Formal first name of school staff member (E.g. Michael instead
of Mike)
D. Initial: (optional) Middle initial of school staff member
E. Last Name: Surname of school staff member
F. Suffix: (optional) Jr., etc.
G. Phone #: Direct phone number to the school staff member
H. Fax #: Fax number for the school staff member
I. Email Address: Preferred email address of the school staff member
J. Mail Address: Street address of the contact person
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K. Address Line 2: (optional) Second line of street address of the contact person
L. City: City of the contact person
M. State: “WY” is automatically being entered for you.
N. Zip Code: Postal zip code of the contact person
O. Zip + 4: Four digit extension of the zip code

III. District Profile

A. District Name: This is the name of the district where the school is located.
B. District State ID: This is the identification number that the state has assigned
to the district within which the school resides.

IV. District Contacts
This section is for recording the contact people at the district office. This will
include the superintendent, and possibly an assistant superintendent and/or
director of curriculum and instruction. Anyone else you interview should also be
recorded here. Any notes you’d like to make about these individuals (e.g.
phonetic spelling of their name) should go in the notes sections, as well as what
the data source is.

A. Title: The job title of the person who you interview from the school.
B. Honorific: Mr., Mrs., Ms., Dr., Rev., etc.
C. First Name: Formal first name of school staff member (E.g. Michael instead
of Mike)
D. Initial: (optional) Middle initial of school staff member
E. Last Name: Surname of school staff member
F. Suffix: (optional) Jr., etc.
G. Phone #: Direct phone number to the school staff member
H. Fax #: Fax number for the school staff member
I. Email Address: Preferred email address of the school staff member
J. Mail Address: Street address of the contact person
K. Address Line 2: (optional) Second line of street address of the contact person
L. City: City of the contact person
M. State: “WY” is automatically being entered for you.
N. Zip Code: Postal zip code of the contact person
O. Zip + 4: Four digit extension of the zip code

V. School Resource Indicators
School resource indicators should be collected for the 2009-2010 school year.
Enter personal notations pertaining to the data in the yellow notes fields.

A. Current Student Enrollment: Headcount of students enrolled at the school on
the day of the site visit minus any pre-kindergarten students.
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B. Pre-kindergarten Student Enrollment: Headcount of students enrolled in any
pre-kindergarten programs at the school on the day of the site visit. These
students should not be included in the previous category, Current Student
Enrollment. Make sure to also ask this question at secondary schools.
C. Grade Span: Range of grades that the school provides instruction in. (E.g. K-
5)
D. Number of ELL/Bilingual Students: As of the day of the site visit, the number
of students eligible for services as an English language learner (ELL) as
defined by the federal No Child Left Behind Act of 2001
E. Number of Students Eligible for Free- or Reduced-Price Lunch (FRL):
Number of enrolled students who are eligible for the federal free- and
reduced-price lunch program.
F. Total number of Special Education Students (IEPs): As of the day of the site
visit, number of students in the school with an Individualized Education
Program (IEP) indicating their eligibility for special education services. (This
will most likely be a larger number than the number of students who are in a
self-contained special education classroom.) Does not include gifted and
talented students.
G. Number of Special Education Students (self-contained): Number of students
in the school with an Individualized Education Program (IEP) indicating their
eligibility for special education services.
H. Total Length of School Day: Number of minutes per day that students are
required to be present at school. If multiple grade spans are present for
different amounts of time, report the average length. (e.g. If the school day
begins at 8:30am and ends at 3:15pm, then the total length of the school day is
405 minutes.)
I. Length of Instructional Day: Number of minutes per day that students are
present for instruction. This information should be available from the school
bell schedule or a school staff member. Subtract recess, lunch, and passing
periods time from the total minutes in the school day. This calculation is
different from how the state measures the “instructional day.” (E.g. If the
length of the school day is 405 minutes, and the students have 20 minutes for
lunch and 25 minutes for recess, then the length of the instructional day is 360
minutes.)
J. Length of Mathematics Class: Number of minutes of mathematics class
periods per day. These include periods when students are specially grouped
for extended mathematics instruction. Report an average per day length.
K. Length of Reading/English/LA Class: Number of minutes of reading, English,
and language arts (LA) class periods. These include periods when students are
specially grouped for extended literacy instruction. (E.g. reading, writing,
comprehension) Report an average per day length.
L. Length of Science Class: Number of minutes of science class periods per day.
These include periods when students are specially grouped for extended
science instruction. Report an average per day length.
232
M. Length of Social Studies Class: Number of minutes of social studies and
history class periods per day. These include periods when students are
specially grouped for extended history or social studies instruction. Report an
average per day length.
N. AYP: This is a measure as to whether the school made Adequate Yearly
Progress (AYP) during the previous school year (2007-08). Enter “Y” or “N”
or “NA.”
O. API

VI. Core Academic Teachers
The classroom teachers primarily responsible for teaching a school’s core
academic subjects of reading/English/language arts, mathematics, science,
history/social studies, and foreign language. In elementary schools, core academic
teachers consist of the teachers in the self-contained regular education classrooms.
Some elementary schools may also departmentalize certain core subjects such as
math or science, especially in the upper grades. These teachers are also to be
included as core teachers. In middle schools, high schools, or any other
departmentalized school, core teachers consist of those teachers who are members
of the English/language arts, mathematics, science, social studies, and foreign
language departments along with special education or ESL/bilingual teachers who
provide classes in these subjects. The teachers should be entered as full-time
equivalents (FTEs), which may include decimals. (E.g. a half-time teacher would
be entered as 0.5) If teachers are assigned to multiage classrooms, divide up the
FTEs weighted by students per each grade. Enter each teacher’s name that
corresponds to the FTEs entered in the corresponding notes fields. Indicate in
parentheses if the teacher is not a 1.0 FTE in that category.
Example:
Grade 1: Matthew Perry (0.5), Lisa Kudrow, Jennifer Aniston;
Grade 2: David Schwimmer (0.25), Courtney Cox (0.33), Matt LeBlanc

A. Grades K-12: Number of FTE licensed grade-level teachers who teach the
core subjects. The FTEs should not duplicate those in the individual subject
categories.
B. English/Reading/LA, History/Social Studies, Mathematics, Science, and
Foreign Language: Number of FTE licensed subject-specific teachers who
teach the core subjects. The FTEs should not duplicate those in the grade
categories.

VII. Specialist and Elective Teachers
This expenditure element consists of teachers who teach non-core academic
classes, and usually provide planning and preparation time for core academic
teachers. The teachers should be entered as full-time equivalents (FTEs), which
may include decimals. In the notes sections, enter each teacher’s name that
233
corresponds to the FTEs entered in the related fields. Indicate in parentheses if the
teacher is not a 1.0 FTE in that category.

A. Art/Music/PE: Number of FTE specialist teachers, such as art, music, and
physical education (PE) teachers, who usually provide regular classroom
teachers with planning and preparation time.
B. Drama/Technology/Health: Number of FTE teachers who provide instruction
in a subject area that represents a special academic focus.
C. Career & Technical Education: Number of FTE vocational education teachers
D. Driver Education: Number of FTE drivers education teachers.
E. Study Hall: Number of FTE teachers who monitor study hall.
F. Athletics: Number of FTE teachers who coach an athletic team during the
school day. This does not include time spent as an athletic director, which
would be captured under the Administration section.
G. Other: Number of FTE specialist teachers who are not specifically listed
above.
H. Other Description: Indicate the subject area that the “Other” specialist
teacher(s) instruct.

VIII. Library Staff
Library staff should be entered as full-time equivalents (FTEs), which may
include decimals. Enter each staff member’s name that corresponds to the FTEs
entered in the related fields. Indicate in parentheses if the staff member is not a
1.0 FTE in that category.

A. Librarian/ Library Media Specialist: Number of FTE licensed librarians or
media specialists who instruct students
B. Library Aide: Number of FTE library aides who help instruct students

IX. Extra Help Staff
This category mainly consists of licensed teachers from a wide variety of
strategies designed to assist struggling students, or students with special needs, to
learn a school’s regular curriculum. The educational strategies that these teachers
deploy are generally supplemental to the instruction of the regular classroom.
Extra help staff should be entered as full-time equivalents (FTEs), which may
include decimals. Do not include volunteers in the FTE counts. Enter each staff
member’s name that corresponds to the FTEs entered in the related fields.
Indicate in parentheses if the staff member is not a 1.0 FTE in that category.

A. Certified Teacher Tutors: Number of FTE tutors who are licensed teachers
and provide help to students one-on-one or in small groups of 2-5.
B. Non-Certified Tutors: Number of FTE tutors who are not licensed teachers
and provide help to students one-on-one or in small groups of 2-5.
234
C. ISS Teachers: Number of FTE licensed teachers who monitor/teach In-
School Suspension (ISS) students.
D. ISS Aides: Number of FTE Title I funded aides who monitor/teach In-
School Suspension (ISS) students.
E. Title I Teachers: Number of FTE non-special education teachers who
provide small groups of students with extra help as a function of the Title I
program.
F. Title I Aides: Number of FTE non-special education aides who provide
small groups of students with extra help as a function of the Title I program.
G. ELL Class Teachers: Number of FTE licensed teachers of English as a
second language (ESL) who work with non-English speaking students to
teach them English.
H. Aides for ELL: Number of FTE aides of English as second language (ESL)
classes who work with non-English speaking students to teach them English.
I. Gifted Program Teachers: Number of FTE teachers who instruct students in
the gifted program.
J. Gifted Program Aides: Number of FTE aides who instruct students in the
gifted program.
K. Gifted Program Funds: Dollar amount budgeted for the gifted program for
the 2008-09 school year
L. Other Extra Help Teachers: Number of FTE teachers who provide
supplemental instructional assistance to students to learn the school’s
curriculum. (Use this category sparingly.)
M. Other Extra Help Teachers Description: Indicate what the “Other” extra help
staff do.
N. Other Extra Help Classified Staff: Number of FTE classified staff that
provides supplemental instructional assistance to students to learn the
school’s curriculum. (Use this category sparingly.)
O. Other Extra Help Classified Staff Description: Indicate what the “Other”
extra help classified staff does.
P. Special Ed. Teacher (Self-contained for students with severe disabilities):
Number of FTE licensed teachers who teach in self-contained special
education classrooms and work with “severely” disabled students for most
or all of the school day. These teachers may teach a modified version of a
school’s curriculum or other learning goals required by their students’
Individualized Education Programs (IEPs).
Q. Special Ed. Inclusion Teachers: Number of FTE licensed teachers who assist
regular classroom teachers with mainstreamed students who have physical
or mental disabilities, or a learning problem. These students generally have
“less severe” disabling conditions.
R. Special Ed. Resource Room Teachers: Number of FTE licensed special
education teachers who provide small groups of students in special
education with extra help in specific areas.
235
S. Special Ed. Self-contained Aides: Number of FTE aides who assist in self-
contained special education classrooms and work with “severely” disabled
students for most or all of the school day.
T. Special Ed. Inclusion Aides: Number of FTE aides who assist regular
classroom teachers with mainstreamed students who have physical or mental
disabilities, or some learning problem. These students generally have “less
severe” disabling conditions.
U. Special Ed. Resource Room Aides: Number of FTE special education aides
who provide small groups of students in special education with extra help in
specific areas.
V. Number of Extended Day Students: Number of students who participate in
the extended day program.
W. Minutes per Week of Extended Day Program: Number of minutes per week
that the extended day program is offered.
X. Teacher Contract Minutes per Week: Number of work minutes per week in
the teacher contract.
Y. Extended Day Teachers: Number of FTE licensed teachers who provide
students with extra instructional time to achieve to the standards in the
regular curriculum after school.
Z. Extended Day Classified Staff: Number of FTE staff who provides students
with extra instructional time to achieve to the standards in the regular
curriculum after school.
AA. Description of Extended Day Classified Staff: Description of classified
staff’s role in the extended day program.
BB. Minutes Per Week of Summer School: Number of minutes per day
multiplied by the number of days per week that students attend summer
school.
CC. Length of Session: Number of weeks that summer school is in session.
DD. School’s Students Enrolled in the Summer School Program: Number of
students from the individual school who are enrolled in the summer school
program (a subset of the following item).
EE. All Students in Summer School: Total number of students enrolled in the
summer school program.
FF. Summer School Teachers: Number of FTE teachers who provided students
with extra instructional time to achieve to the standards in the regular
curriculum during summer 2008.
GG. Summer School Classified Staff: Number of FTE classified staff that
provided students with extra instructional time to achieve to the standards in
the regular curriculum during summer 2008.

X. Other Instructional Staff
Included here are instructional staff members that support a school’s instructional
program, but do not fit in the previous categories. Other instructional staff should
be entered as full-time equivalents (FTEs), which may include decimals. Enter
236
each staff member’s name that corresponds to the FTEs entered in the related
fields. Indicate in parentheses if the staff member is not a 1.0 FTE in that
category.

A. Consultants (other than PD contracted services): Dollar amount for all other
consultants other than professional development contracted services.
B. Building Substitutes: Number of FTE permanent substitutes.
C. Other Teachers: Number of FTE teachers who instruct, but were not included
in previous categories.
D. Other Instructional Aides: Number of FTE aides who assist instruction, but
were not included in previous categories.
E. Funds for Daily Subs: Daily rate for daily certified teacher substitutes who
replace sick teachers. (This is not for substitutes who replace teachers who are
participating in professional development.)

XI. Professional Development Staff & Costs
This expenditure element includes spending on the professional development of a
school’s staff and the staffing resources necessary to support it. Professional
development staff should be entered as full-time equivalents (FTEs), and cost
figures should be entered as a dollar amount, both of which may include decimals.
Enter each staff member’s name that corresponds to the FTEs entered in the
related fields. Indicate in parentheses if the staff member is not a 1.0 FTE in that
category.

A. Number of Professional Development Days in the Teacher Contract: Number
of days the teacher contract specifies for professional development.
B. Substitutes and Stipends (teacher time): Dollar amount budgeted for
substitutes and stipends that cover teacher time for professional development.
For time outside the regular contract day when students are not present before
or after school or on scheduled in-service days, half days or early release days,
the dollar amount is calculated by multiplying the teachers’ hourly salary
times the number of student-free hours used for professional development. For
planning time within the regular contract, the dollar amount is calculated as
the cost of the portion of the salary of the person used to cover the teachers’
class during planning time used for professional development. For other time
during the regular school day, including release time provided by substitutes,
cost is calculated with substitute wages. For time outside the regular school
day, including time after school, on weekends, or for summer institutes, the
dollar amount is calculated from the stipends or additional pay based on the
hourly rate that the teachers receive to compensate them for their time.
C. Instructional Facilitators/Coaches: Number of FTE instructional facilitators
and coaches. This may include on-site facilitators and district coaches (though
only the FTE for the specific school should be recorded). Outside consultants
237
who provide coaching should be captured in an estimated FTE amount
depending on how much time they spend at the school.
D. Trainers/Consultants: Dollar amount for outside consultants who provide
training or other professional development services. If trainers are from the
district, convert to a dollar amount.
E. Administration: Number of FTE district or school-level administrators of
professional development programs. (Again, only the FTE for the specific
school should be recorded).
F. Travel: Dollar amount of the costs of travel to off-site professional
development activities, and costs of transportation within the district for
professional development.
G. Materials, Equipment, and Facilities: Dollar amount of the materials for
professional development including the cost of classroom materials,
equipment needed for professional development activities, and rental or other
costs for facilities used for professional development.
H. Tuition & Conference Fees: Dollar amount of tuition payments or
reimbursement for college-based professional development, and fees for
conferences related to professional development.
I. Other Professional Development: Either FTEs or Dollar amount for other
professional development staff or costs. (Use this category sparingly.)
J. Other Description: Specify what the “Other” professional developments are,
and indicate whether it is a FTE or dollar amount.

XII. Student Services Staff
This expenditure element consists of school-based student support staff, as well as
school expenditures for extra-curricular activities and athletics. Student services
staff should be entered as full-time equivalents (FTEs), which may include
decimals. Enter each staff member’s name that corresponds to the FTEs entered in
the related fields. Indicate in parentheses if the staff member is not a 1.0 FTE in
that category.

A. Guidance: Number of FTE licensed guidance counselors.
B. Attendance/dropout: Number of FTE staff members who manage attendance
and report dropouts.
C. Social Workers: Number of FTE licensed school social workers.
D. Nurse: Number of FTE registered nurses or nurse practitioners
E. Parent advocate/community liaison: Number of FTE staff members who serve
as the parent advocate and/or community liaison, often working with parents
to get their children to attend school.
F. Psychologist: Number of FTE licensed school psychologists or educational
diagnosticians.
G. Speech/OT/PT: Number of FTE licensed speech, occupational (OT), and
physical therapists (PT) who provide services to the school’s students
H. Health Asst.: Number of FTE health assistants
238
I. Non-teaching aides: Number of FTE non-teaching aides. (E.g. Lunchroom
aides, Aides who help students board buses; DO NOT include cooks – the
defining difference is whether the staff member is supervising students or
not.)
J. Other Student Services: Number of FTE other student services staff. (Use this
category sparingly.)
K. Other Description: Indicate what the “other” student services staff member
does.

XIII. Administration
This expenditure element consists of all staffing resources pertaining to the
administration of a school. Administrators should be entered as full-time
equivalents (FTEs), which may include decimals. Enter each staff member’s name
that corresponds to the FTEs entered in the related fields. Indicate in parentheses
if the staff member is not a 1.0 FTE in that category.

A. Principal: Number of FTE licensed principals.
B. Assistant Principal: Number of FTE assistant principals.
C. Other Administrators: Number of FTE other administrators. (Use this category
sparingly.)
D. Other Description: Indicate what the “Other” administrators’ duties are.
E. Secretary: Number of FTE Secretaries.
F. Clerical Staff: Number of FTE clerical staff members.
G. Technology Coordinator: Number of FTE technology coordinators and IT
staff.
H. Security: Number of FTE security staff.
I. Custodians: Number of FTE staff who provide custodial services

XIV. Elementary Class Sizes (We are NOT collecting this data for middle and high
schools.)
Sometimes it is easiest to get this information when you get the staff list, but other
times the secretary can just copy the sheet that tells them how many students are
in each classroom (we don’t want student names). You want a (preferably
electronic) copy of the master class schedule to enter this data. When entering the
data online, make sure to enter the class size for every class that is taught at the
school. Click on the Class Size option from the main menu and a new menu will
be displayed on the left. This menu will have options for grades Pre-8 plus
Special Education. When you click on a grade, the page with that grade's sections
will be displayed where you can enter the individual class sizes.

239
APPENDIX C – QUALITATIVE DATA COLLECTION
Following are open-ended questions intended to capture each school’s strategies for
improving student performance. Ask the questions in the order that they appear on this
protocol. Record the principal’s answers as s/he gives them and focus on getting the key
elements of the instructional improvement effort with less emphasis on the process
aspect.

I. Tell me the story of how your school improved student performance.
A. What were the curriculum and instruction pieces of the strategy?
1. What has the content focus of your improvement process been?
(E.g. Reading, Math, Reading First, Math Helping Corps, etc.)
2. What curricula have you used during your instructional improvement
effort? (E.g. Open Court reading, Everyday Math, etc.)
• Is it aligned with state standards?
• How do you know it is aligned? (E.g. District recent review for
alignment)
3. What has been the instructional piece of your improvement effort?
• Does your staff have an agreed upon definition of effective teaching?
4. What is the instructional vision for your improvement effort?
(E.g. Connecticut standards or the Danielson Framework)
5. Have assessments been an integral part of your instructional
improvement process?
• If so, what types of assessments have been key? (E.g. formative,
diagnostic, summative)
• How often are those assessments utilized?
• What actions were taken with the results?
6. What type of instructional implementation has taken place as a part of
your reform efforts? (E.g. Individualized instruction, differentiated
instruction, 90 minutes of uninterrupted reading instruction)
• Were teachers trained in a specific instructional strategy?
• How did you know that the instructional strategies were being
implemented?
B. What were the resource pieces of the strategy? How long have the resources
been in place?
240
1. Early Childhood program: Is it half or full day? Number kids? Staffing
ratios? Eligibility?
2. Full Day Kindergarten
• If yes, how long have they had full day kindergarten?
3. Class Size Reduction
• Reduction Strategy (E.g. 15 all day long K-3 or reading only with
15)
4. Professional Development:
• When are the professional development days scheduled for? (E.g.
Summer Institutes, Inservice Days)
• What is the focus of the professional development?
• Do you have instructional coaches in schools? Were there enough
coaches? (Did they need more but couldn’t afford it?)
5. “Interventions” or Extra Help Strategies for Struggling Students:
• Tutoring: Specify 1:1, in small groups (2-4), or in medium groups
(3-5)
• Extended day: How frequently (Number minutes & Number of times
per week), Academic focus, Who instructs (certified teachers or
aides), Who participates
• Summer school: How Frequently (Number hours a day, Number
weeks), Who instructs (certified teachers or aides), Who participates
• ELL
• Scheduling: (E.g. double periods in secondary schools)
6. Parent outreach or community involvement
7. Technology
C. Was the improvement effort centrist (central office orchestrated) or bottom
up?
D. What type of instructional leadership was present?
E. Was there accountability built into this improvement plan? (E.g. School
Board report which helped solidify focus)
F. What additional resources would be needed to continue and expand your
efforts?
G. How has the recent budget effected your future decisions regarding your
instructional vision plan?
H. Any additional things you would like to share that I haven’t asked?

241
APPENDIX D – PINE ELEMENTARY
Background on School and District
Pine Elementary School is a Title I, kindergarten through sixth grade school
located in a large sub-urban unified school district within Orange County, California.
During the 2009-10 academic school year, Pine Elementary reported an enrollment of
425 students and was one of 22 elementary schools in the district. As a basic-aid district,
the district serves nearly 22,000 students in 22 elementary schools, 4 intermediate
schools, 4 comprehensive high schools, 3 alternative schools and 11 preschools. The
district spans 58.83 square miles serving three different cities with an operating budget
over $240 million dollars. Table D.1 provides a demographic comparison and description
of the school, district, county and state average.
Table D.1: Pine Elementary Demographic Comparison 2009-10

%
Hispanic
%
White
%
EL
%
Free/Reduced
Pine Elementary 50 29 44 68
District Average 41 49 25 47
Orange County Average 44.7 32.8 27.9 42.3
State Average 49.0 27.9 24.2 55.7
Note: Adapted from DataQuest by California Department of Education (2010b).

Pine Elementary school opened in September, 1963 and has 17 permanent
classrooms and 9 portable classrooms. Prior to 2008, Pine was a K-3 elementary school.
In 2008, the district decided to reconfigure all its elementary schools into a K-6 structure
instead of the past K-3 and 4-6 model. During the transition, Pine was allowed to grow
into the next grade level each year until it grew into a K-6 structure. Around the same
242
time, the district opened up a K-6 science magnet school near Pine’s attendance
boundaries and they experienced a drop in student enrollment due to the science magnet
school nearby. The 2010-11 school year is the first year every elementary school in the
district will have fully transitioned into the K-6 structure.
Figure D.1 School Demographics Percentage for Pine Elementary

Source: California Department of Education, 2010

As illustrated in Figure D.1, Pine serves a somewhat disproportionately large
Hispanic and Socioeconomically Disadvantaged (SED) student population with fifty
percent of the total population reporting their ethnicity as Hispanic and twenty-nine
percent white. Sixty-eight percent of the students were identified as SED and enrolled in
the free and reduced meals program (California Department of Education, 2010a). Of the
total population, forty-four percent were reported as English Learners (EL) and 14
percent were identified as students with disabilities (SWD). The purpose of this case
study is to identify effective resource allocation and researched based instructional
strategies at Pine Elementary School.

50
29
44
68
14
0
20
40
60
80
100
Hispanic White EL SED SWD
Hispanic
White
EL
SED
SWD
243
Figure D.2 Pine Elementary School’s Yearly API Trend

Source: California Department of Education, 2010

At the start of this study, Pine has not been in Program Improvement (PI) as
indicated by the 2009 Federal AYP (California Department of Education, 2010a) and
continues to meet Adequate Yearly Progress. As indicated in Figure D.2, the school’s
State Annual Performance Indicator (API) score has been inconsistent the past five years.
From 2002 to 2010, Pine’s API cumulative growth has been negative 2 points, the lowest
of all the schools within the sample of this study. In 2007 Pine’s API dropped 19 points.
In 2008, Pine’s API dropped another 40 points. Figure D.2 does not reflect the total 40
point drop in 2008 as the State changes its API formula each year and since the school
transitioned from a K-2 structure towards a K-6 structure, it affected the base formula the
state uses to track growth each year. In 2009 Pine’s rebounded 63 points, more than 1.45
standard deviation from the county average for elementary schools. Pine’s 2009 API was
the highest API growth for the district and among the highest growth in the county. In
2010, Pine’s API dropped again by 13 points to 800. Amid 2006 and 2010, Pine’s student
demographics changed substantially, while it also changed from a K-3 to a K-6 school.
600
650
700
750
800
850
900
2006 2007 2008 2009 2010
802
786
763
813
800
244
Between 2006 and 2010, Pine’s Hispanic population increased by 10%, its EL population
increased by 10%, its SED population increased by 22%, while its White population
decreased by 12%. When it was a K-2 school, only two of its grades were tested on the
CSTs, with only second and third grade students’ performance factoring into the school’s
reported academic performance. By the 2009-10 school year, Pine was a K-6 school with
CSTs results being reported from second to sixth grade.
The Average Yearly Progress (AYP) report shows a similar trend of inconsistent
school progress over the past five years. Figure D.3 indicates Pine’s English Language
Arts (ELA) progress has only grown 7.4 points over the course of five years with its
highest ELA proficiency in 2009 of 59.3% proficiency. Pine’s 2010 ELA proficiency is
0.9 points above the AYP target of 56.8% proficiency but did not meet its AYP targets
for every subgroup. The widest achievement gaps exist among the EL and Hispanic
subgroups. Since 2006, Pine had gradually narrowed the achievement gap among EL
students from 21.7 points, to 13.4 points. However, the Hispanic achievement gap has
constricted and contracted over the five year period. From 2006 to 2008, the Hispanic
achievement gap decreased 9 points from 21.2 points to 12.2. However, the Hispanic
achievement gap increased almost 3 points in 2009 to a 15.1 differential. In 2010, the
Hispanic ELA proficiency gap narrowed slightly, but was still below the 2008 level.

245
Figure D.3 Pine Elementary ELA - Percent Proficient or Above Trend

Source: California Department of Education, 2010

Figure D.4 indicates the math AYP for Pine. A much more dramatic pattern of
poor progress is seen in math. Over the past five years math proficiency has decreased
four of the past five years. From 2006 to 2010 Math proficiency dropped 17.1 points
from 72% proficiency to 54.9%. EL and Hispanic students have been the lowest
performing subgroup for both ELA and Math proficiency at Pine. In 2007, the EL
achievement gap nearly doubled to 17.6% and remained similar in 2008. 2009 was the
school’s largest API growth of 63 points and it translated in narrowing the achievement
gap for EL and Hispanic subgroups in half. In 2010 the Hispanic achievement gap widen
slightly to 13.4 points. By 2010, the EL achievement gap dropped slightly but that was
also due to the fact that every subgroup declined in 2010. Pine’s 2010 Math proficiency is
3.1 points below the AYP target of 58% proficiency and failed to meet Adequate Yearly
Progress for the SED, EL and Hispanic subgroups.

50.3
54
46.6
59.3
57.7
0
10
20
30
40
50
60
70
80
90
100
2006 2007 2008 2009 2010
School Wide
Hispanic
EL
SED
246
Figure D.4 Pine Elementary Math Percent Proficient or Above

Source: California Department of Education, 2010

Key Elements and Themes of the Improvement Process
In 2009, Pine had a State ranking of 6, just above the median statewide ranking
ranging from 1 to 10. When compared to similar schools, schools with similar
demographics and student mobility rates, it received a similar schools rank of 7, with 10
being the highest similar schools ranking possible. The improvements efforts of Pine over
the past 5 years have failed to produce dramatic results. The school has undergone
significant changes over the 5 years, including a new principal and the district changing
from a K-2 and 3-6 elementary structure to a K-6 structure. Pine was originally a K-2
school and was allowed to grow in the new K-6 structure one year at a time. Last year
was the first year Pine was a K-6 school and had only one sixth grade class. It had eleven
primary classrooms and four upper grades classes in grades four through sixth grade.
Improving student proficiency for all students should be the primary mission of all
72
67.6
55.2
62.5
54.9
0
10
20
30
40
50
60
70
80
90
100
2006 2007 2008 2009 2010
School Wide
Hispanic
EL
SED
247
schools and can be one of the most overwhelming challenges any school undertakes
(Reeves, 2005). However, research continues to provide growing evidence that schools
have much more control over student performance and other school related problems than
many choose to believe (Darling-Hammond, 1997; Marzano 2003, Odden 2009, Odden
& Archibald, 2009; Schmoker, The purpose of this section is to review effective
research-based educational elements that have led to improved student learning. Odden
and Archibald (2009) outline ten strategies successful schools and districts implement to
dramatically improve student performance. The following is a description of what has
occurred at Pine within the framework of these ten strategies.
Understanding the performance problem and challenge. Teachers, principals,
and school leaders must fully understand the performance challenge and have a strong
desire to want to address student performance (Odden & Archibald, 2009). Stakeholders
must feel a sense of urgency to change student performance levels and use this urgency to
drive the instructional improvement process. The principal at Pine arrived four years ago
and came through the ranks of the district being a classroom teacher and district Teacher
on Special Assignment (TOSA) in the past. Pine is the first school the principal has been
an administrator at and was given a mentor principal when she first arrived at Pine. She
still keeps in close contact with her mentor principal (another elementary principal in the
district at a school nearby) and at times plans staff development opportunities with her
staff and the staff where her mentor works. The school has never been in Program
Improvement (PI) in the past and for the first time in 2010 did not meet the AYP
proficiency targets in math. The school had the largest percentage of white students over
248
all the schools in the study, in fact it was the only school with double-digit percentages of
white students. It also had the lowest percentage of Hispanic and EL students compared
to other schools in this study. It is also the only school in the study with an API of 800,
meeting the State’s target API score for all schools. It was extremely difficult to
determine a strong sense of urgency to improve student proficiency during the principal
interview conducted and couldn’t help but to wonder if the higher overall API score
somehow minimized the overall sense of urgency to improve the proficiency of all
students.
Set ambitious goals. One of the most significant things any school can do to
improve student performance is to set specific, yet ambitious goals for student
proficiency (Odden, 2009; Odden & Archibald, 2009). While the district has established
learning goals for all students in grades two through eleven, it was hard to see this
cascade down into a driving force at the school site, in fact the principal made little
mention of school goals for student performance other than her overall vision for the
school was for students to be engaged in their learning and to instill a love for learning.
The goals shared seemed more like a school’s mission statement and less like setting
specific and ambitious learning goals for all students. The principal acknowledged
teachers often complained that they have little effect on changing student results and that
many of the students lack the support at home to make them successful. According to the
district, students in second grade are expected to score proficient or advanced on the
CST. Students in grades three through sixth are expected to make at least one
proficiency’s band growth on the CST in both English Language Arts and Math. This
249
growth is expected to take place until they are able to maintain proficiency or advanced
status. Along with goals for the CST, all English Learner students are expected to make
one band’s growth each year on the California English Language Development Test
(CELDT) until they become English language proficient. While these were district wide
goals, there was no discussion of this during the principal interview.
Change the curriculum program and create a new instructional vision. The
principal noted the teachers were 100% dependent on the Houghton Mifflin (HM)
textbook series for ELA. This was also strongly supported by the district office and
district pacing guides that stipulated exactly where a classroom should be within the ELA
HM series at any given time. The principal was proud of her teachers’ fidelity to the HM
ELA program. The entire staff previously received five days of training with the HM
series and continues to receive additional HM curriculum support and integration from
district TOSAs.
The principal has been working with staff to improve the level of differentiated
instruction, level of student engagement and raising the level of rigor expected for
students as instructional pieces of her improvement process. Another curricular change
was in the area of writing. Data and staff observations revealed writing was an area of
weakness for students at Pine, especially in the upper grades. Thus, last year, the
principal offered training for upper grade teachers along with the subscription to an on-
line writing program for students. Students produced their writing on computers and sent
their results on-line. Immediately, feedback was generated for both the students and the
teacher on their writing. The results helped students identify areas to improve and
250
provided brief computer generated lessons to support targeted areas. Recently, the district
adopted the Medallion “add on” component to the HM series to update is ELA program.
The school also used various supplemental computer-based programs like Accelerated
Reader, Accelerated Math, Math Facts in a Flash (for math fluency), and English in a
Flash (English Language Development- ELD computer based program).
Formative assessments and data-based decision making. A variety of
formative and summative assessments are utilized at Pine to support student learning.
This process has taken a few years to become engrained in the school culture and the
principal acknowledges some grade levels are better at using assessment results to drive
instruction than others. All teachers are required to give district benchmarks throughout
the year. The ELA district benchmarks are the HM summative test and are administered
three times a year. The math district benchmarks are given three times a year at the end of
each trimester. In addition to the district benchmarks, teachers are expected to give
formative assessments using the HM ELA Theme Skills Test and math chapter test. All
district benchmark assessments are entered into Data Director, the district’s on-line
student assessment data management system, where teachers can pull various reports to
help facilitate data analysis.
A universal screening assessment Pine uses at the beginning of each school year
to predict which students will be “at-risk” for not reading to grade level standards by
third grade is the Dynamic Indicators of Basic Early Literacy Skills (DIBELS). This
assessment is given to every student in grades K-1 to measure the acquisition of early
literacy skills. If a student was identified as “at-risk”, an additional assessment was
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given, the Comprehensive Literacy Assessment (CLA). This further identified where
students were breaking down with their literacy skills. Teachers used this information
along with district benchmarks to group students for leveled ELA instruction within their
classroom. Teachers used this data to assist them in differentiating the language arts
program. All data gleaned from these assessments were entered into Data Director for
teachers and administrators to utilize.
Teachers were released for “data days” after district benchmark one and two were
administered to work collaboratively along with a site TOSA to analyze the assessment
results and compare it to the standards they already taught. During “data days” teachers
compared student results to target instruction and planned additional support for students
not meeting expectations.
Ongoing, intensive professional development. A key strategy to improve
student performance is to improve the knowledge and skills of teacher through providing
ongoing, systematic and intensive professional development (Odden, 2009, Odden &
Archibald, 2009). One of the mandates of being in Program Improvement is that ten
percent of the school’s Title I budget must be set aside for professional development. The
principal has tried to make professional development a priority at Pine, but it seemed to
lack depth. Professional development opportunities included the use of consultants,
coaching, site and classroom visitations and collaborative dialogue at staff meetings.
Additionally, the 2009-10 staff included an 80% teacher on special assignment (TOSA)
who acted as 40% ELA instructional coach a 40% intervention TOSA providing
intervention support for struggling students. Teachers previously received professional
252
development in SADIE teaching strategies. Pine staff joined another school in the district
for training in the area of differentiated instruction and raising the rigor of instruction
from Dr. Sandra Kaplan, USC professor. The differentiated instruction included the
integration of Dr. Kaplan’s GATE Icons. Teachers later in the year met with like grade
level teams from the other school to plan differentiated lessons and small group activities
that supported the knowledge gained through the Dr. Kaplan in-service. The two schools
also provided opportunities for both staffs to observe one another’s classrooms to see the
application of the strategies in practice but not very many teachers took advantage of this
opportunity. This partnership opened the door for further discussions between the two
staffs and provided opportunities for best practices to be shared by those that participated.
Additionally, staff was also released to work with site TOSA to co-plan, co-teach
lessons in ELA and debrief instructional strategies observed over two half-day sessions.
The principal wanted the TOSA to work on engagement strategies and provided
additional time at staff meetings with the district curriculum specialist to provide active
engagement strategies teachers could employ more consistently in their instruction
throughout the day. The principal provided every teacher with a class set of white boards
and student markers to further support student engagement.
Using time efficiently and effectively. Class size reduction is a strategy
designed to help educators use time more efficiently (Odden, 2009; Odden & Archibald,
2009; Odden & Picus, 2008). Pine utilized a modified class size reduction strategy in
kindergarten through third grade, narrowing the total class size to twenty-two students. In
grades three through six, class size grew with an average of about thirty-six students in
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each class. Pine utilized a .4 FTE instructional aide in the upper grades to help teachers in
fourth through sixth grade with the larger class size. However, the IA spent more of the
time acting as clerical support to the teacher, copying materials, entering grades in the
grade book etc and less time working directly with students in the classroom. The upper
grade students also received forty-five minutes a week of science lab instruction through
a part-time science teacher funded by the school. The principal at Pine reported the
school placed a strong emphasis on providing ninety minutes of uninterrupted reading
instruction during the school day and reserved morning instruction for ELA. All
assemblies for students were intentionally planned for the afternoons to protect morning
instruction.
Extending learning time for struggling students. Providing multiple-extra help
strategies for students struggling to achieve proficiency is a critical component to
improving the learning outcomes for struggling students (Odden, 2009, Odden &
Archibald, 2009). Pine offered additional support to struggling students during the school
day. During the school day in ELD instruction, students were divided up in to various
groups based upon their instructional level and CELDT scores. EL students were
provided ELD instruction was an additional forty-five minutes of instruction a day from a
part-time TOSA funded by the district. The problem with this TOSA is the position was
staffed with a long-term sub to save cost, thus the quality of the instructor was not as
good as a regular district teacher.
Additionally, the other 80% site TOSA served half of her time as an intervention
teacher and half as a literacy coach. Beginning in December, the intervention TOSA
254
pulled small groups of students in grades kinder through sixth grade throughout the year
to target specific ELA areas identified by the classroom teacher. The intervention TOSA
pulled student groups of four to six students in the primary grades and student groups of
five to ten in the upper grades. Unfortunately, providing additional support to students
with an extended school year was not an option as the district cut all summer programs at
the elementary level.
Collaborative and distributed leadership. Powerful and effective instructional
systems require strong instructional leadership provided by principals, teachers, and
central office staff collaborating purposefully toward utilizing shared instructional
strategies and using common assessment tools (Odden 2009; Raudenbush, 2009). In
professional literature, this often referred to as creating a collaborative and professional
culture with leadership distributed across the organization to enhance effectiveness
(Odden, 2009; Odden & Archibald, 2009; Raudenbush, 2009) and is the eighth and ninth
step in Odden’s (2009) ten strategies to doubling student performance. Pine implemented
professional learning communities (PLCs) about three years ago soon after the principal
arrived and was a goal supported by the district. The principal noticed the teachers were
congenial with each other and often planned together, however they lacked collaborating
around agreed upon expectations for student learning, common formative assessments
and strategies to improve every student’s achievement. Grade level PLC teams were
required to submit a summary report of their collaborative dialogue after each PLC team.
The principal acknowledged that some grade levels were very powerful PLC teams,
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analyzing students’ assessment results, planning response strategies for students who
were struggling and sharing best practices while others were not.
The school schedule provided an early out day for students once a week,
providing time for teachers with additional time to meet, plan and receive professional
development. Three of the four early out days of the month could be used at the
principal’s discretion, the other week was given to teachers to use for personal planning.
The principal decided to use two of early out day options she controlled for PLC
meetings and professional development opportunities. As the Pine staff began trying to
implement a collaborative and professional culture, the principal invited district support
staff (district TOSAs and curriculum specialist) to help teachers make better use of
effective formative assessments and universal diagnostic screening tools for students.
While the staff at Pine see the value of collaboration and are beginning to discuss such
things as data analysis, and differentiation, they still have yet to tackle creating formative
common assessments other than their HM Theme Skills test and math chapter test. The
principal also assembled a leadership team with representatives from each grade level
that she purposefully selected along with her TOSAs. The site leadership team meets at
least once a month to discuss grade level progress and pitfalls and engage in collaborative
dialogue to address curricular and instructional issues.
Professional and best practices. Odden and Archibald (2009) argue that
exemplary schools use evidence from research, advice from experts and work
collaboratively together to significantly improve student performance. Throughout the
curricular change process, the principal spent time and resources on training teachers on
256
best instructional practices. Teachers at Pine received specialized training in SDAIE
instructional strategies, training and coaching on differentiation, critical thinking and
student engagement. Additionally, teachers conducted visits at other schools to glean
best practices observed and engaged in classroom walk through to observe engagement
strategies. Three areas the school focused on was core instruction, active engagement
strategies and higher level thinking. The principal, site TOSA and intervention teacher
spent a lot of time working with staff at staff meetings on active engagement strategies,
checking for understanding and higher level thinking. The principal provided every
teacher with student white boards, markers and erasers to improve the level of student
engagement. The use of the site TOSA and intervention teacher positively impacted
teachers’ understanding of instructional strategies and the level of core curriculum they
are expected to deliver. Unfortunately, the principal reports both the TOSA and the
intervention teacher will be cut in the 2010-11 school year and teachers will now be faced
to carry on this work without their support.
Comparison of School Resources to the Evidence-Based Model
An evidence-based model approach to improving academic performance for all
students strives to identify a comprehensive set of effective educational elements based
upon proven research strategies necessary to deliver a high-quality comprehensive
instructional program for all students at the school (Odden, 2000; 2003; Odden & Picus,
2008). The evidence based approach employs current educational research to determine
what resources are needed to reach proficiency for every learner. One such framework
that can be used to help identify resource allocations and effective educational strategies
257
is the Evidence-Based Model outlined by Odden and Picus (2008). The following table is
a comparison of Pine Elementary to that of the core resources allocated to a prototypical
elementary school using Odden and Picus’ (2009) Evidence-Based Model.
As illustrated in Table D.2, on average Pine Elementary employed far less
resources compared to the prototypical school using the Evidence-Based Model (Odden
& Picus, 2008) throughout their school improvement plan. The majority of the
discrepancies fall in the area of class size, number of core and specialist teachers,
instructional coaches, professional development resources and opportunities, extended
support staff to help struggling students and length of the instructional year and extended
school year. The model would provide an additional 6.89 core teachers to lower class size
and 3.28 specialist teachers to provide release for teachers to work in powerful
collaborative PLC teams. As a school with 68% socially economically disadvantaged
population and 44% EL student population, the Evidence-Based Model (Odden & Picus,
2008) would provide nearly an additional 5.36 more full time staff members to provide
additional support for struggling students in the form of tutors, English Language
Development (ELD) instruction, and extended school day programs for struggling
students. It would also allocate the equivalent of 1.8 full time teachers for summer
school, something currently lacking at Pine Elementary.

258
Table D.2: Pine Elementary Evidence-Based Model Comparison
School Element
Evidence-Based
Model
Current Allocation
Resources
Resources Based on
Prototypical Model
School Size K-5; 432 Students K-6; 425 Students 1.62 % smaller
Class Size
K-3 : 15
4-5 : 25
K-3: 22
4-6: 36
K-3: 47 % larger
4-6: 44 % larger
Instructional Days 190; + 10 PD days
180; + 2 PD & 4
prep. days
10 less student days
and 8 less PD days
Kindergarten Full-day K
Part-day K (85% of
1-6
th
grade day)
Full-day K
Administrative Support
Principal 1.0 FTE 1.0 FTE 1.00 FTE
School Site Secretary 1.0 FTE 1.0 FTE 1.00 FTE
School Site Clerical 1.0 FTE 0.5 FTE 1.00 FTE
General Personnel Resources
Core Teachers 24 FTE 15.0 FTE 21.89 FTE
Specialist Teachers 20% of core teachers
1.1 FTE 7% of core
teachers
4.38 FTE
Instructional Facilitators 2.2 FTE 0.4 FTE 2.2 FTE
Extended Support
Tutors 1.0 FTE : 100 low SES
0.4 FTE
(289 students)
2.89 FTE
Teacher for EL 1.0 FTE : 100 EL
0.8 FTE
(187 students)
1.87 FTE
Extended Day 1.8 FTE 0.0 FTE 1.80 FTE
Summer School 1.8 FTE 0.0 FTE 1.80 FTE
Other Staffing Resources
Substitutes 5% of personnel 5.0% of personnel 5% of personnel
Librarians/Media Specialist 1.0 FTE 1.0 Media clerk FTE 1.0 FTE
Instructional Aides 0.0 FTE 0.43 FTE 0.0 FTE
Pupil support staff 1.0 FTE : 100 low SES
0.3 FTE Com.
Liaison
0.44 FTE health aid
2.89 FTE
Professional Development
$100 per pupil for other
PD expenses-trainers,
conferences, travel etc.
$13,200 $ 42,500
Note: Adapted from School finance: A policy perspective (4
th
ed.) by Odden and Picus (2008), pp. 132-133.
Copyright 2008 by McGraw-Hill. Adapted with permission.
259

Summary and Lessons Learned
Pine Elementary school’s improvement effort over the past five years has
experienced sporadic results with little overall student improvement. Over the past five
years, the school’s academic API score has experienced a cumulative growth of negative
two points including a recent thirteen point decline from the previous year’s API score.
The district changed its elementary school structure from a two tier system of K-3
rd
grade
and 4
th
- 6
th
grade schools to a single K-6
th
grade structure. During this transition, the
district allowed Pine to grow into the single tier system one year at a time. Thus far, Pine
has never been in PI and meets the state’s minimum API target of 800. However, for the
first time, the school failed to meet the AYP proficiency targets in 2010 for math and is
facing further budget cuts resulting in loosing personnel.
Despite these barriers, the principal has tried to move her staff toward improving
differentiation and student expectations. This change is helping teachers reflect on the
level of rigor they are engaging students in during their teaching. Teachers at Pine
received specialized training in SDAIE instructional strategies, training and coaching on
differentiation, critical thinking and student engagement. Additionally, teachers
conducted visits at other schools to glean best practices observed and engaged in
classroom walk through to observe engagement strategies. While the school invested in
professional development, it seemed fragmented and superficial; it lacked depth and
intensity. There was little accountability built into the professional development provided
and lack of consistent focus over the past three years was apparent. While the school
260
transitioned from a K-3 model to a K-6, there was no mention of providing further
training for primary teachers now forced to teach upper grades. The school has
implemented up to thirty minutes of intervention support during the school day for
struggling students by using an intervention TOSA in ELA and a long term sub for ELD
instruction. However, the student to teacher ratio is still too large to have a dramatic
impact on student learning and the amount of time is not sufficient to cover the gaps in
reading, writing, and math. Additionally, a long-term sub is not has highly trained as
teacher on regular assignment.
While the school as implemented creating a more collaborative culture by
implementing PLCs, teachers are not consistent across grade level teams at applying the
major tenets of a PLC and are not creating common formative assessments. It was hard to
determine a strong sense of urgency within both the principal and staff to improve
proficiency for every student. Additionally, the school’s over dependence on HM and
fidelity to program instruction fails to recognize the disconnect in rigor between the
adopted curriculum and the standards assessed on the CSTs. The critical thinking
required of the standards and the CST blueprints do not fully align to the adopted
curriculum. Although the school demonstrated the application of all ten evidence-based
strategies outlined within the nine categories in Table D.3, none were implemented to the
level and intensity supported by research. Table D.3 summarizes Pine Elementary
School’s educational reform efforts compared to the ten evidence-based strategies
supported by research and recommended by Odden and Archibald (2009) for doubling
student performance. Pine ranked weak in one of the categories in Table D.3, below-
261
average on six of the categories and average in two of the categories. The funding levels
are not near what is called for in the Evidence-Based Model (Odden & Picus, 2008) and
the school continues to encounter further budget restrictions.

Table D.3: Pine Elementary Performance of Evidence-Based Strategies
Evidence-Based Strategy Weak
Below
Average Average
Above
Average Strong
Understanding the Performance Problem
and Challenge
√

Setting Ambitious Goals √
Change the Curriculum Program and Create
a New Instructional Vision
√

Formative Assessments and Data-Based
Decision Making
√

Ongoing, intensive Professional
Development
√

Using time Efficiently and Effectively √
Extend Learning Opportunities for
Struggling Students
√

Collaborative Culture and Distributed
Leadership

√

Professional and Best Practices √
Note: Adapted from Doubling student performance:…and finding the resources to do it by Odden and
Archibald (2009). Copyright 2009 by Corwin Press.

Future Considerations
Pine Elementary School continues to meet state benchmark targets for student
achievement but has failed to reach the federal benchmarks for math and will be hard
pressed to meet them in the future as the targets grow dramatically the next few years.
The school experienced a 13 point decline in API for 2010 and continues to serve a
262
majority of underperforming students. Thus far, district employees were not facing any
furlough days, thus allowing the school to maintain the same number of instructional
days as previous years. Discussions with the principal indicated there is still much more
work and support necessary to help ensure every student reaches proficiency. The 2010-
11 school year further cut the resources previously allocated to the school, including the
loss of the TOSA, intervention teacher, and community liaison. The principal addressed
the need for additional resources to provide lower class sizes throughout the school, more
intense and ongoing professional development, instructional tutors and intervention
specialist, and instructional coaches. Additional resources are also needed to offer a
targeted afterschool program for struggling students and a summer school program
focusing on reading and math.

263
APPENDIX E – ELM ELEMENTARY
Background on School and District
Elm Elementary School is a Title I, kindergarten through sixth grade school
located in a large urban unified school district within Orange County, California. During
the 2009-10 academic school year, Elm Elementary reported an enrollment of 560
students and was one of 47 elementary schools in the district. The district is the third
largest among 28 public school districts in Orange County with more than 47,860
students, ranks 11th in size of more than 1,000 school districts in California, and is the
96th largest school district of 17,900 in the U.S. The district employs more than 5,000
staff members and operates 70 schools: 47 elementary, 10 intermediate, 7 high schools, 2
continuation schools, 2 adult education centers, and 2 special education schools. The
district spans 28 square miles serving largely one main city and portions of six
surrounding cities with an operating budget over $443 million dollars. In 2004, the
district earned the Broad Prize for Urban Education from the Broad Foundation. Table
E.1 provides a demographic comparison and description of the school, district, county
and state average.
Table E.1: Elm Elementary Demographic Comparison 2009-10

%
Hispanic
%
White
%
EL
%
Free/Reduced
Elm Elementary 83 2 66 75
District Average 53 11 43 59
Orange County Average 44.7 32.8 27.9 42.3
State Average 49.0 27.9 24.2 55.7
Note: Adapted from DataQuest by California Department of Education (2010b).
264

Elm Elementary school opened in September, 1960 and has 20 permanent
classrooms and 15 portable classrooms. According to the principal, Elm is typically
within the ten lowest performing schools in the district and is currently the sixth lowest
performing elementary school within the district. The current principal at Elm arrived last
year, with the 2009-10 school year being his first year at Elm. The principal previously
worked as an elementary school principal in the district at a school that recently earned a
National Blue Ribbon School of Excellence Award. The principal said he was brought to
the school by the district to help improve results at Elm.
As illustrated in Figure E.1, Elm serves a disproportionately large Hispanic and
Socioeconomically Disadvantaged (SED) student population with eighty-three percent of
the total population reporting their ethnicity as Hispanic and 2 percent white. Seventy-
five percent of the students were identified as SED and enrolled in the free and reduced
meals program (California Department of Education, 2010a). Of the total population,
Sixty-six percent were reported as English Learners (EL) and 12 percent were identified
as students with disabilities (SWD). Over the past year, Elm’s EL population has
decreased by 6% and its SED population has decreased by 9%. The purpose of this case
study is to identify effective resource allocation and researched based instructional
strategies at Elm Elementary School.

265
Figure E.1 School Demographics Percentage for Elm Elementary

Source: California Department of Education, 2010

At the start of this study, Elm was in Year 2 of Program Improvement (PI) as
indicated by the 2009 Federal AYP (California Department of Education, 2010a) and has
currently moved in Year 3 of PI. RS is the sixth lowest performing elementary school in
the district and has been the past several years. As indicated in Figure E.2, the school’s
State Annual Performance Indicator (API) score has experienced steady growth four of
the past five years. From 2007 to 2010, Elm’s API cumulative growth has been 77 points,
the third of all the schools within the sample of this study. In 2009 Elm’s API soared 55
points, more than 1.43 standard deviation from the county average for elementary
schools. In 2010, RS’s API score declined 3 points; the first time the school’s API did not
see a positive growth in the past five years.

83
2
66
75
12
0
20
40
60
80
100
Hispanic White EL SED SWD
Hispanic
White
EL
SED
SWD
266
Figure E.2 Elm Elementary School’s Yearly API Trend

Source: California Department of Education, 2010
The Average Yearly Progress (AYP) report shows a similar trend of school
progress over the past five years. Elm has been in Program Improvement (PI) for the past
two years and is currently in Year 3 of PI. Figure E.3 indicates Elm’s English Language
Arts (ELA) progress has only grown 18.1 points over the course of five years with his
highest ELA proficiency in 2010 of 42.7% proficiency school wide. The Hispanic, SED
and School Wide subgroups ELA scores were nearly identical in 2008, but by 2010, the
gap began to increase. In 2010, the ELA proficiency continued to rise but has never
surpassed a proficiency rate above 50%. The ELA achievement gap was widest for EL
students. In 2008, the achievement gap in ELA between EL students was 2%, but by
2010, the achievement gap increased to 9%. While the school experienced growth each
year over the past 5 years in ELA, the growth was at a slower rate for EL students. Elm’s
2010 ELA proficiency is 14.1 points below the AYP target of 56.8% proficiency.

500
550
600
650
700
750
800
850
2006 2007 2008 2009 2010
664
687
713
767 764
267
Figure E.3 Elm Elementary ELA - Percent Proficient or Above Trend

Source: California Department of Education, 2010

Figure E.4 indicates the math AYP for Elm. A much more dramatic pattern of
progress is seen in math. Over the past five years math proficiency has increased almost
28 points with the largest percentage of growth occurring between 2008 and 2009 when
the school piloted the district’s Project G in math. There has been an inconsistent gap
among the various subgroups within math proficiency over the past three years. In 2008,
the Hispanic subgroup had the widest achievement gap of 3.7%. In 2009, the SED
subgroup had the widest achievement gap of 3.2%, and in 2010, the EL subgroup had the
widest achievement gap of 7.3%. EL students were the lowest performing subgroup for
both ELA and Math proficiency at Elm in 2010, with a 9% gap in ELA proficiency and a
7.3% gap in math proficiency. Elm’s 2010 Math proficiency is 9.2 points above the AYP
target of 58% proficiency.

24.6
28.1
29.8
38.6
42.7
0
10
20
30
40
50
60
70
80
90
100
2006 2007 2008 2009 2010
School Wide (data labels)
Hispanic
EL
SED
268
Figure E.4 Elm Elementary Math Percent Proficient or Above

Source: California Department of Education, 2010

Key Elements and Themes of the Improvement Process
In 2009, Elm had a State ranking of 4, just below the medium statewide ranking
ranging from 1 to 10. When compared to similar schools, schools with similar
demographics and student mobility rates, it received a similar schools rank of 8, with 10
being the highest similar schools ranking possible. This ranking has improved over the
year, in 2007 Elm had a State ranking of 2 and a similar schools ranking of 4. The
improvements efforts of Elm over the past 5 years have made steady progress with
dramatic results in 2009. Improving student proficiency for all students should be the
primary mission of all schools and can be one of the most overwhelming challenges any
school undertakes (Reeves, 2005). However, research continues to provide growing
evidence that schools have much more control over student performance and other school
related problems than many choose to believe (Darling-Hammond, 1997; Marzano 2003,
39.4
40.6
50
66.8 67.2
0
10
20
30
40
50
60
70
80
90
100
2006 2007 2008 2009 2010
School Wide
Hispanic
EL
SED
269
Odden 2009, Odden & Archibald, 2009; Schmoker, 1999). The purpose of this section is
to review effective research-based educational elements that have led to improved student
learning. Odden and Archibald (2009) outline ten strategies successful schools and
districts implement to dramatically improve student performance. In addition to the
framework and strategies outlined by Odden and Archibald (2009), the Evidence-Based
Model (Odden & Picus, 2008) of resource allocation will be utilized to examine the
alignment between how schools use their allocated resources along with research-based
strategies to improve student performance. The following is a description of what has
occurred at Elm within the framework of these ten strategies and the Evidence-Based
Model (Odden and Picus, 2008).
Understanding the performance problem and challenge. Teachers, principals,
and school leaders must fully understand the performance challenge and have a strong
desire to want to address student performance (Odden & Archibald, 2009). Stakeholders
must feel a sense of urgency to change student performance levels and use this urgency to
drive the instructional improvement process. The principal at Elm arrived one year ago as
the school had the reputation of being within the ten lowest performing schools in the
district. The district is a highly centralized district with much of the improvement efforts
for both the school and the district being driven by the central office. The principal
arrived in September 2009 to Elm, coming from a previous elementary school in the
district which recently won a National Blue Ribbon School of Excellence award. The
district frequently moves principals to schools across the district to help staff move along
improvement efforts set forth by the district and tries to link the needs of the school
270
culture to the skills of the principal. After successfully moving his previous school
forward in student proficiency, the district hoped the new principal could help Elm raise
above the bottom six performing schools within the district. The previous year, in 2008,
the school was one of six schools in the district to pilot the district’s Project M math
initiative and saw its math scores climb from forty-two percent proficient or advanced to
sixty-two percent proficient or advanced. After much success in the pilot schools, the
district implemented Project M across the district in 2009.
The principal reported the staff at Elm had a reputation from the previous
principal that they were reluctant to change practices and whined that students not being
motivated to learn. He reported the staff “drove away a couple TOSAs” after they tried
working with them on instructional practices but stated he has not encountered this with
the staff since he has been there. The principal stated he has seen his staff willing to
change practices and implement what he has asked them to after they were given a
chance to ask clarifying questions. However, the sense of urgency to implement changes
at the rate necessary to witness dramatic results has been sporadic at various grade levels.
Set ambitious goals. One of the most significant things any school can do to
improve student performance is to set specific, yet ambitious goals for student
proficiency (Odden, 2009; Odden & Archibald, 2009). While the district has established
learning goals for all students in grades two through eleven, it was hard to see this
cascade down into a driving force at the school site, in fact the principal made little
mention of school goals for student performance other than to be out of Program
Improvement (PI) and perhaps the desire to earn a National Blue Ribbon School of
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Excellence at his new school. The principal acknowledged teachers often complained that
they have little effect on changing student results and that many of the students lack the
support at home to make them successful. According to the district, students in second
grade are expected to score proficient or advanced on the CST. Students in grades three
through sixth are expected to make at least one proficiency’s band growth on the CST in
both English Language Arts and Math. This growth is expected to take place until they
are able to maintain proficiency or advanced status. Along with goals for the CST, all
English Learner students are expected to make one band’s growth each year on the
California English Language Development Test (CELDT) until they become English
language proficient. While these were district wide goals, there was no discussion of this
during the principal interview.
The principal almost seemed complacent with the school’s math progress. The
principal stated the students were “flying” with math as two thirds of them were
proficient or advanced in math but they earned that the year prior and saw no growth in
math proficiency in 2010. It almost appeared that, sixty-six percent proficient or
advanced in math was “good enough” as there was no conversation mentioned to move
that target and no sense of urgency observed to set that goal beyond what was already
accomplished. The goal became to push the ELA proficiency as it was at thirty-four
percent proficiency across the school. Thus, the school goals seemed more tied to
improving whatever was the current weakest performance instead of creating ambitious
and lofty goals with any specific set targets.
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Change the curriculum program and create a new instructional vision. As
mentioned briefly above, in 2008, the school was one of six schools that piloted the
district’s Project M math initiative that was later rolled out to all elementary schools in
2009. Project M was created by district TOSAs and it provided various problems for the
day, scope and sequence, question stems, lesson design and formative assessments for
each grade level. The lessons were similar to the old Madeline Hunter (1994) lesson
template, where each lesson included an opening set, which was typically a problem of
the day. The problems of the day for the first trimester were pre-created for teachers
within the provided Project M curriculum. For the subsequent trimesters teachers were
expected to use their current data from the formative assessments to go back and spiral
review concepts that might have been more challenging for the students. Project M
requires teachers to start with the problem of the day, state the objective of the lesson and
then they discuss the various vocabulary terms that might need to go along with it.
Teachers are then expected to write out explicitly the steps that students are going to need
to understood in order to solve the problem. Teachers then progress the lesson through
structured practice, guided practice, independent practice, and a final wrap up.
The instructional framework taught to teachers and implemented in Project M
centers around Fisher and Frey’s (2009) Gradual Release of Responsibility Instructional
Model (GRR). This instructional framework was a central focus across the district.
However, at the elementary level they refer to this framework more as direct instruction
or DI. At the end of 2008, the school experienced huge gains in math proficiency, over
sixteen percentage points from the previous year. Thus, when the principal arrive in 2009,
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he decided to use the framework of Project M and apply it to ELA. This became the
curricular focus in 2009.
The principal had staff analyze what would make sense in their ELA program in
order to add some more structure especially to the area they call the red block of
Houghton Mifflin (HM), word work. The goal was to determine how teachers could be
more explicit using direct instruction lesson in this area of ELA. Teachers were released
in grade levels with the TOSA to look at the CST blueprints, CST released questions and
results of district benchmarks to find learning gaps and then took this information to
create problems of the day that mirrored what they would do in Project M. Based on the
problems of the day identified, they then created direct instruction lesson plans in order to
scaffold the instruction students were missing. As they conducted this analysis, the
principal noticed the level or rigor and differentiation within the ELA instruction was
limited. The principal reported the teachers were focused 100% on the HM program as
this was a huge district focus. Their entire ELA curriculum, in terms of instruction,
pacing guides and both formative and summative assessments were HM driven. As they
looked at the CST blueprints further, they discovered the level of rigor within the HM
program does not match that of the CSTs. Thus, the principal made raising the level of
rigor for all students another curricular focus.
Formative assessments and data-based decision making. A variety of
formative and summative assessments are utilized at Elm to support student learning. All
teachers are required to give district benchmarks throughout the year. The ELA district
benchmarks are the HM summative test and are administered four times a year with the
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third benchmark being correlated to CST performance according to the district’s research
and evaluation department. In addition to district benchmarks, teachers are required to
give formative assessments in the form of the HM Theme Skills test. The math district
benchmarks are given three times a year at the end of each trimester and about nine
formative assessments are administered in the new Project M math initiative. Teachers
were released for “data days” after district benchmark one, two and three were
administered to work collaboratively along with a site TOSA to analyze the assessment
results and compare it to the standards they already taught. During “data days” teachers
compared student results to target instruction and provide additional support for students
not meeting expectations.
All assessments administered in ELA, both formative and summative, are
program directed from the HM series while the math benchmarks administered are from
the text book or ones created by district TOSA within Project M. Teachers do not meet as
grade level teams in the form of Professional Learning Communities (PLC) to create
formative assessments. Thus, the assessments do not necessarily match the instruction in
the classroom or the differentiation of instruction, it merely assesses mastery to the
program adopted and delivered.
A universal screening assessment Elm uses at the beginning of each school year
to predict which students will be “at-risk” for not reading to grade level standards by
third grade is the Dynamic Indicators of Basic Early Literacy Skills (DIBELS). This
assessment is given to every student in grades K-3 to measure the acquisition of early
literacy skills. If a student was identified as “at-risk”, an additional assessment was
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given, the Comprehensive Literacy Assessment (CLA). This further identified where
students were breaking down with their literacy skills. Teachers used this information
along with district benchmarks to group students for leveled ELA instruction by
intensive, strategic, benchmark and extended groups. Teachers used this data to assist
them in differentiating the language arts program. All data gleaned from these
assessments were entered into Data Director for teachers and administrators to utilize.
Ongoing, intensive professional development. A key strategy to improve
student performance is to improve the knowledge and skills of teacher through providing
ongoing, systematic and intensive professional development (Odden, 2009, Odden &
Archibald, 2009). One of the mandates of being in Program Improvement is that ten
percent of the school’s Title I budget must be set aside for professional development.
Professional development has been a priority at Elm. The district contract does not
provide official, mandated professional development days in the teacher’s contract.
Instead teachers are allowed to attend and receive professional development rate pay the
week prior to school starting in what the district refers to as Super Week. A host of
different professional development opportunities are provided for teachers to select from
both during Super Week and throughout the year. Teachers are also given eighteen hours
they can cash in throughout the year for attending various professional development
opportunities throughout the year provided by the district. Because the district is highly
centralized, the bulk of the professional development opportunities are offered directly
from the district and presented by district TOSAs or other district staff. A professional
development catalog with various sessions offered throughout the year is published and
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available to staff throughout the year. The principal reported his entire staff attended all
or parts of Super Week before school started. During Super Week, all of them attended
training on writing strategies called Write from the Beginning. Write from the Beginning
connects previous learning teachers’ received with Thinking Maps and integrates them
throughout the writing process and genres of writing. After Super week, a trainer of
trainer model was used during the year to demo a few lessons and follow up training for
teachers. The principal reported the training was helpful for the entire staff as it brought
about a consistent expectation of what is going on in writing across the grade levels and
provided a common language for writing instruction.
The majority of professional development opportunities for staff came through
release days throughout the year. The principal released teachers about five times during
the year to work in grade level teams with the seven hour a week, district provided
TOSA. Throughout the year, the focus of the release days was backwards planning,
backwards mapping, development of direct instructional lessons for ELA and
development of small group instruction.
Using time efficiently and effectively. Class size reduction is a strategy
designed to help educators use time more efficiently (Odden, 2009; Odden & Archibald,
2009; Odden & Picus, 2008). Elm utilized class size reduction in first through third
grade, narrowing the total class size to twenty students. However, in kindergarten, class
size was up to thirty-four and the student’s instructional day was only about four hours.
In grades four through six, class size grew with an average of about thirty-two students in
each class.
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The principal at Elm acknowledged the school was not maximizing the use of
instructional time in the past and made this a focus area in 2009. Previous district practice
was to divide students by levels for ELA instruction. The hope was that by separating
students by levels, teachers would have fewer groups to plan for and could target their
instruction more purposefully. During ELA instruction, they divided students up by
levels and grouped them by intensive, strategic, benchmark and extended. Within each of
those groups, there was still a wide instructional level. Teachers were not effective at
differentiating instruction within the group of students they had in their group. Teachers
knew the principal wanted them to do small group instruction but they did not fully
understand the pedagogy behind small group instruction. Instead, teachers taught in small
groups, but taught the same material to each small group, thus delivering the same lesson
three times to groups of five to six instead of teaching it whole group or differentiating
the instruction with each group. The independent work students engaged in while not
working directly with the teacher in small group instruction was also found to be lower in
rigor and less meaningful use of academic learning time. Time was not utilized efficiently
and effectively as precious minutes that could have been used to teach the whole group
was lost when the teachers re-taught the same lesson three times to different students.
The principal recognized this and will make it a focus area for teachers in 2010. The
principal will release teachers to work with the TOSA to help plan both the small group
instructional lessons and the independent work done by students while not in small group.
Extending learning time for struggling students. Providing multiple-extra help
strategies for students struggling to achieve proficiency is a critical component to
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improving the learning outcomes for struggling students (Odden, 2009, Odden &
Archibald, 2009). Elm offered support to struggling students both during the school day
and after school. As a Title I school in PI, the school was required to provide
supplemental educational services in the form of tutoring to low-income students.
Tutoring was provided to over one hundred students by private outside companies using
district funds for about for one hour a day, one to two days a week. However the tutoring
efforts did not seem to be coordinated with the school, other than to invite parents to
utilize this service. Beyond hosting a parent night, the tutors did not interact with the
school nor classroom teachers to find out how best to support the individual learner.
As mentioned above, during the school day in ELA instruction, students were
divided up in to various groups based upon their instructional level. Students were
divided into four homogeneous instructional levels, intensive, strategic, benchmark and
extended. The primary grade levels all had at least four teachers with each teacher taking
a homogenous grouping of students for the reading comprehension block of ELA
instruction and then the students went back to their homeroom for the remaining block of
ELA. In the upper grades, each grade level had three teachers except fourth grade. Thus
the principal decided to use their half time intervention TOSA to work solely with 4
th

grade for ELA and math to be able to divide groups into the intensive, strategic,
benchmark and extended level. Thus, the intervention TOSA was less of a true
intervention teacher working with various students in need throughout the school and
across the day and more like an additional part-time 4
th
grade teacher. Grades four
through five only have three teachers, yet they needed four ELA groups so they used their
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RSP teacher and RSP aid to work with the intensive groups for all students in grades four
through six. They did not divide the intensive group by grade level, but rather by level
and thus had two instructional intensive levels for grades four through six combined. The
intervention TOSA taught the strategic level of 4
th
grade while the rest of the grade level
teachers taught the respective groups in ELA. The upper grade teachers divided the
homogenous groups for the entire ELA block of instruction, not just the reading
comprehension like the primary grades.
The school also offered an extended day for thirty minutes four days a week.
Eight teachers taught up to ten students a day working primarily in ELA and math. The
district offered a two week summer school, but it focus was less on intervention for
students and more for professional development for teachers. As the district was rolling
out its Project M math initiative, it offered 2, two-week training sessions for three hours a
day for teachers to work with students on the new math program.
The school also employed six part-time instructional aides. Three of the
instructional aides were used in kindergarten due to the larger class size of up to thirty-
four students. It was not clear how exactly these kindergarten aides were used
instructionally as more discussion centered on the aides helping the teacher with
supervision, prepping material etc. The other three additional instructional aides were
used for the rest of the school, with each teacher getting thirty minutes of aid support a
day in grades first through sixth. The principal acknowledges this was not the best use of
aides and it may have been distributed equally to all teachers, but not necessarily
equitable based upon student needs. The principal reported he will change this for 2010
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and will train aides to work with the intensive group of students using Six Minute
Solutions, a reading fluency program.
Collaborative and distributed leadership. Powerful and effective instructional
systems require strong instructional leadership provided by principals, teachers, and
central office staff collaborating purposefully toward utilizing shared instructional
strategies and using common assessment tools (Odden 2009; Raudenbush, 2009). In
professional literature, this often referred to as creating a collaborative and professional
culture with leadership distributed across the organization to enhance effectiveness
(Odden, 2009; Odden & Archibald, 2009; Raudenbush, 2009) and is the eighth and ninth
step in Odden’s (2009) ten strategies to doubling student performance. The principal
assembled a leadership team with representatives from each grade level that he
purposefully selected. The leadership team met on a monthly basis to discuss
instructional concerns and vision of next steps. The district released each site’s leadership
team and principal three times a year for leadership training called the Leadership
Academy. Teachers met in grade level teams at least four times a year to analyze
benchmark data and plan instruction on how they were going to respond to the data
results. The principal acknowledges that neither the school, not the district has embodied
Professional Learning Communities (PLC) as part of their instructional improvement
plan. The district itself is highly centralized and at times sees the notion of PLC as
counter intuitive to the highly structured, highly centralized culture they have worked
hard to establish. The principal reports that teachers find comfort in knowing their district
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is highly centralized and will be supported as long as they follow the district’s
instructional vision.
The school schedule provides an early out day for students once a week,
providing time for teachers with time to plan. The hour of planning earned from the early
out day is “sacred time” and the principal is not allowed to use that time for any reason, it
is solely for teachers to have common collaborative planning time.
Professional and best practices. Throughout the curricular change process, the
principal spent a lot of time and resources on releasing teachers to work with the TOSA
on best instructional practices. Odden and Archibald (2009) argue that exemplary
schools use evidence from research, advice from experts and work collaboratively
together to significantly improve student performance. Teachers at Elm received
specialized training in SDAIE instructional strategies, training and coaching on writing
instruction, core-instruction, and rigor. The principal and TOSA spent time working with
staff during release days to plan direct instruction lessons, backwards plan, and
backwards map ELA instruction. The use of the site TOSA has had a significant impact
on teachers’ understanding of instructional strategies and the level of core curriculum
they are expected to deliver. Teachers group students by their instructional level and built
problems-of-the-day to spiral review concepts not mastered on district benchmark
assessments. While teachers never created their own common formative assessments,
teachers administered formative assessments in ELA and math on a monthly basis to help
inform their instruction and identify areas for re-teaching. Additionally, the school used
its community liaisons to improve parent participation. Community liaisons conducted
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parent education workshops on The Ten Commandments for Parent Involvement.
Unfortunately, the principal reports both the TOSA and the intervention teacher will be
cut in the 2010-11 school year and teachers will now be forced to carry on this work
without their support.
Comparison of School Resources to the Evidence-Based Model
An evidence-based model approach to improving academic performance for all
students strives to identify a comprehensive set of effective educational elements based
upon proven research strategies necessary to deliver a high-quality comprehensive
instructional program for all students at the school (Odden, 2000; 2003; Odden & Picus,
2008). The evidence based approach employs current educational research to determine
what resources are needed to reach proficiency for every learner. One such framework
that can be used to help identify resource allocations and effective educational strategies
is the Evidence-Based Model outlined by Odden and Picus (2008). The following table is
a comparison of Elm Elementary to that of the core resources allocated to a prototypical
elementary school using Odden and Picus’ (2009) Evidence-Based Model.
As illustrated in Table E.2, on average Elm Elementary employed far less
resources compared to the prototypical school using the Evidence-Based Model (Odden
& Picus, 2008) throughout their school improvement plan. The majority of the
discrepancies fall in the area of class size, number of core teachers, instructional coaches,
professional development resources and opportunities, extended support staff to help
struggling students and length of the instructional year and extended school year. As a
Title I school in program improvement, the district must provide tutoring for students, but
283
this is done outside the school day through private companies and often lacks a feedback
loop between the private tutor and the classroom teacher. As a school with 75% socially
economically disadvantaged population and 66% EL student population, the Evidence-
Based Model (Odden & Picus, 2008) would provide nearly an additional 8.74 more full
time staff members to provide additional support for struggling students in the form of
tutors, English Language Development (ELD) instruction, and extended school programs
for struggling students. It would also allocate the equivalent of 2.3 full time teachers for
summer school, something currently lacking at Elm Elementary.

284
Table E.2: Elm Elementary Evidence-Based Model Comparison
School Element
Evidence-Based
Model
Current Allocation
Resources
Resources Based
on Prototypical
Model
School Size K-5; 432 Students K-6; 560 Students 30 % larger
Class Size
K-3 : 15
4-5 : 25
K: 34
1-3: 20
4-6: 32
K: 127% larger
1-3: 60 % larger
4-6: 28% larger
Instructional Days 190; + 10 PD days
180; + 5prep. 5 PD
days + 18 hours optional
10 less student
days and 10 less
mandatory PD days
Kindergarten Full-day K Half-Day Full-day K
Administrative Support
Principal 1.0 FTE 1.0 FTE 1.3 FTE
School Site Secretary 1.0 FTE 1.0 FTE 1.3 FTE
School Site Clerical 1.0 FTE 0.375 FTE 1.3 FTE
General Personnel Resources
Core Teachers 24 FTE 24 FTE 33.9 FTE
Specialist Teachers 20% of core teachers
0.4 FTE music
1.7% of core teachers
6.78 FTE
Instructional Facilitators 2.2 FTE 0.2 FTE 2.86 FTE
Extended Support
Tutors 1.0 FTE : 100 low SES 0.5 FTE (420 students) 4.20 FTE
Teacher for EL 1.0 FTE : 100 EL 0.0 FTE (370 students) 3.70 FTE
Extended Day 1.8 FTE 1.83 FTE 2.34 FTE
Summer School 1.8 FTE 0.0 FTE 2.34 FTE
Other Staffing Resources
Substitutes 5% of personnel 5.4% of personnel 5% of personnel
Librarians/Media Specialist 1.0 FTE
0.94 Media & tech clerk
FTE
1.30FTE
Instructional Aides 0.0 FTE 2.25FTE 0.0 FTE
Pupil support staff 1.0 FTE : 100 low SES
0.875 FTE Liaison
0.48 FTE health aid
4.7 FTE
Professional Development
$100 per pupil for other
PD expenses-trainers,
conferences, travel etc.
$31,662 $ 56,000
Note: Adapted from School finance: A policy perspective (4
th
ed.) by Odden and Picus (2008), pp. 132-133.
Copyright 2008 by McGraw-Hill. Adapted with permission.
285
Summary and Lessons Learned
Elm Elementary school’s improvement effort over the past few years has
experienced positive results with large gains in student improvement. Over the past five
years, the school’s academic API score has experienced a cumulative growth of 99
points. The school continues to be within the bottom six performing schools in the
district. Elm is in Year 3 of Program Improvement and is facing severe cut backs in
personnel, making progress harder.
Despite these barriers, the principal has worked hard to move his staff to provide
more direct instruction in both ELA and math and group students by their instructional
level. This change is helping teachers reflect on the level of rigor they are engaging
students in during their teaching. It is also allowing teachers to re-think how they use
their adopted curriculum series. Teachers received training and coaching on core-
instruction, small group instruction, backwards planning and rigor. Teachers have begun
to place a stronger emphasis on using data to inform their instruction, tracking student
performance on formative assessments and district benchmarks. Although the school
demonstrated the application of all ten evidence-based strategies outlined within the nine
categories in Table E.3, none were implemented to the level and intensity supported by
research. Table E.3 summarizes Elm Elementary School’s educational reform efforts
compared to the ten evidence-based strategies supported by research and recommended
by Odden and Archibald (2009) for doubling student performance.

286
Table E.3: Elm Elementary Performance of Evidence-Based Strategies
Evidence-Based Strategy Weak
Below
Average Average
Above
Average Strong
Understanding the Performance Problem and
Challenge

√

Setting Ambitious Goals √
Change the Curriculum Program and Create a
New Instructional Vision

√

Formative Assessments and Data-Based Decision
Making

√

Ongoing, intensive Professional Development √
Using time Efficiently and Effectively √
Extend Learning Opportunities for Struggling
Students

√

Collaborative Culture and Distributed Leadership √
Professional and Best Practices √
Note: Adapted from Doubling student performance:…and finding the resources to do it by Odden and
Archibald (2009). Copyright 2009 by Corwin Press.
Future Considerations
Elm Elementary School continues to not meet federal and state benchmark targets
for student achievement as evidenced by their Year 3 PI status. While the school
experienced a slight decline point in API for 2010, it has seen steady growth in math
proficiency. Elm continues to serve a majority of underperforming students and is one of
the lowest performing schools in the district. Discussions with the principal indicated
there is still much more work and support necessary to help ensure every student reaches
proficiency. The 2010-11 school year further cut the resources previously allocated to the
school, including the loss of the intervention TOSA, larger class sizes, and four less
instructional days. The school has begun to implement thirty minutes of intervention
287
support during the school day for struggling students by using grade level teachers and
has now targeted the use of instructional aides based upon student needs. When the
principal was asked about what additional resources were needed to help move all
students to proficiency, the principal reported he did not need any additional resources.

288
APPENDIX F – ORANGEWOOD ELEMENTARY
Background on School and District
Orangewood Elementary School is a Title I, kindergarten through sixth grade
school located in a sub-urban K-8 school district within Orange County, California.
During the 2009-10 academic school year, Orangewood Elementary reported an
enrollment of 694 students and was one of 20 schools in the district. The district serves
nearly 13,600 students in seventeen elementary schools and three middle schools. The
district spans 23 square miles and has an operating budget of $104 million dollars. Table
F.1 provides a demographic comparison and description of the school, district, county
and state average.
Table F.1: Orangewood Elementary Demographic Comparison 20009-10

%
Hispanic
%
White
%
EL
%
Free/Reduced
Orangewood Elementary 84 8 56 67
District Average 47 24 30 35
Orange County Average 44.7 32.8 27.9 42.3
State Average 49.0 27.9 24.2 55.7
Note: Adapted from DataQuest by California Department of Education (2010b).

Orangewood Elementary school opened in September, 1949 and has 38
classrooms. It is located on the western section of the district and serves a diverse ethnic
and socioeconomic background of students. Fifty-six percent of Orangewood’s students
are EL and speak over 10 different languages. The school is the only school in the district
that receives funding from the State’s Quality Education Investment Act (QEIA) Grant.
The QEIA Grant provides approximately $3 billion authorizing school districts and other
289
local educational agencies to apply for funding to allocate to elementary, secondary and
charter schools that are ranked in either decile 1 or 2 as determined by the 2005 API base
(California Department of Education, 2010). The bulk of the QEIA grant is intended to
lower class size to 20: 1 in kindergarten through third grade and between 24 and 25 to 1
in fourth through sixth grade. Orangewood has received funding for the QEIA grant since
the 2007-08 school year and will expire at the end of the 2012-13 school year. The
principal at Orangewood is currently serving her second year as principal at the school
and relatively new to the district. She is a driving force behind the school’s recent
improvement efforts. The school has been within the lowest five performing elementary
schools in the district over the past several years.
As illustrated in Figure F.1, Orangewood serves a disproportionately large
Hispanic, EL and Socioeconomically Disadvantaged (SED) student population with
eighty-four percent of the total population reporting their ethnicity as Hispanic and eight
percent white. Sixty-seven percent of the students were identified as SED and enrolled in
the free and reduced meals program (California Department of Education, 2010a). Of the
total population, fifty-six percent were reported as English Learners (EL) and eight
percent were identified as students with disabilities (SWD). The purpose of this case
study is to identify effective resource allocation and researched based instructional
strategies at Orangewood Elementary School (OE).

290
Figure F.1 School Demographics Percentage for Orangewood Elementary

Source: California Department of Education, 2010

At the start of this study, Orangewood was in Year 4 of Program Improvement
(PI) as indicated by the 2009 Federal AYP (California Department of Education, 2010a)
but has exited Program Improvement in 2010 due to meeting Adequate Yearly Progress
(AYP) goals. As indicated in Figure F.2, the school’s State Annual Performance
Indicator (API) score has experienced inconsistent growth over the past five years, but
has achieved significant growth within the past two years. From 2007 to 2010, OE’s API
cumulative growth has been 81 points, the second highest of all the schools within the
sample of this. In 2008 Orangewood’s API dropped 20 points, but in 2009 it rebounded
by 50 points. The 2009 API gain was greater than 1.43 standard deviations from the
county average for all elementary schools. In 2010, OE’s API score jumped an additional
54 points from 745 to 798 and was the largest API growth in the district. Over the past
two years alone, OE’s API has increased by 104 points.

84
8
56
67
8
0
20
40
60
80
100
Hispanic White EL SED SWD
Hispanic
White
EL
SED
SWD
291
Figure F.2 Orangewood Elementary School’s Yearly API Trend

Source: California Department of Education, 2010

The Average Yearly Progress (AYP) report shows a similar trend of school
progress over the past five years. Orangewood has been in Program Improvement (PI) for
the past four years but has currently exited PI by being in what is called Safe Harbor.
Figure F.3 indicates Orangewood’s English Language Arts (ELA) progress has grown
16.8 points over the course of five years with its highest ELA proficiency in 2010 of
50.6% proficiency school wide. Since 2008, ELA proficiency has increased; in 2009 it
increased 27.5% from the previous year, and in 2010 it increased an additional 17%. The
EL subgroup has been the lowest performing subgroup three of the last five years and has
experienced the widest gap in achievement compared to the other subgroups. The
achievement gap between the EL subgroup and school wide progress has increased from
a gap of less than 4% in 2008 to a 6% gap in 2009 and a 6.9% achievement gap in 2010.
The SED subgroup’s achievement gap has also increased from 2% in 2008 to 4.9% in
2010. The only subgroup that has narrowed its achievement gap is the Hispanic
subgroup. Since 2008, the Hispanic achievement gap has decreased from 6.1% to 4.2%.
600
650
700
750
800
850
900
2006 2007 2008 2009 2010
715 717
695
745
798
292
While Orangewood is no longer in PI, it’s 2010 ELA proficiency is still 6.2 points below
the AYP target of 56.8% proficiency.
Figure F.3 Orangewood Elementary ELA - Percent Proficient or Above Trend

Source: California Department of Education, 2010

Figure F.4 indicates the math AYP for Orangewood. Since 2008, a more dramatic
pattern of progress has been seen in math. Over the past five years math proficiency has
increased almost 18 points with the largest percentage of growth occurring between 2008
and 2010. Since 2008, OE’s math proficiency has jumped nine to ten points each year. In
2008, math proficiency growth doubled to 40.9% proficiency and grew an additional nine
points in 2010. Similar to ELA proficiency, the Hispanic and EL subgroup had the widest
achievement gap across the five year span in math. In 2008, the Hispanic achievement
gap was 4.61% but by 2010, the achievement gap was narrowed by 2.8% to a current
1.8% gap. The EL achievement gap decreased from 4.9% in 2008 to 1% in 2010.
Orangewood’s 2010 Math proficiency is 1.9 points above the AYP target of 58%
proficiency.
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Figure F.4 Orangewood Elementary Math Percent Proficient or Above

Source: California Department of Education, 2010

Key Elements and Themes of the Improvement Process
In 2009, OE had a State ranking of 3, below the median statewide ranking
ranging from 1 to 10. When compared to similar schools, schools with similar
demographics and student mobility rates, it received a similar schools rank of 4, with 10
being the highest similar schools ranking possible. This ranking has improved over the
year, in 2008 OE had a State ranking of 2 and a similar schools ranking of 2. The
improvements efforts of OE over the past 5 years have made inconsistent progress but
over the past two years OE has begun to see a turnaround with two years of consecutive
growth of fifty or more points each year in their API. Improving student proficiency for
all students should be the primary mission of all schools and can be one of the most
overwhelming challenges any school undertakes (Reeves, 2005). However, research
45.7 45.5
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50.9
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2006 2007 2008 2009 2010
School Wide
Hispanic
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continues to provide growing evidence that schools have much more control over student
performance and other school related problems than many choose to believe (Darling-
Hammond, 1997; Marzano 2003, Odden 2009, Odden & Archibald, 2009; Schmoker,
1999). The purpose of this section is to review effective research-based educational
elements that have led to improved student learning. Odden and Archibald (2009) outline
ten strategies successful schools and districts implement to dramatically improve student
performance. In addition to the framework and strategies outlined by Odden and
Archibald (2009), the Evidence-Based Model (Odden & Picus, 2008) of resource
allocation will be utilized to examine the alignment between how schools use their
allocated resources along with research-based strategies to improve student performance.
The following is a description of what has occurred at Orangewood within the framework
of these ten strategies and the Evidence-Based Model (Odden and Picus, 2008).
Understanding the performance problem and challenge. Teachers, principals,
and school leaders must fully understand the performance challenge and have a strong
desire to want to address student performance (Odden & Archibald, 2009). Stakeholders
must feel a sense of urgency to change student performance levels and use this urgency to
drive the instructional improvement process. The principal at Orangewood arrived one
year ago as the school had the reputation of being within three lowest performing
elementary schools in the district. In 2008, OE was the lowest performing school in the
district and was the only elementary school in the district with an API score in the six
hundreds. The principal was previously a principal and assistant principal in a two
different districts in Los Angeles County and recently worked for a non-profit
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organization before coming back to education. When she came back to education, she
intentionally wanted to work at the lowest performing school in a district as she stated
she likes to turn things around and see tangible growth. Since then, OE’s API has grown
104 points in large part because the new principal had a sense of urgency to improve
learning for students and instilled this urgency within the staff. She recalled a meeting
she had with her kindergarten team the first few months she arrived at the school. The
kindergarten program is a full day program, but the first month of school the kindergarten
students got out of school at 12:30 to help them transition into school. When she met with
them, the teachers were asking for various things that were non-academic. The principal
reported that she closed her laptop and looked at the group of kindergarten teachers
stating, “I don’t know if we share the same sense of urgency. These kids don’t have three
years for us to figure it out.” She went down their list of request and told them they were
not going to do that and instead pushed a more rigorous academic agenda she expected
them to pursue.
Towards the end of the principal’s first year she had a couple teachers complain to
their union reps about the level of accountability and expectations she placed on staff. At
the end of a professional development day the union rep got up and spoke to the staff
about some of the changes taking place in negotiations across the district with class sizes
going up due to various budget cuts. Class sizes across the district were expected to go up
from 24 to 31 in grades K-3 and up from 30 to 35 in grades 4-6. OE was the only QEIA
school in the district which is mandated to have class sizes 20 to 1 in K-3 and between 24
and 25 to 1 in grades four through six. After the union rep spoke to the staff about some
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of the changes going on through negotiations, the principal got up and wanted to address
the staff, especially the few who were complaining about the level of work and
accountability she has brought since arriving at the school. She got up and told the staff
how fortunate they were, they were the only school in the district that regardless of what
happens in negotiations, will remain with class size reduction. She informed them saying,
“we have a grant, and when there’s a grant, there is a lot of accountability, and when
you’re PI four, the accountability just goes up.” She told the whole staff, you have a
choice: they could stay at OE with all the accountability and expectations to improve
student learning with class sizes of 20 in primary and class sizes of 24 in upper grades; or
they could go to another school where there is 31 students in primary and 35 in upper
grades. She told them, “make your choice, but this is the last time we’re going to have
this discussion.” After she addressed the staff, many came up to her privately thanking
her for addressing the staff as they too shared her sense of urgency and was tired of a few
people whining. This sense of urgency is the same sense of urgency and level of
expectations the principal brought with her during every conversation she had with staff,
parents, and the community. She knew her purpose and would not take any excuses for
complacency.
Set ambitious goals. One of the most significant things any school can do to
improve student performance is to set specific, yet ambitious goals for student
proficiency (Odden, 2009; Odden & Archibald, 2009). The principal never stated her
over all vision for the school was to be out of PI; however she used it as leverage to help
drive her mission. Her mission was to ensure every student reached grade level
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proficiency. She did not allow excuses that certain groups of students could not reach
proficiency, she expected every student regardless if they were an EL student, if they
came from SED backgrounds or if they had special needs, to be proficient. She
understood that various students would need additional support and various intervention
strategies to help them reach proficiency but she believed every student could reach
proficiency. Understanding this, the principal began to implement various levels of
interventions and support to help students reach proficiency. During her first year at OE,
the principal noticed teachers held a lot of Student Study Team (SST) meetings, not for
the purpose of helping the child or doing any intervention, but simply to retain the child.
She put a stop to that and completely overhauled their intervention and SST process (See
extended learning time for struggling students). After much dialogue and collaboration, it
was clear a common goal for student proficiency became a shared goal and the sense of
urgency to accomplish this goal was evident across the staff.
Change the curriculum program and create a new instructional vision. When
the principal arrived at the school, the school was one of the lowest performing schools in
the district and their ELA proficiency hovered around 42% proficiency and their math
around 51% proficiency. The principal knew they had to address ELA as a focus and
knew the importance reading and language arts proficiency has on other content areas.
After many discussions with the leadership teams (made up of the principal, support staff
and grade level reps from each grade level) the leadership team decided to make ELA
and English Language Development (ELD) the primary focus for the school’s
instructional vision. The staff recognized they also needed to work in math, but they
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understood they could not go deep into a focus area and still try to do everything. They
wanted to focus on ELA first and dig deep into ways to improve student learning by
improving instruction and their response to intervention in ELA. The school invested
heavily in Professional development with Action Learning Systems with most of the
professional development supporting ELA.
The principal stated that majority of the schools improvement progress has been
done through collaboration and accountability within each grade levels’ Professional
Learning Community (PLC). Teachers are provided one-hundred minutes a week during
the school day to meet collaboratively as a PLC team discussing individual student needs,
analyzing data, planning intervention responses for students not meeting proficiency and
sharing best practices. This release of 100 minutes a week is unique to OE, it is not
provided in the teachers’ contract by the district. The school has made this a powerful
aspect of their improvement process and has hired a half-time PE teacher and two
recreational aides to provide release time for grade levels to meet. Since teachers are
released during the school day, the principal can put various requirements and pressures
on how teachers utilize this time. The principal and or a program specialist meets with
grade level’s PLC about 60% of the time typically on Mondays, Wednesdays and
Fridays. The principal contributes to the conversations and analyzes student data with the
PLC team. Teachers are required to be looking at student data and submit a report each
week to the principal about the students they are monitoring and the conversations
discussed at the PLC meeting. It is during these PLC meetings and data analysis that
various instructional needs pop up and express themselves.
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During various data discussions within grade levels PLC, it became evident that
the schools ELD instruction needed improvement. The principal offered professional
development in ELD strategies and purchased new ELD curriculum. OE purchased
Systematic ELD published by EL Achieve and authored by Susana Dutro. According to
the principal, Susana Dutro is one of the leading authorities on ELD instruction and
provides professional development and consulting to districts across the nation. The
principal reports the series is brand new and a bit costly, but is an excellent resource. It
breaks ELD instruction into various levels and has various units for each level. The staff
was previously trained using many strategies suggested by Susana Dutro, but this is the
first time where Susana Dutro actually published lessons and put them into a published
curriculum. Various PLC grade level conversations also discovered that OE had many EL
students brand new to the country. These students were struggling with basic skills across
kinder through sixth grade as they had been in the country for less than a year. Hearing
the need arise from PLC discussions, the principal went to her community liaison and
told her she would be teaching a newcomer program to these EL students at the end of
each day for twenty minutes. PLC teams provided the list of student names and provided
input on the types of instruction these students needed. The teachers, principal and
community liaison created the curriculum they were going to use with these students as
they did not have a newcomer curriculum. They mostly focused on picture cards, family
names, colors, basic vocabulary and survival skills to function in a classroom and on the
playground. Additionally, the school implemented MIND Research’s ST Math program
which is a non-linguistical computer-based mathematical reasoning curriculum tied to
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standards. It is especially designed for EL students since the instruction is completely
visual and does not involve language. They qualified for a grant through the Orange
County Math Initiative to bring the MIND program to Orangewood starting in second
and third grade. The ST Math program is in addition to the regular math curriculum
adopted. The school plans to add two additional grade levels in 2010 to expand ST Math
to fourth and fifth grade as well.
The other curriculum change that came out of PLC data analysis and collaborative
dialogue process was an ELA curriculum to support students who are two years or more
below grade level. The school identified they had over 90 students in grades four through
sixth who were two or more years below grade level. They adopted Gateways created by
Action Learning Systems. The school already had a professional development contract
for the past couple of years with Action Learning Systems and teaches were previously
trained in many of the instructional strategies used in the series. Gateways is an intensive
ELA curriculum with ELD instruction embedded within it for grades four and above who
are two or more years below grade level. It replaces the standard Houghton Mifflin (HM)
ELA program and both teachers and the principal received a week long training on the
series. The school had four classes in grades four through six with over 90 students who
received this replacement curriculum for both ELA and ELD.
Formative assessments and data-based decision making. A variety of
formative and summative assessments are utilized at OE to support student learning. This
process has taken a few years to become engrained in the school culture and has moved
beyond the district’s focus on summative benchmark assessments. All teachers are
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required to give district benchmarks throughout the year. The ELA district benchmarks
are the HM summative test and are administered three times a year. The math district
benchmarks are given three times a year at the end of each trimester. Formative
assessments became an integral part of the instructional improvement plan and vision for
improvement at OE. Since teachers were released for one hundred minutes a week during
the instructional day to meet in PLC teams, teachers were regularly analyzing student
data and results for various formative assessments. Teachers would administer common
formative assessments and scan them into Data Director, the district’s on-line student
assessment data management system. OE also funded a program specialist, who acted as
a quasi-administrator to oversee the QEIA grant. The program specialist worked with
each PLC team pulling data reports from Data Director and helped them further analyze
the data to inform instruction and facilitate grouping of students for ELD instruction.
Teachers met weekly along with either the principal and/or the program specialist in
PLCs to discuss student progress and create plans for students not meeting grade level
proficiency.
Response to intervention (RTI) plans for specific students came about during PLC
discussions. It was after the principal met with various PLC teams when she noticed the
data was pointing to the fact that they had a large number of EL students who just came
to the country and were now floundering in various classrooms. From this realization, she
created a newcomer instructional program taught by the school’s community liaison the
last twenty minutes of the day to all students grade K-6 new to the country. In PLC
conversations with the second grade team analyzing various formative assessment results,
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the staff and administration noticed they had a large number of resource students and
other students who were struggling to meet grade level proficiency that may soon be
recommended for special educational testing. After some negotiations between the
second grade team and the principal, they devised a plan where they created an intensive
intervention plan for a cluster of twenty-one students. The cluster of twenty-one students
would work with one of the second grade teachers, the RSP teacher and the RSP aides for
approximately forty minutes a day two days a week for an intensive ELA intervention.
The rest of the grade level students were divided among the rest of the second grade
teachers. Grouping of students and leveling students to target a specific skill in ELA or
math was a common practice at all grade levels as PLC teams analyzed formative
assessment results on a weekly basis in their PLC teams.
Ongoing, intensive professional development. A key strategy to improve
student performance is to improve the knowledge and skills of teachers through providing
ongoing, systematic and intensive professional development (Odden, 2009, Odden &
Archibald, 2009). One of the mandates of being in Program Improvement is that ten
percent of the school’s Title I budget must be set aside for professional development.
Professional development has been a major priority at OE and the school has invested
large amounts of resources, more than any other school in this study, towards
professional development. Orangewood had a $40,000 contract with Action Learning
Systems for the 2009-10 school year for professional development. OE used Action
Learning Systems for a couple years prior for on-going, intensive professional
development and negotiated to have the same presenter/coach through Action Learning
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Systems to work with the OE staff as they saw improved results in their knowledge and
skills. In 2009-10, each teacher received approximately ten days of professional
development during the school year with Action Learning Systems. Teachers were
provided with substitutes and released during the school day for the majority of these
opportunities. The principal acknowledged she struggled with the amount of time she was
pulling teachers out of the classroom for professional development as she understands the
most effective use of a teacher’s time is when they are actually in the classroom working
with students. However, she noticed teachers continued to get “so much better on what
they do” after the training so the principal continued to allocate resources to support
ongoing and intensive professional development. In total, OE allocated over $80,000 on
professional development in 2009-10 with $40,000 towards Action Learning Systems and
just over $40,000 in substitutes or stipend cost.
The focus of professional development for 2009-10 aligned with the schools
instructional focus for the year in ELA and ELD instruction. Action Learning Systems
main focus with staff was on question strategies. Teachers received training and coaching
on how to ask deeper level types of questions, questions that would promote more opened
ended response and require students to think critically. They focused on surface
questions, under the surface questions, below the surface questions, in addition to
clarifying, summarizing and predicting types of questions. The consultant with Action
Learning Systems has worked with the OE staff for a couple of years and has built a
rapport and trust with teachers. The consultant provided professional development in the
forms of training, coaching, modeling lessons, and co-planning instruction and RTI
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strategies. In addition to the professional development through Action Learning systems,
OE also trained over eighteen teachers in systematic ELD instruction. Some of the OE
staff had already received Systematic ELD training, but the goal was to have 100% of the
staff trained in systematic ELD instruction. The training was provided by the district with
the school funding the substitute costs.
The teachers’ contract only provides for two days of professional development
during the school year. Since the principal was new to the OE in 2009-10, she bought an
extra staff development day before the school started to conduct a staff retreat at the local
city library. The purpose of the staff retreat was team building and to allow the staff to
get to know the new principal. The principal used the time getting to know the staff,
listening to their ideas and expectations while also sharing her instructional vision,
philosophy and expectations. The other two days of professional development allotted in
the teacher’s contractual year was spent with Action Learning Systems to help defray the
cost of subs during the school year.
Using time efficiently and effectively. Class size reduction is a strategy
designed to help educators use time more efficiently (Odden, 2009; Odden & Archibald,
2009; Odden & Picus, 2008). OE utilized class size reduction in kindergarten through
sixth grade, the only school in this study to reduce class size in the upper grades. Since
the school was a QEIA school, the funds had to be used to reduce class size to 20 to 1 in
kinder through third grade and between 24 and 25 to 1 in fourth through sixth grade,
depending on the grade.
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Another way teachers used time more effectively and efficiently was by grouping
students by instructional level for some portion of the instructional week. Each grade
level did this various ways depending upon the various needs of their students and the
agreements made with their team. After analyzing student results on formative
assessments, teachers formed various groups to level students for more specific targeted
instruction and intervention. The example of second grade shared above under the section
formative assessments and data based decision making is just one example of how
teachers structured their time. In sixth grade, teachers leveled students for math one day a
week. Every Thursday, sixth grade teachers divided their students across the grade level
based upon instructional needs, making the class size even smaller for those needing
more scaffolding and support and larger for those students at benchmark and above. In
fifth grade, teachers would give a quick formative math assessment every two weeks
based upon the standard they were teaching. They would level students for one to three
days using different strategies to address the gaps for that particular group or extend the
learning for those students that already mastered the concept. The principal allowed grade
level teams flexibility on how and when they would level students for targeted
instruction, but ensured that every grade level did it throughout the year.
Extending learning time for struggling students. Providing multiple-extra help
strategies for students struggling to achieve proficiency is a critical component to
improving the learning outcomes for struggling students (Odden, 2009, Odden &
Archibald, 2009). OE offered support to struggling students both during the school day
and after school. The bulk of extra support offered to students during the school day was
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offered to students by leveling and grouping students for portions of the instructional day
described above. In addition, students in grades four through six who were at least two or
more grade levels below in ELA were in the Gateways program for the entire ELA and
ELD instructional block. OE also offered a full day kindergarten program. In addition,
the school hired a part time intervention specialist, a classified person who the principal
worked with in the past who used to work under the old SB 65 grant (dropout prevention,
pupil motivation and maintenance program). The intervention specialist worked with
grade levels teams revamping their Student Study team process so that the process
involved more strategies and interventions to support the child before teachers
recommended the child for retention or special education services. The intervention
specialist created Grade Level Intervention Team meetings (GLIDT) prior to any grade
level recommending a student for a Student Study team meeting. The intervention
specialist attended every GLIDT meeting and would pull relevant information on the
student requested by the teachers prior to the meeting. At the meeting, grade level
teachers discussed each student to the grade level PLC team seeking suggestions and
input. The team came up with a plan and monitored the student’s progress for at least six
weeks with progress monitoring sheets and would report the results at a future GLIDT
meeting. Based upon the results, the team would decide on next steps or if a Student
Study Team meeting was needed.
What was unique about Orangewood was its elaborate and systematic extended
day program for struggling students after school. The school’s extended day program
was new to OE last year and was created by the new principal and her vision for
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providing additional support to struggling students. The extended day program began in
January of 2010 and served one hundred-eighty students.
Teachers in grades two through sixth identified two groups of students. The first
group involved students who were their bubble kids, students who were at basic or low
proficient on the CSTs. The idea for this group was that they could give them enough
tutoring and enough extended day opportunities to push the basic students up to
proficiency and to the low-proficient students so that they don’t fall down. These
students attended the extended day program three days a week on Mondays, Wednesdays
and Fridays. The second group was students who were far below basic and below basic
on CSTs. These students attended the same extended day program two days a week on
Tuesdays and Thursday. OE hired eight part-time non-certificated tutors to work in the
extended school day program. The tutors worked from 2 to 5 PM. From 2 to 2:40, the
tutors pulled kinder and first grade students providing tutoring support for twenty-one
kinder students and twenty-four first grade students in a small group setting of about five
or six to one. The principal intentionally pulled the kinder and first grade students during
the school day for tutoring because she did not want kinder and first grade students in the
extended day program due to maturity and intensity concerns.
During the extended day program, second though sixth grade students would go
into the multi-purpose room. OE worked with nutrition services and provided a snack to
each child attending the extended day program. From there, students were broken into
two groups; group A and group B. Students in group A, went directly to the tutors for the
first hour. Students in group B went directly to the homework side where volunteers
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helped students with their homework for an hour. The volunteers on the homework side
were provided through a partnership with a local church in the area. When working with
the tutors, students were working in a small group setting of five or six to one. The tutors
were working with children based on their grade level. The principal, intervention
specialist and input from teachers created an extended day curriculum based upon grade
level standards, the CST blue prints and CST released questions. The curriculum was
beyond CST test preparation and was more about teaching the material and topics
addressed within the CST blue prints and CST released questions. After the first hour,
group A would go to the homework side and group B would go to the tutoring side.
The principal and the intervention specialist trained the eight tutors for two weeks
prior to the extended day program being offered. They assumed the tutors had never
worked with students before and trained them how to work with kids. They trained them
on classroom management including the school’s reward program, how to communicate
with parents, basic instructional strategies and the actual curriculum they would be using.
When asked about the rationale for having the basic and low-proficient students attending
the extended day program three days a week and the far below basic (FBB) and below-
basic (BB) students attending the extended day program two days a week, the principal
stated quite frankly they could only handle two days with the FBB and BB students. She
said those students are intense, and often have various behavior issues associated with
them. She stated the tutors were not teachers and not as highly trained to deal with those
additional challenges. Thus, the decision was to provide support to those students two
days a week and the other students three days a week. All in all she said, one hundred-
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eighty students in an extended day program is a lot of students to serve and is an intense
program for those providing the additional support.
The extended day program was only offered for about half the year and the
principal knew they would not be able to sustain the level of cost and service the same
number of students in the extended day program the following year so she decided to
apply for a School Improvement Grant (SIG). She said just about any QEIA school who
applied for the grant received the grant. For the 2010-11 school year OE received a
$200,000 grant in technology to pilot the IPods in Educational Learning project. The
school purchased 15 carts of 40 IPod Touches for a total of 600 IPod Touches. Teachers
who signed up to participate in the program had to agree to receive additional
professional development, and work outside the instructional day to develop strategies
and best practices for implementing the IPods into classroom instruction.
In addition to classroom use, OE will use the IPod carts as part of the extended
day program. Due to funding, the extended day staffing will be decreased to about five
tutors. The program will still have a similar format with a group A and group B, only this
year the tutoring group will have eight kids instead of five or six. Thus, the eight students
on the tutoring side will be further divided into two groups of four. Four of the students
will work with the tutor for 30 minutes and the other four will work with the IPod
Touches on using different educational software. There are numerous applications that
can be downloaded to the IPod Touch, including applications that work with anything
from reading fluency to single digit multiplication. OE is piloting the IPod in Educational
Learning Project this year and hopes this will continue to help them organize their time to
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support the same number of students in the extended day program with fewer personnel
due to budget constraints.
Collaborative and distributed leadership. Powerful and effective instructional
systems require strong instructional leadership provided by principals, teachers, and
central office staff collaborating purposefully toward utilizing shared instructional
strategies and using common assessment tools (Odden 2009; Raudenbush, 2009). In
professional literature, this often referred to as creating a collaborative and professional
culture with leadership distributed across the organization to enhance effectiveness
(Odden, 2009; Odden & Archibald, 2009; Raudenbush, 2009) and is the eighth and ninth
step in Odden’s (2009) ten strategies to doubling student performance. OE implemented
professional learning communities (PLCs) about three years ago prior to the new
principal’s arrival as it was a goal supported by the district but the new principal took the
staff’s notion of PLC to a deeper level and focused the collaborative dialogue on student
data and student results.
The principal stated that majority of the schools improvement progress has been
done through collaboration and accountability within each grade levels’ Professional
Learning Community (PLC). Teachers are provided one-hundred minutes a week during
the school day to meet collaboratively as a PLC team discussing individual student needs,
analyzing data, planning intervention responses for students not meeting proficiency and
sharing best practices. This release of 100 minutes a week is unique to OE, it is not
provided in the teachers’ contract by the district. The school has made this a powerful
aspect of their improvement process and has hired a PE teacher and two recreational
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aides to provide release time for grade levels to meet. The principal and or a program
specialist meets with grade level’s PLC about 60% of the time typically on Mondays,
Wednesdays and Fridays. The principal contributes to the conversations and analyzes
student data with the PLC team. Teachers are required to be looking at student data and
submit a report each week to the principal about the students they are monitoring and the
conversations discussed at the PLC meeting.
The principal assembled a leadership team with representatives from each grade
level that she purposefully selected. The principal wanted to ensure the leadership team
shared here same sense of urgency to move the school forward and wanted staff members
who were willing to put in the extra time to move this vision into reality. The leadership
team met on a bi-monthly basis to discuss instructional concerns and vision of next steps.
The principal reported she always gave the leadership team credit where she could and
used the leadership team to drive the instructional improvement process. OE also
received support from the district to carry out its instructional vision. The district
provided ELD systematic training for OE staff at no charge to the site and often
supported the site with training at staff meetings using the district’s curriculum or
program specialist.
Professional and best practices. Odden and Archibald (2009) argue that
exemplary schools use evidence from research, advice from experts and work
collaboratively together to significantly improve student performance. Throughout the
curricular change process, the principal spent a lot of time and resources on training
teachers on best instructional practices. Teachers at OE received intensive and on-going
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professional development in ELA and ELD instruction throughout the year and were
provided with demo-lessons and coaching. Teachers were provided with a hundred
minutes release time during the school day to collaborate in PLC teams to analyze student
data and share best practices. The school implemented an elaborate extended day
program to one hundred-eighty students and trained the tutors two weeks prior to the
program. Additionally, the school adopted a new ELA curriculum for students in grades
four through six who were two or more years below grade level. Another best practice
observed at OE was the use of the school’s community liaisons. The community liaisons
taught a newcomer program to EL students brand new to the country for 20 minutes a day
focusing on English survival skills. The community liaisons also taught a series of
workshops in Spanish and English on the 10 Commandments of Parenting. To improve
student attendance, the community liaisons also conducted home visits to families with
chronic absences asking why their child is not in school and putting pressure on them to
improve attendance. Lastly, the school worked with local non-profit agencies and
provided a backpack program where fifty of their neediest students received a backpack
filled with groceries every Thursday to take home. The backpacks were returned to the
school on Friday and sent back to the non-profit agency to have the backpacks filled
again the following Thursday.
Comparison of School Resources to the Evidence-Based Model
An evidence-based model approach to improving academic performance for all
students strives to identify a comprehensive set of effective educational elements based
upon proven research strategies necessary to deliver a high-quality comprehensive
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instructional program for all students at the school (Odden, 2000; 2003; Odden & Picus,
2008). The evidence based approach employs current educational research to determine
what resources are needed to reach proficiency for every learner. One such framework
that can be used to help identify resource allocations and effective educational strategies
is the Evidence-Based Model outlined by Odden and Picus (2008). The following table is
a comparison of Orangewood Elementary to that of the core resources allocated to a
prototypical elementary school using Odden and Picus’ (2009) Evidence-Based Model.
As illustrated in Table F.2, on average Orangewood Elementary employed less
resources throughout their school improvement plan compared to the prototypical school
using the Evidence-Based Model (Odden & Picus, 2008). The majority of the
discrepancies fall in the area of primary class size, number of core and specialist teachers,
instructional coaches, instructional tutors during the school day for EL and SED students,
pupil support staff and extended year staffing. The school provided tutoring after school
to students in a extended day program similar to the resource model called for by the
Evidence-Based Model (Odden and Picus, 2008) but did not provide any additional tutors
during the school day. As a school with a 67% socially economically disadvantaged
population and a 57% EL student population, the Evidence-Based Model (Odden &
Picus, 2008) would provide nearly an additional 9.4 full time staff members to provide
additional support for struggling students in the form of tutors, English Language
Development (ELD) instruction during the regular school day. It would also allocate the
equivalent of 2.9 full time teachers for summer school, something currently lacking at
Orangewood Elementary. OE provided slightly more administrators and $13,600 more in
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other professional development resources than what the Evidence Based Model (Odden
& Picus, 2008) allocates, but OE also provides eight less professional development days
built into the contractual year than what is called for in the model.

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Table F.2: Orangewood Elementary Evidence-Based Model Comparison
School Element
Evidence-Based
Model
Current Allocation
Resources
Resources Based on
Prototypical Model
School Size K-5; 432 Students K-6; 694 Students 61 % larger
Class Size
K-3 : 15
4-5 : 25
K-3: 20
4-6: 25
K-3: 33% larger
4-6: Same as EBM
Instructional Days 190; + 10 PD days
176; + 2 PD & 2 prep.
days
10 less student days
and 8 less PD days
Kindergarten Full-day K Full-day K Full-day K
Administrative Support
Principal & Other Admin 1.0 FTE 2.0 FTE 1.61 FTE
School Site Secretary 1.0 FTE 1.0 FTE 1.61 FTE
School Site Clerical 1.0 FTE 0.75 FTE 1.61 FTE
General Personnel Resources
Core Teachers 24 FTE 32 FTE 39 FTE
Specialist Teachers 20% of core teachers
.5 FTE PE plus 1 FTE
PE Aides
4.69% of core teachers
7.8FTE
Instructional Facilitators 2.2 FTE 0.0 FTE 3.54 FTE
Extended Support
Tutors
1.0 FTE : 100 low
SES
0.0 FTE (562 students) 5.62 FTE
certificated tutors
Teacher for EL 1.0 FTE : 100 EL 0.0FTE (388 students) 3.88 FTE
Extended Day 1.8 FTE 3.0 FTE 2.90 FTE
Summer School 1.8 FTE 0.0 FTE 2.90 FTE
Other Staffing Resources
Substitutes 5% of personnel 5.4% of personnel 5% of personnel
Librarians/Media Specialist 1.0 FTE 0.72 FTE Media clerks 1.61 FTE
Instructional Aides 0.0 FTE 0.0 FTE 0.0 FTE
Pupil support staff
1.0 FTE : 100 low
SES
0.93 FTE Com. Liaison
.6 FTE intervention spec
5.62 FTE
Professional Development
$100 per pupil for
other PD expenses-
trainers, conferences,
travel etc.
$83,000 $ 69,400
Note: Adapted from School finance: A policy perspective (4
th
ed.) by Odden and Picus (2008), pp. 132-133.
Copyright 2008 by McGraw-Hill. Adapted with permission.
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Summary and Lessons Learned
Orangewood Elementary school’s improvement effort over the past two years has
experienced dramatic results with large gains in student improvement. Over the past four
years, the school’s academic API score has experienced a cumulative growth of 81
points, the second highest cumulative growth over the same four year period of all the
schools in this study. Over the past two years alone the school has experienced 104
points in API growth and is no longer the lowest performing school in the district. This
remarkable turnaround occurred in just two years and has resulted in the school’s exiting
Program Improvement while the school has faced cut backs in personnel, categorical
budgets, and a loss of four instructional days in the 2009-10 school year. The four
furlough days were negotiated late in the school year as the district ended the school year
four days earlier in June.
Despite these barriers, the principal has worked hard to instill a sense of urgency
within her staff for improving student proficiency and has set up systems to provide
additional support for students not meeting proficiency. Teachers at OE received
intensive and on-going professional development in ELA and ELD instruction throughout
the year and were provided with demo-lessons and coaching. Teachers were provided
with a hundred minutes release time during the school day to collaborate in PLC teams to
analyze student data and share best practices. The school implemented an elaborate
extended day program to one hundred-eighty students and trained the tutors two weeks
prior to the program. Additionally, the school adopted a new ELA curriculum for
students in grades four through six who were two or more years below grade level.
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Although the school demonstrated the application of all ten evidence-based
strategies outlined within the nine categories in Table F.3, many were not implemented to
the level and intensity supported by research. Table F.3 summarizes Orangewood
Elementary School’s educational reform efforts compared to the ten evidence-based
strategies supported by research and recommended by Odden and Archibald (2009) for
doubling student performance. OE ranked strong on five of the categories in Table F.3
and above average in four of the categories. Even with such high marks, the funding
levels and level of support provided were not near what is called for in the Evidence-
Based Model (Odden & Picus, 2008) and the school continues to encounter further
budget restrictions. While OE ranked above-average and strong in all ten strategies and
had the strongest alignment to the prototypical school, it still lacked the level of
instructional facilitators, specialist teachers, instructional tutors during the school day,
and pupil support staff. Additionally, it lacked a summer school program to support
struggling students. Instead of investing in instructional facilitators and coaches, OE
funded a program specialist that acted as a quasi-administrator. While the program
specialist was valuable to the PLC teams and facilitating data analysis, he did not provide
instructional coaching. Instead, instructional coaching was built into OE’s professional
development plan. OE’s level of professional development and its extended day program
for struggling students was the strongest observed within all the schools of this study.

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Table F.3: Orangewood Elementary Performance of Evidence-Based Strategies
Evidence-Based Strategy Weak
Below
Average Average
Above
Average Strong
Understanding the Performance Problem and
Challenge

√
Setting Ambitious Goals √
Change the Curriculum Program and Create a
New Instructional Vision

√
Formative Assessments and Data-Based
Decision Making

√
Ongoing, intensive Professional Development √
Using time Efficiently and Effectively √
Extend Learning Opportunities for Struggling
Students

√

Collaborative Culture and Distributed Leadership √
Professional and Best Practices √
Note: Adapted from Doubling student performance:…and finding the resources to do it by Odden and
Archibald (2009). Copyright 2009 by Corwin Press.

Future Considerations
Orangewood Elementary School continues to not meet federal and state
benchmark targets for student achievement in ELA and will be hard pressed to meet the
benchmark for math in 2011. While the school experienced a 54 point growth in API for
2010 and has exited PI for now, it continues to serve a majority of underperforming
students and is among the seven lowest performing schools in the district. Discussions
with the principal indicated there is still much more work and support necessary to help
ensure every student reaches proficiency. The 2010-11 school year further cut the
resources previously allocated to the school, including the loss the program specialist,
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three after school tutors, and less money for professional development. . Employees are
facing six furlough days in 2010-11. The furlough days decreased the number of
instructional days by five, decreased the number of professional development days by
one, but kept the two teacher-planning days. The school’s professional development
budget was cut by almost 40% for the 2010-11 school year. OE’s principal identified her
concern about the difficulty OE will face in maintaining the level of focus, intensity and
support provided to struggling students in the near future due to the looming budget
reductions on the horizon. The principal addressed the need for additional resources to
provide instructional tutors and intervention specialist and instructional coaches. Ideally,
the principal would like to see a primary and an upper grade coach as she said the
instructional needs and pedagogy differ at these levels. Additional resources are also
needed to offer an expanded targeted afterschool program for struggling students along
with a summer school program focusing on reading and math.
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APPENDIX G – GREENWOOD ELEMENTARY
Background on School and District
Greenwood Elementary School is a Title I, kindergarten through sixth grade
school located in a large urban elementary school district within Orange County,
California. During the 2009-10 academic school year, Greenwood Elementary reported
an enrollment of 700 students and was one of 24 elementary schools in the district. The
district is one of the largest elementary school districts in California. The district spans 22
square miles serving largely the downtown region of one large city within Orange County
and has an operating budget of $176 million dollars. Table G.1 provides a demographic
comparison and description of the school, district, county and state average.
Table G.1: Greenwood Elementary Demographic Comparison 2009-10

%
Hispanic
%
White
%
EL
%
Free/Reduced
Greenwood Elementary 81 4 60 86
District Average 85 5 53 85
Orange County Average 44.7 32.8 27.9 42.3
State Average 49.0 27.9 24.2 55.7
Note: Adapted from DataQuest by California Department of Education (2010b).

Greenwood Elementary school opened in September, 1957 and has 27
classrooms. It is located on the northwest border of the district and serves a diverse ethnic
and socioeconomic background of students. Sixty percent of Greenwood’s students are
EL and speak over 14 different languages. The principal at Greenwood has served as
principal for four years and has helped the school achieve remarkable growth within her
tenure. The principal has worked in the district the bulk of her career and has worked as
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principal at other sites and a director at the district office in the past. According to the
principal, three years ago the school was the district’s lowest performing school in the
district. In 2008, the school ranked 10
th
out of 24 schools in the district and in 2009 it
ranked 3
rd
.
As illustrated in Figure G.1, Greenwood serves a disproportionately large
Hispanic, EL and Socioeconomically Disadvantaged (SED) student population with
eighty-one percent of the total population reporting their ethnicity as Hispanic and four
percent white. Eighty-six percent of the students were identified as SED and enrolled in
the free and reduced meals program (California Department of Education, 2010a). Of the
total population, sixty percent were reported as English Learners (EL) and twelve percent
were identified as students with disabilities (SWD). The purpose of this case study is to
identify effective resource allocation and research based instructional strategies at
Greenwood Elementary School (GE).
Figure G.1 School Demographics Percentage for Greenwood Elementary

Source: California Department of Education, 2010

At the start of this study, Greenwood was in Year 5 of Program Improvement (PI)
as indicated by the 2009 Federal AYP (California Department of Education, 2010a) and
81
4
60
86
10
0
20
40
60
80
100
Hispanic White EL SED SWD
Hispanic
White
EL
SED
SWD
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has remained in Year 5 of PI. GE, once the lowest performing elementary school in the
district, is now the seventh highest performing school. As indicated in Figure G.2, the
school’s State Annual Performance Indicator (API) score has experienced significant
growth over the past five years. From 2007 to 2010, Greenwood’s API cumulative
growth has been 130 points, the highest of all the schools within the sample of this study
with a forty-nine point differential between the school with the second largest cumulative
growth in the study. In 2008 Greenwood’s API soared 98 points, and in 2009 it jumped
an additional 42 points. The 2009 API gain was more than 1.43 standard deviations from
the county average for all elementary schools. In 2010, GE’s API score declined 4 points
from 787 to 780; the first time the school’s API did not see a positive growth in the past
five years.
Figure G.2 Greenwood Elementary School’s Yearly API Trend

Source: California Department of Education, 2010

The Average Yearly Progress (AYP) report shows a similar trend of school
progress over the past five years. Greenwood has been in Program Improvement (PI) for
the past five years and is currently in Year 5 of PI. Figure G.3 indicates Greenwood’s
600
650
700
750
800
850
900
2006 2007 2008 2009 2010
644
650
745
787
780
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English Language Arts (ELA) progress has grown 12.7 points over the course of five
years with his highest ELA proficiency in 2009 of 44.4% proficiency school wide. The
Hispanic subgroup has been the lowest performing subgroup over the five years and has
experienced the widest gap in achievement compared to the other subgroups. The
achievement gap between the Hispanic subgroup and school wide progress has increased
each year from 2006 to 2009 from a 6.3% gap to a 7.8% gap. In 2010, the gap decreased
to 5.5% but that is because the other subgroups ELA proficiency dropped more than the
Hispanic subgroup. The SED and EL School Wide subgroups ELA scores were nearly
identical from 2006 to 2009, but by 2010 the SED subgroup achievement surpassed the
other subgroups with 39% proficiency. In 2010, the ELA proficiency dipped 2.6 points
and has never surpassed a proficiency rate above 45%. GE’s 2010 ELA proficiency is 15
points below the AYP target of 56.8% proficiency.
Figure G.4 indicates the math AYP for Greenwood. A much more dramatic
pattern of progress is seen in math. Over the past five years math proficiency has
increased almost 24 points with the largest percentage of growth occurring between 2007
and 2009. In 2008, math proficiency school wide increased by forty-seven percent and in
2009 it increased another thirty-seven percent from the previous year. Similar to ELA
proficiency the Hispanic subgroup had the widest achievement gap across the five year
span. In 2007, the Hispanic achievement gap was 7.1% but by 2010, the achievement gap
was narrowed by 3.4% to a current 3.7% gap. GE’s 2010 Math proficiency is 4.1 points
above the AYP target of 58% proficiency.

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Figure G.3 Greenwood Elementary ELA - Percent Proficient or Above Trend

Source: California Department of Education, 2010

Figure G.4 Greenwood Elementary Math Percent Proficient or Above

Source: California Department of Education, 2010

29.1 28.8
39.3
44.4
41.8
0
10
20
30
40
50
60
70
80
90
100
2006 2007 2008 2009 2010
School Wide
Hispanic
EL
SED
28.7
31.8
46.7
63.8
62.1
0
10
20
30
40
50
60
70
80
90
100
2006 2007 2008 2009 2010
School Wide
Hispanic
EL
SED
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Key Elements and Themes of the Improvement Process
In 2009, Greenwood Elementary (GE) had a State ranking of 5, the medium
statewide ranking ranging from 1 to 10. When compared to similar schools, schools with
similar demographics and student mobility rates, it received a similar schools rank of 8,
with 10 being the highest similar schools ranking possible. This ranking has improved
significantly over the past two years; in 2007 the GE had a State ranking of 1 and a
similar schools ranking of 2 and in 2008 GE had a State ranking of 2 along with a similar
schools ranking of 4. The improvements efforts of GE over the past 5 years have made
steady progress with dramatic results in 2008 and 2009. Improving student proficiency
for all students should be the primary mission of all schools and can be one of the most
overwhelming challenges any school undertakes (Reeves, 2005). However, research
continues to provide growing evidence that schools have much more control over student
performance and other school related problems than many choose to believe (Darling-
Hammond, 1997; Marzano 2003, Odden 2009, Odden & Archibald, 2009; Schmoker,
1999). The purpose of this section is to review effective research-based educational
elements that have led to improved student learning. Odden and Archibald (2009) outline
ten strategies successful schools and districts implement to dramatically improve student
performance. In addition to the framework and strategies outlined by Odden and
Archibald (2009), the Evidence-Based Model (Odden & Picus, 2008) of resource
allocation will be utilized to examine the alignment between how schools use their
allocated resources along with research-based strategies to improve student performance.
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The following is a description of what has occurred at Greenwood within the framework
of these ten strategies and the Evidence-Based Model (Odden and Picus, 2008).
Understanding the performance problem and challenge. Teachers, principals,
and school leaders must fully understand the performance challenge and have a strong
desire to want to address student performance (Odden & Archibald, 2009). Stakeholders
must feel a sense of urgency to change student performance levels and use this urgency to
drive the instructional improvement process. The principal at GE arrived three years ago
as the school had the reputation of being the lowest performing school in the district; it
was the twenty-forth performing school out of twenty-four schools in the district. The
principal had a strong background in curriculum and worked as a curriculum specialist in
the area of math for two years. Subsequent to being a curriculum specialist, the principal
worked as a principal at another school in the district that produced great growth and she
recently worked at the district office as a Director of School Improvement. In April of
2007, she asked the district if she could go back to work at the school site. The district
obliged and placed their previous Director of School improvement to their lowest
performing school within the district.
The principal knew the staff was working hard but they felt defeated by having a
sense of being the lowest performing school in the district. She made teachers a part of
the solution, not part of the blame and entrusted their professionalism and classroom
knowledge. She also knew she needed to move staff from fidelity to program teaching to
standards alignment and standards mastery. She chose the area of math, as she knew math
was a strength of hers and an area she worked as a curriculum specialist in the past. She
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also knew it would be easier for the staff to find early success as unpacking math
standards was much more concrete and easier to do than ELA. After starting with math in
April of her first year, the staff moved on to ELA. Within two years the results were
amazing. The growth in student proficiency grew a staggering one-hundred-forty points
within the first two years. By 2010, the school leaped from being the lowest performing
school in the district to within the top seven highest performing schools in the district.
Set ambitious goals. One of the most significant things any school can do to
improve student performance is to set specific, yet ambitious goals for student
proficiency (Odden, 2009; Odden & Archibald, 2009). The principal never stated her
over all vision for the school was to be out of PI; instead she focused her goal on standard
mastery and getting students to become scholars. She almost never used the word student,
and instead referred to them as scholars. This language became a part of the common
language teachers, classified staff and even parents started using. Scholarly thinking
became a motto and part of the school’s mission and vision. As the staff started working
on unpacking the standards and identifying power standards (see change the curriculum
program and create a new instructional vision section below) the goal and expectation
moved beyond exposing students to the standards to having them master the standards. It
was clear every teacher at the school shared that same goal and the sense of urgency to
accomplish this goal was evident. The teachers had agreement on the power standards
and these became the things teachers were willing “to die on the hill” for to ensure every
student mastered the identified standards. Teachers began creating formative assessments
to help them identify students not meeting mastery and began setting systems in place to
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offer additional learning opportunities for students not meeting the standards mastery
goal.
Change the curriculum program and create a new instructional vision.
Within the first year at the school, the principal noticed the teachers were 100%
dependent on the Houghton Mifflin (HM) textbook series for ELA. This was also
strongly supported by the district office and district pacing guides that stipulated exactly
where a classroom should be within the HM series at any given time. The principal
reported she noticed her teachers were focused 100% on the HM program but had a hard
time addressing questions on ELA standards. The teachers were so enmeshed in having
fidelity to a program that they were not very sophisticated in terms of standard alignment
processes. The principal shared her belief with teachers that being so concerned with
program fidelity shuts off the brains of teachers as they no longer have to think critically
about student learning, all they have to do is follow a script. Thus she began working
with staff on standards alignment. As mentioned above, she started the staff in the area of
math as math is more concrete and teachers could understand the process better before
undertaking ELA. The staff started working with the book, Unwrapping the Standards
(Ainsworth, 2003b) and Power Standards (Ainsworth, 2003a). Through staff meetings
and release time with the site instructional coach TOSA and principal, teachers began the
selection of power standards and un-wrapping the standards for rigor, prior knowledge
and establishing mastery benchmarks for each standard. Once the standards were
unpacked, they created formative assessments that would measure standards mastery and
guide further instruction. Through this process, teachers realized they expected mastery
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thinking and wanted to do more than mere exposure of the standards to the students. As a
staff, they started talking about scholarly thinking and the expectation for students to
master the standards. This realization uncovered the need for them to raise the level or
rigor and expectations they hold for students.
Upon this revelation, contrary to the district’s H.M. programmatic focus, the staff
worked collectively to address this mismatch and focused more on standards. The
principal brought in a consultant to work with the teachers to train them on standard
alignment and standard-based instruction. Another curricular change was in the area of
writing. Data and staff observations revealed writing was a huge deficiency for students
at GE. Thus, last year, the principal provided training for teachers before the school year
began in Write from the Beginning. Write from the Beginning connects previous learning
teachers’ received with Thinking Maps and integrates them throughout the writing
process and genres of writing. In addition to Write from the Beginning, the school added
MIND Research’s ST Math program which is a non-linguistical computer-based
mathematical reasoning curriculum tied to standards. They qualified for a grant through
the Orange County Math Initiative to bring the MIND program to Greenwood. Teachers
tried to fit the additional curriculum in their day but discovered it was taking too much
class time in some grade levels. Thus, third and fourth grade teachers decided to offer it
after school two days a week for forty minutes and the parents simply accepted it. The
principal made arrangements with transportation so bus riders would not miss out on this
additional learning opportunity.
330
In addition to standards alignment and standards mastery, the principal started
facilitating conversations with staff about student engagement. A focus point became
scholarly engagement and they used this focal point to conduct classroom walkthroughs
looking for evidence where scholarly engagement was observed. The school used UCLA
SMP as their external entity required when a school is in PI and used UCLA SMP to help
them dive deeper into this focal point. They set up various classroom observation
protocols for the walkthroughs and facilitated conversations with staff after the
walkthroughs.
Formative assessments and data-based decision making. A variety of
formative and summative assessments are utilized at GE to support student learning. As
the GE staff implemented the standards alignment process they included the formative
assessment piece too. As teachers were identifying power standards, and unpacking
them, teachers also had to commit to coming up with various formative assessments they
would use at a minimum, a monthly basis, to determine whether or not their instruction
worked, whether their scholars really earned mastery. The formative assessments were
created in PLC grade level teams along with the TOSA coach’s support. As teachers
began implementing the common formative assessments, teachers felt the need to do both
a mid-month as well as an end of the month formative assessment. Teachers found the
end of the month was too late and thus planned intervention based upon the scholars who
did not meet mastery. In response, teachers created a teaming system for a small portion
of the day where some scholars were provided enrichment, some scholars received
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additional help on pre-requisite skills and other scholars were receiving additional help
with the specific standard they did not master.
The principal stated the school’s assessment focus to inform instruction was
working beautifully until the district implemented district benchmarks across the district
last year. Once this occurred, she said it put the teachers and students on assessment
overload. The school was ahead of the district on formative assessments, but suddenly
they school had to go along with the district testing cycle. The district implemented six
benchmark assessments in ELA and six in math, many of them requiring one-on-one
assessments. This did not include the ELD assessments which were in place for their
ELD curriculum series. The principal reported that teachers were now more forced to
teach to a set benchmark at regular intervals instead of teaching to standards mastery. She
has encouraged teachers to not look at the benchmarks as a whole, but rather on an item
analysis and not worry about items student did not yet master if they did not teach it yet.
She is encouraging teachers to continue to use the formative assessments they created
when they created power standards but understands the teachers concern about too much
assessing and not enough instruction. She is confident they will find the right balance.
Ongoing, intensive professional development. A key strategy to improve
student performance is to improve the knowledge and skills of teachers through providing
ongoing, systematic and intensive professional development (Odden, 2009, Odden &
Archibald, 2009). One of the mandates of being in Program Improvement is that ten
percent of the school’s Title I budget must be set aside for professional development.
Professional development has been a major priority at GE. Professional development
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opportunities included the use of consultants, coaching, site and classroom visitations,
release time for planning and collaborative dialogue at staff meetings. Additionally, the
2009-10 staff included a full-time teacher on special assignment (TOSA) who acted 50%
of her time as an instructional coach (paid by the district) and the other 50% as an
intervention teacher (paid with site funds). The coach was used to co-plan, co-teach
lessons with staff members in all subject areas and debrief instructional strategies
observed. The principal provided training for teachers on writing strategies called Write
from the Beginning using a trainer of trainer’s model. Write from the Beginning connects
previous learning teachers’ received with Thinking Maps and integrates them throughout
the writing process and genres of writing. District curriculum specialist provided the
training for GE staff, thus saving money. The only problem was the principal needed to
find a time she could gather all her teachers. Due to budget cuts, the district had several
furlough days including all the days leading up to the start of the school year. The district
did not allow sites to use those days for anything, even if they had site budgets they could
use for professional development. Thus, the principal got creative and held the
professional development on the Saturday before school started and all but three teachers
attended the training. She paid teachers to attend the day through her staff development
budget and it allowed teachers to earn money they lost for less contracted days worked
under the furlough structure. The principal released the three teachers who missed the
training later in the year to get the Write from the Beginning training. The principal
reported the training was helpful for the entire staff as it brought about a consistent
expectation of what is going on in writing across the grade levels and provided a common
333
language for writing instruction. Additionally, teachers were trained on Bridges to
Understanding (SADIE strategies), spent five days receiving training on the new math
adoption and two days on ST Math.
The majority of professional development opportunities for staff came through
release days throughout the year. The principal released teachers about three full days (or
six half-days) during the year to plan and work in grade level teams with the coach.
Throughout the year, the focus of the release days was standard mastery, unpacking
standards and creating formative assessments to support mastery learning. The planning
was also time for teachers to plan response strategies and interventions for students who
were not meeting standard mastery.
Using time efficiently and effectively. Class size reduction is a strategy
designed to help educators use time more efficiently (Odden, 2009; Odden & Archibald,
2009; Odden & Picus, 2008). Greenwood utilized a modified class size reduction strategy
in first through second grade, narrowing the total class size to twenty-four students.
However, in kindergarten, class size was up to thirty-two and the student’s instructional
day was only about four hours instead of a full day. In grades three through six, class
size grew with an average of about thirty-two students in each class.
Teachers and administration worked collaboratively to come up with a better way
to increase the active learning time (Odden, 2009) more effectively, especially in the area
of ELA. Last year teachers began infusing much more expository text in the traditional
ELA block of instruction. The principal described it as, “instead of reading every cute
little story in the HM series”, they began infusing much more of the science and the
334
social studies expository text in the ELA block, as they found there was not enough time
to teach that content area. One of the main purposes of using more expository text during
ELA instruction was to increase the content knowledge in their scholars, especially
considering the socio-economic backgrounds of many of their scholars. The staff read
various research and felt compelled that students, especially socially-economically
disadvantaged (SED) students needed an expanded vocabulary and greater background
knowledge to master learning. The decision to use more expository text during part of the
ELA block was an awareness that many of their SED students are not coming to school
with the same background knowledge and do not have the same dining room
conversations compared to more affluent peers. The staff felt an urgency to really teach
science and social studies to expand the background knowledge and vocabulary of their
scholars. Thus, they were very comfortable infusing more of that content with the
assurance they were still teaching English Language Arts at the same time.
Another strategy the principal implemented to use time efficiently and effectively
was through the use of altering the working hours of her two full intervention TOSA’s.
The principal had a late start for the intervention TOSAs, having their work hours start a
little more than an hour after the school day began, thus building into their contracted
hour’s time after school to provide additional tutoring for students needing extended
learning time. This was not an easy task to implement, the principal had to work with
human resources and the individual intervention TOSAs to alter their work hours to have
a late start. Since the first half hour block of instruction in the morning was ELD
instruction and students would not be pulled for intervention during ELD instruction, she
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had the TOSA’s come in later and thus stay later. The principal also found that teachers
were not really ready to release their students for intervention until after the first hour in
the day so it worked out it well. Since the primary grades got out of school about a half
hour earlier than the upper grades, it provided primary students with an additional thirty
minutes of tutoring after school and upper grade students an additional hour of tutoring
after school.
Extending learning time for struggling students. Providing multiple-extra help
strategies for students struggling to achieve proficiency is a critical component to
improving the learning outcomes for struggling students (Odden, 2009, Odden &
Archibald, 2009). GE offered support to struggling students both during the school day
and after school. As a Title I school in PI, the school was required to provide
supplemental educational services in the form of tutoring to low-income students.
Tutoring was provided to nearly one hundred-thirty students by private outside
companies using district funds for about one hour a day, one to two days a week. The
school made efforts to have teachers use a communication log between the tutors and
teachers to help communicate and articulate areas to target with the various students. The
principal reported this communication log was both utilized and more successful and with
some teachers but not with all.
During the school day, the school used the equivalent of 3.5 TOSAs, to provide
additional support for struggling students. The intervention support with the TOSA’s was
mostly a pull-out program where the TOSAs pulled small groups of 6-7 students at a time
working on a variety of targeted skills in ELA and math. Since the school had identified
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the power standards they expected all students to master, the TOSA’s were usually
working with students who needed additional support to help master the specified
standard. In addition, teachers analyzed both the mid-month and end of the month
formative assessments and used the data to help target and inform small group
intervention support through the TOSAs. Additionally, teachers responded to the results
of the formative assessments and created a teaming system within their grade level for
twenty-thirty minutes a day where some scholars were provided enrichment, some
scholars received additional help on pre-requisite skills and other scholars were receiving
additional help with the specific standard they did not master. At times, the TOSAs
pulled small groups to provide background knowledge and scaffolding pre-requisite skills
to students prior to a lesson or unit being taught in the classroom. The goal of this was to
intervene ahead of time so that students could be successful during the normal class
instruction instead of targeting them after it was already determined they did not master
the content.
Various opportunities for extended learning were offered at GE. Teachers offered
various clubs afterschool funded through the site’s extra-service pay budget within the
teachers contract. Clubs included art, creative writing, video production, running, Peer
Assisted Learning (PAL) as well as academic tutoring by teachers. Third and fourth grade
teachers offered math support through MIND’s ST Math computer-based program after
school two days a week for forty minutes. The principal made arrangements with
transportation so bus riders would not miss out on this additional learning opportunity.
The intervention TOSA’s had a late start so they too could provide extended learning
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opportunities for students beyond the normal school day. The TOSA’s offered tutoring
for thirty minutes a day, five days a week for their primary scholars and sixty minutes a
day, five days a week for the upper grade scholars. Unfortunately, due to recent budget
cuts, the district stopped offering a summer school program for struggling students other
than what was required by law for students under an IEP with an extended school year.
Collaborative and distributed leadership. Powerful and effective instructional
systems require strong instructional leadership provided by principals, teachers, and
central office staff collaborating purposefully toward utilizing shared instructional
strategies and using common assessment tools (Odden 2009; Raudenbush, 2009). In
professional literature, this often referred to as creating a collaborative and professional
culture with leadership distributed across the organization to enhance effectiveness
(Odden, 2009; Odden & Archibald, 2009; Raudenbush, 2009) and is the eighth and ninth
step in Odden’s (2009) ten strategies to doubling student performance. GE implemented
professional learning communities (PLCs) about three years ago soon after the principal
arrived and was a goal supported by the district. The principal noticed the teachers were
congenial with each other and often planned together, however they lacked collaborating
around agreed upon expectations for student learning, common formative assessments
and strategies to improve every student’s achievement. The principal brought teams of
teachers to similar schools outside the district who were working productively in PLC
serving similar students as GE. After watching teams of teachers working collaboratively
planning instruction, creating formative assessments, analyzing assessments results and
planning interventions, the GE leadership team was ready to go back to their grade level
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teams to duplicate similar practices. The principal assembled a leadership team with
representatives from each grade level that she purposefully selected along with the TOSA
to help implement PLCs throughout the campus. The school schedule provided an early
out day for students once a week, providing time for teachers with collaborative planning
time. Teachers used this common time to meet as a PLC.
The principal holds a philosophy and vision that gives teachers a lot of credit for
what they know and what she describes as what administrators often lose as soon as they
become a site administrator. She trusts her teachers that they know what they are talking
about and creates what she calls a brain trust model at the school. She values the
professional judgment and experience her teachers have. They spend a lot of time
dialoging and collaborating about student learning at staff meetings and during the school
day in the teachers’ lounge. The principal reported that when teachers come in and talk
with her, she listens very closely, and if they make sense, she tries to find the support to
make it happen. She attributes much of the school’s success because she has established a
brain trust with her staff and values their input. This has a created a collaborative culture
where teachers are willing to do more simply because they have a voice at the table and
are valued for the contributions they provide.
Professional and best practices. Throughout the curricular change process, the
principal spent a lot of time and resources on training teachers on best instructional
practices. Odden and Archibald (2009) argue that exemplary schools use evidence from
research, advice from experts and work collaboratively together to significantly improve
student performance. Teachers at GE received specialized training in SDAIE
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instructional strategies, training and coaching on standards-based instruction, core-
instruction, standards alignment and rigor, along with training and coaching on the
writing process. Four areas the school focused on were standards alignment, scholarly
engagement, parental involvement and helping their scholars create a sense of
belongingness to their school. The principal, site coach and intervention teachers spent a
lot of time working with staff at staff meetings on scholarly engagement, checking for
understanding and higher level thinking. Teachers conducted classroom walkthroughs to
analyze the level of scholarly engagement and shared best practices. The principal
provided every teacher with student white boards, markers and erasers to improve the
level of student engagement. Teachers have begun to hold one another more accountable
for implementing strategies they have agreed as a staff.
Additional best practices implemented at GE include the infusion of expository
text within the ELA block of instruction and creating several common formative
assessments to help inform their teaching. Lastly, the principal hired a TOSA with fifty
percent as a intervention TOSA and a fifty percent parent TOSA to create programs and
services for parents on how parents can help support the academic learning in the
classroom. Rather than using a classified staff member as a community liaison, the parent
TOSA could speak to parents from a classroom teacher’s perspective and teach parents
ways they could support their child at home. The parent TOSA position also created a
parent center and trained classroom parent volunteers. The training focused on how
parent volunteers could be used to support academic learning instead of the traditional
filing, organizing, and prepping materials for the teacher. The parent volunteers were
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taught simple, yet specific ways the teacher could use them to help facilitate student
learning in small groups or monitoring independent student work while the teacher
worked with small groups.
The use of the site coach and interventions teachers has had a significant impact
on teachers’ understanding of instructional strategies and the level of core curriculum
they are expected to deliver and have students master. Unfortunately, the principal
reports both the TOSA coach and the bulk of the intervention teachers, along with the
parent TOSA will be cut in the 2010-11 school year.
Comparison of School Resources to the Evidence-Based Model
An evidence-based model approach to improving academic performance for all
students strives to identify a comprehensive set of effective educational elements based
upon proven research strategies necessary to deliver a high-quality comprehensive
instructional program for all students at the school (Odden, 2000; 2003; Odden & Picus,
2008). The evidence based approach employs current educational research to determine
what resources are needed to reach proficiency for every learner. One such framework
that can be used to help identify resource allocations and effective educational strategies
is the Evidence-Based Model outlined by Odden and Picus (2008). The following table is
a comparison of Greenwood Elementary to that of the core resources allocated to a
prototypical elementary school using Odden and Picus’ (2009) Evidence-Based Model.
As illustrated in Table G.2, on average Greenwood Elementary employed far less
resources compared to the prototypical school using the Evidence-Based Model (Odden
& Picus, 2008) throughout their school improvement plan. The majority of the
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discrepancies fall in the area of class size, number of core teachers, instructional coaches,
professional development resources and opportunities, extended support staff to help
struggling students and length of the instructional year and extended school year. The
school provided tutoring during the school day and some afterschool tutoring by having
altering the start time of intervention TOSAs but it still did not provide the level of
support called for by the Evidence-Based Model (Odden and Picus, 2008). As a school
with an 86% socially economically disadvantaged population and a 60% EL student
population, the Evidence-Based Model (Odden & Picus, 2008) would provide nearly an
additional nine full time staff members to provide additional support for struggling
students in the form of tutors, English Language Development (ELD) instruction, and
extended school programs for struggling students. It would also allocate the equivalent of
2.9 full time teachers for summer school, something currently lacking at Greenwood
Elementary.

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Table G.2: Greenwood Elementary Evidence-Based Model Comparison
School Element
Evidence-Based
Model
Current Allocation
Resources
Resources Based on
Prototypical Model
School Size K-5; 432 Students K-6; 700 Students 62 % larger
Class Size
K-3 : 15
4-5 : 25
K & 3: 32
1-2: 24
4-6: 32
K & 3: 113% larger
1-2: 33.3 % larger
4-6: 28 % larger
Instructional Days 190; + 10 PD days
180; + 1 PD & 3
prep.
10 less student days
and 9 less PD days
Kindergarten Full-day K Half-Day Full-day K
Administrative Support
Principal & Other Admin 1.0 FTE 2.0 FTE + 1.62 FTE
School Site Secretary 1.0 FTE 1.0 FTE 1.62 FTE
School Site Clerical 1.0 FTE 1.2 FTE 1.62 FTE
General Personnel Resources
Core Teachers 24 FTE 25 FTE 39.8 FTE
Specialist Teachers 20% of core teachers 0.0 FTE 7.96 FTE
Instructional Facilitators 2.2 FTE 0.5 FTE 3.56 FTE
Extended Support
Tutors
1.0 FTE : 100 low
SES
3.5 FTE
(602 students)
6.02 FTE
Teacher for EL 1.0 FTE : 100 EL
0.0 FTE
(420 students)
4.2 FTE
Extended Day 1.8 FTE 0.5 FTE 2.9 FTE
Summer School 1.8 FTE 0.0 FTE 2.9 FTE
Other Staffing Resources
Substitutes 5% of personnel 5.4% of personnel 5% of personnel
Librarians/Media Specialist 1.0 FTE 1.0 Media clerk FTE 1.62FTE
Instructional Aides 0.0 FTE 0.0FTE 0.0 FTE
Pupil support staff
1.0 FTE : 100 low
SES
0.5 FTE Parent
Liaison (certificated)
0.48 FTE health aid
.5 FTE Guidance
6.02 FTE
Professional Development
$100 per pupil for
other PD expenses
$33,000 $ 70,000
Note: Adapted from School finance: A policy perspective (4
th
ed.) by Odden and Picus (2008), pp. 132-133.
Copyright 2008 by McGraw-Hill. Adapted with permission.
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Summary and Lessons Learned
Greenwood Elementary school’s improvement effort over the past few years has
experienced dramatic results with large gains in student improvement. Over the past four
years, the school’s academic API score has experienced a cumulative growth of 130
points, the highest cumulative growth of all the schools in this study. The school, once
the lowest performing school out of 24 schools in the district is now within the top seven
highest performing schools in the district. This remarkable turnaround occurred in just
three years. The school continues to be in Year 5 of Program Improvement and is facing
severe cut backs in personnel.
Despite these barriers, the principal has worked hard to move her staff away from
a strong textbook driven program focus to a strong standards driven focus. Staff have
identified power standards and unpacked the standards to identify the prior skills needed
to be successful. The standards alignment and identification of power standards has
produced a guaranteed and viable curriculum (Marzano, 2003) where every teacher
expects students to master. As teachers identified and unpacked the power standards, they
created various formative assessments to use on a bi-monthly basis to determine whether
their scholars really earned mastery. This change is helping teachers reflect on the level
of rigor they are engaging students in during their teaching. It is also allowing teachers to
re-think how they use their adopted curriculum series, using their textbook as a tool,
instead of as an omnipotent teaching resource. Teachers received training and coaching
on standards-based instruction, core-instruction, standards alignment and rigor, along
with training and coaching on the writing process. Additionally, teachers focused on
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scholarly engagement and conducted classroom walkthroughs to glean best practices
observed.
Although the school demonstrated the application of all ten evidence-based
strategies outlined within the nine categories in Table G.3, only one was implemented to
the level and intensity supported by research. Table G.3 summarizes Greenwood
Elementary School’s educational reform efforts compared to the ten evidence-based
strategies supported by research and recommended by Odden and Archibald (2009) for
doubling student performance. While most of strategies earned an above average
marking, they did not meet the level of support and intensity that the Evidence-Based
Model (Odden & Picus, 2008) would have provided when implemented appropriately.

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Table G.3: Greenwood Elementary Performance of Evidence-Based Strategies
Evidence-Based Strategy Weak
Below
Average Average
Above
Average Strong
Understanding the Performance Problem and
Challenge

√
Setting Ambitious Goals √
Change the Curriculum Program and Create a
New Instructional Vision

√

Formative Assessments and Data-Based
Decision Making

√

Ongoing, intensive Professional Development √
Using time Efficiently and Effectively √
Extend Learning Opportunities for Struggling
Students

√

Collaborative Culture and Distributed Leadership √
Professional and Best Practices √
Note: Adapted from Doubling student performance:…and finding the resources to do it by Odden and
Archibald (2009). Copyright 2009 by Corwin Press.
Future Considerations
Greenwood Elementary School continues to not meet federal and state benchmark
targets for student achievement as evidenced by their Year 5 PI status. While the school
experienced a 98 point growth in API in 2008 and a 42 point growth in 2009, it dropped
four points in 2010 and continues to serve a majority of underperforming students.
Discussions with the principal indicated there is still much more work and support
necessary to help ensure every student reaches proficiency. The 2010-11 school year
further cut the resources previously allocated to the school, including the loss of the three
TOSA, intervention teachers, the parent TOSA, health clerk, half-time guidance
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counselor and raised class size. While district administrators took nine furlough days in
2009-19, all employees are facing furlough days negotiated for the next two years. All
district employees are facing nine furlough days in 2010-11 and 2011-12. The furlough
days decreased the number of instructional days by five, decreased the number of
planning days for teachers to zero and removed the single professional development
embedded within work calendar. The teachers first day of work for the school year was
the first day of school with students. This made the start of the school year extremely
difficult at the sites. The principal addressed the need for additional resources to provide
lower class sizes throughout the school, more intense and ongoing professional
development, instructional tutors and intervention specialist, and instructional coaches.
Ideally, the principal would like to see a primary and an upper grade coach as she said the
instructional needs and pedagogy differ at these levels. Additional resources are also
needed to offer a targeted afterschool program for struggling students and a summer
school program focusing on reading and math.

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APPENDIX H – REDWOOD ELEMENTARY
Background on School and District
Redwood Elementary School is a Title I, kindergarten through sixth grade school
located in a large sub-urban unified school district within Orange County, California.
During the 2009-10 academic school year, Redwood Elementary reported an enrollment
of 600 students and was one of 22 elementary schools in the district. As a basic-aid
district, the district serves nearly 22,000 students in 22 elementary schools, 4
intermediate schools, 4 comprehensive high schools, 3 alternative schools and 11
preschools. The district spans 58.83 square miles serving three different cities with an
operating budget over $240 million dollars. Table H.1 provides a demographic
comparison and description of the school, district, county and state average.
Table H.1: Redwood Elementary Demographic Comparison 2009-10

%
Hispanic
%
White
%
EL
%
Free/Reduced
Redwood Elementary 97 2 73 100
District Average 41 49 25 47
Orange County Average 44.7 32.8 27.9 42.3
State Average 49.0 27.9 24.2 55.7
Note: Adapted from DataQuest by California Department of Education (2010b).

Redwood Elementary school (RE) opened in September, 1977 at a former middle
school site and became 4
th
- 6
th
grade feeder school for students attending two other
neighborhood K-3 elementary schools. In 2008, the district decided to reconfigure all its
elementary schools into a K-6 structure instead of the past K-3 and 4-6 model. During the
transition, RE housed the feeder school’s fifth and sixth graders while the feeder schools
348
had the luxury of adding a grade level every year until they grew into a K-6 school.
Students in RE attendance boundary had the option of staying in the previous school they
started in through the transition process with many of them opting to stay in their
previous school. Thus, RE had a disproportion amount of six grade students in the 2009-
10 school year, with seven 6
th
grade classrooms, one 5
th
grade, one 4
th
grade, one and a
half 3
rd
grade, one and a half 2
nd
grade, four 1
st
grade, and three kindergarten classrooms.
According to the principal of RE, the second and third grade CST scores “tanked” in
2009-10. She partially attributes that the fact that all of those teachers were fourth, fifth,
and sixth grade teachers their whole career and suddenly had to transition to teach
primary grades during the district’s transition to a K-6 model. The 2010-11 school year
is the first year every elementary school in the district will have fully transitioned into the
K-6 structure.
As illustrated in Figure H.1, RE serves a disproportionately large Hispanic and
Socioeconomically Disadvantaged (SED) student population with ninety-seven percent of
the total population reporting their ethnicity as Hispanic and two percent white. One
hundred percent of the students were identified as SED and enrolled in the free and
reduced meals program (California Department of Education, 2010a). Of the total
population, seventy-three percent were reported as English Learners (EL) and 14 percent
were identified as students with disabilities (SWD). The purpose of this case study is to
identify effective resource allocation and researched based instructional strategies at
Redwood Elementary School.

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Figure H.1 School Demographics Percentage for Redwood Elementary
Source: California Department of Education, 2010

Figure H.2 Redwood Elementary School’s Yearly API Trend

Source: California Department of Education, 2010
At the start of this study, RE was in Year Four of Program Improvement (PI) as
indicated by the 2009 Federal AYP (California Department of Education, 2010a) and has
currently moved in Year 5 of PI. RE is the lowest performing elementary school in the
district and has been the past several years. As indicated in Figure H.2, the school’s State
Annual Performance Indicator (API) score has been inconsistent the past five years. From
2007 to 2010, RE’s API cumulative growth has been 11 points, the lowest of all the
500
550
600
650
700
750
800
850
2006 2007 2008 2009 2010
672
701
715
693
712
97
2
73
100
14
0
20
40
60
80
100
Hispanic White EL SED SWD
Hispanic
White
EL
SED
SWD
350
schools within the sample of this study. In 2009 RE’s API dropped 17 points, more than -
1.75 standard deviation from the county average for elementary schools. In 2010, RE’s
API score grew 21 points but was still lower than its highest API score of 715 in 2008.
The Average Yearly Progress (AYP) report shows a similar trend of school
progress over the past five years. RE has been in Program Improvement (PI) for the past
several years and is currently in Year 5 of PI. Figure H.3 indicates the RE English
Language Arts (ELA) progress has only grown 7.3 points over the course of five years
with his highest ELA proficiency in 2009 of 35.2% proficiency. The Hispanic, SED and
School Wide subgroups ELA scores are nearly identical as demographics of the school
are over 97% Hispanic and SED. In 2010, the ELA proficiency dropped slightly but has
never surpassed a proficiency rate above 35.2%. RE 2010 ELA proficiency is 21.6 points
below the AYP target of 56.8% proficiency.
Figure H.3 Redwood Elementary ELA - Percent Proficient or Above Trend

Source: California Department of Education, 2010

27.9
30.8
32.8
35.2 34.9
0
10
20
30
40
50
60
70
80
90
100
2006 2007 2008 2009 2010
School Wide
Hispanic
EL
SED
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Figure H.4 indicates the math AYP for RE. A slightly different pattern of progress
is seen in math. Over the past five years math proficiency has increased almost 10 points
with the largest percentage of growth occurring in 2007. Math proficiency dropped in
2009 but in 2010 went back up to the 2008 level. EL students have been the lowest
performing subgroup for both ELA and Math proficiency at RE and have experienced the
same up and down growth pattern as the other subgroups and well below the 2010 AYP
target of 58% proficiency.
Figure H.4 Redwood Elementary Math Percent Proficient or Above

Source: California Department of Education, 2010

Key Elements and Themes of the Improvement Process
In 2009, RE had a State ranking of 1, the lowest statewide ranking ranging from
1 to 10. When compared to similar schools, schools with similar demographics and
student mobility rates, it received a similar schools rank of 5, with 10 being the highest
similar schools ranking possible. The improvements efforts of RE over the past 5 years
have failed to produce dramatic results. The school has undergone significant changes
29.2
37
38.9
35.6
38.9
0
10
20
30
40
50
60
70
80
90
100
2006 2007 2008 2009 2010
School Wide
Hispanic
EL
SED
352
over the 5 years, including a new principal and the district changing from a K-2 and 3-6
elementary structure to a K-6 structure. During this change, students in the school’s
boundaries could stay at the school they were previously enrolled in while RE housed the
neighboring schools fourth, fifth and six grade students. Improving student proficiency
for all students should be the primary mission of all schools and can be one of the most
overwhelming challenges any school undertakes (Reeves, 2005). However, research
continues to provide growing evidence that schools have much more control over student
performance and other school related problems than many choose to believe (Darling-
Hammond, 1997; Marzano 2003, Odden 2009, Odden & Archibald, 2009; Schmoker,
1999). The purpose of this section is to review effective research-based educational
elements that have led to improved student learning. Odden and Archibald (2009) outline
ten strategies successful schools and districts implement to dramatically improve student
performance. In addition to the framework and strategies outlined by Odden and
Archibald (2009), the Evidence-Based Model (Odden & Picus, 2008) of resource
allocation will be utilized to examine the alignment between how schools use their
allocated resources along with research-based strategies to improve student performance.
The following is a description of what has occurred at RE within the framework of these
ten strategies.
Understanding the performance problem and challenge. Teachers, principals,
and school leaders must fully understand the performance challenge and have a strong
desire to want to address student performance (Odden & Archibald, 2009). Stakeholders
must feel a sense of urgency to change student performance levels and use this urgency to
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drive the instructional improvement process. The principal at RE arrived four years ago
as the school had the reputation of being the lowest performing school in the district. The
new principal’s previous work, both as a teacher and administrator had only been at the
high school secondary level. The principal acknowledged she had no background or
experience with elementary pedagogy and elementary curriculum. The superintendent
placed a new principal that had the least knowledge and experience with elementary
instruction at the lowest performing school in the district. At the time, the school was an
upper grade school with only third through sixth grade but within in a year the district
changed course, transitioning all elementary schools into a K-6 structure. The principal
indicated she applied for a high school assistant principal position, but was hired as
principal at RE. The principal stated she was nervous about moving to the elementary
level and expressed reluctance to the superintendent. The superintendent assured her she
would be fine and promised he would not send any district office administrators to her
school other than himself and the assistant superintendent of elementary education.
Instead of understanding the performance problems plaguing the lowest
performing school in the district, district administration allowed the other elementary
schools to grow into the additional grade each year, while RE was forced to house the
neighboring upper grade students. This decision resulted in a disproportionate number of
upper grade classrooms at RE and only one classroom each at the primary level.
Furthermore, during the transition process, teachers were not moved to different schools
to create balance of primary and upper grade teachers at a school site. Instead, at RE,
teachers who taught upper grade for 15 years were suddenly forced to teach primary.
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During the transition process, the principal acknowledges many of her teachers at RE
were forced to teach a different grade level each year for the past three years while the
schools that were able to grow into the transition each year did not face this problem to
the same degree. By 2010, the school has made slight improvements, yet it remains the
lowest performing school within the district.
Set ambitious goals. The principal stated her over all vision for the school was to
be out of PI and to have every child reading and performing at grade level by the time
they left school. It was unclear if every teacher at the school shared that same goal and
the sense of urgency to accomplish this goal was difficult to observe. The principal
acknowledged teachers often complained that they have little effect on changing student
results and that many of the students lack the support at home to make them successful.
The school focused their goal on CST performance by tracking students according to
their CST performance band (Far-Below Basic, Below-Basic, Basic, Proficient and
Advanced). Throughout the classrooms and in the school office, CST performance bands
with sticky notes representing individual students were observed. The goal was to move
students to the next CST performance band, especially those students hovering in the
Basic Band. Students knew their performance Band and were encouraged to set a goal to
improve one band. Data walls were created in classrooms correlating to standards taught
and mastered. When students mastered a particular standard in the classroom, it was
noted on the data wall. Students were also given an extrinsic reward by receiving a ticket
for every standard they met with 80% accuracy. Tickets were placed in a large jar in the
office and at the end of the year, a drawing for an IPOD Touch, Target gift card and other
355
incentives were given away. While the ticket jar at the end of the year grew to
accommodate the overwhelming number of tickets representing 80% mastery of a goal, it
did not translate into substantial growth in ELA or math performance on the 2010 CST
results.
Change the curriculum program and create a new instructional vision.
Within the first year at the school, the principal noticed the teachers were 100%
dependent on the Houghton Mifflin (HM) textbook series for ELA. This was also
strongly supported by the district office and district pacing guides that stipulated exactly
where a classroom should be within the HM series at any given time. The principal
reported she noticed her teachers were focused 100% on the HM program but had a hard
time addressing questions on ELA standards. According to the principal, the teachers
were like robots, where one could walk into any classroom and see the teachers would all
be on the same page, and could finish each others’ sentence. The teachers assumed that
since HM was standards-based that they were teaching the standards. When the principal
challenged them with the question, “What standard are you teaching” they could not
answer it, but they could site where the pacing guide told them they should be. By her
second year, the principal’s vision was to change teachers focus from “program” to
standards. On a staff development day early in her second year, the principal conducted a
Bloom’s Taxonomy (taxonomy of thinking levels from lowest to highest using action
verbs) activity with her teachers. She had her teachers do an alignment with CST blue
prints, Bloom’s Taxonomy and the HM series. Her teachers discovered the CST blue
356
prints and standards had a higher thinking level in Bloom’s Taxonomy then what the HM
series was asking students to perform.
Upon this revelation, contrary to the district’s HM programmatic focus, the staff
worked collectively to address this mismatch and focused more on standards. The
principal brought in a consultant to work with the teachers to train them on standard
alignment and standard-based instruction. Another curricular change was in the area of
writing. Data and staff observations revealed writing was a huge deficiency for students
at RE. Thus, last year, the principal brought in another consultant/coach in the area of
writing where teachers implemented new writing strategies and writing rubrics for
analyzing results. Recently, the district adopted the Medallion “add on” component to the
HM series to update is ELA program. The school also used various supplemental
computer-based programs like Accelerated Reader, Accelerated Math, Math Facts in a
Flash (for math fluency), and English in a Flash (English Language Development- ELD
computer based program).
Formative assessments and data-based decision making. A variety of
formative and summative assessments are utilized at RE to support student learning. This
process has taken a few years to become engrained in the school culture and has moved
beyond the district’s focus on summative benchmark assessments. All teachers are
required to give district benchmarks throughout the year. The ELA district benchmarks
are the HM summative test and are administered three times a year. The math district
benchmarks are given three times a year at the end of each trimester. As the staff shifted
their teaching away from HM program fidelity to a stronger standards focus, they found
357
the district benchmarks were not as standards based as they would like and were not as
validating or useful when it came to what they were doing in the classroom. Teachers
were released for “data days” after district benchmark one and two were administered to
work collaboratively along with a site TOSA to analyze the assessment results and
compare it to the standards they already taught. During “data days” teachers compared
student results to target instruction and provide additional support for students not
meeting expectations. Teachers began creating a five question formative assessment for
each standard taught in ELA and used it as a pre-post assessment within a four to five
week cycle. At the third to fourth week, the five question assessment is given. Students
with less than 80% mastery spend the next week with re-teaching and those with 80%
mastery and above receive enrichment opportunities.
Formative assessments became an integral part of the instructional improvement
plan and vision for improvement at RE while staff refine them each year. Data walls
became a focus across the school where teachers were expected to have at least three data
walls in their classroom tracing student performance or goals in a given area throughout
the year. Data walls started off as merely tracking a student’s CST performance and goal
to improve one performance band, but has evolved into various data walls on the
student’s mastery of each standard, their Accelerated Reader level, Accelerated Math
level, sight words, math facts etc. Teachers engaged in classroom walks after school
where they each walked into every classroom to observe the types of student data posted
and tracked in each room. Data walls were created in classrooms correlating to standards
taught and mastered. When students mastered a particular standard in the classroom, it
358
was noted on the data wall. Students were also given an extrinsic reward by receiving a
ticket for every standard they met with 80% accuracy.
Ongoing, intensive professional development. A key strategy to improve
student performance is to improve the knowledge and skills of teacher through providing
ongoing, systematic and intensive professional development (Odden, 2009, Odden &
Archibald, 2009). One of the mandates of being in Program Improvement is that ten
percent of the school’s Title I budget must be set aside for professional development.
Professional development has been a major priority at RE. Professional development
opportunities included the use of consultants, coaching, site and classroom visitations and
collaborative dialogue at staff meetings. Additionally, the 2009-10 staff included two
teachers on special assignment (TOSA) who acted as both instructional coaches (one in
ELA and one in math) and provided intervention support for struggling students.
Teachers previously received professional development in SADIE teaching strategies. A
consultant was used to help the staff move away from strict H.M. program instruction to
a stronger emphasis on standards and rigor. Through the use of Title I funds and district
staff development days, teachers attended two days of training on core instruction and
standards driven instruction prior to the start of the previous school year. The principal
noticed teachers were still having problems grasping the concept and translating the
practice into their classroom so she arranged for her teachers to observe another school in
a different district that had implemented similar strategies and achieved over 50 points
growth in their API within the last two years. Teachers were released as grade level teams
359
along with the two TOSAs and school principal to observe classrooms at the other school
and then came back to reflect and debrief as a team on the best practices observed.
Additionally, teachers noticed their students were struggling with writing and
requested support in this area. The principal hired an outside writing consultant and coach
in the second half of the 2009-10 school year. RE used a “trainer of trainers” model
selecting a few teachers to get trained by the consultant and having those teachers come
back and train teachers at staff meetings. Later the consultant spent more time coaching
and working with each grade level for a day to create rubrics for each writing assignment
and developing writing lessons. The writing consultant/coach is expected to work with
the staff again in 2010-11. What appeared to be lacking was professional development on
how to support teachers who taught upper grades for 15 or more years now having to
teach primary grades emphasizing early literacy skills, phonics, fluency and reading
development.
Using time efficiently and effectively. The principal at RE acknowledged the
school was not maximizing the use of instructional time. As a previous high school
teacher and administrator, she did not understand the importance of having ninety
minutes of uninterrupted time for language arts instruction. She naively thought, time
shouldn’t matter, as long as they have the same number of instructional minutes. The bell
schedule utilized in 2009-10 chopped up instructional blocks into various inconsistent
blocks of time and was more geared toward providing recess and lunch to accommodate
the food service staff. Some grade levels taught for only sixty minutes in the morning and
then went to recess. After listening to her leadership team made up of grade level
360
representatives, she understood their need for longer blocks of uninterrupted time in
language arts and is implementing a new schedule this year.
Extending learning time for struggling students. Providing multiple-extra help
strategies for students struggling to achieve proficiency is a critical component to
improving the learning outcomes for struggling students (Odden, 2009, Odden &
Archibald, 2009). RE offered support to struggling students both during the school day
and after school. As a Title I school in PI, the school was required to provide
supplemental educational services in the form of tutoring to low-income students.
Tutoring was provided to nearly one hundred-thirty students by private outside
companies using district funds for about for one hour a day, one to two days a week.
However the tutoring efforts did not seem to be coordinated with the school, other than to
invite parents to utilize this service. Beyond hosting a parent night, the tutors did not
interact with the school nor classroom teachers to find out how best to support the
individual learner.
During the school day, the school used two full-time TOSAs, a half time ELD
teacher and two full time instructional aides to provide additional support for struggling
students. One TOSA specialized in ELA and trained the ELD teacher and one
instructional aide in various ELA strategies prior to having them work with students. The
other TOSA specialized in math and trained the other instructional aide in a math
program called Momentum Math. The math program included diagnostic assessments
telling the teacher or aide exactly where the student should start and included different
colored books based upon the instructional level prescribed from the diagnostic
361
assessment. The TOSAs, ELD teacher and instructional aides created a team of five
support staff to work with small groups of seven to ten students at a time who were
struggling in ELA or math. The ELA team would push in or pull students out during the
grade level’s ELA instruction time for 20-30 minutes depending upon the grade level,
while the math team would push in or pull students during the grade level’s math time.
Some students received additional support in both ELA and math, while some students
only needed extra support in one subject area. Unfortunately, providing additional
support to students with an extended school year was not an option as the district cut all
summer programs at the elementary level.
Collaborative and distributed leadership. Powerful and effective instructional
systems require strong instructional leadership provided by principals, teachers, and
central office staff collaborating purposefully toward utilizing shared instructional
strategies and using common assessment tools (Odden 2009; Raudenbush, 2009). In
professional literature, this often referred to as creating a collaborative and professional
culture with leadership distributed across the organization to enhance effectiveness
(Odden, 2009; Odden & Archibald, 2009; Raudenbush, 2009) and is the eighth and ninth
step in Odden’s (2009) ten strategies to doubling student performance. RE implemented
professional learning communities (PLCs) about three years ago soon after the principal
arrived and was a goal supported by the district. The principal noticed the teachers were
congenial with each other and often planned together, however they lacked collaborating
around agreed upon expectations for student learning, common formative assessments
and strategies to improve every student’s achievement. The principal brought teams of
362
teachers to similar schools outside the district who were working productively in PLC
serving similar students as RE. After watching teams of teachers working collaboratively
planning instruction, creating formative assessments, analyzing assessments results and
planning interventions, the RE leadership team was ready to go back to their grade level
teams to duplicate similar practices.
RE’s principal assembled a leadership team with representatives from each grade
level that she purposefully selected along with her TOSAs. The leadership team agreed to
conduct a book study on PLC, titled Learning by Doing, a handbook for professional
learning communities at work (Dufour et al., 2006). Unfortunately, the implementation
process was slow initially as teachers were still struggling moving away from a strong
HM program focus to a greater emphasis on standards. However, the teachers made
progress and began creating common formative assessments within their grade level team
and analyzing their results. The school schedule provided an early out day for students
once a week, providing time for teachers with additional time to meet, plan and receive
professional development. Three of the four early out days of the month could be used at
the principal’s discretion, the other week was given to teachers to use for personal
planning. The principal decided to use the early out day options she controlled for staff
meetings and professional development opportunities instead of providing teachers time
to meet as a PLC. Thus, the teachers lacked common time where they could meet as a
PLC. Most grade level teams decided to meet once a week before or after school as a
PLC but the principal reports some grade level teams are better at meeting that others.
The RE staff see the value of collaboration and are beginning to discuss such things as
363
data analysis, differentiation, backward planning and creating common assessments, but
it continues to be sporadically implemented within grade levels. They continue to refine
and tweak the formative assessments created as the ones created previously have lacked
the value they were hoping. They are now attempting to make a five question common
formative assessment for each ELA standard taught monthly.
As the RE staff began trying to implement a collaborative and professional
culture, the principal invited district support staff (district TOSAs and curriculum
specialist) to help teachers create more effective formative assessments and universal
diagnostic screening tools for students. The site leadership team meet at least monthly to
discuss grade level progress and pitfalls and would engage in collaborative dialogue to
address curricular and instructional issues. The leadership team along with the principal
would plan the professional development topics at the staff meetings for the month. In
addition to distributed leadership across the school and district staff, the principal
instituted a parent volunteer program which required families to fulfill twenty parent
volunteer hours. A classroom not used at the site was turned into a parent center and
provided space for parents to work on campus to help teachers with various classroom
needs. The vision of having twenty parent volunteer hours came out of parent meeting the
principal had to discuss the school’s PI status. Parents receive hours for joining PTA,
attending parent conference, Back to School Nights, Open House, photocopying
materials for teachers, cutting and sorting classroom materials, etc. The parent center also
has a data wall in it, similar to the classrooms, tracking each family’s volunteer hours.
364
Professional and best practices. Throughout the curricular change process, the
principal spent a lot of time and resources on training teachers on best instructional
practices. Odden and Archibald (2009) argue that exemplary schools use evidence from
research, advice from experts and work collaboratively together to significantly improve
student performance. Teachers at RE received specialized training in SDAIE instructional
strategies, training and coaching on standards-based instruction, core-instruction,
standards alignment and rigor, training and coaching on the writing process and using
rubrics. Additionally, teachers conducted visits at schools outside the district to glean best
practices observed and engaged in classroom data walks to observe each other’s data
walls. Three areas the school focused on was Core instruction, active engagement
strategies and higher level thinking. The principal, site TOSA and intervention teacher
spent a lot of time working with staff at staff meetings on active engagement strategies,
checking for understanding and higher level thinking. The principal provided every
teacher with student white boards, markers and erasers to improve the level of student
engagement. Teachers have begun to hold one another more accountable for
implementing strategies they have agreed as a staff. The use of the site TOSA and
intervention teacher has had a significant impact on teachers’ understanding of
instructional strategies and the level of core curriculum they are expected to deliver.
Unfortunately, the principal reports both the TOSA and the intervention teacher will be
cut in the 2010-11 school year and teachers will now be faced to carry on this work
without their support.

365
Comparison of School Resources to the Evidence-Based Model
An evidence-based model approach to improving academic performance for all
students strives to identify a comprehensive set of effective educational elements based
upon proven research strategies necessary to deliver a high-quality comprehensive
instructional program for all students at the school (Odden, 2000; 2003; Odden & Picus,
2008). The evidence based approach employs current educational research to determine
what resources are needed to reach proficiency for every learner. One such framework
that can be used to help identify resource allocations and effective educational strategies
is the Evidence-Based Model outlined by Odden and Picus (2008). The following table is
a comparison of Redwood Elementary to that of the core resources allocated to a
prototypical elementary school using Odden and Picus’ (2009) Evidence-Based Model.
As illustrated in Table H.2, on average Redwood Elementary employed far less
resources compared to the prototypical school using the Evidence-Based Model (Odden
& Picus, 2008) throughout their school improvement plan. The majority of the
discrepancies fall in the area of class size, number of core teachers, instructional coaches,
professional development resources and opportunities, extended support staff to help
struggling students and length of the instructional year and extended school year. As a
Title I school in program improvement, the district must provide tutoring for students, but
this is done outside the school day through private companies and often lacks a feedback
loop between the private tutor and the classroom teacher. As a school with 100% socially
economically disadvantaged population and 73% EL student population, the Evidence-
Based Model (Odden & Picus, 2008) would provide over eleven more full time staff
366
members to provide additional support for struggling students in the form of tutors,
English Language Development (ELD) instruction, and extended school programs for
struggling students. It would also allocate the equivalent of 2.5 full time teachers for
summer school, something currently lacking at Redwood Elementary.

367
Table H.2: Redwood Elementary Evidence-Based Model Comparison
School Element
Evidence-Based
Model
Current Allocation
Resources
Resources Based on
Prototypical Model
School Size K-5; 432 Students K-6; 600 Students 39 % larger
Class Size
K-3 : 15
4-5 : 25
K-3: 24
4-6: 36
K-3: 60 % larger
4-6: 44 % larger
Instructional Days 190; + 10 PD days
180; + 2 PD & 4
prep. days
10 less student days
and 8 less PD days
Kindergarten Full-day K
Part-day K (85% of
1-6
th
grade day)
Full-day K
Administrative Support
Principal 1.0 FTE 1.0 FTE 1.39 FTE
School Site Secretary 1.0 FTE 1.0 FTE 1.39 FTE
School Site Clerical 1.0 FTE 0.5 FTE 1.39 FTE
General Personnel Resources
Core Teachers 24 FTE 19.5 FTE 29 FTE
Specialist Teachers 20% of core teachers
2.0 FTE 10.2% of
core teachers
5.8 FTE
Instructional Facilitators 2.2 FTE 1.0 FTE 3.06 FTE
Extended Support
Tutors 1.0 FTE : 100 low SES
1.0 FTE
(600 students)
6.00 FTE
Teacher for EL 1.0 FTE : 100 EL
0.5 FTE
(438 students)
4.38 FTE
Extended Day 1.8 FTE 0.0 FTE 2.50 FTE
Summer School 1.8 FTE 0.0 FTE 2.50 FTE
Other Staffing Resources
Substitutes 5% of personnel 5.4% of personnel 5% of personnel
Librarians/Media Specialist 1.0 FTE 1.0 Media clerk FTE 1.39 FTE
Instructional Aides 0.0 FTE 2.0 FTE 0.0 FTE
Pupil support staff 1.0 FTE : 100 low SES
0.8 FTE Com.
Liaison
.9 FTE health aid
5.94 FTE
Professional Development
$100 per pupil for other
PD expenses-trainers,
conferences, travel etc.
$21,000 $ 60,000
Note: Adapted from School finance: A policy perspective (4
th
ed.) by Odden and Picus (2008), pp. 132-133.
Copyright 2008 by McGraw-Hill. Adapted with permission.
368
Summary and Lessons Learned
Redwood Elementary school’s improvement effort over the past few years has
experienced sporadic results with little overall student improvement. Over the past four
years, the school’s academic API score has experienced a cumulative growth of 11 points
but recently rebounded 21 points from previous decline. The school continues to be the
lowest performing school in the district and is in Year 5 of Program Improvement. The
district changed its elementary school structure from a two tier system of K-3
rd
grade and
4
th
- 6
th
grade schools to a single K-6
th
grade structure. During this transition, the district
allowed other schools to grow into the single tier system, but forced its lowest performing
school to house the local elementary school’s upper grade students resulting in a
disproportionate number of upper grade classrooms changing each year until the
transition was complete. Additionally the district placed a new principal without any
prior elementary experience to its lowest performing school.
Despite these barriers, the principal has worked hard to move her staff away from
a strong textbook driven program focus to a stronger standards driven focus. This change
helped teachers reflect on the level of rigor they are engaging students in during their
teaching. It is also allowing teachers to re-think how they use their adopted curriculum
series, using their textbook as a tool, instead of as an omnipotent teaching resource.
Teachers received training and coaching on standards-based instruction, core-instruction,
standards alignment and rigor, training and coaching on the writing process and using
rubrics. Additionally, teachers conducted visits at schools outside the district to glean best
practices observed and engaged in classroom data walks to observe each other’s data
369
walls. While the school invested in professional development, it seemed at times
fragmented and disjointed; it lacked depth. The principal recognized this and said she that
this year she planned on providing more follow up training on previous professional
development to help teachers go more in depth. While the school transitioned from a 4
th
-
6
th
grade model to a K-6, there was no mention of providing training for upper grade
teachers who were suddenly forced to teach primary. Teachers have begun to place a
stronger emphasis on using data to inform their instruction by implementing and updating
various instructional data walls weekly and tracking student performance. The school has
begun to implement thirty minutes of intervention support during the school day for
struggling students by using grade level teachers, a TOSA, an part time EL teacher and a
intervention teacher but the student to teacher ratio is still too large to have a dramatic
impact on student learning and the amount of time is not sufficient to cover the gaps in
reading, writing, and math. While the school as implemented creating a more
collaborative culture by implementing PLCs, teachers are not provided time to effectively
and efficiently engage as a powerful PLC and are only given two days of professional
development outside the instructional year.

370
Table H.3: Redwood Elementary Performance of Evidence-Based Strategies
Evidence-Based Strategy Weak
Below
Average Average
Above
Average Strong
Understanding the Performance Problem and
Challenge
√

Setting Ambitious Goals √
Change the Curriculum Program and Create a
New Instructional Vision

√

Formative Assessments and Data-Based
Decision Making

√

Ongoing, intensive Professional Development √
Using time Efficiently and Effectively √
Extend Learning Opportunities for Struggling
Students
√

Collaborative Culture and Distributed Leadership √
Professional and Best Practices √
Note: Adapted from Doubling student performance:…and finding the resources to do it by Odden and
Archibald (2009). Copyright 2009 by Corwin Press.

Although the school demonstrated the application of all ten evidence-based
strategies outlined within the nine categories in Table H.3, none were implemented to the
level and intensity supported by research. Table H.3 above summarizes Redwood
Elementary School’s educational reform efforts compared to the ten evidence-based
strategies supported by research and recommended by Odden and Archibald (2009) for
doubling student performance.
Future Considerations
Redwood Elementary School continues to not meet federal and state benchmark
targets for student achievement as evidenced by their Year 5 PI status. While the school
371
experienced a 21 point growth in API for 2010, it continues to serve a majority of
underperforming students and is the lowest performing school in the district. Discussions
with the principal indicated there is still much more work and support necessary to help
ensure every student reaches proficiency. The 2010-11 school year further cut the
resources previously allocated to the school, including the loss of the TOSA, intervention
teacher, bilingual aides and community liaison. Thus far, district employees were not
facing any furlough days, thus allowing the school to maintain the same number of
instructional days as previous years. The principal addressed the need for additional
resources to provide lower class sizes throughout the school, more intense and ongoing
professional development, instructional tutors and intervention specialist, and
instructional coaches. Additional resources are also needed to offer a targeted afterschool
program for struggling students and a summer school program focusing on reading and
math. Already, the principal has instituted a change to the school bell schedule to allow
for longer periods of uninterrupted time.

Abstract (if available)

Abstract This study analyzes effective research-based educational elements that have led to improved student learning. Odden and Archibald (2009) outline ten core elements successful schools and districts implement to dramatically improve student performance. In addition to the framework and strategies outlined by Odden and Archibald (2009), the Evidence-Based Model (Odden & Picus, 2008) of resource allocation was utilized to examine the alignment between how schools use their allocated resources along with research-based strategies to improve student performance. Case studies of five diverse elementary schools include interviews and analysis of student performance data and resource allocations. The findings were compared with a prototypical school using the Evidence Based Model. Although each of the case study schools demonstrated the application of all ten evidence-based strategies, many were not implemented to the level and intensity research suggests is needed to make substantial gains in student performance. The common theme interwoven throughout the most successful schools was the sense of intense urgency and personal responsibility to improve student proficiency for all students. The results of this study support the current research on the effectiveness of setting lofty goals, providing targeted interventions and extended learning opportunities for struggling students coupled with frequent progress monitoring, and a commitment to improving student performance by improving instruction through intense and ongoing professional development.

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Asset Metadata

Creator Pulver, Andrew Phillip (author)

Core Title Aligning educational resources and strategies to improve student learning: effective practices using an evidence-based model

School Rossier School of Education

Degree Doctor of Education

Degree Program Education (Leadership)

Publication Date 03/02/2011

Defense Date 02/02/2011

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag adequacy studies,adequacy study,educational resource allocation,evidence-based model,improving student learning,OAI-PMH Harvest,research based strategies to improve student performance,researched-based strategies

Place Name California (states), Orange (counties)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Picus, Lawrence O. (committee chair), Hentschke, Guilbert C. (committee member), Nelson, John L. (committee member)

Creator Email apulver@losal.org,pulver13@yahoo.com

Permanent Link (DOI) https://doi.org/10.25549/usctheses-m3679

Unique identifier UC1146287

Identifier etd-Pulver-4367 (filename),usctheses-m40 (legacy collection record id),usctheses-c127-442747 (legacy record id),usctheses-m3679 (legacy record id)

Legacy Identifier etd-Pulver-4367.pdf

Dmrecord 442747

Document Type Dissertation

Rights Pulver, Andrew Phillip

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Repository Name Libraries, University of Southern California

Repository Location Los Angeles, California

Repository Email cisadmin@lib.usc.edu