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Allocation of educational resources to improve student learning: case studies of California schools

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ALLOCATION OF EDUCATIONAL RESOURCES
TO IMPROVE STUDENT LEARNING:
CASE STUDIES OF CALIFORNIA SCHOOLS

by

Christopher David Coulter

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

May 2009

Copyright 2009 Christopher David Coulter

ii
DEDICATION

This dissertation is dedicated to my lovely and brilliant wife, Michelle and to our child
that will be born just a couple months after I walk across the stage. I can only hope that
this work makes some small contribution to my own child’s education. Michelle’s
support and occasional nudging has been instrumental in this process.

iii
ACKNOWLEDGMENTS
First, I would like to thank my faculty dissertation chair, Dr. Larry Picus. His
encyclopedic knowledge on this subject is awe inspiring and his guidance has been much
valued. His ability to talk about the complexities of school finance in a way that it makes
sense to his graduate students, policy makers and politicians gives me hope for the future
of education.
Second, I would like to thank my boss and mentor, Linda Evans. More than all
the literature I have read, she has helped me gain an understanding of what it takes to run
an effective school. I hope to be half the principal she is someday.
Third, I would like to thank Michelle Turner Mangan for what I’m sure was a
very uncomfortable flight in her third trimester to come train us all in the data collection
protocol.
I would also like to thank the other three dissertation committee members for their
guidance and time. Dr. Hocevar, we all hope that you are feeling better soon and I
appreciated your insightful questions and comments during the qualifying exam. Dr.
Nelson, thank you for taking time from your professional life to read all these
dissertations and for providing your feedback as a practitioner. Dr. Hentschke, thank
your for coming on board at the eleventh hour to provide your unique insight into this
topic.
Many thanks are in order for the principals of the six schools that are part of this
study. They were all more than generous with their time in both the lengthy interview
process and with my follow-up questions. I hope the process was useful or interesting for

iv
them. In each case the school community is lucky to have them as they are serving the
students well.
Finally, I would like to thank my support group of fellow graduate students and
thematic group members. We pushed each other to get through this even with our careers
and families there to “distract” us.

v
TABLE OF CONTENTS

DEDICATION ii

ACKNOWLEDGMENTS iii

LIST OF TABLES viii

LIST OF FIGURES x

ABSTRACT xii

CHAPTER 1 – Introduction 1
The Current State of California School Finance and Student Performance. 1
School Finance History 3
National Trends 3
California School Finance 4
A National Shift Toward “Adequacy” 5
“Costing Out” an Adequate Level of Funding: Four Models 6
Statement of the Problem 8
Purpose of the Study 9
Importance of the Study 10
Limitations, Delimitations and Assumptions 11
Definitions 13

CHAPTER 2 – Literature Review 19
History of Compensatory Education and Education Financing 20
National trends: From Segregation to Adequacy 20
A trend toward Adequacy 22
History of School Funding in California 24
Current State of Education in California 27
Resource Use 29
Historical trends 30
Where has the money gone? 31
Why has student achievement not improved despite increased funding? 33
What happens when funding systems are reformed? 36
Resource use at the school level 37
Can resources be effectively reallocated? 38
A model to track resources by educational strategies 39
Evidence Based Model 44
Instructional Improvement 50
Closing the Achievement gap 54
Conclusion 55

vi
CHAPTER 3 – Methodology 58
Sample Selection 60
Data Analysis 65

CHAPTER 4 – Findings 67
Summary of Study Schools’ Characteristics and Performance 67
Study School Characteristics and Demographics 68
Performance Data of Study Schools 69
What are the Current Instructional Improvement Strategies at the School Level? 82
Leadership 83
Data used to inform practice 84
Collaboration and time for regular collaboration 84
Intervention programs 85
Positive School Culture 86
How are actual resource patterns aligned with or different from the resource use
strategies in the Evidence Based Model? 87
How are the resources used to implement the school’s improvement plan? 96
School Site Leadership 96
Technology resources to analyze data 98
Collaboration Time 98
Intervention Programs to Access a Rigorous Curriculum 99
Improving school culture 100
How does the availability of resources affect the development of the improvement
plan? 101

CHAPTER 5 – Discussion 103
Summary of Findings 104
High Expectations 104
Timely small group support to help struggling students 105
Using data to make decisions and inform practice 106
Distributed Leadership 107
Focus on the core subjects and protection of instructional time 107
Continual professional development and instructional coaches 108
Implications for Practice 109
Implications for Policy Makers 111
Recommendations for future research 113

REFERENCES 116

APPENDIX A – Site Permission Letter 121
APPENDIX B – Determination of NOT Human Subjects Research 122
APPENDIX C – Open-Ended Data Collection Protocol - School Sites 123
APPENDIX D – Data Collection Protocol 126

vii
APPENDIX E – Data Collection Codebook 136
APPENDIX F – Case Studies 146

viii
LIST OF TABLES

Table 2.1: Recommendations for Adequate Resources for Prototypical Elementary,
Middle and High Schools 47

Table 3.1: School Demographic and Achievement Data for Sample Schools. 62
Table 3.2: School Resource Indicators 64
Table 3.3: School Expenditure Structure 64
Table 4.1 – Characteristics of Study Schools 68
Table 4.2 – Core and Specialist Teachers – Actual vs. EBM 89
Table 4.3 –Tutors, Extended Day and Summer School Programs – Actual vs. EBM 90
Table 4.4 – EL, Special Education, Vocation and Gifted Programs – Actual vs. EBM 91
Table 4.5 – Support staff, Librarians and Secretaries – Actual vs. EBM 92
Table 4.6 – Substitutes and Professional Development – Actual vs. EBM 94
Table 4.7 – Administration and Instructional Facilitators – Actual vs. EBM 95
Table F1 – JWHS API Scores 2000 to 2008 including subgroups 147
Table F2 – CAHSEE first attempt pass rates by subgroup 2004 – 2008 150
Table F3 Comparison of actual resources at JWHS to Evidence Based Model 158
Table F4 – KOHS API Scores 2000 to 2008 including subgroups 164
Table F5 – KOHS CAHSEE first attempt pass rates by subgroup 2005 – 2008 166
Table F6 – Comparison of actual resources at KOHS to Evidence Based Model 174
Table F7 – MLHS API Scores 2000 to 2008 including subgroups 180
Table F8 – MLHS CAHSEE first attempt pass rates by subgroup 2005 – 2008 182
Table F9 – Comparison of actual resources at MLHS to Evidence Based Model 188
Table F10 – PMHS API Scores 2000 to 2008 including subgroups 193

ix
Table F11 – PMHS CAHSEE first attempt pass rates by subgroup 2005 – 2008 196
Table F12 – Comparison of actual resources at PMHS to Evidence Based Model 202
Table F13 – SRHS API Scores 2000 to 2008 including subgroups 207
Table F14 – SRHS CAHSEE first attempt pass rates by subgroup 2005 – 2008 210
Table F15 – Comparison of actual resources at SRHS to Evidence Based Model 215
Table F16 – VBHS API Scores 2000 to 2008 including subgroups 220
Table F17 – VBHS CAHSEE first attempt pass rates by subgroup 2005 – 2008 222
Table F18 – Comparison of actual resources at VBHS to Evidence Based Model 229

x
LIST OF FIGURES

Figure 2.1: California School Funding Sources 28
Figure 2.2 National School District Expenditure Averages 31
Figure 4.1 – API Scores 2000-2008 for All Students 69
Figure 4.2 – API Scores, 2000-2008 for Hispanic/Latino Students 70
Figure 4.3 - API Scores, 2000-2008 for African American Students 71
Figure 4.4 – The Closing of the API Gap between White and Hispanic Students 72
Figure 4.5 – English CST Scores for All Schools, 2003-2008 73
Figure 4.6 – History/Social Science CST Scores for All Schools, 2003-2008 74
Figure 4.7 - Science CST Scores for All Schools, 2003-2008 75
Figure 4.8 – Math CST Scores for All Schools, 2003-2008 76
Figure 4.9 – Percent of Students Tested in Geometry, Algebra II or Summative Math 76
Figure 4.10 – CST Math Scores Only for Students in Algebra I or Pre-Algebra I 77
Figure 4.11 – CST Math Scores Only for Students in Geometry or Higher 78
Figure 4.12 – Statewide CST Math Score trend, Grades 2-11, 2003-2008 79
Figure 4.13 – CAHSEE Math –Percent of Students Passing in Tenth Grade, 2005-08 80
Figure 4.14 - CAHSEE English –Percent of Students Passing in Tenth Grade, 2005-08 81
Figure 4.15 – Core Course Offerings – Percent Remedial, Regular and Advanced 82
Figure 5.1 – Statewide CST Math Score trend, Grades 2-11, 2003-2008 114
Figure F1 – JWHS API Scores 2000 to 2008 including subgroups 148
Figure F2 – JWHS CST Scores 2003-2008, percent Proficient or Advanced 149
Figure F3 – CST Scores for students in Geometry and above vs. Algebra I or lower 151

xi
Figure F4 – JWHS Course Offering Levels by Subject Area 152
Figure F5 – KOHS API Scores 2000 to 2008 including subgroups 165
Figure F 7 – KOHS Course Offering Levels by Subject Area 168
Figure F8 – CST Scores for students in Geometry and above vs. Algebra I or lower 169
Figure F9 – MLHS API Scores 2000 to 2008 including subgroups 180
Figure F10 – MLHS CST Scores 2003-2008, percent Proficient or Advanced 181
Figure F11 – MLHS Course Offering Levels by Subject Area 183
Figure F12 – CST Scores for students in Geometry and above vs. Algebra I or lower 184
Figure F13 – PMHS API Scores 2000 to 2008 including subgroups 194
Figure F14 – PMHS CST Scores 2003-2008, percent Proficient or Advanced 195
Figure F15 – PMHS Course Offering Levels by Subject Area 197
Figure F16 – CST Scores for students in Geometry and above vs. Algebra I or lower 198
Figure F17 – SRHS API Scores 2000 to 2008 including subgroups 208
Figure F18 – SRHS CST Scores 2003-2008, percent Proficient or Advanced 209
Figure F19 – CST Scores for students in Geometry and above vs. Algebra I or lower 210
Figure F20 – SRHS Course Offering Levels by Subject Area 211
Figure F21 – VBHS API Scores 2000 to 2008 including subgroups 220
Figure F22 – VBHS CST Scores 2003-2008, percent Proficient or Advanced 221
Figure F23 – CST Scores for students in Geometry and above vs. Algebra I or lower 222
Figure F24 – VBHS Course Offering Levels by Subject Area 223

xii
ABSTRACT

This study used a purposeful sample of six southern California high schools with
demographic characteristics of at least 20% African American, Hispanic or low SES
students that are outperforming similar schools to determine the instructional strategies
and resource use patterns used during their improvement process. Case studies, which
include interview data, performance data and information on school level resource use,
were conducted, and the information was analyzed using the data entry system created by
Lawrence O. Picus and Associates which is aligned with the expenditure structure model
created by Odden, et al (2003). The Evidence Based Model, developed by Odden and
Picus (2008), which identifies the elements of a school-wide instructional program that
research has shown to be effective in improving student performance, was used as the
framework for analyzing the resource use patterns of the study schools. The findings
indicate that although the resources available to the study schools were significantly
fewer than what the Evidence Based Model suggests, the improvement strategies showed
many commonalities to those suggested in the body of literature on school improvement.
Analysis of the case studies indicates that the schools used the following improvement
strategies that are commonly seen in the literature on effective schools: high expectations
for students, timely small group support, the use of data to make decisions and inform
practice, distributed leadership that empowers teachers to improve student achievement,
the protection of instructional time including maximizing the time spent on the core
subject areas and continual professional development with coaches as a key strategy.
Implications for practice and policy are discussed.

1
CHAPTER 1 – Introduction
This study examines how six diverse California high schools have used their
resources to promote student achievement and contributes to a growing body of research
on how resources are used at the school level to efficiently improve student performance.
To understand the complexity of school financing in California, it is helpful to understand
how California compares nationally and how this came to be. After a glance at the
current state of affairs in California, this chapter will provide a brief history of school
funding in the United States and California in particular. The history section ends with
an explanation of key court decisions that led to the move toward adequacy and the more
recent research on costing out an adequate education. After laying out this background
information, the chapter will move to a statement of the problem this research will
address as well as the purpose and importance of the study. The limitation, delimitations
and needed definitions of the study will conclude this chapter.
The Current State of California School Finance and Student Performance.
For the 2005-06 school year, California ranked 29
th
nationally in per-pupil
expenditures at $8,486 per pupil (Edsource, 2008b). The national average the same year
was $9,100 per-pupil. For the same school year, California had the highest average
teacher salaries at $59,825 per year while the national average was $49,026 per year
(EdSource, 2008b). California ranked near the bottom nationally in terms of school
staffing in 2005-06 at 72% of the national average of school staff members (EdSource,
2008b).

2
Despite lower resource levels compared to the national average, California is
successfully educating an increasingly diverse population, including approximately 1.5
million English Learners (Mockler, 2007). Between 1980 and 2005, California’s student
population has changed dramatically. While white students have decreased as a
percentage of all students, the Latino population has increased by 187%. Latino students
now comprise almost half of California’s student population. The African American
population has increased by 24% and the Asian American population has increased by
133% (Mockler, 2007). In short, California’s student population is an extremely diverse
one with many students learning English as their second language.
When examining student performance trends, it is important to note that
California has adopted rigorous content standards and measures of student achievement.
In 1999, California adopted the Academic Performance Index (API) as its accountability
system. A school’s API reflects student performance on the state content standards that
were developed in 1998 and ranks all schools into ten deciles (Mockler, 2007). From
1999 to 2006 all schools improved, but the schools in the lowest deciles improved the
most. “Our lowest-performing elementary schools in 1999 grew 209 points by 2006.
The middle and 9
th
deciles grew by 141 points, respectively. Put simply, the lowest-
performing elementary schools in 2006 scored higher than where the 5
th
decile or
medium schools scored just seven years earlier” (Mockler, 2007, p. 3). Perhaps more
impressive is that traditionally lower achieving groups of students are improving
performance and showing greater gains than White or Asian students. The number of
Latino students who are proficient or above in Language Arts has increased by 45%.

3
African American students have improved on the same measure by 41% and
economically disadvantaged students have improved 45% (Mockler, 2007). Similar
impressive gains are evident in Math and Science with more disadvantaged students
taking more advanced classes and doing well (Mockler, 2007).
School Finance History National Trends
In the early 1900’s U.S. schools received 80% of their funding from local sources.
Between the two World Wars, that percentage fell to only 50%. These local sources of
revenue generally come from property taxes raised by local governments. Today, only
40% of school funding comes from local sources while the other 60% comes from the
state and federal government, the source of which is more often income and sales taxes
rather than property taxes (Hanushek, 2006). As the state share of funding education
increases, the number of regulatory demands placed on schools and districts tends to also
increase (Hanushek, 2006), especially in California where state funds often come in the
form of categorical programs (Duncombe & Yinger, 2007).
In the 1920s, states shifted from providing equal grants to districts based solely on
the number students to providing a minimum “foundation level” of funding from tax
revenues with the state providing additional funds to poorer districts (Rebell, 2007).
Very 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).

4
California School Finance
In California, the 1970s saw the collision of two major events in the life of school
finance. The Serrano v. Priest Supreme Court decision mandated equalization of funding
across districts to eliminate wide disparities in educational access (Lindseth, 2006). The
state’s response was to institute “revenue limits” that capped the amount of revenue
districts could bring in from property taxes (EdSource 2008a). Meanwhile, voters
approved Proposition 13 which drastically cut and capped property taxes statewide
(EdSource, 2008a). Because schools were stripped of a large portion of their revenues
after the passage of Proposition 13, the state had to increase its share of funding schools
as a sort of bail out. The state became the primary source of funding schools in
California for the first time (EdSource, 2008a). By 1983, “the state had assumed control
of approximately 80% of total school funding, leaving schools vulnerable to the volatility
of the state’s sales and income-tax revenue streams” (Kirst, 2007, p.1). Because the state
budgeting process is a political one that is dependent on the ups and downs of the
economy, school funding was volatile. In 1988, voters stepped in again to pass
Proposition 98 which, in effect, earmarked 40% of the states general fund for public
education (Kirst, 2007). According to Kirst (2007),
Voter initiatives in California have put the state finance system in a double blind.
Proposition 13 caps the local property tax and has virtually eliminated tax
increases based on assessed valuation. Other states have enacted variations of
Proposition 13, but none has created an education funding system that sets both a
de facto floor and ceiling on total state and local property tax allocation as does
the combination of Proposition 13 and Proposition 98. (p. 2)

5
A National Shift Toward “Adequacy”
In 1969 the federal Supreme Court ruled in Rodriguez v San Antonio that it was
up to the states to decide cases on education funding. The Serrano decision was only one
of a series of court cases that challenged the funding systems in states across the country
following the Rodriguez decision (Hanushek, 2006; Kirst, 1977). Though outcomes
varied widely, generally, the lawsuits led to more equal funding systems (Ladd, Chalk &
Hansen, 1999). In the 1990s, the courts began to look at the variation in student
outcomes despite the seemingly equal levels of funding. As the standards movement
gained momentum and achievement gaps between White/Asian students and
Hispanic/Black students became more glaring, the movement toward funding equality
turned into a movement toward educational adequacy (Hanushek, 2006). Over the last 17
years, plaintiffs in more than 25 states filed suits that the state’s funding model was not
providing an adequate education in order for all of its students to meet the state’s goals of
proficiency. The plaintiffs prevailed in 75% of the cases.
There were two main reasons for this shift toward adequacy. First, was the
question of whether or not per-pupil funding differences led to different opportunities and
results. Second, the standards movement turned the attention from inputs to results or
outcomes (Odden, 2003). The No Child Left Behind Act (NCLB) added mandates,
increasingly higher expectations and the hammer of potentially losing Title I money if
schools do not make “Adequate Yearly Progress” to the standards movement (EdSource,
2007).

6
“Costing Out” an Adequate Level of Funding: Four Models
The next logical step was to determine exactly how much it costs to provide an
adequate education to the wide variety of students in public school systems in a given
state. “Costing-out” studies attempted to answer this question. According to Rebell
(2007),
The judicial focus on the level of funding needed to provide an adequate
education, together with the nationwide movement to raise educational standards,
has resulted in an explosion of “costing-out” studies that aim to determine
objectively the amount of funding that is actually needed to provide all students
with a meaningful opportunity for an adequate education (p. 1304).

Four models have emerged for conducting costing-out studies. Jay Chambers and
Thomas Parrish were the first to explore what it would cost for a district to meet its goals.
In the 1980s they established the “Resource Cost Model” (RCM) which later evolved into
the “professional judgment” model. The professional judgment model brings together a
panel of experts to design an educational program that would fulfill the established goals
of the state education system. The panel identifies the resources required including any
extra resources needed to educate disadvantaged students. Once the needed inputs are
established by the panel, researchers use economic modeling approaches to determine the
cost of the given inputs (Odden, 2003; Rebell, 2007).
Recently, as part of the “Getting Down To Facts” studies in California, Chambers,
Levin and Delancey (2007) used the professional judgment approach with two different
panels to develop a per-pupil cost of education in California schools. The panels
developed estimates for elementary, middle and high schools in urban, rural and suburban
areas. The two panels came up with different estimates with wide variation in some

7
areas. The statewide average cost of producing an adequate education ranged from
$11,094 to $12,365 per pupil among the two panels (Chambers, et al., 2007).
Jon Sonstelie (2007) used a different approach to the professional judgment panel
by asking study participants to cost-out an adequate education using budget simulations
with a variety of participants. He determined that the average cost to adequately fund
schools in California would be $9,533 with two variables to adjust local costs. The two
variables are percent of students in poverty and local salary costs (Sonstelie, 2007).
The second approach used in costing-out studies is referred to as the “successful
school district” method. 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 adequate education (Rebell, 2007). Typically, the districts identified are non-
urban, homogeneous schools that spend below the state average. This approach does not
effectively account for the challenges that urban districts face (Odden, 2003).
A third model that has emerged is the use of cost function studies. 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 is a much more rigorous analysis than the successful schools approach
and it goes a step further by trying to determine costs for different student groups. Cost
function analyses require copious amounts of data on student performance, student
characteristics and school expenditures per-pupil (Rebell, 2007). Neither the cost

8
function analysis studies nor the successful school district methods address what
strategies should be used to achieve the desired results (Odden, 2003).
Jennifer Imazeki (2007) performed cost-function studies as part of the “Getting
Down to Facts” studies. Using the cost-function model she determined that the average
per-pupil cost to provide an adequate education in California is $8,268 with a minimum
base of $5,832 up to a high of $23,818 for disadvantaged students. Imazeki (2007) also
performed a production function analysis which estimates the effect of spending on
outcomes which concluded that an additional $1.5 trillion is needed in California schools.
The final method, and the one used to inform this study, is the Evidence Based
Model, which Rebell (2007) refers to as expert judgment studies. The Evidence Based
Model uses empirical research to identify the most effective components of a quality,
comprehensive instructional program and then determines the cost of implementing the
program. The research basis for the Evidence Based Model comes from randomized
experimental studies, studies with other statistically sound controls and best practices
research (Odden & Picus, 2008; Rebell, 2007). The most significant advantage of the
Evidence Based Model over the other models discussed above is that, beyond a simple
dollar figure, it identifies proven educational strategies to guide schools and districts in
using their resources more effectively and efficiently (Odden, 2003).
Statement of the Problem
The four approaches to costing-out an adequate level of funding to achieve a
state’s goals for educational attainment for all students have significant differences in
terms of the methodology and the assumptions used by the various practitioners and

9
proponents of each approach. As these models are all relatively new, the proponents of
each approach are open and honest about the advantages and deficiencies of each (Rebell,
2007). The dialogue has been a healthy one in working to improve resource allocation
strategies to improve student achievement.
Each costing-out strategy has been employed in different states around the
country. None can claim it is the dominant method for determining adequate funding.
There is not yet any definitive research on which strategy is most effective or that one is
more effective than another. Furthermore, there is very little research on school-level
resource use. The analyses outlined above are performed at the district or state level. If
the research based practices and comprehensive school designs recommended by the
Evidence Based Model are truly the most effective in raising student achievement, school
level research analyzing resource use patterns in a variety of schools is needed.
Purpose of the Study
This study examines school level data in schools with significant numbers of
disadvantaged students (African American, Hispanic, or from low socio-economic
families) that are achieving at high levels compared to similar schools in the state. Using
the Evidence Based Model, the resource allocation patterns are analyzed and compared.
This analysis of school level data contributes to the discussion of which costing-out study
can best be used to improve student achievement and adds to the body of knowledge on
how successful schools are actually using their resources. The following research
questions guided this study:

10
1. What are the current instructional improvement strategies at the school level?
2. How are actual resource patterns aligned with or different from the resource use
strategies in the Evidence Based Model?
3. How are resources used to implement the school’s improvement plan?
4. How does the availability of resources affect the development of the improvement
plan?
Importance of the Study
Given California’s low ranking in terms of per-pupil expenditure and its high cost
of living, resources must be used very efficiently in order to maximize student
achievement. This study examines how successful schools that face demographic
challenges are using their resources to improve student achievement. The patterns that
emerged and the detailed case studies of successful schools help inform how schools in
California can more efficiently use their limited resources to improve their instructional
strategies and target resources to that end. In addition, there are implications for
policymakers who are working to determine how to better utilize California’s limited
resources in the complex educational finance arena.
By using the Evidence Based Model as the theoretical framework for the study,
professionals in education and policy makers can better understand how successful high
schools in California are actually using their resources in comparison to proven research
strategies. In identifying areas where there are commonalities or discrepancies with the
Evidence Based Model recommendations and what schools are actually doing to improve
student achievement, this study contributes to the active discussion in the literature on

11
how best to fund education to achieve state goals for students. With nine other similar
studies being completed at the same time at the University of Southern California, this
research adds a wealth of information about school level resource use at the school level.
Limitations, Delimitations and Assumptions
For this study, six high schools were chosen based on data obtained from the
California Department of Education (CDE). The six schools have student body
compositions of at least 20% African American and/or Hispanic students with high
Academic Performance Index (API) scores and similar school ranks of at least 8 out of
10. One day visits to the school were conducted in order to collect both quantitative and
qualitative data from the Principal and other key staff members in regards to how the
school is using their resources in terms of time, money and personnel. The quantitative
data were added to the database developed by Lawerence O. Picus and Associates to
analyze how school resources compare to the Evidence Based Model. The qualitative
data were used to develop detailed case studies of each school site (see appendix F). The
analysis in chapter four compares the resource allocation patterns of the schools to each
other and to the Evidence Based Model and identifies common and/or innovative
strategies that the schools used to improve student achievement.
There are three limitations of this study. First, given the nature of the study, it is
not possible to impose a random experimental design. Given the complexity of
California schools, it would be impossible and impractical to randomly assign resources
and strategies to one school or a group of schools and hold others as a control group.
Second, because of the small sample size of only six schools and the geographic

12
considerations of the sample, the ability to generalize the results of the study is limited.
Because this study is part of a larger group of similar studies in California and given the
very limited number of school level resource allocation studies in the literature to date,
the study still has important implications and contributes to the body of literature on the
Evidence Based Model. Finally, given the limited resources in terms of per-pupil
spending in California, it may prove difficult to provide meaningful comparisons to the
Evidence Based Model which calls for significantly more resources. Nonetheless, by
studying higher performing schools that are promoting high achievement of
disadvantaged students, the patterns that emerged enhance the body of research used by
the Evidence Based Model.
There are three delimitations of the study. The research conducted did not
evaluate the effectiveness of the strategies that emerged during the course of the
qualitative data gathering. It was assumed that the strategies implemented were
implemented consistently and effectively as described. Second, given the limited
resources of the researcher and the stated intent to study schools in California, the sample
schools are limited geographically to southern California. Although there were very few
schools in either central or northern California that met the conditions of the sample, it is
important to note that those schools were eliminated from consideration due to travel
constraints of the researcher. Finally, the analysis of the data uses only the Evidence
Based Model for comparison and discussion purposes. The other three costing-out
strategies discussed above were not be used in the analysis portion of the study.

13
It is assumed that during the course of the interviews and quantitative data
gathering that the principals and school staff provided honest, accurate information
regarding school site resource allocation. It was also assumed that any documentation
provided or analyzed was also an accurate reflection of how the school allocates
resources.
Definitions
1. (Educational) Adequacy: Student academic performance expectations as determined
by a state’s curriculum standards, NCLB, and measured by a state’s testing system
with a goal that all but the most severely disabled students will achieve at proficient
or advanced levels – and the funding to support necessary resources to achieve these
outcomes (Odden & Picus, 2008).
2. Adequate Yearly Progress: “A goal of the 2001 federal law No Child Left Behind
(NCLB) that requires schools and districts to measure and report students’ annual
progress toward proficiency in English/language arts and mathematics by 2013-14.
Progress is based on whether the school or district met its Annual Measurable
Objectives and demonstrated 95% participation on standardized tests, achieved its
target on the Academic Performance Index and, for high schools, met target
graduation rates” (Ed-Data, 2008).
3. Annual Measurable Objective (AMO): Target percentage of students whose state
test results identify them as proficient or advanced each year as determined by
NCLB.

14
4. Average Daily Attendance: “The total number of days of student attendance divided
by the total number of days in the regular school year. A student attending every
school day would equal one ADA. Generally, ADA is lower than enrollment due to
such factors as transience, dropouts, and illness. A school district's revenue limit
income is based on its ADA. The state collects ADA counts at the district but not the
school level” (Ed-Data, 2008).
5. California Basic Educational Data System (CBEDS): “An annual collection of basic
student and staff data that; includes student enrollment, graduates, dropouts, course
enrollment, enrollment in alternative education, gifted and talented education, and
more. Statistical information about schools, teachers, and students that is collected
from each public school on a given day in October” (Ed-Data, 2008).
6. California Standards Tests: “Tests in English/language arts and mathematics in
grades 2-11, science in grades 5 and 9-11, and history/social science in grades 8, 10
and 11 based on California's academic content standards. This is the core of
California's statewide Standardized Testing and Reporting Program (STAR)” (Ed-
Data, 2008).
7. Categorical Fund(s): State and federal funds allocated in addition to revenue limit
income and designated for students with special and specific needs, such as
disabilities, and for special purposes and programs.
8. Certificated/Credentialed Employees: Also referred to as “licensed” employees –
staff and faculty holding appropriate state credentials.

15
9. Coaching: “refers to opportunities for active learning that are often ongoing in nature
and assist teachers in active learning” (Odden et al, 2002, p. 69).
10. Comprehensive School Reform: scientifically based and effective practice
improvements implemented school-wide and covering all aspects of a school’s
operations to provide a coherent approach to significant school improvement,
especially for low-achieving children (U.S. Department of Education, 2004).
11. Cost Function approach: Econometric approach to identifying costs associated with
achieving desired/required student achievement outcomes.
12. Cost Function: Cost of inputs that result in given outcomes.
13. Costs: expenditures incurred to produce a certain outcome (Odden et al, 2002, p. 73)
14. Effective Professional Development: “Professional development that produces
change in teachers’ classroom-based instructional practice, which can be linked to
improvements in student learning” (Odden, A., Archibald, S., Fermanich, M. &
Gallagher, H.A., 2002, p. 53).
15. Encroachment: Situation in which a required or restricted program costs more to
operate than funding that is provided, thereby requiring use of unrestricted funds
intended for all students to support programs that benefit specific populations of
students.
16. English Learner: Most current designation for students not yet sufficiently proficient
to access and learn from the regular instructional programs offered at the school.
English language proficiency is assessed annually.
17. Equity: Equalization of funding across per-pupil expenditures.

16
18. Evidence Based model: School instructional improvement design grounded in
scientifically based research and widely documented effective practice based on
resource allocation associated with achieving desired/required student achievement
outcomes.
19. Expenditures: what is spent (Odden et al, 2002, p. 73)
20. Expert Judgment approach: Use of a panel of educators, specialists, and
administrators to determine resources necessary to achieve desired/required student
achievement outcomes.
21. Free/Reduced Price Meals: Program to provide food to low-income students.
22. General Fund: As an accounting term, General Fund refers to all general use
expenditures not required or permitted by law to be accounted for in a separate
accounting category.
23. No Child Left Behind: “The 2001 reauthorization of the federal Elementary and
Secondary Education Act (ESEA) that places comprehensive accountability
requirements on all states, with increasing sanctions for schools and districts that do
not make adequate yearly progress toward proficiency in English/language arts and
mathematics or that fail to test 95% of all students and all significant subgroups. In
California, those sanctions currently apply only to schools and districts that accept
Title I funding” (Ed-Data, 2008).
24. Production Function: Input factors that result in given outcomes.

17
25. Professional Learning Community: (Group of) school staff members improving
instruction by working collaboratively around a common vision for student
achievement and using data to inform shared decision making regarding both student
and professional learning necessities. (North Central Regional Educational
Laboratory)
26. Proposition (Prop) 13: An initiative amendment to the California Constitution passed
in June 1978 restricting property taxes to no more than 1% of "full cash value."
“Proposition 13 also defines assessed value and requires a two-thirds vote to change
existing or levy new special purpose taxes” (Ed-Data, 2008).
27. Redesignated Fluent English Proficient (RFEP): Students who meet language
proficiency and academic achievement criteria to change their English language
proficiency classification from English Learner (EL) to English Proficient (RFEP).
28. Socioeconomically Disadvantaged: Students who participate in the free/reduced
price lunch program.
29. Special Education: Identification processes, individual education plans (IEPs) and
programs to meet educational needs of emotionally, physically, and learning disabled
students – required by federal law through age 21.
30. Successful Schools approach: Identification of programs, strategies, and resources
used in “successful schools” with the intention of transferring them to other schools
to achieve desired/required student achievement outcomes.
31. Title I: Federal funds for “educationally disadvantaged children” (Ed-Data, 2008)
from the Educational Consolidation and Improvement Act.

18
32. Training: “refers to teachers sitting and getting training of any length, from one-day
workshops to three-week summer institutes” (Odden et al, 2002, p. 69).
Chapter two provides a discussion of the relevant literature for this study in the areas
of school resource use, educational adequacy, the Evidence Based Model and school
improvement strategies. Chapter three provides a description of the methodology used in
this study. Chapter four presents the findings from the case studies and quantitative data
on school resources. Finally, Chapter five presents a discussion on the findings and
recommendations for future research.

19
CHAPTER 2 – Literature Review

This chapter details the most recent and some historical information available in
the literature in several areas related to the underlying ideas in this study. The first
section provides a review of historical trends in education financing nationally and
specifically in California including a brief history of the rise of the educational adequacy
movement in both the literature and the judicial system. The second section synthesizes a
great deal of research on how schools and districts allocate and use resources including
discussions on why researchers have struggled to analyze school resource use leading to
the holes in the literature that this study intends to help fill related to how resources can
be used more efficiently. The next section focuses on a model to track resources at the
school level (Odden, Archibald, Fermanich & Gross, 2003) which will be the basis of the
next chapter on the methodology of the study, and also includes an explanation of the
Evidence Based Model developed by Odden and Picus (2008) as a means to cost out the
resources required to fund an adequate education based on the latest research on what
works in schools. The next section provides a brief overview of several meta-analyses on
school level factors that contribute to improvements in student achievement. Finally, the
last section of this review of relevant literature explores research on effective strategies in
closing the achievement gap between disadvantaged (Hispanic, African American and
low socio-economic status) students and more advantaged White and Asian students.

20
History of Compensatory Education and Education Financing
This section begins with an exploration of key historical events and court
decisions that transformed the education system in the United States from one plagued by
segregation and vast inequalities to one based on equity and most recently the rise of the
adequacy movement. After the discussion on national trends, the remainder of this
section will focus on California’s complex system for funding schools.
National trends: From Segregation to Adequacy
The federal government began its involvement in compensatory education with
the passage of the Elementary and Secondary Education Act (ESEA) in 1965 (Odden &
Picus, 2008). Title I of ESEA provides funds specifically to low income students. The
latest of many reauthorizations of ESEA was passed in 2001, known as the No Child Left
Behind Act (NCLB). NCLB provided $13.5 billion in 2001-02 and added an array of
new accountability measures (Odden & Picus, 2008).
Prior to substantial involvement of the legislative branch with the passage of the
ESEA in 1965, the judicial branch, in 1954, established education as a common good
with its decision in Brown v Board of Education. The court’s landmark decision
abolished school segregation. Since Brown, the courts have been active in education
equality and equity issues (Lindseth, 2006).
According to Lindseth (2006), two important court cases involving “educational
enhancements” designed to remedy years of segregation were Milliken v. Bradley (1977)
and Missouri v Jenkins (1985). With these two decisions, the courts intended to re-
integrate schools with “educational enhancements” by increasing funding to schools. It

21
was thought that greater funding would attract white students to minority schools and
promote a racially mixed student body. With greater funding and a more mixed student
body schools would improve the achievement of minority students. Subsequent court
ordered remedies came to be referred to as “Milliken II remedies” (Lindseth, 2006).
In 1995, the court, in Jenkins v. Missouri (Jenkins III), ruled that the desire to
diversify schools and bring the achievement of minority students up to the average is not
justification for the “educational enhancements” previously mandated (Lindseth, 2006).
The Jenkins III decision brought about the end to federal court cases challenging local
and state funding systems on the grounds of prior segregation and civil rights concerns
(Lindseth, 2006).
In 1973, the first equity case was brought to the Supreme Court arguing that local
funding of schools should be equalized across districts in the state of Texas. Plaintiffs
argued, in Rodriguez v San Antonio (1973), that the quality of education a child receives
should not depend on their residence. The Supreme Court decided that there is no
provision in the federal constitution that holds education as a fundamental right. The
court decided that the Texas funding system based on property taxes is a rational method
of funding schools. The decision had the effect of ending federal suits to equalize
education funding in states based on equity (Lindseth, 2006).
As a result of the Rodriguez decision, suits challenging inequitable state funding
systems moved to state courts. Most state constitutions include a provision for a free and
public education. In state courts, plaintiffs found some success in overturning state

22
education funding systems that are primarily based on local property taxes. These cases
have come to be known as “equity” cases (Lindseth, 2006).
Some state courts, on the other hand, have ruled that their state constitution
provides little or no guidance on what a proper education looks like. According to
Lindseth (2006), “unless the constitution itself contains ‘judicially discoverable and
manageable standards’ on which a court can base its decision, the general rule of law is
that issues of educational policy and spending are ‘political questions’ over which the
courts have no jurisdiction” (p. 45).
A trend toward Adequacy
In recent years the courts have worked to determine what it would cost to
adequately fund schools to achieve a given states’ goals for student outcomes. Critics of
the adequacy movement suggest that many factors, other than school funding, affect
student achievement. They also point out that state constitutions do not clearly define
what adequacy looks like (Lindseth, 2006).
In New York, the Campaign for Fiscal Equity filed suit against the state’s funding
system. The New York constitution requires “a system of free common schools” but
does not specify what that means. The rigorous Regents Learning Standards are arguably
the most challenging content standards in the country, and the court, after several appeals,
decided that the education provided in New York City was not adequate to achieve those
standards. It ordered the legislature to provide an additional $5.6 billion to the New York
City Schools. (Lindseth, 2006).

23
In Kansas, the constitution calls for a “suitable education”. In 2003, the trial
judge in Montoy v Kansas ruled that the legislature had to provide the resources adequate
to close the achievement gap. The state supreme court upheld this ruling in 2005 and
ordered an additional $853 million over the next two years. The case was dismissed
when the legislature approved $755 million in additional funding. The state court ruled
that any further challenge to the funding system would have to come from a new suit
(Lindseth, 2006).
In Wyoming, the constitution calls for a “thorough and efficient” and “complete
and uniform” education. The court, in Campbell County School District v Wyoming
decided in its 1995 ruling that the state was obligated to provide the best education.
According to Odden and Picus (2005), in their introduction to the report prepared for the
Wyoming legislature, “Adequacy is best defined as the cost of providing educational
programs and services so that all – or almost all – children have an equal opportunity, in
Wyoming called “the educational basket,” to meet high learning goals” (p. i). The court
ordered the legislature to drastically increase funding to provide the best education. The
legislature developed a block grant funding model that used professional judgment panels
to determine what the basket of educational goods should be using a cost-based model
(Odden & Picus, 2005). In 2001, the court found that parts of the funding model did not
meet the constitutional standards, so the legislature again revised the model for the 2002-
03 school year. The court mandated that the formula be re-evaluated every five years
(Odden & Picus, 2005). The Evidence Based Model was used to fund Wyoming’s

24
schools beginning in the 2006-07 school year. Further discussion of the Evidence Based
funding model created by Odden & Picus (2005) will appear in subsequent sections.
History of School Funding in California
School funding in California has evolved over many years of court rulings,
legislative action and voter-approved initiatives. This section provides a timeline of the
most important actions related to school finance in California. Providing this historical
context helps to understand the climate in which the schools in this study operate in terms
of the resources available to them.
Litigation began in California courts in 1968 on what would become known as the
Serrano v Priest (1968 - 1976) decision. Serrano was one of the first cases nationally
that challenged the disparities in local funding of education that lead to vast funding gaps
between wealthy and poor districts (EdSource, 2008a). In 1976, the California Supreme
court found the state’s system for funding schools unconstitutional because it violated the
equal protection clause due to the funding disparities between wealthy and poor districts.
The court gave the state until 1980 to equalize revenue limit funding to within $100 per
pupil. Categorical funds are not included in the calculations (EdSource, 2008a; Picus
1991). With the court ordered equalization of funding across districts, Serrano had the
effect of eliminating taxpayer’s incentive to tax themselves to fund their local schools.
This shift in attitudes would lead to the passage of Proposition 13 which will be discussed
below. The combination of the Serrano decision and the passage of Proposition 13 lead
to California’s fall from one of the top funded school systems in the country down to the
bottom in just one generation (Lindseth, 2006).

25
In response to the anticipated Serrano decision, the legislature passed Senate Bill
90 in 1972. Senate Bill 90 established “revenue limits” which set a cap on how much
money a district could collect from local taxes per-pupil. This legislation was the first
step in shifting funding from local control to state control (EdSource, 2008a).
In 1977, the legislature passed Assembly Bill 65 to adjust revenue limits over
time to achieve court-mandated equalization (EdSource, 2008a). The legislation included
annual adjustments to increase lower wealth district’s revenue limits more aggressively
than higher wealth district’s revenue limits. High wealth districts would receive little or
no increase while low wealth districts would see substantial gains each year. This served
to phase in the equalization of revenues mandated by Serrano. This method was referred
to as “power equalization” (EdSource, 2008a).
Voters approved Proposition 13 in 1978. Proposition 13 was a constitutional
amendment that limited property taxes to 1% of a property’s assessed value. It also
limited the increase in assessed value per year to either 2% per year, or the growth in the
Consumer Price Index, whichever is lower. It set the local approval level to pass a parcel
tax to a two-thirds vote. In effect, Proposition 13 eliminated 60% of local revenues from
property taxes and made the “power equalization” efforts of Assembly Bill 65 obsolete
(EdSource, 2008a). The elements of Proposition 13 and the voter approved ballot
measures that followed can only be changed through yet another ballot measure to
change the state constitution (EdSource, 2008a).
In response to Proposition 13, the legislature passed Assembly Bill 8 to bail out
school districts that suddenly lost most of their funding. In effect, the state took over

26
control of school funding with the passage of Proposition 13 and Assembly Bill 8
(EdSource, 2008a).
Proposition 4, also known as the Gann Limit, was passed in 1979. The Gann
Limit serves to limit spending at every level of state government, including education.
An agency’s Gann Limit is adjusted annually. Proposition 111 (1990) increased the
Gann Limit (EdSource, 2008a).
In 1984, the state constitution was again amended to create a state lottery system.
The lottery initiative guaranteed that 34% of total receipts would go to public education.
The lottery money, as approved by voters can only be used for instructional purposes and
can not replace another funding source. Lottery funds account for less than 2% of school
district revenues (EdSource, 2008a).
In 1988, yet another constitutional amendment was passed, Proposition 98. Using
a complex formula that is based on tax revenues, Proposition 98 mandates a minimum
level of funding for public schools. It requires a two-thirds vote from the legislature and
approval of the governor in order to suspend the increased funding for a year (EdSource,
2008a). Under Proposition 98 three tests are used to determine funding. Test I is that
41% of the state budget goes to public education. Test II is that public education receive
at least as much as it did the previous year. If state tax revenues increase dramatically so
that the Test I guarantee is more than the Test II guarantee, then the Test I guarantee
applies. The state is allowed to reduce funding to schools if one of two conditions apply.
The first possibility is if the General Fund revenues grow less than personal income –
Test 3. The second requires a vote of two-thirds of the legislature and approval of the

27
governor. In either case, the amount saved must be restored in subsequent years that the
General Fund grows faster than personal income (EdSource 2006, October).
In 1991 and 2004, the legislature, through Assembly Bills 1200 and 2756
respectively, mandated accounting system guidelines to help districts more accurately
track revenues and expenditures and report them to the state for additional oversight.
Districts must demonstrate solvency two years into the future, and county offices of
education were given more oversight power of district budgets. Districts must also
certify that they can meet the costs of collective bargaining agreements (EdSource,
2008a).
A lawsuit filed in 2000, Williams v. California, alleged that the state had not
provided adequate resources for thousands of children in low wealth schools to access a
quality education (EdSource, 2008a). In 2004, the Williams settlement provided
increased accountability and funding to aid low-performing schools. As a result of the
settlement, a variety of bills were passed by the legislature to improve and set minimum
standards for school facilities, teacher quality and instructional materials; fund facility
repair projects; phase out year round schools and encourage quality teachers to work at
low performing schools (EdSource, 2008a).
Current State of Education in California
After years of legislation, voter initiatives and judicial intervention, public
education in California today is funded through state sales and income taxes (57.8%),
local property taxes (21.4%), federal categorical funds (12.3%), local sources such as
contributions from the community, interest income, developer fees and parcel tax revenue

28
(6.2%), and from state lottery funds (1.3%) (see figure 2.1) (EdSource, 2008a). State
funds through Proposition 98 (State sales, income and property taxes) account for 80% of
the funding to school districts. The other 20% comes from local and federal funds
(EdSource 2008a). Compared to other states, a smaller percentage of state funds to
districts can be used for general purposes; instead, California sends a greater portion of
resources to districts in the form of categorical funds which come with additional
constraints and less flexibility (Duncombe & Yinger, 2007).
Figure 2.1: California School Funding Sources
Local Misc.
6.2%
Fed. Gov.
12.3%
Local Prop.
Taxes
21.4%
State
58.8%
Lottery
1.3%

(Source EdSource, 2008a)

The recent economic downturn and projected state budget shortfalls have required
state budget cuts across the board. The projected state budget shortfall is $14.5 billion
(EdSource, 2008, February). In order to cut $360 million from K-12 education for the
2007-08 school year, Governor Arnold Schwarzenegger has proposed that all categorical
money that has not been sent to districts would be cut. If the reduction is not covered

29
from categorical cuts, revenue limits would be cut to make up the difference (EdSource,
2008, February).
Governor Schwarzenegger has proposed a further $4.3 billion cut in education
spending for the 2008-09 school year after already cutting $360 million from K-12
education for the 2007-08 school year budget (EdSource, 2008, February).
Schwarzenegger has called for suspending Proposition 98 funding for the 2008-09 fiscal
year which would require the approval of the legislature with a two-thirds majority.
Education interest groups have come out in strong opposition to suspending Propositin 98
funding (EdSource, 2008, February).
The funding cuts proposed by the governor take from both revenue limits and
categorical programs. The legislature has options as to how the money could be reduced
ranging from equal cuts to all categorical programs and revenue limits or deeper cuts to
some categorical programs to save others and limit the cuts to the revenue limit
(EdSource, 2008, February).

Resource Use
This section on education resource allocation and use begins with a historical
perspective on national funding trends and then explores the question of where
educational dollars have been spent. The next section explores the lack of significant
growth in student achievement in the face of increased spending. Next is a brief section
detailing the research on what happened after funding systems in several states were
overhauled. This study builds on the final two sections of this review of the literature on

30
Resource Use related to school level resource use and how resources can be used more
efficiently at the school level.
Historical trends
Between 1890 and 1990, increases in teacher pay, shrinking student to staff ratios
and greater expenditures outside the classroom have lead to an overall increase in real
expenditures per-pupil by three and a half percent (Hanushek & Rivkin, 1997). This is
even after controlling for inflation, rising student populations and the increase in numbers
of students attending high school from 1925 to 1950. The growth occurred every decade,
even in bad economic times (Hanushek & Rivkin, 1997). The question posed by
Hanushek & Rivkin (1997) and other researchers, and explored below, is why student
achievement has only modestly improved given increased spending and decreasing class
sizes.
The literature refers to educational expenditures by function. The primary
functions include instruction, instructional support, administration (school and district),
student support, operations and maintenance, transportation, food services and other
(Odden & Picus, 2008).
Several trends in education have highlighted the need to develop a better way to
study school resource use. First, as mentioned above, despite increases in school
funding, student achievement has not risen significantly (Odden, Goertz, Goetz,
Archibald, Gross, Weiss & Mangan, 2008). Second, NCLB has mandated drastic
improvements in student achievement with only very modest increases in per-pupil
funding necessitating more efficient use of resources. Third, the shift to adequacy

31
models over equity models has identified promising practices that may improve student
achievement if funded at that adequate level. Finally, increasingly richer data are
available to analyze how resource use is linked to student achievement (Odden et al.,
2008).
Where has the money gone?
Over the last 50 years the pattern of school district funding nationally has been
surprisingly consistent with 60 percent of district funds spent on instruction, eight to ten
percent on professional development, nine percent on operations and maintenance, four
to six percent on transportation, four to six percent on food service, seven percent on site
administration and three percent on district office administration (see figure 2.2) (Odden,
2007; Odden, Monk, Nakib & Picus, 1995; Odden & Picus 2008).
Figure 2.2 National School District Expenditure Averages
Instruction
60%
Prof. Devel.
10%
Operations
9%
Transportation
6%
Food Service
5%
Site Admin.
7%
Dist. Admin
3%

(Source: Odden & Picus, 2008)

32
Much of the debate among researchers has to do with the extent to which the
increased resources over the last 50 years have been used efficiently. Lankford and
Wyckoff (1995) found that 60 percent of New York’s $12 billion increase in school funds
from 1980 to 1992 can be attributed to inflation.
Many studies have determined that increases in funding to school districts lead to
increases in teacher salaries and benefits (Lankford & Wyckoff, 1995; Hanushek &
Rivkin, 1997; Picus, 1994). Other studies show that salaries did not keep up with wage
inflation in other industries. This trend is especially problematic for women (Odden &
Picus, 2008). Odden, Monk Nakib and Picus (1995) found that teacher salaries increased
in 1970s and have been stagnant since.
In addition to increases in teacher salaries, research has also shown that increases
in school funding lead to smaller class sizes and more teachers. Picus (1993) found that a
ten percent increase in district funding would, on average, lead to a four percent increase
in spending to lower class size and a one percent increase in spending to raise teacher
salaries. Other studies have found similar decreases in class sizes and increases in the
numbers of teachers as funding increases (Odden, Monk, Nakib & Picus, 1995; Hanushek
& Rivkin, 1997; Picus, 1994; Odden and Picus, 2008). Increases in funding have also
lead to facilities improvement and more social services offered at schools (Odden et al.,
1995).
A source of agreement among researchers is that a disproportionate percentage of
the funding increases over the last 50 years has gone to fund Special Education costs
(Lankford & Wyckoff, 1995; Hanushek & Rivkin, 1997; Odden & Picus, 2008;

33
Rothstein & Miles, 1995) Despite the drastic increases in funding for Special Education
services, there is little evidence of effective strategies for improving achievement of
Special Education students (Odden et al., 1995).
There is little evidence in the research pointing to an efficient use of the increased
funding to benefit instruction in the core subject areas beyond smaller class sizes. “The
bottom line is that the bulk of new dollars expended within the instructional function
were for teachers providing instruction in subjects outside the core and for teachers
providing a variety of extra help to students with an array of special education needs”
(Odden & Picus, 2008, Chapter 6, p. 8).
Why has student achievement not improved despite increased funding?
With a three and a half percent increase in real expenditures per pupil between
1890 and 1990, why has there not been a corresponding increase in student achievement?
The research cites many reasons for this failure, mostly related to inefficient uses of
resources and the difficulty of measuring how school level expenditures are being used.
Odden et al. (1995) determined that revenues are not connected to pupil needs or costs
and are not spent fairly or wisely. On the other hand they determined that the resources
were not squandered (Odden et al., 1995).
The most consistent problem cited in the research is that new influxes of funds are
not targeted to the core academic areas. In any school, less than 50 percent of the school’s
resources are allocated to core academic areas (Odden et al., 1995). Funds are used for
non-instructional purposes (Hanushek & Rivkin, 1997; Odden and Picus, 2008) or to
support students who need extra help such as Special Education, English Learner (EL)

34
and low-income students (Odden and Picus, 2008). Although support programs seem to
be a wise investment of educational dollars, the money for support programs has shown
little impact on achievement. Pull out programs to help Special Education and EL
students have not effectively improved student achievement (Odden et al., 1995).
Despite the negligible impact in bringing special need students up to proficient, the need
for more resources to support these students is not questioned. Special need students cost
35-100 percent more to educate to an “adequate” level than non-special needs children
(Baker, 2005). In both high and low wealth districts, a declining proportion of money
spent on instruction is actually going to core subject instruction. This may help explain
why there has been little growth in student achievement while total expenditures have
increased over time (Odden & Picus, 2008).
Research has found that low wealth and high wealth districts use influxes of
resources in different ways. In low wealth districts, new influxes of money have been
used to catch up on deferred maintenance, improve social services or provide services to
at-risk students (Odden et al., 1995). In New York, Monk, Roellke & Brent (1996) found
that higher spending and wealthier districts allocated more student time to advanced
courses while poorer and lower spending districts allocated more student time to remedial
courses. Student enrollment in remedial courses had seen an increase between 1983 and
1996. The state of New York as a whole spent more on remedial programs than
advanced (Monk et al., 1996). The Southwest Educational Development Laboratory
(2003) found that higher achieving districts spent significantly more than lower achieving
districts on instruction.

35
In addition to the rise in remedial classes, more non-core or elective classes also
take resources from the core content areas (Odden, 2007; Odden & Picus, 2008). The
trend toward elective classes started in 1960s to provide teachers with planning time
while students took PE, art or another non-core class. At the secondary level, electives
exploded and are seen as desirable by students, teachers, parents and some policy makers.
At some schools, electives make up half the instructional program (Odden & Picus,
2008). This is a concerning trend given that students are not achieving at high enough
levels in core subject areas (Odden & Picus, 2008). To further quantify the problem,
from 1950 to 1995 the proportion of regular classroom teachers to all professional staff
fell from 70% to 52% (Odden & Picus, 2008).
Odden and Picus (2008), in their Evidence Based Model, which will be discussed
in more detail below, recommend that 30 to 40 percent of expenditures go to core
classroom teachers, a principal and professional development. Another 30 to 40 percent
of expenditures should be spent on specialist teachers for electives, to help struggling
students, for support services, instructional aides and other instructional supports. The
remaining 20 to 30 percent should be used on overhead (central office support, business
and personnel services, maintenance and operations, transportation and food services)
(Odden and Picus, 2005). This more intentional approach to linking resource use to
student achievement is different from the approach that many states, including California
take. “California policy has never formally acknowledged the linkage between its pupil
attainment standards and its school finance system” (Kirst, 2007, p. 2).

36
What happens when funding systems are reformed?
A subsection of the literature on resource use explores what has happened in
states where education finance systems have been reformed. This section gives a brief
overview of such studies in California, Kentucky, New Jersey and Texas.
In California, contrary to the expectations of many experts, an increase in
resources to schools did not go disproportionately to teacher salaries, but did go to hire
more teachers and lower class sizes. Salaries actually decreased as a percentage of the
overall budget (Kirst, 1977).
Kirst (1977) also found that lower spending districts and wealthier districts used
influxes of money very differently. Lower spending districts used the influx of new
money to catch up on deferred maintenance and building projects. Other researchers
confirmed this finding with studies in Kentucky, New Jersey and Texas. In Kentucky,
Adams (1994) found that lower-wealth districts showed a greater increase in per-pupil
spending compared to high-wealth districts. In New Jersey, Firestone, Goertz, Nagle and
Smelkinson (1994) found that low-wealth districts used an influx of money in 1992 to
improve facilities. They found that these districts did not invest in programs for fear that
the new funding would be cut (Firestone, et al , 1994). In Texas, low wealth districts
received substantial increases in funding as a result of several court rulings. Following
the change in funding patterns that diverted some funds from high-wealth to low-wealth
districts, the low-wealth districts chose to spend the extra funds on construction projects.
The low-wealth districts feared making long term plans due to skepticism about the long-
term availability of the new funds (Picus, 1994).

37
Theses studies on resource use after a change in funding patterns demonstrate that
influxes of funds are not likely to be used as intended by legislatures if some incentives
or mandates are not in place guiding districts on how to use the resources. Picus (1991)
found that incentive programs introduced in California in 1983 that encouraged districts
to extend school days and increase beginning teacher salaries were more effective than
other types of grants to encourage districts to use funds as intended by the legislature.
Although the effects were temporary and dependent on the type of reform, the lessons
learned are important for states looking to use resources more efficiently (Picus, 1991).
Resource use at the school level
The most recent arena for research on resource use, and the area of research to
which this study hopes to contribute, is looking at how resources are actually used at the
school level. In the past, resource use studies focused on how districts or states used
resources. Resource use studies at the district level do not adequately account for
variations in resource allocation at the school level. In addition, and perhaps more
importantly, there is no way to link resource use patterns to educational strategies using a
district level analysis (Odden, Archibald, Fermanich & Gross, 2003). At this point, there
is very little school level data to examine how funds are actually used by students. Part
of the difficulty with school level studies relates to the difficulty in comparing local
categories of expenditures due to different definitions and assignments (Odden et al.,
1995). Because of the differences in categories, it is difficult to quantify differences in
resource use and, on a more practical level, it is also more time consuming to visit

38
individual school sites. Still, there is some research emerging on school level
expenditures.
Brinson and Mellor (2005) used the school-level expenditure model developed by
Odden et al. (2003) that is similarly used in this study to compare practices of 10 average
and high performing elementary schools in Texas. Although quantitative analyses
showed no structural difference between the average and high performing schools in
terms of resource use, case studies showed that several factors unique to the higher
achieving schools had positive effects on student achievement. Those strategies were: (1)
team teaching, (2) more time spent on instruction, (3) tutoring, (4) teachers with four or
more years of experience and (5) higher levels of teacher compensation and performance
incentives (Brinson & Mellor, 2005). Because the only way to gather the data needed to
make comparisons is to visit specific school sites in order to develop case studies, the
authors recommend that school level data be more readily available to conduct school
level analysis of resource use patterns.
Can resources be effectively reallocated?
The evidence suggests that this line of research on school level resource use can
contribute to substantial improvement in student achievement. Schools have found
success in breaking away from the way they had always done things in order to
restructure to improve student achievement, especially for low income students, EL
students and students with disabilities (Odden, 2007). The most common reallocation
strategies that showed improvement in terms of student results were increasing the time
spent on core academic subjects, lowering class sizes in the core subjects, increasing

39
investment in professional development for teachers, and providing more effective extra
help for students such as one-on-one tutoring (Odden, 2007). In order to guide school
leaders in making decisions on resource use a more robust model for tracking school
level resources by strategies is needed.
A model to track resources by educational strategies
Some have suggested that simply increasing the percentage of school or district
funds spent on instruction from 60% to 65% would improve student achievement.
George Will (2005) labeled this the “65% solution.” What is lacking in this notion is any
sense of how the money spent on instruction is actually being used (Odden, 2007).
Throwing more money at an inefficient system in not helpful (Hanushek, 2006).
Odden, Archibald, Fermanich and Gross (2003), in response to the lack of fiscal
reporting systems that allow school level comparisons of resource use, created the fiscal
reporting system that serves as the foundation for this study. It improves upon previous
models in three important ways. First, the express purpose of the model is to report
school level expenditures rather than district or state level expenditures. Second, it can
accommodate the school within a school design by accounting for multiple school units.
Third, it allows the examination of specific instructional strategies and how resources are
used in line with the latest research on what works to improve student achievement
(Odden et al., 2003).
The fiscal reporting system created by Odden et al. (2003) includes two different
categories of information on school resources and expenditures. The resource indicators
are listed below with brief descriptions of each.

40
1. Student Enrollment is total enrollment of the whole school
2. School Unit Size can be used to reflect school within school design or small
learning communities
3. Percent Low Income is the number of students participating in free or reduced
lunch program. This statistic is often under-reported at the high school level.
4. Percent Special Education reflects students with IEPs
5. Percent ESL/Bilingual reflects students receiving EL services
6. Expenditures Per Pupil is calculated by dividing total expenditures from all
sources and dividing by the total enrollment.
7. Professional Development Expenditures Per Teacher is calculated by dividing
total expenditures for professional development by the total number of
teachers, including mentors and instructional facilitators.
8. Special Academic Focus identifies any academic program focus such as
college prep, science and medicine, technology, etc.
9. Length of Instructional Day is the number of hours per day that students
receive instruction.
10. Length of Class Periods is the number of minutes per class period.
11. Length of Reading and Math Class Periods and Reading and Math Class Size
and Regular Class Size. These categories are only used in elementary grades,
so they are not relevant to this study.
12. Length of Core Class Periods is the number of minutes of core class (Math,
English, Science and Social Science) periods.

41
13. Core Class Size is the average number of students per teacher in Math,
English, Science and Social Science.
14. Non-Core Class Size is the average number of students per teacher in non-core
classes
15. Percent Core Teachers is the percent of all certificated staff, except for
principal and assistant principals, that are core teachers.
The expenditure structures in Odden et al.’s (2003) model capture the
instructional and non-instructional allocation patterns and help to identify specific
strategies that the school uses. The nine elements of the expenditure structure are divided
into seven instructional elements and two non-instructional elements. The seven
instructional elements are:
1. Core Academic Teachers is the number of full-time equivalent (FTE) teachers
teaching in math, English, Science and Social Science
2. Specialist and Elective Teachers reflects teachers who teach non-core classes
such as art, physical education, foreign language, etc. as well librarians and
vocational education teachers.

42
3. Extra Help represents certificated teachers who work in the capacity of
helping struggling or special need students. This may include tutors, math and
English support class teachers, special education teachers providing extra
support classes or resource labs, inclusion teachers, EL teachers, Special
education teachers working with severely disabled students, extended day or
summer school programs and alternative education programs through the
district.
4. Professional Development is the cost of teacher time in professional
development and all the elements of providing professional development
including materials, trainers, coaches, facilities, transportation, etc.
5. Other Non-Classroom Instructional Staff includes both certificated and non-
certificated staff that works in a support role such as substitutes and non-
special education classroom aides.
6. Instructional Materials and Equipment includes supplies needed for all
instructional programs such as books, software, computers, etc.
7. Student Support represents a schools support staff and includes counselors,
psychologists, attendance monitors, parent liaisons, etc as well as expenditures
for athletics and extra-curricular activities.
The non-instructional expenditure elements are:
8. Administration includes administrators and all support and clerical staff,
equipment, supplies, technology and discretionary funds.

43
9. Operations and Maintenance includes custodial services, maintenance staff,
food services, security, etc.
By comparing resource indicators and expenditure structure elements, a much
richer picture of how schools are using their resources on specific strategies is possible.
Without the detail of how instructional dollars are spent, the old category of “instruction”
tells us very little about how the funds were actually used.
By using their proposed instructional expenditure structure model to analyze
similarities and differences between two very different elementary schools, Odden et al.
(2003) were able to compare the schools’ use of resources in terms of instructional time,
class size, resources used toward the instructional program, professional development,
the number of core versus specialist and elective teachers, extra help such as tutors,
special education teachers and EL teachers, administration and other support elements.
An example of a similar analysis for two high schools was also discussed. This level of
resource use analysis is not possible under any other model used to measure resource use.
Another study by Odden, Goertz, Goetz, Archibald, Gross, Weiss and Mangan
(2008) studied eleven elementary schools and also used the school-level expenditure
framework outlined above. Nine of the eleven schools were involved in a whole school
reform strategy to improve instruction. The framework allowed for rich comparisons
among the schools in regard to resource use and accentuated the need to analyze school
level data to better understand how resources can more efficiently be used to improve
student achievement (Odden et al., 2008).

44
Evidence Based Model
Taking the school-level expenditure model a step further, Allan Odden and
Lawrence O. Picus (2008) developed the Evidence Based Model that identifies the
elements of a school-wide instructional program that research has shown to be effective
in improving student performance. The model can be used to cost out each element to
determine an adequate level of funding (Odden, 2003). By identifying and funding
specific strategies, the model guides schools in efficiently using resources to improve
student achievement (Odden, 2003). The Evidence Based Model establishes prototypical
school models and then adjusts for school size and demographics. A prototypical high
school would have a total of 600 students and an average class size of 25 students (Odden
& Picus, 2008). With 600 students, a prototypical high school would be staffed with 24
full time core teachers. A full time teacher is referred to as a Full Time Equivalent
(FTE). In addition to the 24 core FTEs, the model also provides resources for eight
specialist teacher FTEs and three instructional facilitators or coaches and a technology
coordinator. Coaches would spend most of their time in classrooms giving feedback to
teachers and modeling lessons. They would also coordinate the instructional program
and provide other staff development (Odden & Picus, 2008).
The Evidence Based Model includes resources for extra support and staff to assist
low income and disadvantaged students. The resources allocated for extra help vary
according to the number of disadvantaged students. The model funds one credentialed
tutor for every 100 students on free or reduced lunch. The tutor provides one-on-one
tutoring for 20 minutes per student or for a group of three students for an hour. The

45
credentialed tutors are trained in specific strategies and the tutoring is intended to support
the regular curriculum to catch students back up and return them to the regular classroom
(Odden & Picus, 2008). The model also funds support to English Learner (EL) students
with one FTE teacher for every 100 EL students to provide additional support classes for
EL students. In addition to the support classes, EL students would also be supported by
the tutoring program (Odden & Picus, 2008).
Gándara & Rumberger (2007) recommend five elements to provide adequate
resources for EL students. The first element is a high quality preschool program. The
second element is an instructional program that includes both the core curriculum and
English language development. The third element is student and family support to help
with understanding expectations. The fourth element focuses on improving teacher
capacity to work with EL students through professional development. The final element
involves creating a safe and nurturing environment for students.
The Evidence Based Model funds programs outside of the regular school day to
support struggling or disadvantaged students. The model funds one teacher for an
extended day program (five days per week for three hours) for every 15 free and reduce
price lunch students paid at 25% of the teacher’s annual salary (Odden & Picus, 2008). A
summer school program is resourced for 50% of the number of students in free or
reduced lunch program with teachers paid 25% of their annual salary. The recommended
summer program is eight weeks long with class sizes of 15 students for six hours a day.
Students in summer school would receive extra help in reading and math (Odden &
Picus, 2008).

46
For special education students, the model funds four special education teachers
for mild and moderate disability students. More severe special education services should
be fully funded by the state and are not included in the Evidence Based Model funding
formula (Odden & Picus, 2008).
In addition to credentialed core teachers, elective teachers and tutors, the model
allocates 5% of all teacher resources for substitute teachers in order to free teachers for
staff development opportunities and provide sick leave (Odden & Picus, 2008).
The Evidence Based Model funds student support, family outreach and guidance
counselors at the rate of one teacher level position for every 100 low-income students
plus one for every 250 students. The prototypical 600-student school would be resourced
with 5.4 counselors (Odden & Picus, 2008). The research does not support the use of
classroom instructional aides outside of the special education classroom. The Evidence
Based Model funds three aides in a prototypical high school to help relieve teachers and
provide supervision, but not for instructional purposes.
There would be one principal for each school unit, so a school-within-school
model may have multiple principals with one lead principal (Odden & Picus, 2008). The
school office would be staffed with one secretary and three clerks. The model also funds
one librarian and one media specialist in a prototypical school.
For professional development, the model funds a ten day summer institute with
teachers paid at their daily rate as well as on-going on-site coaching as discussed earlier
in this section. In order to facilitate teacher collaboration during common preparation
periods, strategic master scheduling is required on the part of the site administration. The

47
professional development strategies are funded at $100 per pupil for summer and ongoing
training which would equal $60,000 in the prototypical high school (Odden & Picus,
2008).
The Evidence Based Model funds technology and equipment at a rate of $250 per
pupil for computer purchasing, upgrading and maintaining as well as copiers and
software (Odden & Picus, 2008). Instructional materials are resourced at a prototypical
high school at the rate of $25 per pupil for library books and electronic services along
with $150 per pupil for textbooks and consumables. Finally, the latest research indicates
that schools spend between $200 and $250 per pupil on student activities such as clubs,
athletics and music programs. Table 2.1 provides an overview of how the Evidence
Based Model allocates resources in prototypical elementary, middle and high schools.
Table 2.1: Recommendations for Adequate Resources for Prototypical Elementary,
Middle and High Schools
School Element Elementary Schools Middle Schools High Schools
School
Characteristics

School
Configuration
K-5 6-8 9-12
Class Size
K-3: 15
4-5: 25
6-8: 25 9-12: 25
Full-day
Kindergarten
Yes N/A N/A
Number of teacher
work days
200, including 10
days for intensive
training
200, including 10
days for intensive
training
200, including 10
days for intensive
training
% Disabled 12% 12% 12%
% Poverty (free &
reduced lunch)
50% 50% 50%
% English Learner 10% 10% 10%
% Minority 30% 30% 30%

48
Table 2.1: Recommendations for Adequate Resources for Prototypical Elementary,
Middle and High Schools (continued)
Personnel
Resources

1. Core Teachers 24 18 24
2. Specialist
Teachers
20% more: 4.8 20% more: 3.6 33% more: 8.0
3. Instructional
Facilitators/Mentors
2.2 2.25 3
4. Tutors for
struggling students
One for every 100
poverty students: 2.16
One for every 100
poverty students:
2.25
One for every
100 poverty
students: 3
5. Teachers for EL
students
An additional 1.0
teacher for every 100
EL students: .43
An additional 1.0
teacher for every
100 EL students: .45
An additional
1.0 teacher for
every 100 EL
students: .60
6. Extended Day 1.8 1.875 2.5
7. Summer School 1.8 1.875 2.5
School
Characteristics

8. Learning & mild
disabled students
Additional 3
professional teacher
positions
Additional 3
professional teacher
positions
Additional 4
professional
teacher
positions
9. Severely disabled
students
100% state
reimbursement minus
federal funds
100% state
reimbursement
minus federal funds
100% state
reimbursement
minus federal
funds
10. Teachers for
gifted students
$25 per student $25 per student $25 per student
11. Vocational
Education
N/A N/A No extra cost
12. Substitutes 5% of lines 1-9 5% of lines 1-9 5% of lines 1-9
13. Pupil support
staff
1 for every 100
poverty students: 2.16
1 for every 100
poverty students
plus 1.0 guidance
per 250 students:
3.25 total
1 for every 100
poverty students
plus 1.0
guidance per
250 students:
5.4 total

49
Table 2.1: Recommendations for Adequate Resources for Prototypical Elementary,
Middle and High Schools (continued)
14. Non-
Instructional Aides
2.0 2.0 3.0
15. Librarians/media
specialists
1.0 1.0
1.0 Librarian
1.0 Library Tech
16. Principal 1 1 1
17. School Site
Secretary
1.0 Secretary and 1.0
Clerical
1.0 Secretary and
1.0 Clerical
1.0 Secretary
and 3.0 Clerical
18. Professional
Development
Included above:
Instructional
facilitators, Planning
and prep time, 10
summer days
Additional: $100 per
pupil for other PD
expenses - trainers,
conferences, travel,
etc.
Included above:
Instructional
facilitators, Planning
and prep time, 10
summer days
Additional: $100 per
pupil for other PD
expenses - trainers,
conferences, travel,
etc.
Included above:
Instructional
facilitators,
Planning and
prep time, 10
summer days
Additional:
$100 per pupil
for other PD
expenses -
trainers,
conferences,
travel, etc.
19. Technology $250 per pupil $250 per pupil $250 per pupil
20. Instructional
Materials
$140 per pupil $140 per pupil $175 per pupil
21. Student
Activities
$200 per pupil $200 per pupil $250 per pupil
(Source: Odden & Picus, 2008

The resource patterns proposed in the Evidence Based Model are based on a large
body of research that identifies strategies that improve student achievement. The
Evidence Based Model is not used in the state of California, so it is not expected that the
schools in this study will have the same resource allocation patterns. The Evidence
Based Model, along with Odden et al.’s (2003) school-level expenditure framework, does
provide a robust model to compare how the schools in this study’s sample use their
resources to improve student achievement.

50
Instructional Improvement
A detailed review of the vast literature on what works to improve student
performance is not possible in the context of this study. To provide a brief overview of
the research three meta-analyses of what works to improve schools will be examined.
Marzano (2003) conducted a meta-analysis of 35 years of research on what works
to improve schools. He condensed what other researchers had found as the most
important components of schools into five key factors. The first, and most important
factor, according to Marzano, is a guaranteed and viable curriculum (Marzano, 2003). A
guaranteed and viable curriculum includes both the opportunity to learn, or the extent to
which the curriculum actually taught is standards based, and the time actually devoted to
instruction along with a strategic emphasis on most important standards.
The second factor relates to challenging goals and effective feedback (Marzano,
2003). Schools that provide academic goal setting that challenges all students, timely
feedback using formative assessments and specific feedback that assesses what students
are being taught are more likely to improve student achievement.
Marzano (2003) identifies the third factor as parent and community involvement
which involves parents in three ways. First is basic communication with parents on
student performance. Second is getting participation from parents and community
members as aides or guest speakers. Third, is establishing formal structures that allow
for parents and community members to have a voice in making key decisions.

51
The fourth factor identified by Marzano (2003) is a safe and orderly environment.
A positive learning environment is an obvious requirement and often cited in literature as
a key component.
Finally, Marzano (2003) identifies collegiality and professionalism as a key
component to improve student achievement. Collegiality is defined as authentic
professional relationships that allow for open, respectful sharing and analyzing of
practice. Such relationships cannot be contrived and simple “friendship” relationships
among teachers may actually have a negative effect on student achievement.
Professionalism requires that teachers feel a sense of efficacy. “Efficacy is grounded in
teachers’ perception that they can effect change in their schools. To do this, they must be
a valued and critical part of the school’s policy setting mechanisms” (Marzano, 2003, p.
62).
Allan Odden (2007) examined research supported by the Consortium for Policy
Research in Education (CPRE) in both Washington State and Wisconsin which found
examples of successful schools who had doubled student performance over a four to
seven year period. These schools followed eleven very similar steps to double student
performance.
1. Set high goals for student achievement.
2. Analyze student data to become intimately familiar with both macro
(standardized assessments) and micro (formative assessments) levels of
student achievement and the curricular areas that need more attention.

52
3. Review research on effective curriculum and instruction and implement best
practices.
4. Invest heavily in teacher training through the use of instructional coaches and
summer institutes.
5. Provide extra help to struggling students in the form of one-on-one or very
small group tutoring as well as extended day programs and summer school.
English Learner (EL) students require specialized EL instruction.
6. Smaller class sizes in early elementary grades
7. Protect class time to keep it free from distractions and concentrating more
time on core subjects, including double blocks of time for core subjects in the
upper grades.
8. Create professional school communities where teachers collaborate and
analyze formative assessments.
9. Empower teachers as instructional leaders with support from the district
office.
10. Connect the school with the latest research on curriculum, instruction and
programs and bring in experts as needed.
11. The schools in the study used programs and strategies that can be funded with
the national average expenditure per pupil.
Duke (2006) identified five studies on successful turnaround schools and
identified eleven characteristics that those schools had in common.
1. Timely student assistance

53
2. Teacher collaboration to identify struggling students and provide assistance
3. Use of data to make decisions on resource allocation, student needs and
teacher effectiveness.
4. Leadership that sets the tone for improvement
5. School organizational structure adjustment for improvement
6. Alignment of tests to curriculum to instruction
7. Ongoing teacher training
8. Regular assessment
9. High expectations
10. Outreach and communication to parents on student progress and opportunities
for support
11. Schedules that increase academic work time.
Among these meta-analyses there is consensus that the following strategies can
improve student performance:
1. high expectations
2. timely small group support to help struggling students
3. Using data to make larger school decisions and to serve as a basis for teacher
collaboration around formative, summative and standardized assessments to
identify common curricular or instructional areas for improvement.
4. School leadership that involves teachers in decision making and promotes a
professional, collegial environment where teachers feel empowered to
improve the instructional program to improve student achievement.

54
5. Protection of instructional time with a focus on maximizing class time spent
on core academic areas.
6. Continual professional development with instructional coaches as a key
strategy, and exposing teachers to the latest research on effective programs
and strategies.
Closing the Achievement gap
Since the schools in the sample for this study are at least 20 percent minority or
low socio-economic status and still high performing, another area of interest in the case
studies will be what the schools have done to close the achievement gap. This section of
the literature review provides a brief discussion of the strategies found in the research that
have been associated with closing the achievement gap.
First, the research shows that teacher quality does make a difference, especially in
the areas of math and science (Darling-Hammond, 1999). Studies in Texas by Fuller
(1999) and Ferguson (1991) determined that teacher quality based on experience and
credentials did make a difference in terms of student achievement compared to similar
students with less qualified teachers.
As discussed in the previous section on improving performance in schools, a
focus on the key content standards in the core subjects is critical to improving the
performance of poor and minority students (Anderson, Medrich & Fowler, 2007). Also
critical to closing the achievement gap is the elimination of tracking mechanisms that
perpetuate achievement gaps by offering a college bound track separate from a remedial
track (Burris & Welner, 2005).

55
Guskey (2007) advocates the use of formative assessment to constantly gauge
student learning and provide feedback to the student. When used as a tool for teacher
collaboration to discover best practices, formative assessments are even more powerful to
both improve teacher practice and student achievement.
Conclusion
This study contributes to the literature in two significant ways. First, by using the
expenditure structure framework developed by Odden et al. (2003) in developing the case
studies of individual schools, this study adds to a growing list of studies that are
examining school level factors and strategies that affect student achievement. Second, by
using the Evidence Based Model and the literature on what school level factors have been
attributed to successful schools as points of comparison, this study examines what school
level strategies these high minority schools have employed to find success. This study
highlights the importance of using resources to maximum efficiency by employing
research based strategies to improve student achievement.
Ultimately, the hope is that state legislatures or court systems will find from the
growing school level evidence of what works to make schools successful that an
adequacy approach to funding schools that takes into account what strategies are most
successful is a better approach to school finance. According to Paul Hill (2008), “public
school funding in the United States is not a product of intelligent design. Funding
programs have grown willy-nilly based on political entrepreneurship, interest group
pressure, and intergovernmental competition” (p.238).

56
This chapter began with a review of both national and California specific
legislation and court decisions that have led to the current state of education finance in
this state. It is important to understand this context, especially in light of the move
toward adequacy funding in some other states such as Wyoming and Arkansas. Various
aspects of resource use were discussed next. The question that remains to be answered is
why student achievement has not significantly increased as overall funding for education
has increased. This has left many, namely Hanushek, to argue that resources are not
being used efficiently. Given the current commonly used systems to track resources, it is
difficult to ascertain what an efficient use of resources looks like. Odden et al.’s (2003)
model to track resources significantly contributes to the research that will follow to better
understand how resources can be used to maximum efficiently as it tracks resource use by
strategy. Using Odden et al.’s model (2003) and a wide range of research on effective
strategies, Odden and Picus (2008) developed the Evidence Based Model to cost-out
what it would cost to provide and adequate education. The use of research based
strategies sets the Evidence Based Model apart from other costing-out methods.
Again, this study uses Odden et al.’s expenditure structure framework to examine
how the schools in this study are using their resources in a strategic way to improve
student achievement. The Evidence Based Model offers a research-based point of
comparison when looking at the individual school case studies. Since the schools in this
study are doing well with challenging student demographics, the interest of the study is in
comparing the strategies that the school is using with those outlined above in the

57
Evidence Based Model. The next chapter explains the methodology of the study
including the research questions and the sample selection.

58
CHAPTER 3 – Methodology

This chapter presents an overview of how the study was conducted including a
brief review of the purpose of the study and the research questions, how the sample
schools were selected, the instruments used and how data were collected and analyzed.
This study is one of ten studies exploring school level data in California schools
to determine how resources are being used to accomplish the vision of the school. There
has been very little research done nationally to explore school level resource use. This
study employs a purposeful sample of schools and combines both quantitative and
qualitative methods in the analysis. This study, taken together with the other studies
being conducted with similar methodology, provides a basis to begin exploring how
scarce resources are or are not used efficiently to improve student achievement in
California schools and across the country. The Evidence-Based Model (Odden and
Picus, 2008) for allocating resources is used as a means of comparison to examine how
resources are used in specific schools compared to effective research-based practices.
The schools examined in this study are schools serving diverse populations of at least
20% African American, Hispanic, or socio-economically disadvantaged students that are
outperforming other high schools in California. Of interest is the degree to which the
schools allocate resources in similar ways to achieve their goals of high performance.
To explore these issues, four research questions guided the analysis:
1.) What are the current instructional improvement strategies at the school level?
2.) How are actual resource patterns aligned with or different from the resource uses
strategies in the Evidence Based Model?

59
3.) How are resources used to implement the school’s instructional improvement
plan? (instructional vision, plan goals, etc.)
4.) How does the availability of resources effect the development of the instructional
improvement plan?
The quantitative data were compiled using the data entry system created by Lawrence
O. Picus and Associates as used in other states such as Wyoming and Arkansas. The data
entry system is aligned with the expenditure structure model created by Odden, et al
(2003) that allows examination of how resources are used at the school level to support
instructional strategies. The quantitative data, along with support from the qualitative
data were used to answer the second research question: How are actual resource patterns
aligned with or different from the resource uses strategies in the Evidence Based Model?
Simple comparative statistics were used to identify similarities and differences between
and among the Evidence Based Model recommendations and the school data from the six
school sites.
The qualitative data, collected through interviews and document analysis, were
complied into detailed case studies for each school (see appendix F). The analysis
section provides a discussion of the similarities, differences and trends found among the
six schools as well as further discussion of how the school resource allocation patterns
compare with the Evidence Based Model. These analyses help to answer the other three
research questions listed above.

60
Sample Selection
This study uses a purposeful sample of six high schools that have demonstrated
high achievement with their significant subgroups. All schools selected are traditional
comprehensive high schools without a magnet program or any kind of competitive
admission process. The schools selected may not be considered “high performing” in the
context of all schools in California, but they are some of the highest performing schools
in California that are serving significant numbers of disadvantaged students. To begin
the selection process, a 2007 API data base was downloaded from the California
Department of Education website (www.cde.ca.gov) that included all schools in the state
of California and their statistics related to the Academic Performance Index (API) and
other demographic information. The spreadsheet was filtered down to high schools with
at least 20% of their population designated as some combination of African American
and/or Hispanic students. This was accomplished by adding a column that summed the
number of African American and Hispanic students and then divided it by the total
student population to achieve a percentage of minority students. A similar computation
was made to determine the percentage of socio-economically disadvantaged students
using the number of students participating in the free or reduced lunch program. This
computation was done separate from the ethnicity computation because it was assumed
that students may fall into both categories. Schools with more than 20% of students in
either the Hispanic/African American or socio-economically disadvantaged categories
were included in the spreadsheet. All other schools were removed from consideration in
the sample. Another column was added to obtain the average API of the two

61
disadvantage minority groups along with the free or reduced price lunch students. This
last column was used to sort the remaining schools in the spreadsheet from highest to
lowest. The top twenty schools were considered for this study. Due to the researchers
time and budget restrictions, the schools selected are limited geographically to Los
Angeles, Ventura, Orange and San Bernardino counties. Of the remaining schools, six
were chosen for the study. Further data were collected (see table 3.1) for the six schools
to examine trends over three years in terms of overall API and the performance of the
significant subgroups.
Pseudonyms are used in place of school names to honor the promise of anonymity
for each school. Table 3.1 shows each school’s overall API and the APIs of the
significant subgroups along with the numbers of students in each category.

62
Table 3.1: School Demographic and Achievement Data for Sample Schools.
School Year
#
Tested
API
Base
State
Rank
Similar
Rank
#
Wht
%
Wht
Wht
API
# Af
Amer
% Af
Amer
Af
Amer
API
#
Hisp
%
Hisp
Hisp
API
#
SES
%
SES
SES
API
%
AA
or
Hisp
AVG
API
Disadv
JWHS
2008 1857 759 ? ? 794 43% 789 164 9% 724 772 42% 728 397 21% 716 50% 723
2007 1987 761 8 8 913 46% 789 157 8% 723 790 40% 733 461 23% 715 48% 724
2006 2082 734 7 5 997 48% 763 159 8% 704 806 39% 697 367 18% 682 46% 694
2005 2068 724 7 7 992 48% 754 176 9% 702 789 38% 680 362 18% 664 47% 682
KOHS
2008 2104 791 ? ? 752 36% 823 310 15% 759 749 36% 743 413 20% 729 50% 744
2007 2033 781 9 9 755 37% 804 314 15% 744 696 34% 742 427 21% 724 50% 737
2006 1951 763 8 9 758 39% 791 294 15% 718 655 34% 722 355 18% 697 49% 712
2005 1827 770 9 10 716 39% 799 290 16% 741 613 34% 719 332 18% 711 49% 724
MLHS
2008 1779 804 ? ? 985 55% 822 121 7% 734 409 23% 739 323 18% 738 30% 737
2007 1745 793 9 10 1004 58% 809 115 7% 707 390 22% 741 336 19% 743 29% 730
2006 1798 790 9 8 1043 58% 811 108 6% 725 409 23% 732 312 17% 709 29% 722
2005 1633 783 9 8 971 59% 805 99 6% - 366 22% 716 301 18% 666 28% 691
PMHS
2008 1653 750 ? ? 377 23% 816 365 22% 711 638 39% 705 531 32% 707 61% 708
2007 1559 751 8 8 364 23% 821 356 23% 701 589 38% 703 402 26% 691 61% 698
2006 1629 732 7 6 370 23% 808 376 23% 680 600 37% 683 411 25% 660 60% 674
2005 1534 734 7 7 373 24% 814 338 22% 700 579 38% 674 433 28% 649 60% 674
SRHS
2008 1263 808 ? ? 314 25% 822 155 12% 795 515 41% 779 316 25% 769 53% 781
2007 1316 798 9 10 301 23% 749 152 12% 750 558 42% 750 317 24% 749 54% 750
2006 1360 807 9 10 309 23% 847 176 13% 737 551 41% 775 307 23% 781 53% 764
2005 1350 791 9 10 312 23% 821 167 12% 725 561 42% 756 307 23% 757 54% 746
VBHS
2008 915 750 ? ? 53 6% - 169 18% 724 612 67% 746 731 80% 748 85% 739
2007 954 733 7 10 55 6% - 201 21% 695 630 66% 734 699 73% 730 87% 720
2006 991 725 7 10 60 6% - 251 25% 693 609 61% 733 703 71% 725 87% 717
2005 1009 706 6 10 60 6% - 260 26% 676 616 61% 707 675 67% 698 87% 694

63

Instruments and Data Collection
In order to maintain a standardization of the data collection among the nine
researchers collecting data from different schools in California, the researchers were all
trained over two days in June of 2008 by Dr. Michelle Turner Mangan who has
performed similar studies using the same data collection system in Arkansas and
Wyoming. Dr. Turner Mangan trained the group on the protocol to make contact with
each school site and district using appropriate letters (see appendix A) and follow-up
phone calls and emails. The training also covered the pre-interview data collection, the
interview itself and the analysis of other documentation.
After the permission letters had been sent out, the Institutional Review Board
(IRB) decided that, given the study’s parameters, IRB approval is not needed (see
appendix B). Beginning in September 2008, data were requested from each school
related to staffing, schedules and professional development expenditures. Each school
was contacted to schedule half-day interviews with the principal. The interview protocol
(see appendix C), as well as the pre-interview data collection, were standardized across
the other nine researchers conducting similar studies. The interviews included detailed
discussions about the use of resources using the data collection protocol (see appendix D)
and the data collection codebook (see appendix E). The data were input into a database
created by Lawrence O. Picus and Associates and served as a starting point in analyzing
school expenditures.
The instruments are designed to gather detailed information about how the
schools use resources to target instruction. Secondary school resource indicators (see

64

table 3.2), as described in the previous chapter, and as defined by Odden, Archibald,
Fermanich & Gross (2003), provide basic information about the school and what
resources are available.
Table 3.2: School Resource Indicators
School Building Size School Unit Size
Percent Low Income Percent Special Education
Percent ELL/LEP Expenditures Per Pupil
Professional Development Expenditures
per Teacher
Length of Core (Math, English/LA,
Science and Social Science) Class Periods
Special Academic Focus of School/Unit Core Class Size
Length of Class Periods Non-Core class Size
Length of Instructional Day Percent Core Teachers
(Source: Odden et al, 2003)

Odden et al (2003) further recommend breaking down expenditures into
instructional and non-instructional categories as part of the school expenditure structure.
These categories were defined in chapter 2 and are again listed in table 3.3 below. These
categories reflect what research has shown to be effective instructional strategies and
effective/efficient uses of resources.

Table 3.3: School Expenditure Structure
INSTRUCTIONAL NON-INSTRUCTIONAL
1. Core Academic Teachers 8. Administration
2. Specialist and Elective
Teachers/Planning and Preparation
9. Operations and Maintenance
3. Extra Help
4. Professional Development
5. Other Non-Classroom Instructional
Staff

6. Instructional Materials and Equipment
7. Student Support
(Source: Odden et al, 2003)

65

The data collection training included a codebook of definitions of the items in the
data collection protocol that were input into the database (see appendix E). The protocol
includes information on 13 categories of information and school resources: the school
profile, school contacts, district profile, district contacts, school resource indicators, core
academic teachers, specialist and elective teachers, library staff, extra help staff, other
instructional staff, professional development staff and costs, student services staff and
administration.
Data Analysis
The data gathered prior to the interviews provided some insights on each school’s
resources and how those resources are allocated according to the model above. The
interview protocol is designed to gain a detailed understanding of the schools
instructional goals and how the use of resources reflects those goals. Using the
expenditure structure model recommended by Odden et al (2003) along with the data
entry system created by Lawrence O. Picus and Associates allowed the analysis of school
resource use compared to the schools instructional vision as well as the latest research as
reflected in the Evidence Based Model (Odden & Picus, 2008) of school funding. Since
resources for schools in California are especially scarce, the efficiency of resource use
and decisions made to target resources are of great interest.
Once all the data were collected and interviews were complete, the data were
entered into the data-base. For missing or unclear, follow-up phone or email contacts
with individual principals were made. The data were checked for accuracy and cleaned
as appropriate. The data, along with information obtained from the interviews, were

66

compiled into detailed case studies on each of the six schools. These case studies serve
as the basis for the analysis in chapter four.
Each school in the study has significant numbers of disadvantaged students. After
an in-depth exploration of the performance data using information from the California
Department of Education website (www.cde.gov), the second step of the analysis was to
compare the school resource indicators to find commonalities and areas of significant
difference among the six schools. How the schools use their resources was the primary
concern of the study. Exploring how the expenditure structure categories are similar
among the schools and how their expenditures line up with the school’s instructional
vision and how it all compares to the Evidence Based Model provides an interesting
analysis of how higher performing schools serve disadvantaged students well. Also of
importance are the decisions school leaders have had to make about programs and
priorities given the expected declines in state funding and the always unpredictable
budget process.
The next chapter presents the findings of the case studies and the quantitative
analysis of how the schools are using their scarce resources to promote student
achievement.

67

CHAPTER 4 – Findings
In this chapter, the findings of the study are presented beginning with an overview
of the characteristics and performance data of the six schools. More detailed information
on each of the schools is provided in Appendix F which includes case studies on each of
the six schools. The research questions serve as a framework to review the findings from
the schools with sections on the improvement strategies that were used, how the
resources of the schools compare to the Evidence Based Model, how resources were used
to implement the schools improvement process and finally how the availability of
resources affected the schools’ development and implementation of the improvement
plan.
Summary of Study Schools’ Characteristics and Performance
The schools in this study were selected because they met two criteria. First, their
student bodies are made up of at least 20% low socio-economic status (SES), Hispanic or
African American students. Second, they are out-performing schools with similar
demographic characteristics in terms of Academic Performance Index (API) scores. API
scores are determined primarily by scores on the California Standards Tests (CSTs) and
scores on the California High School Exit Exam (CAHSEE), which students must pass in
order to graduate from High School. This section will explore the demographic
characteristics of each school and then review the performance data for those schools
compared to statewide averages on the CSTs and CAHSEE. The rigor of the courses
offered at each school will also be explored.

68

Study School Characteristics and Demographics
Each of the schools in this study has its own unique story (see Appendix F).
Some have seen rapid changes in demographics while others have been stable over time.
The average school size was 2,281 students ranging from the smallest school with an
enrollment of 1,400 students to the largest school at 2,978 students. Four of the six high
schools have enrollments over 2,000 students as shown in Table 4.1. With the exception
of one school, more than 20% of all students are considered in poverty based on their
participation in the federal free or reduced price lunch program. Only one school in the
study has a high enough percentage of students in poverty to receive Title I funding.
Table 4.1 – Characteristics of Study Schools
School Grades Enrollment
%
Disabled
(IEPs)
% Poverty
(Free/
Reduced
Lunch)
Title I
Funding
% English
Learner
%
Minority
(non-
White)
JWHS 9-12 2727 10.70% 21% NO 3.0% 57%
KOHS 9-12 2978 7.30% 21.0% NO 2.5% 51%
MLHS 9-12 2471 10.40% 15.0% NO 15.0% 45%
PMHS 9-12 2295 7.40% 30.6% NO 10.7% 77%
SRHS 9-12 1815 7.20% 29.0% NO 8.8% 59%
VBHS 9-12 1400 8.60% 64.9% YES 15.6% 94%

The percentage of English Learner (EL) students in the different schools varied
from 7.2% to 10.7%. It should be noted that several of the schools sent their beginner EL
students to programs in other schools within the district so the EL students they do have
are in higher levels of the English Language Development (ELD) program and preparing
to mainstream to regular classes. With the exception of one school, all the schools are
over half non-White. In other words, they are majority minority schools.

69

Performance Data of Study Schools
This section begins with an exploration of the API scores from 2000 to 2008 for
the study schools and for the significant subgroups. API scores reflect data from CST
scores and CAHSEE scores, so the next section provides a closer examination of those
test scores and includes statewide averages as a point of comparison. Appendix F shows
more detailed performance data on individual schools as part of each schools case study.
Figure 4.1 illustrates the API growth trends of all the schools from 2000 to 2008.
All schools have made large gains. Two have met the statewide goal of 800 for the
whole school API. The other four schools are all within 50 points of reaching the goal of
800. VBHS has made particularly impressive gains from a low of 498 in 2000 up to 750
in 2008.
Figure 4.1 – API Scores 2000-2008 for All Students
400
450
500
550
600
650
700
750
800
850
900
2000 2001 2002 2003 2004 2005 2006 2007 2008
API Scores - All Students
JWHS KOHS MLHS PMHS SRHS VBHS

For each school impressive gains have been made in closing the achievement gaps
between White students and Hispanic students and between White students and African

70

American students. Figure 4.2 shows the gains Hispanic students have made since 2000
for the six study schools. All six study schools have seen, at minimum, a 100 API point
gain for Hispanic students and all are within 100 API points of the state target of 800.
Figure 4.2 – API Scores, 2000-2008 for Hispanic/Latino Students
400
450
500
550
600
650
700
750
800
850
900
2000 2001 2002 2003 2004 2005 2006 2007 2008
API Scores - Hispanic Students
JWHS KOHS MLHS PMHS SRHS VBHS

API scores for African American students at the six study schools are shown in
Figure 4.3. (MLHS has not always had a significant number of African American
students, so API scores for some years at MLHS are not shown). The trend for African
American students is very similar to that of Hispanic students in the study schools. All
began with API scores below 600 in 2000 and have now reached at least 700, within 100
points of the state target. The results for the low SES subgroup show a very similar
trend.

71

Figure 4.3 - API Scores, 2000-2008 for African American Students
400
450
500
550
600
650
700
750
800
850
900
2000 2001 2002 2003 2004 2005 2006 2007 2008
API Scores - African American Students
JWHS KOHS MLHS PMHS SRHS VBHS

The gap between White students and Hispanic students is shown in Figure 4.4.
Note that VBHS is not represented in this graph because, at 94% minority, there is not a
significant White student population to report. The graph for the gap between African
American students and white students shows a very similar trend and is not shown here.
As figure 4.4 shows, the gap has closed for all schools. Some had larger gaps to begin
with and have made impressive gains, such as PMHS, others have steadily made
progress.

72

Figure 4.4 – The Closing of the API Gap between White and Hispanic Students
0
50
100
150
200
250
2000 2001 2002 2003 2004 2005 2006 2007 2008
API Gap between White and Hispanic Students
JWHS KOHS MLHS PMHS SRHS

This section presents performance data on the California Standards Tests (CSTs)
which all students in California take in grades 2-11. With the exception of the NCLB
Science test, all the CSTs are end-of-course exams. It is interesting to note that each
subject area shows a very different trend. In English, as shown in figure 4.5, the gains for
all schools have been slow and steady, almost linear for most. In 2003, only one school
had at least 50% of students scoring advanced or proficient in English. By 2008, all but
one school, VBHS, had students scoring at least 50% proficient or advanced. VBHS did
improve from 23% proficient or advanced in 2003, (12% below the state average) to 44%
in 2008 (surpassing the state average). All schools are above the state average, based on
the 2008 scores, and half of the schools are outperforming the state average by at least
10% of students scoring proficient or advanced.

73

Figure 4.5 – English CST Scores for All Schools, 2003-2008
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
2003 2004 2005 2006 2007 2008
% Proficient or Advanced - English CST
CA Avg JWHS KOHS MLHS PMHS SRHS VBHS

History CST trends show more variation than English Scores, but again, all
schools have increased the percent scoring proficient or advanced between 2003 and
2008. Figure 4.6 shows the ups and downs that most schools have had with History CST
scores. In most years, all schools have outperformed the state average. Four of the six
schools reached at least 50% of students scoring advanced or proficient in 2008. VBHS,
again, grew the most from a low of 13% advanced or proficient in 2003 (17% below the
state average) to 39% in 2008 (4% above the state average).

74

Figure 4.6 – History/Social Science CST Scores for All Schools, 2003-2008
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
2003 2004 2005 2006 2007 2008
% Proficient or Advanced - History CST
CA Avg JWHS KOHS MLHS PMHS SRHS VBHS

Science CST scores were very sporadic from 2003 to 2006, but since 2006,
substantial gains can be seen for all the study schools and even for the statewide average
(See figure 4.7). All six schools increased the number of proficient or advanced students
by at least 7% in science in the two year span from 2006 to 2008. KOHS gained 12%
and VBHS gained 22% in those two years.

75

Figure 4.7 - Science CST Scores for All Schools, 2003-2008
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
2003 2004 2005 2006 2007 2008
% Proficient or Advanced - Sci CST
CA Avg JWHS KOHS MLHS PMHS SRHS VBHS

Math CST scores are a noticeable exception to the positive trends in the core
subject areas. In English, Science and History almost all schools achieved more than
40% of students scoring proficient or advanced. Math CST scores have been low and
stagnant; between 10% and 25% of students scored proficient or advanced between 2003
and 2008 (see figure 4.8). MLHS is the once exception, but Math scores there have
dipped back below 40% proficient or advanced in 2008. The other five schools are right
around the state average of 21% proficient or advanced.

76

Figure 4.8 – Math CST Scores for All Schools, 2003-2008
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
2003 2004 2005 2006 2007 2008
% Proficient or Advanced - Math CST
CA Avg JWHS KOHS MLHS PMHS SRHS VBHS

In California today there is a movement to require all students to take Algebra I in
eighth grade which is the state standard. Figure 4.9 shows that the study schools have
made substantial progress in getting more students into Geometry or higher in grades
nine through eleven. Four of the schools are above the state average in this regard.
Figure 4.9 – Percent of Students Tested in Geometry, Algebra II or Summative Math
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
90.00%
100.00%
2003 2004 2005 2006 2007 2008
% Tested in Geometry or Above
CA Avg JWHS KOHS MLHS PMHS SRHS VBHS

77

Despite the increasing number of students moving to higher levels of math, and
presumably more students taking the grade appropriate Math course, scores have not
improved. For the most part, scores in Algebra I or Pre-Algebra have remained stagnant
or even declined for the study schools at the same time they are moving more students to
grade level appropriate math courses (see figure 4.10).
Figure 4.10 – CST Math Scores Only for Students in Algebra I or Pre-Algebra I
0.00%
5.00%
10.00%
15.00%
20.00%
25.00%
30.00%
35.00%
40.00%
2003 2004 2005 2006 2007 2008
% Prof or Adv in Alg I or Gen Math
CA Avg JWHS KOHS MLHS PMHS SRHS VBHS

Even for students in Geometry or above, scores have shown little growth or even
declines for all the study schools and the state average. Figure 4.11 illustrates that, even
in the higher math classes, only 20-30% of students scored proficient or advanced for all
but one school, MLHS. These numbers are indicative of the state average, so this
problem is not isolated to these six schools.

78

Figure 4.11 – CST Math Scores Only for Students in Geometry or Higher
0.00%
5.00%
10.00%
15.00%
20.00%
25.00%
30.00%
35.00%
40.00%
45.00%
50.00%
2003 2004 2005 2006 2007 2008
% Prof or Adv in Geom or Above
CA Avg JWHS KOHS MLHS PMHS SRHS VBHS

Figure 4.12 illustrates the larger problem for the state of California. In the early
grades, students showed improvement from 2003 to 2008 in terms of the percent scoring
proficient or advanced in Math. In fourth grade, Math scores statewide improved from
41% proficient or advanced in 2003, to 61% in 2008, but then after fourth grade, scores
begin to drop until students reach Algebra I in middle or high school, a requirement for
graduation. The scores rebound in Geometry and higher courses as students self-select to
move on to higher levels of math. Further discussion of this trend is beyond the scope of
this study, but this brief analysis helps put the math performance of the study schools into
a larger context.

79

Figure 4.12 – Statewide CST Math Score trend, Grades 2-11, 2003-2008
0%
10%
20%
30%
40%
50%
60%
70%
Grade 2 Grade 3 Grade 4 Grade 5 Grade 6 Grade 7 Gen
Math
Grd 8
Gen
Math
Grd 9
Alg I -
H.S.
Geom Alg 2 Summ
% Prof or Advanced - Statewide Math CSTs by Grade Level
2003 2004 2005 2006 2007 2008

Despite the low Math CST scores for the study schools (and state in general),
student scores on the Math portion of the CAHSEE for the study schools consistently
outperform the state average. Figure 4.13 illustrates that while the pass rate statewide on
the CAHSEE is slowly approaching 80% for first time test takers in tenth grade, most of
the study schools have pass rates over 85%.

80

Figure 4.13 – CAHSEE Math –Percent of Students Passing in Tenth Grade, 2005-08
70.00%
75.00%
80.00%
85.00%
90.00%
95.00%
100.00%
2005 2006 2007 2008
All Students - Math CAHSEE - % Passed
CA Avg JWHS KOHS MLHS PMHS SRHS VBHS

A similar trend in CAHSEE scores can be seen in English. While the statewide
pass rate on the English portion of the CAHSEE for first time test takers in tenth grade is
approaching 80%, the pass rates for all but one of the study schools is over 85%, and two
of the schools are approaching 95%. Similar trends can be seen for all the significant
subgroups in that they are outperforming the state averages for the comparable subgroup.

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Figure 4.14 - CAHSEE English –Percent of Students Passing in Tenth Grade, 2005-08
70.00%
75.00%
80.00%
85.00%
90.00%
95.00%
100.00%
2005 2006 2007 2008
All Students - English CAHSEE - % Passed
CA Avg JWHS KOHS MLHS PMHS SRHS VBHS

A look at the courses offered in the master schedule presents an interesting
parallel to the test data presented above. Figure 4.15 demonstrates the types of courses
offered at each school in terms of the percentage of courses that are remedial, regular and
advanced (honors or Advanced Placement). One quarter of the core courses offered at
SRHS are honors or Advanced Placement (AP); at least 12% more than any other school.
SRHS has the second highest number of students in poverty yet has the highest (or near
highest) scores in every performance category above, with the exception of Math. SRHS
also has the highest percentage of students taking Geometry or higher in Math. This
supports some of the findings in the literature that a highly rigorous curriculum free from
tracking mechanisms promotes higher test scores for all students (Burris & Welner,
2005). Each school in this study offers a balance of advanced courses and remedial
courses to meet the needs of advanced and struggling students. Algebra I courses are

82

included in the remedial course category for all schools as the course is below grade level
for high school students.
Figure 4.15 – Core Course Offerings – Percent Remedial, Regular and Advanced
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
JWHS KOHS MLHS PMHS SRHS VBHS
% Remedial % Regular % AP/Honors

The remaining sections of the chapter will address the research questions using
data from of the case studies found in Appendix F for each school. The first question
looks at the improvement strategies used by the schools. The second question examines
how the resources of the schools compare to the Evidence Based Model. The third
question addresses the use of resources to implement the strategies used by the schools.
Finally, the last question ponders how the availability of resources affected the
improvement process.
What are the Current Instructional Improvement Strategies at the School Level?
The common strategies used by the schools to improve student performance fall
into five categories that are described in more detail in this section. First, the
improvement process begins with strong leadership from the principal and, in most cases,

83

a leadership team of teachers and administrators. Second, the leadership team works with
individual departments to analyze data and develop their own assessments to better
understand student performance and where adjustments in instruction are needed. Third,
collaboration and, most importantly, time for collaboration among teachers in some sort
of Professional Learning Community (PLC) is used to look at the data and adjust
instruction. Fourth, each school provides intervention programs for struggling students
so that they can access a rigorous curriculum. Finally, each school talked about the
strategies they use to help students feel connected to the school and to foster a positive
school climate.
Leadership
Without exception, each school was led by a principal and leadership team that
talked about the importance of developing a shared vision with the staff and nurturing
buy-in in order to move the school forward. Each principal talked about the dedication of
the staff to educating all students. Some schools had the advantage of being relatively
new. The principals felt this was a distinct advantage toward developing a shared vision
and creating a positive school climate from the beginning. Other schools have had to
overcome low morale, entrenched ideas and a culture of teacher isolation that are
counterproductive to moving a school forward. The principals, in their own ways, earned
the respect of the staff as instructional leaders and each works with the leadership of the
school to promote bottom-up change and improvement. Most principals rose through the
ranks of the school or district to their leadership position. Some came from other districts
and experiences. Spending time in classrooms was cited as a key strategy for many of

84

the administrators. One in particular works to spend 80% of his time visiting classrooms.
Many of the school leaders promoted particular instructional strategies and created
rubrics for the administrative team to use when informally observing classes such as
checking for understanding or ensuring the standard and objective for each lesson is
posted in the room.
Data used to inform practice
A common theme during the interviews with the school leaders was the
importance of analyzing data. Most of the schools used Data Director as their tool for
analyzing student performance data. One school uses EduSoft and another uses Galileo
but each has and uses technology to analyze data effectively. How the data are used
varies from school to school. Some have active leadership teams that analyze data and
share with staff through department meetings. Others use a mixture of whole staff
meeting to share aggregate data and department meetings to review subject specific data.
All schools have some sort of benchmark exam process to periodically measure and
discuss student progress. Most of the schools are beginning to create both summative
and formative common assessments so that teachers can review the data in the moment
and adjust instruction as needed. None of the principals described the establishment of
formal data teams but they are all making steps in that direction with informal data
discussions during collaboration time.
Collaboration and time for regular collaboration
Collaboration is a key component of each school’s improvement. With little or no
Professional Development time provided by the district for five of the six schools, each

85

school banks minutes in order to have weekly or bi-weekly collaboration time. Most of
the schools in this study had weekly banking time for collaboration: one hour per week.
The banking time is used to meet mostly in departments to ensure that the curriculum is
aligned to the state standards and each teacher is pacing appropriately to cover as much
of the curriculum as possible in as much depth as possible with particular focus on the
key standards. The collaboration time is also used to develop common assessments and
then to analyze the results in order to adjust instruction as needed. Teachers also used the
time to discuss instructional strategies to meet the needs of students.
Intervention programs
In addition to CAHSEE intervention programs, each school offered double
periods of English and in some cases math support to help struggling students. Each
school uses the Read 180 program to help struggling English students and most used the
Measuring Up curriculum for CASHEE intervention in both Math and English. Few of
the schools were able to offer formal after school or extended day programs, but all had
informal tutoring from individual teachers outside of school hours. Some of the schools
have started using the co-teaching or collaboration model for special education classes
where students are supported in a regular education class by a special education teacher.
The collaborative classes provide students with a more rigorous course of study as
compared to a purely special education environment and also provide the support of a
special education teacher to assist the students in accessing the regular education
curriculum. One school has committed to putting all special education students who have
passed the CAHSEE into mainstream classes with special education support.

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Positive School Culture
All of the school leaders take great pride in the unique climate of their school
because the students feel connected and the staff reaches out to help and mentor students.
The success of each school breeds a self sustaining pride among students in their school.
Two of the schools used the Renaissance program to systematically reward
students for success. The Renaissance program is a class offered during the school day
made up of 50 students selected by the staff who have shown some leadership
characteristics. The students look for ways to recognize and reward students for
achievement. The Renaissance students organize events such as a g.p.a. picnic and report
card night to promote a culture of achievement.
Most of the schools also offer the Link-Crew program which assigns mentors to
help incoming ninth grade students with the transition to high school. All schools have a
period of student council that promotes clubs and other student activities. Many of the
schools also had a period or more of a conflict resolution program or peer counseling.
Some principals spoke of informal mentoring from coaches and teachers as a key
element of school culture. One of the school leaders, in particular, spoke of a coach who
meets informally with many of the African American students at the school as a sort of
support group and mentoring program that helps hold the students accountable for their
achievement. The school is trying to replicate the success of this coach with a program
for Hispanic students.

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How are actual resource patterns aligned with or different from the resource use
strategies in the Evidence Based Model?
This section provides a brief review of the Evidence Based Model for resourcing
schools and then explores in-depth how each school is resourced in comparison to the
recommendations of the Evidence Based Model (EBM) for a school of its size and
demographic breakdown. Further detail for each school is provided in the case studies
located in Appendix F.
Allan Odden and Lawrence O. Picus (2008) developed the Evidence Based Model
that identifies the elements of a school-wide instructional program research has shown to
be effective in improving student performance. The model can be used to cost out each
element to determine an adequate level of funding (Odden, 2003). By identifying and
funding specific strategies, the model guides schools in efficiently using resources to
improve student achievement (Odden, 2003). The Evidence Based Model establishes
prototypical schools and then adjusts for school size and demographics. A prototypical
high school would have a total of 600 students and an average class size of 25 students
(Odden & Picus, 2008). With 600 students, a prototypical high school would be staffed
with 24 full time core teachers. A full time teacher is referred to as a Full Time
Equivalent (FTE). In addition to the 24 core FTEs, the model also provides resources for
eight specialist teacher FTEs and three instructional facilitators or coaches and a
technology coordinator. Coaches would spend most of their time in classrooms giving
feedback to teachers and modeling lessons. They would also coordinate the instructional
program and provide other staff development (Odden & Picus, 2008).

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The Evidence Based Model includes resources for extra support and staff to assist
low income and disadvantaged students. The resources allocated for extra help vary
according to the number of disadvantaged students. The model funds one credentialed
tutor for every 100 students on free or reduced lunch. The tutor provides one-on-one
tutoring for 20 minutes per student or for a group of three students for an hour. The
credentialed tutors are trained in specific strategies and the tutoring is intended to support
the regular curriculum to catch students back up and return them to the regular classroom
(Odden & Picus, 2008). The model also funds support to English Learner (EL) students,
struggling or disadvantaged students and special education students. More severe special
education services should be fully funded by the state and are not included in the
Evidence Based Model funding formula (Odden & Picus, 2008).
The Evidence Based Model also provides formulas to fund administration,
librarians, support staff and clerical staff. The model provides ten days in the summer for
professional development in the form of a teacher institute and continued coaching
throughout the school year. Budgets for professional development, technology, gifted
students and instructional materials are based on the number of students in the school.
The next section compares how the study schools compare to the Evidence Based Model
in resource allocation.
Table 4.2 shows how the Evidence Based Model would staff a school of the same
size in terms of core and specialist teachers in comparison to how the schools are actually
staffed. The class sizes for all schools are larger than the recommended 25 students per
teacher in the core classes, but the averages are all 30 or lower. All the high schools have

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class size reduction funds in some of the ninth grade core classes so the average class
sizes in grades ten, eleven and twelve are higher than 30 students per teacher. The
schools are all understaffed in comparison to the Evidence Based Model
recommendations, but the recommended percentage of core (75%) and specialist (25%)
classes is proportional. In some cases the schools exceed the recommended proportion of
core classes versus specialist or elective classes. It is also important to note here that the
recommended size of a high school in the Evidence Based Model is 600 students. The
smallest school in this study is 2.3 times the recommended size and the largest school is
five times bigger at 1,400 and 2,978 students respectively.
Table 4.2 – Core and Specialist Teachers – Actual vs. EBM
Core Class Size Core Teacher FTEs
Specialist Teacher
FTEs
School Enrollment
EBM
Suggests
Actual
School
EBM
Suggests
(75%)
Actual
School
EBM
Suggests
(25%)
Actual
School
JWHS 2727 25 29 109
73.6
(72%)
36
29
(28%)
KOHS 2978 25 29 119
80.8
(77%)
39
24.8
(23%)
MLHS 2471 25 29.75 98.8
73.8
(75%)
32.9
24.2
(25%)
PMHS 2295 25 27 91.8
68.6
(77%)
30.6
20.6
(23%)
SRHS 1815 25 30 72.6
55
(74%)
24.2
19.4
(26%)
VBHS 1400 25 27.6 56
46.8
(83%)
18.7
9.6
(17%)

The Evidence Based Model recommends certified teacher tutors to work with
students who fall behind so that the students can quickly get caught up and back on track
with the rest of the curriculum. None of the schools in this study use such tutors. Three
of the schools offer extended day programs, but with shorter hours and less staff than the

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model recommends (see table 4.3). In all but one case, the summer school programs of
the study schools are larger than what the model recommends despite the fact that each
school only offers summer school for remediation.
Table 4.3 –Tutors, Extended Day and Summer School Programs – Actual vs. EBM
Tutors Extended Day FTEs Summer School FTEs
School Enrollment
EBM
Suggests
Actual
School
EBM
Suggests
Actual
School
EBM
Suggests
Actual
School
JWHS 2727 5.8 0 4.8 0 4.8 6.3
KOHS 2978 6.3 0 5.3 0 5.3 7.8
MLHS 2471 3.7 0 3.1 0.2 3.1 6.3
PMHS 2295 7 0 5.9 1.5 5.9 4.5
SRHS 1815 5.3 0 4.4 0 4.4 6.3
VBHS 1400 9.1 0 7.6 0.4 7.6 6.3

As table 4.4 shows, the Evidence Based Model would staff each school with
significantly more teachers in the English Learner, Special Education and Vocational
programs of each school. In addition, each school is underfunded for Gifted and Talented
programs compared to the Evidence Based Model recommendations.

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Table 4.4 – EL, Special Education, Vocation and Gifted Programs – Actual vs. EBM

English Learner
FTEs
Special Education
FTEs
Vocational FTEs Gifted Funds
School
EBM
Suggests
Actual
School
EBM
Suggests
Actual
School
EBM
Suggests
Actual
School
EBM
Suggests
Actual
School
JWHS 0.8 0.4 18
4 +
SPED
counted
in Core
7.9 4.4 $68,175 $3,276
KOHS 0.8 0.2 19.9
5.2 +
SPED
counted
in Core
13.3 7.4 $74,450 $6,612
MLHS 1.2 0.6 16.5
1 +
SPED
counted
in Core
11.2 6.2 $61,775 $8,000
PMHS 2.5 1 15.3
2.8 +
SPED
counted
in Core
7.2 4 $57,375
No
GATE
Funds
SRHS 1.6 0.2 12.1
6.4 +
SPED
counted
in Core
8.3 4.6 $45,375 $3,000
VBHS 2.2 0.2 9.3
1.4 +
SPED
counted
in Core
4.7 2.6 $35,000 $8,543

Because California recently provided an influx of funds to lower the student to
counselor ratio to 400 to 1 the schools in the study compare rather well to the
recommendations of the Evidence Based Model in terms of support staff. In most cases
the schools also compare well when it comes to secretaries and clerks. The Evidence
Based Model provides significantly more library staff than any school in the study
provided.

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Table 4.5 – Support staff, Librarians and Secretaries – Actual vs. EBM
Support Staff FTEs Librarians & Techs FTEs
Secretaries & Clerks
FTEs
School Enrollment
EBM
Suggests
Actual
School
EBM
Suggests
Actual
School
EBM
Suggests
Actual
School
JWHS 2727 16.7 13
4.5 of
each
1 Librarian,
3 Techs
18 14
KOHS 2978 18.2 11
5 of
each
1 Librarian,
3 Techs
19.9 22
MLHS 2471 13.6 12.9
4.1 of
each
1 Librarian,
2 Techs
16.5 19
PMHS 2295 16.2 16
3.8 of
each
1 Librarian,
2 Techs
15.3 10
SRHS 1815 12.5 13.6
3 of
each
1 Librarian,
1 Techs
12 12
VBHS 1400 14.7 8
2.3 of
each
0 Librarian,
1 Tech
9.3 8

The Evidence Based Model provides ten days for substitutes per teacher to be
used when the teacher is out due to illness, personal necessity or for professional
development. In California, teachers are also allotted ten days for substitutes, but only
for illness and personal necessity. Any unused days are banked for retirement. The ten
days allotted are not typically used for Professional Development. The number of school
days recommended by the Evidence Based Model is 20 more than the minimum of 180 in
California. All but one school offered the minimum of 180 school days in the calendar.
Professional Development is used very differently in the study schools compared
to what the model recommends and the funding levels are much lower in comparison to
the Evidence Based Model. The Evidence Based Model recommends a ten day summer
institute to provide professional development for teachers and to prepare for the school
year. Coaching is also provided throughout the year in the model. Most of the schools in

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this study offer three days of professional development or less as part of the teachers’
contract. In order for principals to provide professional development or send teachers to
outside trainings, they must patch together funds from a variety of sources. Each school
has been resourceful in finding funds and banking time for collaboration but none of the
schools approach the ten days of professional development suggested by the Evidence
Based Model. All principals cited the need for more professional development as one of
their first priorities if more funds were available.

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Table 4.6 – Substitutes and Professional Development – Actual vs. EBM
Substitutes Professional Development Number of Teacher Work Days
School
EBM
Suggests
Actual
School
EBM
Suggests
Actual
School
EBM
Suggests
Actual School
JWHS
10 days
per
Teacher
10 for
Illness and
Personal
Necessity
10 days
PD,
$272,700
for PD
0 days PD +
38 hours
Collaboration
Time,
$17,949 for
PD
200,
including
10 days
for
intensive
training
180, no PD days
KOHS
10 days
per
Teacher
10 for
Illness and
PN + 2 for
PD
10 days
PD,
$297,800
for PD
0 days PD +
38 hours
Collaboration
Time,
$10,952 for
PD
200,
including
10 days
for
intensive
training
180, no PD days
MLHS
10 days
per
Teacher
10 for
Illness and
Personal
Necessity
10 days
PD,
$247,100
for PD
1 days PD +
10 hours
Collaboration
Time,
$145,000 for
PD
200,
including
10 days
for
intensive
training
181, including 1 PD
day
PMHS
10 days
per
Teacher
10 for
Illness and
Personal
Necessity
10 days
PD,
$229,500
for PD
4 days PD +
38 hours
Collaboration
Time,
$26,500 for
PD
200,
including
10 days
for
intensive
training
184, including 4 PD
days
SRHS
10 days
per
Teacher
10 for
Illness and
Personal
Necessity
10 days
PD,
$181,500
6 days PD +
38 hours
Collaboration
Time, $9,500
for PD
200,
including
10 days
for
intensive
training
188, including 6 PD
days
VBHS
10 days
per
Teacher
10 for
Illness and
Personal
Necessity
10 days
PD,
$140,000
for PD
$750,000
including: 3
days PD + 18
hours
Collaboration
Time
200,
including
10 days
for
intensive
training
183, including 3 PD
days

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One school in this study provides instructional facilitators (see table 4.7), but the
two offered in Math and English are still substantially fewer than what the model
recommends. It is worth noting that this one school with instructional facilitators has
seen the most impressive gains in performance data. In terms of administration, the
Evidence Based Model and the study schools are staffed very similarly. KOHS would
receive one more assistant principal if funded according the guidelines of the model and
SRHS has one more than the model recommends.
Table 4.7 – Administration and Instructional Facilitators – Actual vs. EBM
Principal Assistant Principal
Instructional
Facilitator FTEs
School Enrollment
EBM
Suggests
Actual
School
EBM
Suggests
Actual
School
EBM
Suggests
Actual
School
JWHS 2727 1 1 4.5 4 13.6 0
KOHS 2978 1 1 5 3 14.9 0
MLHS 2471 1 1 4.1 3 12.4 0
PMHS 2295 1 1 3.8 3 11.5 0
SRHS 1815 1 1 3 4 9 0
VBHS 1400 1 1 2.3 2 7 2

In summary, the schools in this study, which are 2.3 to 5 times larger than the
Evidence Based Model recommends, have larger class sizes, fewer teachers, fewer
instructional facilitators, shorter school years, fewer support providers, fewer staff
development days, no tutors and substantially less dollars in all categorical programs than
the model recommends. The schools do all have at least the same proportion of core
classes to elective classes in the master schedule and are staffed similarly in regard to
administrators, support staff and clerical staff.

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How are the resources used to implement the school’s improvement plan?
Given that the actual resources are substantially less than what the Evidence
Based Model recommends, the schools in this study have had to use their resources
efficiently and target the needs of the school. The common strategies used by the six
schools include a distributed leadership model, use of data to inform instruction,
collaboration time for teachers to look at the data and improve strategies, intervention
programs for struggling students and a focus on building a positive learning environment.
Most of these strategies do not depend on specific resources to be implemented. They
simply involve the staff working together to use the time they have with the students to
the greatest benefit for students meeting the standards.
School Site Leadership
The schools in this study had wide disparities in terms of the support from the
district office. Some had very stable district offices that provide support and help in
moving the schools forward. Some schools are the only achieving schools in their
program improvement districts and are mostly left alone to chart their own course. Some
are the only high schools in their unified district where the focus tends to be more on the
lower grade levels. There is no common theme in terms of district leadership that helps
in explaining why these schools have been successful.
At the site level, there are some common leadership themes across the schools in
this study. Each school involved a team of teachers and administrators in the
instructional improvement process and used what Elmore (2000) refers to as “distributed
leadership”:

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In a knowledge-intensive enterprise like teaching and learning, there is no way to
perform these complex tasks without widely distributing the responsibility for
leadership (again, guidance and direction) among roles in the organization, and
without working hard at creating a common culture, or set of values, symbols, and
rituals. Distributed leadership, then, means multiple sources of guidance and
direction, following the contours of expertise in an organization, made coherent
through a common culture (p. 15).

Teachers and administrators work together to develop a bottom-up improvement process
that involves teachers looking at data in departments and developing department
strategies and common assessments which leads to more data to analyze and inform
decisions. Two of the schools in the study have benefited from a district priority to send
large numbers of teachers to local Effective Schools conferences. The principals of these
two schools, the two largest in the study, cited the ability to send large numbers of
teachers to these conferences as a key to getting their large staffs to buy into the
improvement process as they all have a common vocabulary around school improvement.
The two smallest schools in the study are also two of the newest. Principals of the
three newest schools (the two smallest and the largest school in the study) cited the
ability to hire teachers that shared the vision of the school from the start as critical to the
school’s success. Also, for the smaller schools in the study, the small size of the staffs
allows for the continued development and fine-tuning of the schools vision. The three
mid-sized schools in the study have longer histories and in some cases have had to
overcome some dysfunction among the staff and rapidly changing demographic
characteristics among the student body to develop a common vision. In these schools
there are wide disparities among the core departments in terms of buy-in to the schools

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vision. Because the process to develop buy-in is a bottom-up process, the disparity
among departments is not surprising, but it is frustrating for the school leaders.
Only one school in the study has implemented the use of instructional facilitators,
but all principals cited them as a need if more resources were available. In the place of
instructional facilitators, the schools rely on their leadership teams and collaboration
among teachers to provide professional development, analyze data and discuss
instructional strategies.
Technology resources to analyze data
All six schools in the study are allocating technology resources for computer
software such as Data Director, EduSoft or Galileo to provide teachers with performance
data on their students. The data are consistently used as a basis for discussion in
collaboration.
Data are also used to identify incoming ninth grade students who may need
additional support. Getting data for incoming ninth grade students is more seamless in
the unified districts, but even the high school districts are finding ways to access the data
from their feeder districts because they understand the importance of identifying those
students early and targeting them for success.
Collaboration Time
None of the schools in this study have the resources to provide a ten day summer
institute as recommended in the Evidence Based Model. Some of the schools have zero
days of professional development. Each school recognizes the importance of having time
for teachers to collaborate by looking at data, discussing strategies for instruction,

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developing common assessments and having conversations around common assessments.
Each staff has voted to bank minutes with longer instructional days than required in order
to provide weekly, or bi-weekly, hour-long meetings for teachers to collaborate. Four of
the six schools meet one day every week for collaboration. One meets every other week
and the sixth meets five times per year for two hours each time.
The time for collaboration is not only used to look at data and produce common
assessments, but it is also a valuable opportunity to tap the knowledge of more expert
teachers to train newer teachers. With few resources for professional development, the
collaboration time is a creative way to use in-house resources to provide training and
resources to newer or struggling teachers with very little cost. Some of the principals are
formalizing this process by using their expert teachers to present strategies to the whole
staff in larger staff meetings.
Intervention Programs to Access a Rigorous Curriculum
Each school in this study offers a balance of rigorous honors and AP level courses
and remedial or intervention programs to meet the needs of all students. Each of the
schools also meets or exceeds the Evidence Based Model’s recommendation that 75% of
the courses offered be in the core curriculum areas (English, Math, Science, Social
Science and Foreign Language). With fewer resources than the model suggests in terms
of teachers, each school made the decision to focus most of the teacher resources on the
core subject areas.
To help struggling students access a rigorous curriculum, each school has
protocols in place to identify struggling students and provide them support in English and

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Math to get caught up to grade level standards, usually with double periods of Math or
English. The Read 180 program is used by all schools to help students improve their
reading ability. The programs had different degrees of success based on comments from
the principals depending on the degree of fidelity to the program. There was not a
common math program, but half of the schools are using the Mastery Math program for
Algebra I and have high hopes for its success.
Improving school culture
All six principals spoke of the unique environment of their campus that makes
students feel connected to the school. The environments on each campus were fostered
through a combination of programs to help students feel connected and through the
efforts of individual teachers to reach out and mentor students. Few monetary resources
are required to build a positive school culture, but each principal cited it as an important
piece of the improvement process.
The Renaissance program is used at two of the schools as a formal way to
recognize individual students for their achievements. Resources are allocated to this
program as a single class period in the school day. In addition to a period in the day for
student council, some of the schools also offered a peer counseling or conflict resolution
program ranging from a single period to multiple periods in the day.
Above and beyond specific programs, athletics and other student activities offered
during the school day, the principals cited specific teachers that mentor and go out of
their way to connect with students. Some of the schools assigned teachers to mentor
struggling students. In the cases of the newer schools a positive environment was the

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norm from the beginning, but for some of the older schools, the positive environment has
been a work in progress for the last several years.
How does the availability of resources affect the development of the improvement plan?
The Evidence Based Model provides resources well above and beyond what any
of the schools in this study receive. The section above describes how the schools in this
study have overcome the lack of resources to improve student achievement. This section
describes in more detail how the trade offs that schools have had to make may be
affecting the schools improvement process.
The smallest school in this study would be resourced seven instructional
facilitators, or coaches, under the Evidence Based Model. The largest school would see
13.6 instructional facilitators. Only one school in this study has any instructional
facilitators. The schools instead use their limited collaboration time and the expertise of
the leadership team to accomplish the tasks of aligning curriculum, developing
assessments and coaching teachers.
Each school has committed resources to data analysis software that teachers can
access for information about their students. These technology resources are used
effectively to gather information, but each principal expressed that more training is
needed for teachers to access all the software has to offer. Principals also expressed
frustration with the wide disparities across their campuses in terms of the availability of
instructional technology such as Smart Boards, document cameras and LCD projectors.
As discussed earlier, the limited amount of professional development time and the
limited monetary resources allocated to professional development have necessitated the

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creative use of time and site level resources by the schools’ leadership teams. When each
principal was asked about what resources would be needed to continue the improvement
process, each one named more resources and time for professional development as the
first priority.
Few of the schools in this study offered extended day tutoring programs and those
that are offered have significantly fewer resources than the model recommends. Some of
the principals felt that interventions offered during the day are more effective due to the
difficulty of keeping students after school for help. Since none of the schools have any
certificated tutors to help students get caught up in their academic classes, as
recommended in the Evidence Based Model, the intervention programs offered at the
study schools are a limited number of class periods offered for remediation. Once a
student lands in a remedial class, it is difficult to accelerate that student to grade level
work.
The schools that allocated resources to collaborative or co-teaching classes for
special education students found that the performance data on those students improved
dramatically. Most of the schools did not have the available resources to offer a
significant number of collaborative special education courses so that those students could
access the regular education content with the support of a special education teacher.
Under the Evidence Based Model, those resources would be available.

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CHAPTER 5 – Discussion

This final chapter presents a brief overview of the study, a discussion of the
findings related to what the literature identifies as effective improvement strategies,
possible implications of this study on practice and policy and suggestions for future
research.
This study used a purposeful sample of six southern California high schools with
demographic characteristics of at least 20% African American, Hispanic or low SES
students that are outperforming similar schools to determine their instructional strategies
and resource use patterns. Case studies which include interview data, performance data
and information on school level resource use were conducted and the information was
analyzed using the data entry system created by Lawrence O. Picus and Associates which
is aligned with the expenditure structure model created by Odden, et al (2003). The
Evidence Based Model, developed by Odden and Picus (2008), which identifies the
elements of a school-wide instructional program that research has shown to be effective
in improving student performance, was used as the framework for analyzing the resource
use patterns of the study schools.
The findings indicate that the study schools have fewer resources than
recommended by the Evidence Based Model. Despite the lack of resources, there were
some similarities to the model in terms of the proportion of teacher FTEs devoted to the
core subject areas versus electives and in terms of resource allocation to administration,
student support services and office staff. The next section provides a discussion of the

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instructional improvement strategies used by the schools in comparison to the strategies
found to be effective in the literature that informs the Evidence Based Model.
Summary of Findings
Three meta-analysis studies, by Marzano (2003), Odden (2007) and Duke (2006),
on effective strategies to improve schools were summarized in the review of literature.
The common findings among the three studies to improve student performance were:
high expectations for students, timely small group support, the use of data to make
decisions and inform practice, distributed leadership that empowers teachers to improve
student achievement, the protection of instructional time including maximizing the time
spent on the core subject areas and continual professional development with coaches as a
key strategy. The strategies found in the study schools, as described in the previous
chapter, support the body of research on effective improvement strategies. Evidence
from the study schools of the six strategies listed above is discussed here in more detail.
High Expectations
This study did not collect specific data on the rigor of the course of study such as
an examination of the percentage of graduating students that fulfill the minimum a-g
requirements to be considered for admission to a California State University or a
University of California campus. The a-g requirements are above and beyond what is
required by each district in this study in order to graduate from high school. Analysis of
student work and the rigor of day to day classroom instruction were also beyond the
scope of this study. Given that this study did not focus on analyzing the rigor of the

105

courses offered or any specific measure of high expectations for students it is difficult to
measure the degree to which the schools hold high standards for student achievement.
Keeping the limitations of the study in mind, there is still some evidence from the
case studies that each school holds high expectations for students. Examinations of each
school’s master calendar showed a balance of remedial, regular and advanced (honors
and Advanced Placement) classes. None of the schools had remedial tracks for students
(other than in Special Education) that would preclude a student from a college
preparatory curriculum. None of the schools offered a substantial number of non-college
preparatory classes. The principals spoke of high expectations for students and the
exploration of CST and CAHSEE data in the previous chapter indicate that students are
achieving above the state average in all subject areas. Most of the principals specifically
mentioned that efforts have been made to remove barriers to students entering honors and
AP classes.
Timely small group support to help struggling students
None of the schools in this study had the available resources to offer certificated
tutors, as the Evidence Based Model recommends, to provide immediate intervention to
students who fall behind so that the students can stay caught up with the regular
curriculum. Each school does offer double periods of Math and English support for
struggling students and each school has protocols in place to identify the students that
need those interventions as quickly as possible when they enter ninth grade. Each school
also offers CAHSEE intervention programs for students who have not or may not pass
the CAHSEE in Math or English. Some of the schools offer extended day tutoring

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programs, but most did not have the resources to fund such a program. Given the
resources the schools do have, they are all effectively reaching out to struggling students,
but, given more resources, they could do even more to help struggling students access a
rigorous curriculum. The concept of tutors to help students who fall behind to get caught
back up quickly so they can return to the regular classroom is not something that has been
explored by any of the schools in this study. If such a program were put in place
additional resources would be needed to train the staff on the effective use of tutors.
Using data to make decisions and inform practice
Each principal spoke at length about the use of data to make decisions and to
enhance teacher collaboration. The methods for using and distributing the data varied
among the schools, but there was a common practice of teachers looking at data in small
groups and identifying areas of needed improvement. To varying degrees, teachers at
each school are creating common formative and summative assessments to provide more
data for discussion. Data analysis is a key component of the teacher collaboration time.
At each school resources have been allocated for software such as Data Director to assist
teachers and other school staff in analyzing the data.
The six schools in the study were in different places in their evolving use of data.
Each school would benefit from more training in the effective use of data teams. As each
principal pointed out, the buy-in to the process is a key to effective use of teacher data
discussions. The training and use of data should include effective teacher created
formative and summative assessments so that teachers are discussing student
performance both in the moment (formative) and in a reflective capacity (summative).

107

Distributed Leadership
Each principal emphasized the importance of a teacher leadership team that shares
in the decision making process and helps set the direction of the school. Creating change
from the bottom up was especially important for some of the school sites to overcome
entrenched views and teacher isolation in developing collaborative work groups focused
on improving student performance. Most of the principals spend a significant portion of
their time in classrooms and encourage their administrative teams to do the same. In
some cases they used feedback forms that measure the use of specific school-wide
strategies. Most of the principals talked about the leadership team’s role in keeping up
with the latest research and providing professional develop to the staff using the expert
teachers on the campus as resources, especially given the lack of resources for
professional development.
Focus on the core subjects and protection of instructional time
Each school in this study focused most of their resources on the core curriculum.
This is a key element of the Evidence Based Model. Although none of the schools are
resourced as the Evidence Based Model would recommend as far as the number of core
teachers, some did exceeded the Evidence Based Model proportions that 75% of the
teacher FTEs are in the core subject areas. This common finding among the schools in
this study, which is also supported in the literature, suggests this is a key element for
school improvement. This strategy can be easily replicated and requires no additional
resources (although an increased number of teachers would add to the benefits).

108

VBHS, which has made the largest performance gains with arguably the most
challenging population, devotes over 80% of FTEs to the core subject areas. Even with
9.2 fewer core FTE teachers than recommended in the Evidence Based Model,
proportionally, there is a clear resource focus on the core subject areas. With more
highly qualified teachers with the same level of buy-in, smaller class sizes and the tutors
recommended in the model, VBHS would likely have a much higher level of
achievement and higher percentages of students mastering standards. This finding
suggests that for schools with less than 75% of their teachers in the core subject areas, an
increase in core teachers, even if only proportionally, would have a large impact on
student achievement.
Some of the schools use a block schedule to provide larger blocks of time during
the week for each class. Other schools use a traditional six period schedule. There is no
data in this study to suggest that one is more effective than the other.
Continual professional development and instructional coaches
Despite the large gap between what the Evidence Based Model recommends for both
instructional coaches and professional development funds and time, each school has
found creative ways to develop their professional staff and find time for them to meet and
share.
Only one school uses available resources for instructional coaches and the principal
cited the coaches a key component of the improvement process. Some of the other
principals cited the need for coaches as a critical need to move the school forward.

109

Although none of the schools offers a ten day summer institute for teachers, as the
Evidence Based Model recommends, they all value collaboration time for teachers to
meet and discuss data and strategies. Each school banks time to allow for weekly or bi-
weekly collaboration time. The principals all cited this time as invaluable to the
improvement process. In larger schools, where common planning periods, which are
called for in the Evidence Based Model, are difficult to accommodate in the master
schedule, this use of banking time to allow for collaboration is critical.
Implications for Practice
The analysis of the resource use patterns and instructional improvement strategies
employed by the study schools lends support to the literature on improving schools.
Specifically, the schools in this study have found success with their significant
disadvantaged populations by emphasizing the core subject areas, targeting intervention
programs to students in need as quickly as possible, using data to guide collaboration and
make decisions, involving teachers in the decision making process and finding ways to
provide continual professional development even with few resources to do so. None of
the schools demonstrated any highly innovative strategies to improve student
achievement; instead, they focus their limited resources on what is proven to work in
schools. Instead of being distracted by the latest quick fix strategy, the staff and
leadership focus on the proven day-to-day work of improving student performance.
Conversations in collaboration (in most cases weekly) are guided by data and are targeted
to improve classroom instruction. Administrators are in the classrooms lending support

110

and guidance in the improvement process. With the limited resources available this
efficient mode of operation has served these schools well.
The one school using instructional coaches, VBHS, identifies the coaches as a key
component to the improvement efforts. Given the impressive performance gains at
VBHS, with a 252 point API growth in eight years, the use of coaches seems a wise use
of resources. The principal feels the coaches are effective because they are well
respected by the staff as former teachers and teacher leaders of the school. This suggests
that the quality of the coaches and the buy-in from the staff is an important consideration.
The coaches also represent a further resource commitment to the core subject areas
beyond the 80% of core teachers at VBHS.
Without any influx of resources there are still important lessons for school and
district administrators from this study. Perhaps most importantly, and easiest to
implement, is the proportional focus of teacher FTEs on the core subject areas. High
expectations and a rigorous curriculum must accompany the increased resource focus on
the core. The second lesson, which is also relatively easy to implement and requires no
resources, involves the creative use of teacher time to create collaboration time. Using a
Professional Learning Community model to guide the use of the collaboration time in the
analysis of student data is needed to ensure that the collaboration time is not wasted on
activities that do not directly impact student achievement. A third lesson that requires no
additional resources is a distributed leadership approach. There is no formulaic way to
implement this strategy as it relies on the talents of an effective leader who can build

111

capacity and buy-in from the staff in order to implement a PLC model, foster high
expectations, guide the use of data and provide site-level professional development.
If more resources were available, school and district leaders should consider the
body of research on school improvement to make informed decisions on how to use the
resources to gain the most improvement in student achievement per dollar. Again, the
VBHS example suggests that instructional coaches, if implemented effectively, can have
a significant impact on instruction and student achievement. If resources are used to hire
more teachers, research and the lessons from this study indicate that the increased FTEs
would have the most impact if resourced to the core subject areas. Though this study was
not able to gather any data on the use of certificated teacher tutors as suggested in the
Evidence Based Model, other research indicates that it is an effective use of resources to
improve achievement for struggling students.
Implications for Policy Makers
A portion of the review of literature was focused on what happens when schools
or districts see influxes of funds. Some found that influxes of funds went to increases in
teacher salaries (Lankford & Wyckoff, 1995; Hanushek & Rivkin, 1997; Picus 1994) or
to reduce class sizes and increase the number of teachers (Odden, et al., 1995; Hanushek
& Rivkin, 1997, Picus 1994, Odden & Picus, 2008). These resource use strategies,
increasing teacher salaries and reducing class sizes, are not supported by the literature on
what is most effective in improving student performance. Some researchers argue that
the efficiency of how resources are used is more important than the amount of resources
(Hanushek & Rivkin, 1997).

112

This study seems to indicate that schools with limited resources can work efficiently
to employ proven strategies and improve student achievement. Policy makers, when
providing more resources to schools and districts, would be well served to consider the
research on effective improvement strategies. Funds that are targeted to these strategies
may prove more beneficial than discretionary funds that may be used to raise teacher
salaries or simply reduce class sizes.
The Evidence Based Model for funding schools provides policy makers with a
blueprint for funding schools based on the latest research on what works in schools.
Schools and districts are often skeptical about the longevity of new resources so those
resources are often not used to invest in long-term programs. In order for schools to
invest in more teachers in the core subject areas, teacher tutors, intervention programs or
other strategies suggested in the research on school improvement, there must be a long
term commitment to these programs at the state level. If schools or districts feel the
resources are temporary they will not be used effectively to gain long-term improvements
in student achievement. New resources should be allocated according to the
recommendations of the Evidence Based Model, and with a long term commitment,
through categorical programs or with incentives that target specific strategies instead of
though block grants that may direct the funds to other, potentially less effective
programs.
Even without influxes of new resources, policy makers should consider incentive
programs that would help districts and schools to direct their limited resources to the

113

most effective strategies including a proportional focus of FTEs on the core subject areas
of 75%, collaboration time and a distributed leadership model.
Recommendations for future research
This study adds to a growing body of school level resource use studies using the
school-level expenditure framework developed by Odden et al. (2003) to examine what
strategies schools are using. More of these school level studies are needed to draw out
larger implications and better inform practice and policy. A suggested improvement to
the data collection protocol is to look more in depth at the rigor of the course of study
offered at a school site as a measure of what the literature refers to as high expectations
for students. This is especially helpful at the high school level where it could reasonably
be determined what courses fulfill the college entrance requirements in the given state; in
California, this would mean an analysis of what courses meet one of the a-g
requirements. It would also be informative to examine what percent of the graduating
classes meet the college entrance requirements of the given state and what percent of the
students are enrolled in Advanced Placement or International Baccalaureate classes and
their pass rates on the AP or IB exams. An analysis of the rigor of the adopted textbooks
would also provide some data on the day-to-day classroom expectations of a school.
This study only looked at schools that have significant disadvantaged populations
that are outperforming schools with similar demographics. Comparisons between the
resource use patterns and improvement strategies of these schools compared to schools
that are not performing well may prove to be a worthwhile study.

114

Apart from further research on school level resource use, the concerning trend in
California Math scores discussed in chapter four requires further study. Figure 5.1 shows
again the percent of students scoring proficient or advanced on the CSTs in second grade
Math through the high school summative exam.
Figure 5.1 – Statewide CST Math Score trend, Grades 2-11, 2003-2008
0%
10%
20%
30%
40%
50%
60%
70%
Grade 2 Grade 3 Grade 4 Grade 5 Grade 6 Grade 7 Gen
Math
Grd 8
Gen
Math
Grd 9
Alg I -
H.S.
Geom Alg 2 Summ
% Prof or Advanced - Statewide Math CSTs by Grade Level
2003 2004 2005 2006 2007 2008

Figure 5.1 suggests that, state-wide, students are falling further and further behind
in their level of Math comprehension each year. Only about 15% of students state-wide
are scoring proficient or advanced in Algebra by the time they reach Algebra I, a
graduation requirement. Further study is needed to determine the cause of the rapid and
precipitous decline and policy solutions are needed.

115

Concluding comments
As this study is completed, it seems futile to recommend increased resources for
schools targeted to specific improvement strategies. The state budget crisis, as part of the
larger global economic downturn, presents the reality that school budgets will be cut
drastically over the coming months and perhaps years. Still, the implications of this
study go beyond just an argument for more dollars for professional development,
intervention programs and other effective school improvement strategies. The hope that
can be gleaned from these case studies on effective schools in this political end economic
climate is that targeted, efficient, research based strategies can be used with existing
resources to improve student achievement.

116

REFERENCES

Adams, J. E. (1994). Spending school reform dollars in Kentucky: Familiar patterns and
new programs, but is this reform?” Educational Evaluation and Policy Analysis,
16(4), 375–390

Anderson, S. Medrich, E. & Fowler, D. (2007). Which Achievement Gap? Phi Delta
Kappan, 88, 7

Baker, B. (2005). The emerging shape of educational adequacy: From theoretical
assumptions to empirical evidence. Journal of Education Finance, 30(3), 259
-287.

Brinson, V. R., & Mellor, L. (2005, March). How are high-performing schools spending
their money? A case study. Paper presented at the annual meeting of the American
Education Finance Association, Louisville, KY. Retrieved September 20, 2006,
from http://www.nc4ea.org/files/Atlantic.pdf#search=%22How%20are%20high-
performing%20schools%20spending%20their%20money%3F%22.

Burris, C. & Welner, K. (2005). A special section on the achievement gap: Closing the
achievement gap by Detracking. Phi Delta Kappa, 86(8).

Chambers, Jay, Levin, Jesse and DeLancey, Danielle (2007). Efficiency and Adequacy in
California School Finance: A Professional Judgment Approach. From Getting
Down to Facts study summaries downloaded June 16, 2008 from www.irepp.net

Darling-Hammond, L. (1999). Teacher Quality and Student Achievement: A review of
state policy evidence. Center for the study of teaching and policy. December
1999.

Duke, D. L. (2006). What we know and don’t know about improving low-performing
schools. Phi Delta Kappan, 87(10), 728-734.

Duncombe, William and Yinger, John (2007) Understanding the Incentive in California’s
Education Finance System. From Getting Down to Facts study summaries
downloaded June 16, 2008 from www.irepp.net

EdSource. (2006, October) Proposition 98 Guarantees a Minimum Level of Funding for
Public Schools. Mountain View, CA

EdSource. (2007, May) Commentary by John Mockler. Retreived on July 4, 2008 from
http://www.californiaschoolfinance.org/IssuesCommentarynbspnbsp/MoneysWor
thMocklerCommentary/tabid/162/Default.aspx

117

EdSource. (2008, February) The Governor’s Budget for 2008-09 Proposes Historic Cuts
for Education. Mountain View, CA

EdSource. (2008a) California’s School Finance System: The Basics. Retreived June 24,
2008, from http://www.californiaschoolfinance.org/FinanceSystem/tabid/54/
Default.aspx

EdSource. (2008b) How Does California’s Education Spending Compare with that of
Other States? Retreived June 24, 2008 from
http://californiaschoolfinance.org/BudgetandFunding/FrequentlyAskedQuestions/
FAQCaliforniaSpendingComparisons/tabid/183/Default.aspx

Elmore, Richard (2000). Building a New Structure for School Leadership. Washington,
D.C.: Albert Shanker Institute.

Ferguson, Ronald F. (1991). Racial Patterns in How School and Teacher Quality Affect
Achievement and Earnings. Challenge. 2(1), p. 1-35.

Firestone, W. A., Goertz, M. E., Nagle, B., & Smelkinson, M. F. (1994). Where did the
$800 million go? The first years of New Jersey’s quality education act.
Educational Evaluation and Policy Analysis, 16(4), 359–374.

Fuller, E. J., (1999). Does teacher certification matter? A comparison of TAAS
performance in 1997 between schools with low and high percentages of certified
teachers. Austin: University of Texas at Austin, Charles A. Dana Center.

Gandara, Patricia and Rumberger, Russell W. (2007). Resource Needs for California’s
English Learners. From Getting Down to Facts study summaries downloaded
June 16, 2008 from www.irepp.net

Guskey, T. (2007, December). The Power of Formative Classroom Assessment Depends
on How You Use The Results. Educational Leadership, 28-35.

Hanushek, E. (2006). Courting Failure: How School Finance Lawsuits Exploit Judges’
Good Intentions and Harm our Children. Stanford, CA: Hoover Press.

Hanushek, E. & Rivkin, S. (1997). Understanding the Twentieth-Century Growth in U.S.
School Spending. Journal of Human Resources 32(1), 35–68.

Hill, Paul (2008) Spending Money When it is Not Clear What Works. Peabody Journal
of Education. 83, p. 238-258.

118

Imazeki, Jennifer (2007). Assessing the Costs of K-12 Education in California Public
Schools. From Getting Down to Facts study summaries downloaded June 16,
2008 from www.irepp.net

Kirst, M. (1977). What happens at the local level after school finance reform? Policy
Analysis 3(1), 302–324.

Kirst, Michael W. (2007). The Evolution of California’s State School Finance System and
Implications from Other States. From Getting Down to Facts study summaries
downloaded June 16, 2008 from www.irepp.net

Ladd, Helen, Chalk, R. and Hanse, Janet (Eds.) (1999). Equity and Adequacy in
Education Finance: Issues and Perspectives. Washington, DC: National Academy
Press.

Lankford, H. & Wyckoff, J. H.. (1995). Where has the money gone? An analysis of
school spending in New York. Educational Evaluation and Policy Analysis,
17(2), 195–218.

Lindseth, Alfred A. (2006). The Legal Backdrop to Adequacy. In Hanushek, E. (2006).
Courting Failure: How School Finance Lawsuits Exploit Judges’ Good Intentions
and Harm our Children. Stanford, CA: Hoover Press.

Marzano, Robert J. (2003). What Works in Schools: Translating Research Into Action.
Alexandria, VA: Association for Supervision and Curriculum Development.

Mockler, John (2007). Are Californians Getting Their Money’s Worth from Their Public
Schools? Retrieved July 4, 2008 from
http://www.californiaschoolfinance.org/IssuesCommentarynbspnbsp/MoneysWor
thMocklerCommentary/tabid/162/Default.aspx

Monk, D.H., Roellke, C. F. & Brent, B. O. (1996). What education dollars buy: An
examination of resource allocation patterns in New York state public school
systems. Madison, WI: University of Wisconsin, Wisconsin Center for Education
Research, Consortium for Policy Research in Education. Retrieved October 1,
2006, from
http://eric.ed.gov/ERICDocs/data/ericdocs2/content_storage_01/0000000b/80/22/
8b/34.pdf

Odden, A. (2003). Equity and adequacy in school finance today. Phi Delta Kappan,
85(2), 120-125.

Odden, A. (2007). Redesigning School Finance Systems: Lessons from CPRE Research.
CPRE Policy Briefs. RB-50

119

Odden, A., Archibald, S., Fermanich, M., & Gross, B. (2003). Defining school-level
expenditures that reflect educational strategies. Journal of Education Finance,
28(3), 323-356.

Odden, A., Goertz, M., Goetz, M., Archibald, S., Gross, B., Weiss, M., & Mangan, M. T.
(2008). The cost of instructional improvement: Resource allocation in schools
using comprehensive strategies to change classroom practice. Journal of
Education Finance. 33(4). p. 381-405.

Odden, A., Monk, D., Nakib, Y., & Picus, L. (1995). The Story of the Education Dollar:
No Academy Awards and No Fiscal Smoking Guns. Phi Delta Kappan, 77(2),
161-168.

Odden, A., Picus, L. O., et al. (2005). An Evidence-Based Approach to School Finance
Adequacy in Wyoming. Report prepared for the Wyoming Legislature. Report
available at
http://legisweb.state.wy.us/2006/interim/schoolfinance/Recalibration/WY%20RecaFin
al.pdf

Odden, A.R. and Picus, L.O. (2008). School Finance: A Policy Perspective, 4
th
Edition.
New York, NY: McGraw-Hill.

Picus, Lawrence O. (1991). "Incentive Funding Programs and School District Response:
California and Senate Bill 813" Educational Evaluation and Policy Analysis,
13(3), 289-308

Picus, L. O. (1993). The allocation and use of educational resources: District level
evidence from the Schools and Staffing Survey. Paper prepared for the Consortium
for Policy Research in Education Finance Center, University of Wisconsin–
Madison. Retrieved October 1, 2006, from
http://eric.ed.gov/ERICDocs/data/ericdocs2/content_storage_01/0000000b/80/26/
53/4b.pdf

Picus, L. O. (1994). The Local Impact of School Finance Reform in Texas. Educational
Evaluation and Policy Analysis 16(4), 391–404.

Rebell, M. (2007). Professional Rigor, Public Engagement and Judicial Review: A
Proposal for Enhancing the Validity of Education Adequacy Studies. Teacher
College Record 109(6) ID Number 12743, Available at
http://www.tcrecord.org/Content.asp?ContentID=12743

Rothstein, R. & Miles, K. H. (1995). Where’s the money gone? Washington, DC:
Economic Policy Institute.

120

Southwest Educational Development Laboratory (SEDL). (2003). Examination of
resource allocations in education: Connecting spending to student performance.
Austin, TX: Author.

Studer, Quint (2007). Results That Last: Hardwiring Behaviors That Will Take Your
Company to the Top. Hoboken, NJ: Wiley and Sons, Inc.

Will, G.F. (2005, April 10). One Man’s Way to Better Schools. Washington Post. B7.

121

APPENDIX A – Site Permission Letter

July 1, 2008

MEMO

To: School Resource Allocation Use Study Participants
From: Chris Coulter, Researcher
RE: Research Study Information and Site Permission Letter

Thank you for your preliminary agreement to participate in my dissertation study. This memo provides a
brief description of the study. In addition, please find the “site permission letter” template attached to this
memo. In order to proceed with the study I must submit this letter of permission with your signature on
your school’s letterhead to the Institutional Review Board (IRB) at USC. I would greatly appreciate it if
you could please copy the letter on to your school’s letterhead, sign it and return it in the attached
envelope. If you prefer that I send you the text electronically, please send me an email (cdcoulte@usc.edu)
and I will send it to you right away.

After confirming receipt of the “Site Permission Letter,” I do not anticipate troubling you again until end-
of-summer/early fall to set an appointment. However, if you would like to schedule earlier, please let me
know your preferred date(s). As I mentioned in our initial conversation, the interview is lengthy – part of
the reason you may be inclined to include additional staff members – I know and respect how busy you are!

I have the privilege of working with Larry Picus, Ph.D. at the University of Southern California, a
nationally recognized expert in the area of school finance adequacy – the topic of my dissertation. The
basic premise is that we have a body of research about effective instructional practices along with
measurable academic achievement standards, definitions of academic proficiency, and an expectation that
all students will achieve those levels of proficiency. At the same time, schools in California are funded
through a political process that is not built around achieving the states performance expectations. I hope to
contribute to research efforts that have begun to paint a picture of what an adequate education looks like by
identifying resource use (e.g., FTEs teaching English, instructional minutes, FTEs serving as classroom
aides, etc.) at schools in California that are having the most success in improving the achievement of
minority and socio-economically disadvantaged students. The ultimate hope is to figure out how much it
costs to provide every child with the resources s/he needs in order to achieve proficiency.

This fall I would like to conduct a structured interview with you and/or appropriate staff members (e.g.,
Title I coordinator, assistant principal(s), department chairs – as you see fit). The interview follows a
specific format and includes examination of a variety of documents (e.g, master schedule, bell schedule,
school improvement plan, budgets). I hope to conduct the data-collection interviews in October and
November. Although the data collected are public record types of information, your school will remain
completely anonymous for the purposes of this study.

Thank you again for this initial commitment to help me complete my Ed.D. while contributing to research
that turns out to be extremely timely.

Please do not hesitate to contact me with any thoughts or questions. Again, thank you for assisting in this
research project. Your time and help are greatly appreciated.
cdcoulte@usc.edu 415-286-3127 (cell) 818-249-5871, ext 1217 (work)

122

APPENDIX B – Determination of NOT Human Subjects Research

UNIVERSITY OF SOUTHERN CALIFORNIA
UNIVERSITY PARK INSTITUTIONAL REVIEW BOARD
FWA 00007099
Determination of NOT Human Subjects Research

Date: Tue Jul 22 10:30:36 2008
Principal Investigator: Lawrence O. Picus
Faculty Advisor: Lawrence O. Picus
Co-Investigators: Christopher Coulter
Project Title:
USC UPIRB # (Resource Allocation and Use in California)
The University Park Institutional Review Board (UPIRB) designee reviewed the information you
submitted pertaining to your study on and concluded that the project does not qualify as Human
Subjects Research.*

This project focuses on Educational Resource Allocation and Use. This project is not collecting
information about subjects, but rather seeing information about how they perform their job and
use the resources available to them. The research activities as described do not meet the Federal
definition of a human subject and are not subject to the requirements of 45 CFR 46 or continuing
review.

This review and opinion is based on the information provided and is not valid if the proposed
project is not exactly as described, or if information has been withheld. If your project design
changes in ways that may affect this determination, please contact the IRB for guidance.

Sincerely,

Include Reviewers Name

*From 45 CFR 46.102, The Federal Regulations on Human Subjects Research

Human Subject: A living individual about whom an investigator (whether professional or student)
conducting research obtains:
data through intervention or interaction with the individual, or identifiable private information.

Research : A systematic investigation, including research development, testing, and evaluation,
designed to develop or contribute to generalizable knowledge.

123

APPENDIX C – Open-Ended Data Collection Protocol - School Sites

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?
o 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?
o 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)
o Were teachers trained in a specific instructional strategy?
o How did you know that the instructional strategies were being
implemented?

124

B. What were the resource pieces of the strategy? How long have the
resources been in place?

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 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)

125

F. What additional resources would be needed to continue and expand
your efforts?

126

APPENDIX D – Data Collection Protocol

School Profile
School Name School Pseudonym

Address

City State Zip
CA
Phone Fax

Website

NOTES:

127

School Contact (1)
Title
Principal
Honorific First Name Last Name

Phone # Fax #

Email Address

NOTES:

School Contact (2)
Title

Honorific First Name Last Name

Phone # Fax #

Email Address

NOTES:

School Contact (3)
Title

Honorific First Name Last Name

Phone # Fax #

Email Address

NOTES:

128

District Profile
District Name

District State ID

District Contact (1)
Title
Superintendent
Honorific First Name Last Name

Phone # Fax #

Email Address

NOTES:

District Contact (2)
Title

Honorific First Name Last Name

Phone # Fax #

Email Address

NOTES:

District Contact (3)
Title

Honorific First Name Last Name

Phone # Fax #

Email Address

NOTES:

129

School Resource Indicators
Current Student Enrollment

Pre-Kindergarten Student Enrollment

Grade Span

Number of ELL Students

Number of Students Eligible for Free- and Reduced-Price Lunch
(FRL)

Total Number of Special Education Students (IEPs)

Number of Special Education Students (self-contained)

Total Length of School Day

Length of Instructional Day

Length of Mathematics Class

Length of Reading or English/LA Class

Length of Science Class

Length of Social Studies Class

Length of Foreign Language Class

AYP

NOTES:

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Core academic teachers
(Self-contained Regular Education)
FTEs

Kindergarten
(Full day program)
Grade 1

Grade 2

Grade 3

Grade 4

Grade 5

Grade 6

Grade 7

Grade 8

Grade 9

Grade 10

Grade 11

Grade 12

English/Reading/L.A.

History/Soc. Studies

Math

Science

Foreign Language

NOTES:

131

Specialist and Elective Teachers
/Planning and Prep
FTEs
Art

Music

PE/Health

Drama

Technology

Career & Technical Education

Drivers Education

Study Hall

Athletics

Other Specialist & Elective Teachers

Other Specialist & Elective Teachers Description:

NOTES:

Library Staff
FTEs
Librarian

Library Media Specialist

Library Aide

NOTES:

132

Extra Help I FTEs or Dollars ($)
Certified Teacher Tutors

Non-Certified Tutors

ISS Teachers

ISS Aides

Title I Teachers

Title I Aides

ELL Class Teachers

Aides for ELL

Gifted Program Teachers

Gifted Program Aides

Gifted Program Funds
$
Other Extra Help Teachers

Other Extra Help Classified Staff

NOTES:

Extra Help II FTEs
Special Ed. Teacher (Self-contained for severely disabled students)
Special Ed. Inclusion Teachers

Special Ed. Resource Room Teacher

Special Ed. Self-contained Aides

Special Ed. Inclusion Aides

Special Ed. Resource Room Aides

NOTES:

133

Extra Help III
Number of Extended Day Students

Minutes per Week of Extended Day Program
minutes
Teacher Contract Minutes per Week
minutes
Extended day Teachers

Extended Day Classified Staff

Description of Extended Day Classified Staff

Minutes per Week of Summer School
minutes
Length of Session (# of Weeks)
weeks
School’s Students Enrolled in Summer School

All Students in Summer School

Summer School Teachers

Summer School Classified Staff

NOTES:

Other Instructional Staff FTEs and Dollars ($)
Consultants
(other than pd contracted services)
$
Building substitutes and other substitutes

Other Teachers

Other Instructional Aides

Funds for Daily Subs

$
NOTES:

134

Professional Development Dollars ($) and FTEs
Number of Prof. Dev. Days in Teacher Contract

Substitutes and Stipends (teacher time)

$
Instructional Facilitators/Coaches

Trainers/Consultants

$
Administration

Travel

$
Materials, Equipment and Facilities

$
Tuition & Conference Fees

$
Other Professional Development

$
Other Professional Development Staff Funded
with Federal Dollars:

NOTES:

Student Services FTEs
Guidance

Attendance/Dropout

Social Workers

Nurse

Parent advocate/community liaison

Psychologist

Speech/O.T./P.T.

Health Asst.

Non-teaching aides

Other Student Services

Description Of Other Student Services Staff:

NOTES:

135

Administration FTEs
Principal

Assistant principal

Other Administrator

Description of Other Administrator:

Secretary

Clerical staff

Technology Coordinator/ I.T.

Security

Custodians

NOTES:

Elementary School Class Sizes
Section 1 Section 2 Section 3 Section 4
Special
Education

Grade 1
Grade 2
Grade 3
Grade 4
Grade 5
Grade 6
Grade 7
Grade 8

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APPENDIX E – Data Collection Codebook

This Codebook 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: Each researcher has developed his/her own criteria to identify
California schools to include in this study.
B. School State ID: This is the CDS identification number that the state has
assigned the school.
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”
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
K. Address Line 2: (optional) Second line of street address of the contact person

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L. City: City of the contact person
M. State: “CA”
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 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
K. Address Line 2: (optional) Second line of street address of the contact person
L. City: City of the contact person
M. State: “CA”
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 2008-09 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
(http://www.k12.wy.us/FP/title3/Wy_ELD_ELA.pdf).
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 Plan
(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 Plan (IEP) indicating their
eligibility for special education services and who learn primarily (at least 60%
of the school day*) outside of a regular education classroom.
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.

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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.
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.”

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), Courteny Cox Arquette (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

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may include decimals. In the notes sections, enter each teacher’s name that
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.

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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 a 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 who
provide 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 do.
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.

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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 provide 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 who
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

143

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

144

consultants 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 development is, 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

145

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. (12 month employees)
F. Clerical Staff: Number of FTE clerical staff members. (10 month employees)
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.

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APPENDIX F – Case Studies

JW High School: A case study of Instructional Improvement
and Resource Use with a changing population.

JW High School (JWHS) is a grade 9-12 high school in a large high school
district East of Los Angeles. For much of its history JWHS was the only high school in a
rural school district in a community made up of large properties and horse farms. The
population of the area has increased dramatically and can now be described as a large
suburban community. JWHS is now one of eight comprehensive high schools and two
continuation high schools in this large suburban high school district. The eight high
schools range in size from 2,200 students to 3,400 and serve over 23,500 students. The
average size of the eight high schools is over 2,900 students. Two of the schools in this
study are located in the district, JWHS and KOHS. JWHS serves 2,727 students.
Over the last ten years student demographics have shifted dramatically. JWHS
has had a 16% increase in minority enrollment in 8 years. Once a predominantly white
school population, the student body is now about 40% Hispanic and 10% African
American. In 2000, the school population was over 60% white with Hispanic and
African American students comprising 27% and 7% of the school population
respectively. The changing demographics have presented new challenges to the staff as
the new student population has different needs that require different instructional
approaches. As a result, the staff had to shift from a group of isolated teachers to a
collaborative work group in order to meet the needs of their students.
JWHS does not receive Title I funds despite the 21% of students participating in
the Free or Reduced Price Lunch program. Three percent of the student population is

147

English Learner (EL) students. The school does not have any beginner EL students as
they are served at another school within the district. JWHS has 293 students (10.7%)
with Individual Education Plans (IEPs) as part of the special education program.
At the same time demographics have shifted, JWHS has shown impressive growth
in terms of California’s Academic Performance Index (API) scores, Standardized Testing
and Reporting (STAR) scores and California High School Exit Exam (CAHSEE) scores.
The whole school API has improved 97 points since 2000 from 662 to 759. The goal for
schools is to reach an API of 800 both school-wide and for all significant subgroups.
Even more impressive than the school-wide API growth are the gains of the significant
subgroups as shown in table F1.

Table F1 – JWHS API Scores 2000 to 2008 including subgroups
2000 2001 2002 2003 2004 2005 2006 2007 2008
Change
2000 to
2008
All Students 662 678 638 671 698 724 734 761 759 97
African American 571 611 562 609 666 702 704 723 724 153
Hispanic 583 617 586 622 651 680 697 733 728 145
White 703 710 669 704 730 754 763 789 789 86
Low SES 539 596 541 573 612 664 682 715 716 177
Hisp/White Gap 120 93 83 82 79 74 66 56 61
AA/White Gap 132 99 107 95 64 52 59 66 65

The Hispanic subgroup grew 145 API points from 2000 to 2008 while the low
SES subgroup grew 177 points. The achievement gap between Hispanic students (the
largest minority subgroup) and white students consistently declined from 120 API points
in 2000 to 61 in 2008. Similarly, the achievement gap between African American and
White students also consistently decreased from 132 API points in 2000 to 65 in 2008. It

148

is important to note that both of these gaps decreased while both the Hispanic and
African American populations grew as a proportion of the student body. Figure F1
shows the steady API growth of the whole school and all the subgroups and demonstrates
the closing of the gap between the white students and other subgroups.
Figure F1 – JWHS API Scores 2000 to 2008 including subgroups
400
450
500
550
600
650
700
750
800
850
900
2000 2001 2002 2003 2004 2005 2006 2007 2008
API Score
All Students African American Hispanic White Low SES

An examination of STAR scores at JWHS shows some strong areas of growth and
some areas of stagnation. Figure F2 shows the California Standards Test (CST) scores
for the core subject areas of English, History, Math and Science.

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Figure F2 – JWHS CST Scores 2003-2008, percent Proficient or Advanced
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
2003 2004 2005 2006 2007 2008
% Proficient or Advanced
English/LA History Math EOC Science EOC Science NCLB

While the percent of students scoring proficient or advanced in Science doubled
from 19.2% in 2004 to 40.6% in 2008, Math scores have been stagnant around 20%
advanced or proficient. Both English and History scores have shown strong consistent
growth since 2003 with about half of all students proficient or advanced in English and
44% of students proficient or advanced in History.
CAHSEE scores have remained strong since 2005 with over 80% of all students
passing both the Math and English portions of the test on their first attempt. As table F2
shows, the most impressive gains have been with Low SES students with an 81% pass
rate on the English portion, up from 67% in 2005. In addition, both the Hispanic and
African American pass rates have improved for the Math portion of the exam with scores
growing from lows around 70% to highs of 80%. The fluctuations in CAHSEE scores for

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the English Learner are group are likely due to the small number of students in the EL
category (less than 30 students in any given year) as an individual students performance
has more of an effect on the whole.
Table F2 – CAHSEE first attempt pass rates by subgroup 2004 – 2008.
English % Passed Math % Passed

2005,
n=700
2006,
n=725
2007,
n=737
2008,
n=650
2005,
n=695
2006,
n=724
2007,
n=732
2008,
n=653
All 10th Grade 81% 83% 85% 86% 80% 84% 84% 82%
Hisp/Latino 74% 79% 83% 81% 71% 76% 80% 77%
Af. Amer 73% 80% 76% 90% 73% 83% 81% 76%
White 88% 86% 88% 89% 87% 90% 88% 88%
English Learner 26% 55% 74% 39% 48% 68% 66% 54%
Low SES 67% 71% 76% 81% 72% 78% 79% 72%
SPED 34% 32% 34% 33% 34% 38% 35% 35%

Although the district is in program improvement, JWHS has never been in Program
Improvement and met all AYP targets in 2005, 2007 and 2008. JWHS missed the AYP
target for participation rate (95%) of low SES students on the English portion of the
CAHSEE in 2006.
Master Schedule
The types of courses offered at JWHS show an interesting parallel to the
standardized test score results. In math, by far the weakest area in terms of test scores at
JWHS, over half of the sections in the master schedule are remedial or below grade level
(this includes 27 sections of Algebra 1 – 33% of all math sections). Looking deeper into
the CST scores in math, Figure F3 shows that over the last six years less than half of all
students who took CSTs were enrolled in Geometry or above indicating that half of the
students in grades nine through eleven at JWHS are at least one year below grade level in
math as Geometry is the grade level course for ninth graders according to the state

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standards. Students in Geometry or higher outperformed the students in Algebra I or
lower, but not by a large margin. Students in higher level math classes are still
performing poorly with less than 30% advanced or proficient in any given year. This is a
concerning trend, but further analysis is beyond the scope of this study.
Figure F3 – CST Scores for students in Geometry and above vs. Algebra I or lower
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
90.00%
100.00%
2003 2004 2005 2006 2007 2008
% Prof/Adv in Alg or low er % Prof/Adv in Geom or higher % in Geom & Above

In English, only about 20% of the courses in the master schedule are
remedial/below grade level (see figure F4) and 13% are honors or Advanced Placement.
The CAHSEE data above highlight the importance placed on rigor in the literature as the
Hispanic and African American students show much more parity with White students in
English scores as compared to Math scores.

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Figure F4 – JWHS Course Offering Levels by Subject Area
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
English History Math Science Foreign Lang Elective Total
% Remedial % Regular % Advanced

Instructional Improvement Process
The administrative team at JWHS described their improvement effort as a “three
pronged approach” with efforts to differentiate instruction, provide interventions for
struggling students and develop strong collaboration among the teachers. The impetus
for all three was the changing demographics of the school. In addition to the three
pronged approach, the school has been very intentional about creating a strong school
culture in terms of relationships between and among students and staff. As the
demographics of the school changed the staff came to the realization that it needed to step
out of an environment of isolated classroom teachers to form a cohesive, collaborative
team to confront the challenges of meeting the NCLB targets for all significant

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subgroups. The staff wants to retain the sense of autonomy that comes with being a
successful school that is not in program improvement.
Differentiating Instruction
Differentiating instruction to meet the needs of all students was a key strategy in
the improvement process. In addition to changing demographics in terms of race and
language diversity, JWHS embraced a more inclusive model of educating students with
disabilities. The district is moving toward the Response to Intervention (RTI) model of
special education services. At JWHS, any special education student who passes the
CAHSEE is mainstreamed in the core academic subjects as the least restrictive
environment. Increasingly, the co-teaching model is being used to help mainstream
students and expose them to the most rigorous course of study possible.
In order to effectively serve the diversity of students in any given classroom, the
teachers are using Data Director to create detailed reports on student achievement to gain
insights on each student’s academic strengths and weaknesses. Teachers also participated
in Specially Designed Academic Instruction in English (SDAIE) trainings to develop
strategies in reaching all kinds of learners.
Intervention Programs
JWHS has created a wide variety of intervention programs for struggling students.
California’s recent investment in lowering the counselor to student ratio provided JWHS
with an opportunity to create a variety of programs. In addition to four grade level
counselors, JWHS created positions for intervention counselors to encourage and work
with students in areas such as grief groups, supporting students with alcohol or drug

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problems and providing support to incoming ninth grade students. The counselors used
Data Director and the student information system used by the district and the feeder
elementary district to target at-risk ninth grade students and send them to a summer
program which they called “Fresh Start” designed to help the incoming ninth graders get
to know their counselor and learn about how high school works. Forty families
participated last summer, and 24 of the 40 incoming ninth graders had no failing grades at
the first grading period.
The counselors also used Data Director to identify students who were in need of
specific intervention in English. Students who scored far below basic or below basic on
the English CST in 7
th
grade were placed in a Read 180 class in addition to their regular
English class. Because articulation with the middle schools is not ideal in a high school
district, the counselors have all the English classes go to computer lab for an assessment
to identify struggling English students. Students who show a need are placed in the Read
180 program.
For math, the district has been using Mastery Math for the last six years to target
students who struggle with Algebra. Mastery math is comprised of four modules to cover
all the Algebra I standards. Students must pass each module before moving on to the
next. If a student fails a module at the end of the quarter, he/she repeats the module not
passed with a different teacher. As discussed above, Math CST and CAHSEE scores are
significantly lower than other subject areas. Math scores may be skewed lower because
only the students in the last semester of Algebra can take the Algebra I CST exam. The

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rest of the students automatically score far below basic. Because a third of all math
sections are devoted to Algebra I, the math CST scores are severely impacted.
JWHS has tried after school, weekend and boot camp type programs, but they
have found that intervention classes during the school day work best for their student
population.
For students who fall behind on credits early in high school, JWHS houses an
Opportunity School for 10
th
graders. The Opportunity School is a computer based credit
recovery program. Computers are provided to families in homes as needed through
JWHS’s computer repair class.
Collaboration
The staff at JWHS is highly collaborative and that collaboration is supported at
the district level. The high school department chairs meet quarterly with the assistant
superintendent which allows each school’s department to have direct input at the district
level. The district, in order to create a cohesive district-wide vision of improving student
performance, sends up to 25 teachers from each school site to the summer Effective
Schools conference in Ontario where teachers learn about the latest research in education
from top researchers such as Doug Reeves and Larry Lezotte. Over 60% of the staff at
JWHS have attended the conference so there is a shared vocabulary and vision around
school improvement. To facilitate teacher collaboration, every Friday is a late start for
students which provides one hour a week for teacher collaboration time and meetings.
Teachers work on curriculum guides, identify essential standards and use data to make
instructional decisions. Departments also develop end of course exams, which is a

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district mandate, for each core course. The teachers have access to student data from
Data Director as well as the results of their own common assessments.
School Culture
JWHS values the connection that students have to the school and to the staff.
Much attention has been paid, in terms of time and resources, to promoting a positive
campus learning environment. Three student groups dramatically impact the life of the
school. The first group is Link-Crew which is a group of 45 students that assist with the
difficult transition from middle school for the incoming ninth graders. The second group
is the Associated Student Body who are the elected student leaders of the school. The
third group, Renaissance, is a group of 50 students selected by the staff who have shown
leadership ability. The Renaissance students are responsible for recognizing all the
achievements of the school. They find ways to award students for improvement and plan
events such as “report card night” and the “G.P.A. picnic.” The three groups above work
together to improve student and staff morale.
As explained above, the Friday collaboration time and summer Effective School’s
conference are key elements in providing staff planning time and creating a shared vision.
The staff is diverse and represents a wide range of ages. Many of the teachers are former
students at JWHS. Since JWHS was the first high school in the district there is a long
history. As the demographics have changed the commitment to high standards has
remained. The administrative team has implemented a common white board
configuration school-wide as an expectation when they visit classrooms. The white
board in each classroom must include the standard being addressed, a daily agenda, and

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the lesson objective. There is also an expectation that a formative assessment will be
given at the end of the class period to check for student understanding.
Because it is part of a high school district, JWHS has the advantage of being able
to focus on high school issues. Each high school has remained autonomous, but a large
investment in sending teachers and administrators to “Effective Schools” conferences has
led to a common vision throughout the district. There is a strong belief that every student
can learn in the district as reported by the principal of JWHS. The teachers and
administrators in the district are highly paid with the second highest average salaries in
the state.
Resource Comparison to Evidence Based Model
It is perhaps expected that the large high schools typical of urban areas of
California are staffed differently to what is recommended in the Evidence Based Model.
The most glaring difference is the size of the student body. The Evidence Based Model
recommends a grade 9-12 high school of 600 students. The smallest school in this study
has an enrollment of 1,400 students. JWHS is one of the larger schools in the study with
an enrollment of 2,727 students. Table F3 shows how the resources at JWHS compare to
the Evidence Based Model (EBM). The last column indicates the difference between the
Evidence Based Model and JWHS or indicates how the Evidence Based Model would
staff a school of 2,727 students with the demographics of JWHS.

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Table F3 - Comparison of actual resources at JWHS to Evidence Based Model
School Element
EBM Prototypical
High School
Actual JWHS
Resources
Difference
between EBM
and JWHS or
EBM
suggested
amount for
JWHS
School Characteristics
School Configuration 9-12 9-12
School Size 600 2727
4.5 times
bigger
Core Class Size 25 29
4 more than
EBM
Number of teacher work
days
200, including 10
days for intensive
training
180 with no
inservice days
No inservice
days, 10 less
school days
Number Disabled
(w/IEP)
293 (10.7%)
Number Poverty (free &
reduced lunch)
581 (21%)
Number English Learner 83 (3%)
% Minority (non-white) 57%
Personnel Resources
1. Core Teachers
24 per 600 students
(75% of FTEs)
73.6 FTE
(72% of FTEs)
EBM suggests
109 for 2727
students
2. Specialist Teachers
8.0
(25% of FTEs)
29 FTE
(28% of FTEs))
EBM suggests
36
3. Instructional
Facilitators/Mentors
3
(1 for every
200 students)
0
EBM suggests
13.6
4. Tutors for struggling
students
One for every 100
poverty students
0
EBM suggests
5.8
5. Teachers for EL
students
An additional 1.0
teacher for every 100
EL students
0.4 FTE
EBM suggests
.8

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Table F3-Comparison of actual resources at JWHS to Evidence Based Model (continued)
6. Extended Day
1 teacher for every 15
poverty students
(based on half the
number of poverty
students), 15 hours
per week @ 25% of
salary
0
EBM suggests
4.8 FTE
extended day
teachers
7. Summer School 6.25 FTE
EBM suggests
4.8 FTE
School Characteristics
8. Learning & mild
disabled students
Additional 4
professional teacher
positions for 600
students
4 Inclusion and
Resource Room
Teachers
EBM suggests
18 teachers for
2727 students
9. Severely disabled
students
100% state
reimbursement minus
federal funds
2 FTE teachers and
4 aids for 20
students
Base on need
10. Resources for gifted
students
$25 per student
Gate budget of
$3,276
EBM suggests
funds of
$68,175
11. Vocational
Education
1/3 more per student
enrolled
4.4 FTE
EBM suggests
7.9 FTE
12. Substitutes 10 days per teacher
10 days per teacher
for illness and PN
plus 2 buy-back
days for PD
2 more days
than EBM
suggests
13. Pupil support staff
1 for every 100
poverty students plus
1.0 guidance per 250
students
7 Counselors
2 clerical
attendance
1 Nurse, 1 Psych, 1
Speech, 1 health
clerk (13 FTE)
EBM suggests
16.7 positions
14. Non-Instructional
Aides
3.0 to relieve teachers
and provide
supervision
0
EBM suggests
13.6
15. Librarians/media
specialists
1.0 Librarian
1.0 Library Tech
1 Librarian &
3 library aides
EBM suggests
4.5 Librarians
and 4.5 Library
techs
16. Principal 1 Principal
1 Principal, 4
Assistant Principals
EBM suggests
1 Principal and
4.5 Assistant
Principals

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Table F3-Comparison of actual resources at JWHS to Evidence Based Model (continued)
17. School Site
Secretary
1.0 Secretary and 3.0
Clerical
6 Secretaries &
8 clerks
EBM suggests
4.5 secretaries
& 13.5 clerks
18. Professional
Development
Included above:
Instructional
facilitators, Planning
and prep time, 10
summer days
Additional: $100 per
pupil for other PD
expenses - trainers,
conferences, travel,
etc.
No PD days in
calendar. 1 hour
each week for
collaboration = 5.4
days per year,
$10,449 spent for
conferences,
$2,500 title II, and
$5,000 for
materials
EBM suggests
10 days PD in
summer and
$272,700 for
other PD
expenses.
19. Technology $250 per pupil
No technology
coordinator.
Resources vary
EBM suggests
$681,750
20. Instructional
Materials
$175 per pupil
EBM suggests
$477,225
21. Student Activities $250 per pupil
1 section ASB, 1
section
Renaissance, Link-
Crew, summer
“Fresh Start”
program
EBM suggests
$681,750

Lessons learned
The school culture at JWHS has shifted with the demographics. Teachers who
could once work in isolation now work in collaboration to improve student achievement.
The district has invested substantial funds to send teachers to the summer Effective
Schools conference to promote a shared vision. Teachers work hard to connect with
students and the staff learns from each other to improve teaching strategies. There is a
strong belief that all students can learn. Recent changes in the Special Education
department highlight this belief as students are being challenged to achieve in mainstream

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classrooms with support from the special education staff in an effort to move to the RTI
model of special education.
Through the use of Data Director and common assessments, teachers are using
their weekly collaboration time to discuss student performance and adjust their
instruction to meet the needs of students. Teachers are using formative assessments and
students understand teacher expectations through the use of the common white-board
configuration. The weekly collaboration time has been essential for teachers to create
pacing guides and ensure that each teacher’s curriculum is aligned to the state standards.
The use of common assessments and the conversations around those assessments during
collaboration time has been a key element of the improvement process.
JWHS has implemented a wide array of interventions for struggling students
including the Mastery Math program, the Read 180 program, the Fresh Start Program and
the intervention counselors. The school staff feels that intervention programs outside the
regular school day are not effective for their student population, so all programs are built
into the school day.
JWHS has placed a strong emphasis on recognizing student success. The
Renaissance program, along with Link-Crew and ASB, has been instrumental in building
an atmosphere that breeds success among the students.
Strong leadership from the district level in combination with strong site leadership
from both administrators and teachers has led to strong growth. The district leadership
maintains high expectations and provides the resources to back up the expectations. The

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teachers feel supported and work hard to build their capacity to promote student
achievement.
Needs and Future Implications
Because of the uncertainty of the district budget due to California’s financial
crisis and the expected decline in enrollment, JWHS was understaffed at the beginning of
the school year. In addition to the statewide need for a more stable budget, JWHS needs
additional resources to reduce class sizes and provide even more intervention programs
for struggling students. In addition, more site administrators are needed to manage all the
responsibilities of running a large high school. The staff could benefit from staff
development days to continue their collaborative work.

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KO High School: A case study of Instructional Improvement
and Resource Use with a changing population

KO High School (KOHS) is a large suburban high school east of Los Angeles and
is part of a high school district. KOHS is the largest high school in this study with 2,978
students in grades 9-12. The school district is made up of eight comprehensive high
schools and two continuation schools and serves over 23,500 students. KOHS is one of
two high schools in the study within this district, the other is JWHS.
The demographics of KOHS have changed dramatically over the last eight years.
In 2000, KOHS was a majority white school (53%) with African American and Hispanic
students making up the other significant subgroups at 13% and 25% respectively. By
2008 the demographics had shifted so that there was no majority group. KOHS is now
35% White, 36% Hispanic, 15% African American, 7% Asian, 4% Filipino and 2%
American Indian or Pacific Islander. Part of the reason for the change was the opening of
a new high school only a mile and a half away that took a significant portion of the white
student population when boundaries were redrawn six years ago. KOHS does not have a
significant EL population (2.5%) because newcomer students are served at another school
in the district. Students with Individual Education Plans comprise 7.3% of the population
and students participating in the free or reduced lunch program make up 21% of the
student population. Only 8% of students were on free or reduced lunch eight years ago.
While there has been significant growth of the minority and disadvantaged
population of KOHS, test data indicate that student achievement has steadily and
significantly increased over the last eight years. As Table F4 demonstrates, the whole
school Academic Performance Index (API) score has increased 145 points in eight years

164

to 791. The goal for all schools in the state is to reach a score of 800 school-wide and for
all significant subgroups.
Table F4 – KOHS API Scores 2000 to 2008 including subgroups
2000 2001 2002 2003 2004 2005 2006 2007 2008
Change
2000 to
2008
All Students 646 678 682 713 737 770 763 781 791 145
African American 559 614 621 673 689 741 718 744 759 200
Hispanic 593 615 635 674 700 719 722 742 743 150
White 679 713 713 736 767 799 791 804 823 144
Low SES 579 602 598 635 680 711 697 724 729 150
Hisp/White Gap 86 98 78 62 67 80 69 62 80
AA/White Gap 120 99 92 63 78 58 73 60 64

Both the Hispanic and low socioeconomic status (SES) groups have grown by 150
API points in eight years while the African American group grew 200 points. The gap
between White and Hispanic students steadily declined from a high of 98 points in 2001
down to 62 points in 2007, but grew again to 80 points in 2008. The gap between
African American and White students shrank by half from 120 points in 2000 to 64
points in 2008. Figure F5 illustrates that all groups have steadily increased and the gaps
among the groups are shrinking. Only the white subgroup has reached an API of 800.

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Figure F5 – KOHS API Scores 2000 to 2008 including subgroups
400
450
500
550
600
650
700
750
800
850
2000 2001 2002 2003 2004 2005 2006 2007 2008
API Scores
All Students African American Hispanic White Low SES

California Standards Test (CST) scores at KOHS have improved over the last six
years with particularly impressive gains in English and Science. Figure F6 shows that at
least 50% of students were proficient or advanced in English, History and Science in
2008. The English scores have increased steadily while History regained an upward
trajectory after two years of decline. Science showed the most impressive gain by more
than doubling the percentage of students scoring proficient or advanced between 2003
and 2008. Math scores have shown little growth with only 24% of students scoring
proficient or advanced in 2008.

166

Figure F6 – KOHS CST Scores 2003-2008, percent Proficient or Advanced
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
2003 2004 2005 2006 2007 2008
% Proficient or Advanced
English/LA History Math EOC Science EOC Science NCLB

KOHS has maintained high pass rates on the California High School Exit Exam
(CAHSEE) in both English and Math with overall scores approaching a 90% pass rate on
the first attempt (see Table F5). The Math scores are consistently a few points lower than
the English scores (with the exception of the English Learner subgroup), but there is not
nearly the same discrepancy seen between the English and Math CST scores.
Table F5 – KOHS CAHSEE first attempt pass rates by subgroup 2005 – 2008
English % Passed Math % Passed

2005,
n=667
2006,
n=719
2007,
n=708
2008,
n=779
2005,
n=651
2006,
n=720
2007,
n=699
2008,
n=781
All 10th Grade 87% 87% 89% 89% 84% 84% 85% 87%
Hisp/Latino 82% 84% 83% 84% 77% 79% 80% 80%
Af. Amer 80% 84% 88% 88% 77% 74% 75% 85%
White 92% 89% 92% 93% 90% 91% 90% 92%
English Learner 35% 40% 57% 59% 69% 70% 71% 73%
Low SES 80% 80% 81% 80% 73% 74% 79% 78%
SPED 32% 44% 36% 55% 50% 44% 46% 52%

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Although the district is in program improvement, KOHS has never been in
program improvement. The school has met AYP every year with the exception of 2003
when the only criteria not met was for Hispanic participation on the English portion of
the CAHSEE. KOHS does not receive any Title I funding.
Master Schedule
The courses offered at KOHS show some interesting parallels with the
standardized test data presented above. One third of the courses offered in science are
honors or Advanced Placement (AP) courses (see figure F7) perhaps explaining the
impressive gains in science CST scores. On the other hand, 44% of all math classes are
remedial or below grade level (this includes 19 sections of Algebra I – 21% of all math
classes). This may be partly because of the structure of the Mastery Math program used
in the district. Unless students are in the last semester of Algebra I, they can not take the
Algebra I CST. Students who are held back in the program can not take the Algebra I
CST and would score far below basic. The high number of honors and AP math courses
along with the high pass rate on the CAHSEE suggest that the Mastery Math program
may be artificially bringing down the CST math scores at KOHS.

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Figure F 7 – KOHS Course Offering Levels by Subject Area
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
English History Math Science Foreign Lang Elective OVERALL
% Remedial % Regular % Advanced

Further analysis of the math CST scores show that students enrolled in Algebra I
(the lowest course offered in the Math program) have only modestly improved over time
and only 14% are scoring advanced or proficient. Figure F8 illustrates that the percent of
students enrolled in Geometry or higher has fluctuated between 50% and 60% over the
last five years. Stated another way, approximately half of all students tested are still in
Algebra I . The students who are in Geometry or above are outperforming the Algebra
students, but not by a wide margin with only 30% scoring advanced or proficient in 2008.

169

Figure F8 – CST Scores for students in Geometry and above vs. Algebra I or lower
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
90.00%
100.00%
2003 2004 2005 2006 2007 2008
% P rof/Adv in Alg or low er % P rof/Adv in Geom or higher % in Geom & Above

Instructional Improvement Process
KOHS has reaped the benefits of strong, consistent leadership since it opened its
doors seven years ago. A combination of strong leadership, collaboration, goal setting
and data analysis have led to improved student achievement, and strong intervention
programs and relationships with students have helped to close the achievement gap.
Strong and Consistent School Level and District Leadership
The first Principal of KOHS built a strong culture of professionals and a sense of
family among the staff. He asked the newly hired teachers to sign a values statement in
order to establish a common vision and mission for the school. Over the seven years of
the school’s life that culture has remained because of stable and consistent leadership.
The current principal has tremendous social capital among the teachers and students. He

170

articulates a clear vision for the school and uses a collaborative leadership style. Because
he was a teacher at the school and worked his way up to his current position, he has
strong relationships with the staff. He is a focused, deliberate leader but knows when to
back off when there is no buy-in.
The commitment to instruction at KOHS is evidenced by the amount of time the
administrators spend in classrooms for informal observations. The principal’s goal is to
be in classrooms 80% of each school day. The assistant principals are assigned to
departments as liaisons and are expected to visit each classroom in the department once
per week. All administrators are seen as instructional leaders and the teachers commonly
ask for an administrator to come visit for a particular lesson or activity. The principal
makes his belief clear that success is the result of good teachers and good teaching.
The principal places great importance on continually learning and keeping up
with the latest research. He is enrolled in a doctoral program at a local university in
educational leadership along with one of the Assistant Principals. He meets regularly
with the instructional leadership team which is made up of administrators and teachers.
They are currently reading and discussing Marzano’s (2003) work on improving schools.
The administrators are also reading and discussing Results That Last (Studer, 2007).
In addition to stable leadership at the school level, the district leadership has also
been strong and consistent. The school board has been stable and recently hired a new
superintendent from within the district. The new superintendent brings a new level of
accountability to principals. Because he moved up through the ranks of the district
leadership and worked with many of the principals at different levels he makes his belief

171

clear that relationships without accountability leads to mediocrity. Teachers feel they
have direct access to district administrators and district administrators are often on
campus visiting classrooms.
Goals Driven by Data
Each department at KOHS writes goals that are Specific, Measurable, Attainable
and challenging, Relevant and Time bound (SMART goals) for each of the courses
within the department after looking at the latest test data. The impetus for the
development of SMART goals and data exploration came from the teachers after
attending the summer Effective Schools conference. The process is still evolving but
begins with teachers breaking down the content standards and talking about instructional
strategies to meet the needs of students with each standard. Teachers are using
collaboration time to look at and talk about data and measure their progress toward the
SMART goals. Although the school has not formed formal data teams the discussions in
departments are at high levels.
Curriculum and Instruction
Teachers at KOHS demonstrate excellence in teaching by holding high
expectations for students and exuding a passion for teaching and learning. They are
excited to have administrators visit their classrooms and use their collaboration time to
improve student achievement.
Each department has developed summative benchmark assessments over the last
several years. They are now working to develop common formative assessments as well.
The school focus has been writing for the last several years, but there has been little buy-

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in. The new Principal is working to build buy-in through the leadership team and writing
is now a WASC goal. He is also working with the leadership team and administrators to
implement a common blackboard configuration in each classroom that includes the
standard being addressed in student friendly language, a warm-up activity and the
expected outcome of the lesson. Currently, only a third of the staff is using the
blackboard configuration consistently. For English Learner (EL) students, KOHS uses
the National Geographic Edge curriculum which is very visual, well scaffolded and
targeted to each CELDT level.
Intervention Programs
KOHS has both formal and informal intervention programs for struggling
students. For students who have not passed CAHSEE or are in danger of not passing the
CAHSEE, KOHS uses the Measuring Up program. They make it a point to put their
strongest teachers with these struggling students. For EL students and for some of the
struggling ninth grade students in English they use the Read 180 program. KOHS takes
great pride in the fidelity of the Read 180 program which has led to the best results in the
district. For Special Education students, a full inclusion program is the norm through the
use of the co-teaching model. Only three special education students did not pass the first
Algebra module at the end of the first quarter this year. The math department offers
tutoring in the library before and after school staffed by volunteers. The tutoring
program draws an average of 100 students before and after school each day.
Administrators call in and speak with students that are not being successful to provide
support and encouragement. In addition, specific groups of students are targeted by

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various caring adults on campus. The coaches make it a point to call in African
American students in sports if they are not performing well to offer support. The
basketball coach is a particularly strong mentor to African American students by
providing regular meetings with students after school to discuss issues and provide
tutoring. Similar informal programs have started for Hispanic and Filipino students.
KOHS also offers the Bridge Program for incoming ninth grade students over the
summer.
Collaboration and Professional Development
At the end of each summer the leadership team at KOHS eagerly analyzes test data which
then leads to department goal setting. Each Friday of the school year is a late start day
for students to allow one hour of collaboration or meeting time per week for the staff.
During their collaboration time teachers discuss data and share best practices with their
departments. When the whole staff meets the time is devoted to recognition of
accomplishments instead of school business which is taken care of via email or in
department meetings. It is an expectation that good teaching will be recognized which
feeds the cycle that teachers expect the administrator to be in their rooms and then they
expect to be recognized for what is working well. Professional development time is
increasingly focused on collaboration and sharing tailored to the needs of the site. The
administrative team is developing site based professional development activities guided
by their reading of Marzano (2003) and Studer (2007) that includes their own staff
members in sharing with the rest of the staff in a sort of “think tank” model. This is a

174

move away from the staff development committee of the past which simply approved or
denied individual requests for professional development opportunities.
Resource Comparison to Evidence Based Model
KOHS is the largest school in this study at five times the size of a prototypical
high school suggested by the Evidence Based Model. Though there are some areas
where the school is staffed as the Evidence Based Model (EBM) would suggest, overall
KOHS is under resourced. Table F6 shows how the resources at KOHS compare to the
EBM. The last column indicates the difference between the Evidence Based Model and
KOHS or indicates how the EBM would staff a school of 2,978 students with the
demographics of KOHS.
Table F6 – Comparison of actual resources at KOHS to Evidence Based Model
School Element
EBM Prototypical
High School
Actual KOHS
Resources
Difference
between EBM
and KOHS or
EBM
suggested
amount for
KOHS
School Characteristics
School Configuration 9-12 9-12
School Size 600 2978 5 times bigger
Core Class Size 25 29
4 more than
EBM
Number of teacher work
days
200, including 10
days for intensive
training
180 with no
inservice days
No inservice
days, 10 less
school days
Number Disabled
(w/IEP)
218 (7.3%)
Number Poverty (free &
reduced lunch)
633 (21%)
Number English Learner 76 (2.5%)
% Minority (non-white) 51%

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Table F6–Comparison of actual resources at KOHS to Evidence Based Model
(continued)
Personnel Resources
1. Core Teachers
24 per 600 students
(75% of FTEs)
80.8 FTE
(77% of FTEs)
EBM suggests
119 for 2978
students
2. Specialist Teachers
8.0
(25% of FTEs)
24.8 FTE
(23% of FTEs)
EBM suggests
39
3. Instructional
Facilitators/Mentors
3
(1 for every
200 students)
0
EBM suggests
14.9
4. Tutors for struggling
students
One for every 100
poverty students
0
EBM suggests
6.3
5. Teachers for EL
students
An additional 1.0
teacher for every 100
EL students
0.2 FTE
EBM suggests
.8 FTE
6. Extended Day
1 teacher for every 15
poverty students
(based on half the
number of poverty
students), 15 hours
per week @ 25% of
salary
0
EBM suggests
5.3 FTE
extended day
teachers
7. Summer School 7.8 FTE
EBM suggests
5.3 FTE
School Characteristics
8. Learning & mild
disabled students
Additional 4
professional teacher
positions for 600
students
5.2 Inclusion and
Resource Room
Teachers
EBM suggests
19.9 teachers
for 2978
students
9. Severely disabled
students
100% state
reimbursement minus
federal funds
1 FTE teachers and
5.3 aids for 19
students
Base on need
10. Resources for gifted
students
$25 per student
Gate budget of
$6,612
EBM suggests
funds of
$74,450
11. Vocational
Education
1/3 more per student
enrolled
7.4 FTE
EBM suggests
13.3 FTE

176

Table F6–Comparison of actual resources at KOHS to Evidence Based Model
(continued)
12. Substitutes 10 days per teacher
10 days per teacher
for illness and PN
plus 2 buy-back
days for PD
2 more than
EBM suggests
13. Pupil support staff
1 for every 100
poverty students plus
1.0 guidance per 250
students
6 Counselors
1 clerical
attendance
1 Nurse, 1 Psych, 1
Speech, 1 health
clerk (11 FTE)
EBM suggests
18.2 positions
14. Non-Instructional
Aides
3.0 to relieve teachers
and provide
supervision
0
EBM suggests
14.9
15. Librarians/media
specialists
1.0 Librarian
1.0 Library Tech
1 Librarian &
3 library aides
EBM suggests
5 Librarians
and 5 Library
techs
16. Principal 1 Principal
1 Principal, 3
Assistant Principals
EBM suggests
1 Principal and
5 Assistant
Principals
17. School Site
Secretary
1.0 Secretary and 3.0
Clerical
6 Secretaries &
16 clerks
EBM suggests
5 secretaries &
14.9 clerks
18. Professional
Development
Included above:
Instructional
facilitators, Planning
and prep time, 10
summer days
Additional: $100 per
pupil for other PD
expenses - trainers,
conferences, travel,
etc.
No PD days in
calendar. 1 hour
each week for
collaboration = 5.5
days per year per
teacher.
88 staff members
participated in PD,
$5,952 title II, and
$5,000 for
materials
EBM suggests
10 days PD in
summer and
$297,800 for
other PD
expenses.
19. Technology $250 per pupil
1 technology
coordinator.
Resources vary
EBM suggests
$744,500
20. Instructional
Materials
$175 per pupil
EBM suggests
$521,150

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Table F6–Comparison of actual resources at KOHS to Evidence Based Model
(continued)
21. Student Activities $250 per pupil
1 section ASB, 1
section Peer
Counseling
EBM suggests
$744,500

Lessons Learned
The success of KOHS begins with the staff of dedicated teachers under consistent
leadership from the principals and other administrators that are seen as strong
instructional leaders. The staff provides a rigorous curriculum to all students with very
few course offerings that do not meet one of the University of California a-g
requirements. The teachers set SMART goals and use data as discussion points and to
measure their progress toward the SMART goals. These efforts are teacher led and
sustained and grew out of teacher participation in the Effective Schools conferences.
Over the last two summers, 22 teachers have attended the Effective Schools conference
helping to create a shared vision and vocabulary around student achievement. The
leadership team and administrative team are providing site level professional
development by using the capacity among the staff to share best practices and improve
instruction. Struggling students have a myriad of opportunities in both formal programs,
such as CAHSEE prep and Read 180, and informal mentoring programs to find
connections to the school and get academic support.

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Future Needs
Given the increasingly uncertain budget situation in California today, KOHS,
along with all schools in California needs a stable budget and funds to continue the
programs that currently exist. To continue moving the school forward, the principal
would like to have the resources to reduce class sizes, provide students more elective
options and update all classrooms with the latest educational technology. In addition,
more resources are needed for continuous high quality professional development,
specifically in the areas of differentiating instruction and formative assessment. He
would also like to implement a program to provide opportunities for students to connect
with businesses and organization to get real world experience. In order to connect more
with the community, funds for parent education opportunities are needed. Finally,
resources for an intervention counselor are needed to provide more opportunities for
struggling students.

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ML High School: A case study of Instructional Improvement and Resource Use
Located in what was historically a blue collar beach town located Southwest of
Los Angeles, ML High School (MLHS) is the only high school in a unified school district
that includes eight elementary schools, two middle schools, one high school and one
continuation school. In the midst of a major renovation, MLHS is over 100 years old
making it the oldest school in this study. Over the years, MLHS has had to overcome a
reputation as being one of the lowest performing high schools in the area. That
reputation drove some of the more affluent students to other schools in the area, but as
the reputation of MLHS has improved those students are returning. MLHS has used a
block schedule for the last ten years.
The demographics of MLHS have remained very stable over the last eight years
with a population made up of 55% white students, 23% Hispanic, 10% Asian, 7%
African American and 4% other which includes Filipino, American Indian and Pacific
Islander students. Of the 2,471 students enrolled, 5% are English Learner (EL) students,
15% participate in the free and reduced price lunch program, an indicator of the poverty
level, and 10.4% of the students are in the Special Education program. MLHS is the third
largest school in this study, but it has the smallest percentage of students in poverty and
the smallest percentage of minority students at 45%. MLHS does not receive any Title I
funding.
MLHS is one of only two schools in this study to reach an overall API score that
surpasses the state target of 800 with an overall API of 804. As Table F7 demonstrates,

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the scores overall and for all the subgroups have shown steady progress since 2000,
especially for the Hispanic and low SES subgroups.
Table F7 – MLHS API Scores 2000 to 2008 including subgroups
2000 2001 2002 2003 2004 2005 2006 2007 2008
Change
2000 to
2008
All Students 684 697 699 743 754 783 790 793 804 120
African American 719 682 725 707 734
Hispanic 570 608 622 677 668 716 732 741 739 169
White 729 733 730 768 786 805 811 809 822 93
Low SES 535 553 577 645 651 666 709 723 738 203
Hisp/White Gap 159 125 108 91 118 89 79 68 83

Figure F9 further illustrates the closing of the achievement gap between white
students and all the other subgroups. The white subgroup is the only significant subgroup
to surpass the 800 mark but the gains for the other significant subgroups were nearly
twice what the white group gained over the eight year period.
Figure F9 – MLHS API Scores 2000 to 2008 including subgroups
400
450
500
550
600
650
700
750
800
850
2000 2001 2002 2003 2004 2005 2006 2007 2008
All Students African American Hispanic White Low SES

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CST scores have shown dramatic improvement from 2003 to 2008, especially in
Science and English. Figure F10 illustrates the improvement in each subject area.
History scores made a dramatic jump up in 2008 while Math scores dipped down after
years of steady gains.
Figure F10 – MLHS CST Scores 2003-2008, percent Proficient or Advanced
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
2003 2004 2005 2006 2007 2008
% Proficient or Advanced
English/LA History Math EOC Science EOC Science NCLB

Over 90% of all tenth grade students passed both portions of the CAHSEE exam
in 2008 on their first attempt. Table F8 demonstrates that all subgroups have performed
well on the CAHSEE exams with particularly impressive gains for African American
(98% passed English and 87% passed Math) and Special Education (65% passed Math
and English) students in 2008 compared with 2007. There is still a significant gap

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between White students and the Hispanic, EL, low SES and Special Education
subgroups.
Table F8 – MLHS CAHSEE first attempt pass rates by subgroup 2005 – 2008
English % Passed Math % Passed

2005,
n=601
2006,
n=634
2007,
n=621
2008,
n=612
2005,
n=606
2006,
n=632
2007,
n=622
2008,
n=610
All 10th Grade 92% 93% 91% 93% 89% 90% 89% 92%
Hisp/Latino 88% 89% 86% 84% 87% 84% 82% 84%
Af. Amer 87% 92% 88% 98% 77% 78% 80% 87%
White 94% 96% 93% 95% 90% 93% 91% 94%
English Learner 63% 67% 65% 63% 65% 73% 70% 69%
Low SES 78% 81% 88% 87% 77% 75% 86% 86%
SPED 49% 64% 49% 65% 38% 48% 51% 65%

Master Schedule
An examination of the courses offered in the master schedule at MLHS shows
interesting parallels with the test data above. The CST scores in English, History and
Science are substantially higher than the Math scores. As Figure F11 shows, over 20% of
the sections offered in English, History and Science are honors or AP level with a few
support classes for struggling or Special Education students. On the other hand, over
40% of all math courses are remedial or below grade level, including Algebra I which is
an eighth grade standard course.

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Figure F11 – MLHS Course Offering Levels by Subject Area
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
English History Math Science Foreign
Lang
Elective Overall
% Remedial % Regular % Advanced

A closer look at the Math sections shows that 21 of the 84 sections (25%) offered
in Math are Algebra I. Another 12 sections (14%) out of the 84 are pre-Algebra or
seventh grade standards. Figure F12 shows that of the students who took the CST tests in
grades 9-11 in 2008, 65% were in Geometry or above while the other 35% were in
Algebra I or Pre-Algebra. The students in the below grade level math courses fell from a
high of 34% to 26% in 2008 scoring advanced or proficient on the CST. The students in
Geometry or higher scored higher, but are still under 50% scoring proficient or advanced.

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Figure F12 – CST Scores for students in Geometry and above vs. Algebra I or lower
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
90.00%
100.00%
2003 2004 2005 2006 2007 2008
% Prof/Adv in Alg or low er % Prof/Adv in Geom or higher % in Geom & Above

MLHS has met AYP every year since 2004. In 2002 and 2003 AYP was not met
due to not meeting the required participation rate of 95% for the whole school and all
significant subgroups. The district has never been in program improvement and has met
AYP every year with the exception of 2002 when the participation rate did not meet the
95% standard.
Instructional Improvement Process
The dramatic gains in student performance have been supported by strong
leadership from the principal and instructional leadership team as well as efficient use of
the small amount of collaboration time and professional development opportunities.
Using data and providing intervention programs have also contributed to the gains. Each
of these aspects of the improvement process is explored in more detail in this section.

185

Leadership
The current principal is in her sixth year at MLHS and she has worked with five
different superintendents due to instability on the school board. The board is more stable
now and the current superintendent is in his second year. Because of the rapid turnover
and the nature of a unified school district, the high school operates relatively
autonomously. The principal has worked with the departments to develop pacing guides,
align their curriculums to the state standards, develop common assessments and look at
data. She has worked to get teachers to give up their pet projects that are not aligned to
the state standards. For the most part, these changes have not been top-down, instead she
has allowed each group to work at their own pace to allow buy-in to the process. The
pace in some department has been slow and frustrating for her, but the change that does
occur is more authentic and of higher quality than it would be with a top-down approach.
In Math, the principal had to have difficult conversations with the teachers this
year in order to move away from a two year Algebra program and into a traditional
Algebra program that includes a math support class for struggling students. The data
above validate that this is perhaps a needed change.
In Social Science, the department leadership was poor and change was slow, so
the principal assigned one of the assistant principals to move them along the process of
aligning standards, creating common assessments and discussing equality of the rigor
across teachers. The data were used to show the department the need for improvement.
The change was clearly evident in the CST scores (see Figure 4.2) as Social Science

186

made the largest one year gain from 45% proficient or advanced in 2007 to 52% in 2008.
The department is continuing to move forward.
There has been a great deal of turnover among the assistant principals over the
last several years. The administration meets each morning to ensure the smooth
functioning of the team. The Principal meets regularly with her Education Council which
is made of administrators, department chairs and a few others to discuss issues related to
instruction. The department chairs are expected to be instructional leaders and take an
active role in planning department meeting and collaboration days. An administrator is
also assigned to each department. Administrators are expected to be out in the
classrooms four to five hours per week.
Both the Math and Science departments want to put strict regulations on who can
move on to higher level courses, but the principal has moved in the opposite direction by
eliminating requirements and opening access to honors and AP courses to allow more
students into rigorous courses they will need to be successful in college. For English
Learner students, the principal introduced a transition class to move students into a
mainstream environment quicker than the former ELD teacher wished.
Collaboration and Professional Development
Because there is so little staff development time at MLHS with only one day for
Professional Development and a mere 10 hours built into the whole school year for
collaboration time (the fewest of all the schools in this study) each staff meeting is treated
as precious time to work in departments. The limited staff development resources are
used to provide teachers with planning time to develop common assessments and align

187

curriculum after identifying key standards. The staff is using Edusoft to help analyze
benchmark and CST data to identify trends, strengths and weaknesses.
The block schedule format allows for more activity based instruction and allows
students to work in groups to collaborate, edit and revise their work. Teachers spend
time talking about strategies to use the block time effectively.
The district offers a menu of staff development activities on the one professional
development day in the summer, but most of the offerings tend to be for elementary
teachers.
Intervention Programs
The block schedule allows for the Algebra classes and Algebra support classes to
be offered on alternating days so that students have math each day of the week and can
have the same teacher for both classes. Students also have access to after school tutoring.
A CAHSEE prep class is offered during the school day and is mandated for seniors who
have not yet passed the CAHSEE. Juniors are encouraged to enroll. An extended day
tutoring program is offered for EL students only. The program began last year and the
teachers feel it was successful.
The Infinite Campus Student Information System was phased in last year and has
helped with communication between teachers, parents and students as parents and
students have online access to view grades and attendance. The district also provides
Lead Instructional Tech Teachers (LITT) to assist with the integration of technology into
the classroom with an emphasis on how technology can be used for instruction.

188

The increase in counselors last year, thanks to new state money to lower the
student to counselor ratio, provided opportunities to bring in intervention programs to the
counseling office. Project Achieve was created by the counselors to help students with
attendance and academic problems.
A generous donation from a community member allowed the reintroduction of the
AVID program at MLHS. Given the changing economy and state budget crisis, it is
unclear how this program will be funded in subsequent years.
Resource Comparison to Evidence Based Model
MLHS, at 2,471 students, is 4.1 times bigger than the size of the prototypical high
school suggested by the Evidence Based Model (EBM). Table F9 shows that, while in
some areas MLHS is resourced similarly to the Evidence Based Model, overall MLHS is
understaffed. The last column of the table indicates the difference between the Evidence
Based Model and MLHS or indicates how the Evidence Based Model would staff or fund
a school of 2,471 students with the demographics of MLHS.
Table F9 – Comparison of actual resources at MLHS to Evidence Based Model
School Element
EBM Prototypical
High School
Actual MLHS
Resources
Difference
between EBM
and MLHS or
EBM
suggested
amount for
MLHS
School Characteristics
School Configuration 9-12 9-12
School Size 600 2,471
4.1 times
bigger
Core Class Size 25 29.75
4.75 more than
EBM

189

Table F9 – Comparison of actual resources at MLHS to Evidence Based Model
(continued)
Number of teacher work
days
200, including 10
days for intensive
training
181, including 1
inservice day
9 less inservice
days, 10 less
school days
Number Disabled
(w/IEP)
256 (10.4%)
Number Poverty (free &
reduced lunch)
370 (15%)
Number English Learner 123 (5%)
% Minority (non-white) 45%
Personnel Resources
1. Core Teachers
24 per 600 students
(75% of FTEs)
73.8 FTE
(75% of FTEs)
EBM suggests
98.8 for 2,471
students
2. Specialist Teachers
8.0
(25% of FTEs)
24.2 FTE
(25% of FTEs)
EBM suggests
32.9
3. Instructional
Facilitators/Mentors
3
(1 for every
200 students)
0
EBM suggests
12.4
4. Tutors for struggling
students
One for every 100
poverty students
0
EBM suggests
3.7
5. Teachers for EL
students
An additional 1.0
teacher for every 100
EL students
0.6 FTE
EBM suggests
1.2 FTE
6. Extended Day
1 teacher for every 15
poverty students
(based on half the
number of poverty
students), 15 hours
per week @ 25% of
salary
0.2 FTE
(1 teacher, 4 hours
per week)
EBM suggests
3.1 FTE
extended day
teachers
7. Summer School 6.3 FTE
EBM suggests
3.1 FTE
School Characteristics
8. Learning & mild
disabled students
Additional 4
professional teacher
positions for 600
students
1 Resource Room
Teacher plus core
SPED teachers
EBM suggests
16.5 teachers
for 2,471
students
9. Severely disabled
students
100% state
reimbursement minus
federal funds
1.2 FTE teachers
and 3.3 aids
Based on need
10. Resources for gifted
students
$25 per student
Gate budget of
$8,000
EBM suggests
funds of
$61,775

190

Table F9 – Comparison of actual resources at MLHS to Evidence Based Model
(continued)
11. Vocational
Education
1/3 more per student
enrolled
6.2 FTE
EBM suggests
11.2 FTE
12. Substitutes 10 days per teacher
10 days per teacher
for illness and PN

13. Pupil support staff
1 for every 100
poverty students plus
1.0 guidance per 250
students
8 Counselors
2 clerical
attendance,
1.5 Psych, 0.4
Speech, 1 health
clerk (12.9 FTE)
EBM suggests
13.6 positions
14. Non-Instructional
Aides
3.0 to relieve teachers
and provide
supervision
0
EBM suggests
11.5
15. Librarians/media
specialists
1.0 Librarian
1.0 Library Tech
1 Librarian &
2 library aides
EBM suggests
4.1 Librarians
and 4.1 Library
techs
16. Principal 1 Principal
1 Principal, 3
Assistant Principals
EBM suggests
1 Principal and
4.1 Assistant
Principals
17. School Site
Secretary
1.0 Secretary and 3.0
Clerical
3 Secretaries &
16 clerks
EBM suggests
4.1 secretaries
& 12.4 clerks
18. Professional
Development
Included above:
Instructional
facilitators, Planning
and prep time, 10
summer days
Additional: $100 per
pupil for other PD
expenses - trainers,
conferences, travel,
etc.
1 PD day in
calendar. 10 hours
per year for
collaboration = 1.4
days per year per
teacher.
$145,000 for
conferences,
substitutes, travel
& materials.
EBM suggests
10 days PD in
summer and
$247,100 for
other PD
expenses.
19. Technology $250 per pupil
1 technology
coordinator.
Resources vary
EBM suggests
$617,750
20. Instructional
Materials
$175 per pupil
EBM suggests
$432,425
21. Student Activities $250 per pupil 1 section ASB
EBM suggests
$617,750

191

Lessons Learned
With the help of a strong leader who has had to have difficult conversations with
teachers to open up the curriculum to all students, the focus of most of the staff at MLHS
is on educating all students with a rigorous program and support as needed. Those
difficult conversations and her facilitation of a bottom-up change process to develop each
department at its own pace has lead to authentic improvements in each department.
Teachers use their precious few collaboration times to analyze student data and align
their courses to the standards. A strong counseling department and a variety of
intervention programs help struggling students achieve to the standards.
Future Needs
There is a clear need at MLHS for more time for Professional Development and
collaboration. The principal would like significantly more time for teachers to work
together to look at student work. She would also like to see more intervention programs
for students, especially incoming ninth grade students, such as the Link-Crew program.

192

PM High School: A case study of Instructional Improvement
and Resource Use with a majority minority population
PM High School (PMHS) is located West of downtown Los Angeles in a diverse,
mixed income area of the city. PMHS is the only high school in the unified district that
also includes five elementary schools, one middle school and one continuation school.
PMHS uses a traditional six period per day bell schedule with a shortened day every
Wednesday to allow for collaboration time for teachers.
The demographic breakdown of PMHS has remained relatively stable over the
last several years. Currently, 23% of the student body is white (down from 27% in
2000), 38% Hispanic, 10% Asian, 23% African American (up from 20% in 2000) and 4%
Pacific Islander and Filipino. With an enrollment of 2,295 students, PMHS is the forth
largest of the six schools in this study and is the closest to the average size of the schools
in this study. Of the 2,295 students, 10.7% are English Learners (EL), 30.6% participate
in the federal free or reduced price lunch program, an indicator of poverty status, and
7.4% are in the Special Education program. Although the feeder middle school receives
Title I funding, PMHS does not. The principal feels the free and reduced price lunch rate
is under-reported once the students reach high school. The district projects that
enrollment will decline over the next few years partly due to rising housing prices forcing
younger families out of the area.
Academic Performance Index (API) scores show consistent growth in student
achievement over the last eight years. While the whole school API has grown 80 points
over the eight year time period, the African American, Hispanic and low socio-economic
status (low SES) groups have grown at even faster rates. These trends are illustrated in

193

Table F10. Although there are still significant gaps between Hispanic and white students
and between African American and white students, the gaps are less than half of what
they were only eight years ago.
Table F10 – PMHS API Scores 2000 to 2008 including subgroups
2000 2001 2002 2003 2004 2005 2006 2007 2008
Change
2000 to
2008
All Students 670 664 675 700 714 734 732 751 750 80
African American 587 579 636 652 678 700 680 701 711 124
Hispanic 573 585 609 650 664 674 683 703 705 132
White 809 769 758 768 775 814 808 821 816 7
Low SES 571 561 587 625 641 649 660 691 707 136
Hisp/White Gap 236 184 149 118 111 140 125 118 111
AA/White Gap 222 190 122 116 97 114 128 120 105

The white subgroup is the only one to reach an API over 800, but the subgroup
has not grown shown significant growth over the years. Figure F13 illustrates that the
other subgroups have consistently improved to close the gap between the white and other
subgroups.

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Figure F13 – PMHS API Scores 2000 to 2008 including subgroups
400
450
500
550
600
650
700
750
800
850
2000 2001 2002 2003 2004 2005 2006 2007 2008
API Scores
All Students African American Hispanic White Low SES

California Standards Test (CST) scores have also shown consistent improvement
over the last five years. History and Science gains in recent years are particularly
impressive (see Figure F14). Although Math scores have shown some recent
improvement, they are by far the lowest compared to the other subject areas with only
21% proficient or advanced in 2008 (compared to 54% in History).

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Figure F14 – PMHS CST Scores 2003-2008, percent Proficient or Advanced
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
2003 2004 2005 2006 2007 2008
% Proficient or Advanced
English/LA History Math EOC Science EOC Science NCLB

First time pass rates for tenth grade students on the California High School Exit
Exam (CAHSEE) are shown in Table F11. Overall, 86% passed the English portion of
the exam in 2008 and 89% passed the math portion. White and African American
students consistently have the highest pass rates with larger margins in English than
Math. The Special Education and EL groups show great fluctuation from year to year in
English scores, but they are consistently low.

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Table F11 – PMHS CAHSEE first attempt pass rates by subgroup 2005 – 2008
English % Passed Math % Passed

2005,
n=604
2006,
n=506
2007,
n=578
2008,
n=558
2005,
n=608
2006,
n=510
2007,
n=581
2008,
n=524
All 10th Grade 85% 86% 90% 86% 82% 83% 85% 89%
Hisp/Latino 75% 79% 83% 79% 72% 79% 80% 85%
Af. Amer 86% 82% 87% 90% 83% 73% 77% 87%
White 95% 94% 97% 93% 93% 92% 92% 96%
English Learner 49% 60% 63% 49% 63% 61% 64% 63%
Low SES 70% 75% 81% 81% 73% 76% 79% 83%
SPED 34% 50% 49% 36% 32% 42% 39% 53%

Master Schedule
The courses offered at PMHS show some interesting parallels with the test data
above. In 2008, the highest CST scores were in English and History. These are also the
core subjects in which the most Advanced Placement (AP) and honors courses are
offered. Figure F15 shows the course offerings in each subject area broken into the
percent remedial, regular and advanced (AP and honors). In math, the core subject with
the lowest CST scores, 27 of the 71 sections offered (38%) are Algebra I sections. Since
Algebra I is an eighth grade standard, Algebra I is considered a remedial course.

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Figure F15 – PMHS Course Offering Levels by Subject Area
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
English History Math Science Foreign Lang Elective OVERALL
% Remedial % Regular % AP/Honors

Further analysis of the Math scores shows that 35% of the students tested in
grades 9-11 in 2008 were in Algebra I or General Math. Only 13% of those students
scored proficient or advanced. The other 65% of math CST takers were in Geometry or
above. Those students scored modestly better in 2008 with 26% scoring proficient or
higher. Figure F16 shows that the percent of students tested in Geometry or above has
been fairly stagnant over time. Over the same time period, only modest gains have been
made in the percent of students scoring proficient or advanced in any math course. The
data for Algebra I may be somewhat skewed because PMHS offers a two year Algebra I
program for struggling students. The students in the first year of the two year program
can not take the Algebra I CST. This does not explain the overall poor performance in

198

math relative to the other subjects, but any further discussion is beyond the scope of this
study.
Figure F16 – CST Scores for students in Geometry and above vs. Algebra I or lower
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
90.00%
100.00%
2003 2004 2005 2006 2007 2008
% Prof/Adv in Alg or low er % Prof/Adv in Geom or higher % in Geom & Above

PMHS has made AYP every year with the exception of last year. The EL
subgroup did not make AYP in the area of proficiency rate on the English portion of the
CAHSEE. Table F11 shows the sharp drop from 2007 to 2008 on the English portion of
the CAHSEE for the EL group. All other criteria for AYP were met in 2008. The district
overall made AYP last year and has never been in program improvement.
Instructional Improvement Process
The improvement process at PMHS is largely a function of strong leadership and
a dedicated staff of teachers and support staff that have worked to ensure that every
student succeeds. Some of the key components to the instructional improvement process

199

have been PMHS’s use of data to identify struggling students and key standards to target
with benchmark assessments along with a focus on Professional Development related to
instructional strategies. The time provided for professional development and
collaboration is complimented by a strong instructional leadership team. Finally, PMHS
has implemented a variety of intervention programs to assist struggling students. These
key components are discussed in more detail in this section.
Using Data and Assessments to Guide Instruction
The district recently invested in a new data system, Galileo, to assist in analyzing
data. Teachers are using data to identify the most important standards and standards that
students are struggling with. The teachers then create benchmark assessments to measure
student progress. The English and Math teachers have developed three benchmark
assessments and Science and Social Science are beginning the process. A teacher
specialist assists with inputting data and shares reports with teachers.
Collaboration and Professional Development
Collaboration time is built into the calendar one hour every week. One of the
collaboration days per month is for the whole staff to meet together, two are for
department collaboration and meeting time and the forth is flexible and is used as needed
for either whole staff or department collaboration. The instructional leadership team
(ILT), made up of department chairs, administrators, a counselor, the technology
coordinator, the athletic director and the ASB advisor, is using some of the collaboration
time to review Marzano’s (2003) work on effective strategies for student achievement.
They are also introducing a schoolwide focus on writing and have brought in an

200

educational consultant to help teachers with instructional strategies. The ILT has
surveyed the staff to help set the direction of where the staff wants to go and seeks to
honor the wishes of the staff while still pushing to move the school forward. Developing
buy-in from the teachers is of great importance to the leadership team.
In addition to the weekly collaboration time, PMHS has four staff development
days, three at the beginning of the year and one mid-year for teachers to identify the most
important content standards in their subject area and plan benchmarks. The time is also
used to promote AVID strategies among the staff and develop the mission and direction
of the staff for the year.
PMHS has had little guidance from the district office in their improvement
process due to unstable leadership at the district level. With new leadership, the district
is getting more involved and is adding layers of accountability.
Interventions
Many intervention programs have been implemented and the staff is always
looking for proven ways to meet the needs of struggling students. The Read 180 program
was newly implemented this year to assist struggling English students and the staff is
finding early signs of success with the program.
PMHS is in the third year of implementing the AVID program and they are using
professional development and collaboration time to train the whole staff to use AVID
strategies school-wide. Because PMHS is not a Title I school (even though the middle
school is) the cost of the AVID program is being pieced together from a variety of

201

categorical program funds at the district level including English Learner funds, Title 3
and CAHEE funds.
PMHS offers class size reduction in ninth grade English, pre-Algebra and Algebra
I. Tutoring is offered before and after school with teachers from a variety of subject
areas along with volunteer peer tutors. Data from the Galileo information system are
used to identify students that are not meeting standards and then teachers have
opportunities to discuss what strategies they have found to work with those particular
students. Beginning EL students are in a self-contained environment for their core
classes for the first year in the program. After the first year, the EL students begin the
mainstreaming process in sheltered classes.
A two year Algebra program is offered to students who struggle with math.
Although the department chair likes the program, the principal has doubts about its
effectiveness. The Math data discussed in the previous section seem to validate her
skepticism.
Resource Comparison to the Evidence Based Model
PMHS, at 2,295 students, is 3.8 times bigger than the size of the prototypical high
school suggested by the Evidence Based Model (EBM). Table F12 shows that, while in
some areas PMHS is resourced similarly to the Evidence Based Model, overall PMHS is
understaffed. The last column of the table indicates the difference between the Evidence
Based Model and PMHS or indicates how the Evidence Based Model would staff or fund
a school of 2,295 students with the demographics of PMHS.

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Table F12 – Comparison of actual resources at PMHS to Evidence Based Model
School Element
EBM Prototypical
High School
Actual PMHS
Resources
Difference
between EBM
and PMHS or
EBM
suggested
amount for
PMHS
School Characteristics
School Configuration 9-12 9-12
School Size 600 2,295
3.8 times
bigger
Core Class Size 25 27
2 more than
EBM
Number of teacher work
days
200, including 10
days for intensive
training
184, including 4
inservice days
6 less inservice
days, 10 less
school days
Number Disabled
(w/IEP)
170 (7.4%)
Number Poverty (free &
reduced lunch)
703 (30.6%)
Number English Learner 245 (10.7%)
% Minority (non-white) 77%
Personnel Resources
1. Core Teachers
24 per 600 students
(75% of FTEs)
68.6 FTE
(77% of FTEs)
EBM suggests
91.8 for 2,295
students
2. Specialist Teachers
8.0
(25% of FTEs)
20.6 FTE
(23% of FTEs)
EBM suggests
30.6
3. Instructional
Facilitators/Mentors
3 (1 for every
200 students)
0
EBM suggests
11.5
4. Tutors for struggling
students
One for every 100
poverty students
0
EBM suggests
7
5. Teachers for EL
students
An additional 1.0
teacher for every 100
EL students
1 FTE
EBM suggests
2.5 FTE
6. Extended Day
1 teacher for every 15
poverty students
(based on half the
number of poverty
students), 15 hours
per week @ 25% of
salary
1.5 FTE
(28 teacher hours
per week)
EBM suggests
5.9 FTE
extended day
teachers

203

Table F12 – Comparison of actual resources at PMHS to Evidence Based Model
(continued)
7. Summer School

4.5 FTE
EBM suggests
5.9 FTE
School Characteristics
8. Learning & mild
disabled students
Additional 4
professional teacher
positions for 600
students
2.8 Inclusion and
Resource Room
Teachers
EBM suggests
15.3 teachers
for 2,295
students
9. Severely disabled
students
100% state
reimbursement minus
federal funds
1 FTE teachers and
7 aids
Based on need
10. Resources for gifted
students
$25 per student
No GATE budget.
Accumulated AP
Test Fees =
$15,000
EBM suggests
funds of
$57,375
11. Vocational
Education
1/3 more per student
enrolled
4 FTE
EBM suggests
7.2 FTE
12. Substitutes 10 days per teacher
10 days per teacher
for illness and PN

13. Pupil support staff
1 for every 100
poverty students plus
1.0 guidance per 250
students
9 Counselors
3 clerical
attendance
1 Nurse, 1 Psych, 1
Speech, 1 health
clerk (16 FTE)
EBM suggests
16.2 positions
14. Non-Instructional
Aides
3.0 to relieve teachers
and provide
supervision
1
EBM suggests
11.5
15. Librarians/media
specialists
1.0 Librarian
1.0 Library Tech
1 Librarian &
2 library aides
EBM suggests
3.8 Librarians
and 3.8 Library
techs
16. Principal 1 Principal
1 Principal, 3
Assistant Principals
EBM suggests
1 Principal and
3.8 Assistant
Principals
17. School Site
Secretary
1.0 Secretary and 3.0
Clerical
2 Secretaries &
8 clerks
EBM suggests
3.8 secretaries
& 11.5 clerks

204

Table F12 – Comparison of actual resources at PMHS to Evidence Based Model
(continued)
18. Professional
Development
Included above:
Instructional
facilitators, Planning
and prep time, 10
summer days
Additional: $100 per
pupil for other PD
expenses - trainers,
conferences, travel,
etc.
4 PD days in
calendar. 1 hour
each week for
collaboration = 5.5
days per year per
teacher.
$26,500 for
conferences,
substitutes, travel
& materials.
EBM suggests
10 days PD in
summer and
$229,500 for
other PD
expenses.
19. Technology $250 per pupil
1 technology
coordinator.
Resources vary
EBM suggests
$573,750
20. Instructional
Materials
$175 per pupil
EBM suggests
$401,625
21. Student Activities $250 per pupil
1 section ASB, 1
section Peer
Counseling
EBM suggests
$573,750

Lessons Learned
PMHS is dedicated to educating all students in the school by providing
interventions to struggling students, and opening enrollment in advanced and AP courses
to more and more students. Data are consistently used to guide instruction and plan
benchmark assessments with the help of a teacher specialist. Teachers use data and
assessment to ensure that the curriculum is aligned to state standards and benchmark
assessments measure student progress in meeting those standards. Weekly collaboration
and four PD days are dedicated to planning and training in effective instructional
strategies. Struggling students are given access to a variety of support programs during
the school day and during extended day tutoring time. The Instructional Leadership
Team builds buy-in and challenges the staff to move the school forward and the staff has
ample time to plan and participate in PD opportunities.

205

Future Needs
If more resources were available, the principal of PMHS sees the most critical
needs in the areas of curriculum and instruction. She would like to have more time for
Professional Development and more resources to bring in more consultants and experts to
continue improving instructional strategies. Ideally, she would like to have instructional
coaches to work with her teachers. In addition to more training opportunities, a need that
was evident in the exploration of test data above is a research based math program that is
proven to be effective. She would also like to explore the possible benefits of an
alternative bell schedule which may include block scheduling or an advisory period.

206

SR High School: A case study of Instructional Improvement
and Resource Use with a majority minority population
Located on the Eastern edge of Los Angeles county in a unified district that
includes 44 elementary, middle and high schools, SRHS straddles two diverse middle
income communities. With an enrollment of 1,815 students in grades 9-12, SRHS is one
of only two schools in this study with less than 2,000 students. The demographics of
SRHS reflect the community in which it is located: 13% African American students,
16% Asian students, 5% Filipino students, 41% Hispanic students (up from 33% in 2000)
and 25% white students (down from 33% in 2000). Twenty-nine percent of the student
body participates in the federal free and reduced price lunch program, an indicator of the
poverty level of the school. In addition, 8.8% of the students are English Learners (EL)
and 7.2% are in special education.
SRHS began with a ninth grade class in 1997 and graduated its first senior class in
2001. The current Principal was a teacher at the school when it opened and has been the
Principal for the past four years. From the beginning, the staff and leadership of the
school built a positive learning environment with high expectations and layers of support.
SRHS is on a traditional six period bell schedule five days per week. Because the school
is relatively new and because of a commitment to the latest in technology when it was
built, almost every teacher has an LCD projector and 25 teachers have Smartboards.
There are a plethora of computers available to students.
SRHS is the highest performing school in this study in terms of API and
standardized test scores. Table F13 shows the API gains from 2000 to 2008. The whole
school has grown from an API of 660 to 808, a gain of 148 points in eight years. Even

207

more impressive, the consistently growing Hispanic population has steadily improved
from an API of 590 in 2000 to 779 in 2008, a gain of 189 points over the eight year
period.
Table F13 – SRHS API Scores 2000 to 2008 including subgroups
2000 2001 2002 2003 2004 2005 2006 2007 2008
Change
2000 to
2008
All Students 660 645 694 739 768 791 807 798 808 148
African American 583 574 628 676 746 725 737 750 741 158
Hispanic 590 570 642 685 715 756 775 750 779 189
White 710 703 797 775 795 821 847 839 822 112
Low SES 570 539 615 669 711 757 781 749 769 199
Hisp/White Gap 120 133 155 90 80 65 72 89 43
AA/White Gap 127 129 169 99 49 96 110 89 81

The achievement gap between the White students and Hispanic students has
dwindled from a high of 155 points in 2003 to only 43 API points in 2008. Figure F17
shows these impressive gains and the shrinking gaps between all the subroups.

208

Figure F17 – SRHS API Scores 2000 to 2008 including subgroups
400
450
500
550
600
650
700
750
800
850
900
2000 2001 2002 2003 2004 2005 2006 2007 2008
API Scores
All Students African American Hispanic White Low SES

CST scores have steadily increased in English and Science as shown in Figure
F18. In 2008 66% of all students scored proficient or advanced on the English portion of
the CSTs and 55% scored proficient or advanced on the Science portion. The History
scores have shown some fluctuation with a high of 60% proficient or advanced in 2006
and declines over the last two years. Math scores have been low and stagnate between
21% and 26% proficient or advanced.

209

Figure F18 – SRHS CST Scores 2003-2008, percent Proficient or Advanced
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
2003 2004 2005 2006 2007 2008
% P ro ficie n t o r A d va n ce d
E nglish/LA History M ath E OC Science E OC Science NCLB

Surprisingly, Math CST scores have remained low despite a high percentage of
students enrolled in Geometry and above. Nearly 90% of students tested in grades 9-11
were enrolled in Geometry or above indicating that they are placed at the appropriate
math grade level according to the state standards. Despite the appropriate rigor of the
courses as compared to the other schools in this study, the math CST scores are still low
(see figure F19). This is an interesting trend, but further discussion is beyond the scope
of this study.

210

Figure F19 – CST Scores for students in Geometry and above vs. Algebra I or lower
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
90.00%
100.00%
2003 2004 2005 2006 2007 2008
% Prof/Adv in Alg or low er % Prof/Adv in Geom or higher % in Geom & Above

CAHSEE scores show consistently high performance in both Math and English
overall and for most subgroups. Overall pass rates are above 90% in both Math and
English for first time test takers in tenth grade. The English Learner scores are
particularly impressive with 80% passing the English portion in 2008 while still working
to learn English as a secondary language. Table F14 shows the CAHSEE results in Math
and English for all subgroups.
Table F14 – SRHS CAHSEE first attempt pass rates by subgroup 2005 – 2008
English % Passed Math % Passed

2005,
n=471
2006,
n=459
2007,
n=420
2008,
n=450
2005,
n=471
2006,
n=463
2007,
n=420
2008,
n=449
All 10th Grade 93% 95% 93% 93% 89% 91% 92% 91%
Hisp/Latino 91% 95% 92% 90% 87% 89% 92% 86%
Af. Amer 84% 85% 85% 90% 79% 77% 83% 84%
White 98% 97% 93% 98% 95% 96% 91% 96%
English Learner 78% 79% 74% 80% 78% 78% 85% 83%
Low SES 90% 92% 88% 91% 88% 90% 88% 87%
SPED 46% 47% 43% 46% 35% 38% 43% 40%

211

Although the district in which SRHS is located is in Program Improvement,
SRHS is not and the school has always met its AYP targets.
Master Schedule
An analysis of the master schedule at SRHS shows evidence of the school’s
commitment to high levels of rigor with a variety of support systems. In the core content
areas about 30% of all courses are honors or AP classes. In Math and English, another
30% are devoted to support or remedial classes to help struggling students. Figure F20
shows the percentages of remedial, regular and advanced courses in the various subject
areas. SRHS has the highest percent of honors and AP courses of the six schools in this
study.
Figure F20 – SRHS Course Offering Levels by Subject Area
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
English History Math Science Foreign
Lang
Elective Overall
% Remedial % Regular % Advanced

212

Instructional Improvement Process
Since the doors opened in 1997, SRHS has been dedicated to high standards and
meeting the needs of students. SRHS offers a variety of intervention programs for
struggling students and is very intentional about following protocols to ensure that
students are placed appropriately in these classes. The staff is highly collaborative and
focused on analyzing data and adjusting instruction to meet the needs of students. The
high standards of the staff translate to high levels of achievement from students who are
encouraged to take a rigorous course of study at SRHS. The sections below discuss these
key points in more detail.
Interventions
At the district level, detailed protocols have been designed to assist the site in
placing students in appropriate intervention programs. These protocols are endorsed by
the administrative team and strictly followed. This process is made smoother because
SRHS is located in a unified school district where information about students can easily
be shared between middle school and high school staff. Incoming ninth grade students
who score low in math based on eighth grade benchmark scores, CST scores or grades
are placed in Algebra 1 and Algebra support. Students who score low in English coming
into ninth grade are placed in ninth grade English and a support class that utilizes the
Read 180 curriculum. A small group of the lowest achieving ninth grade students have
all their core classes with one teacher who has a multiple subject credential. This newly
created, small intervention class facilitates more individual attention to the struggling
students.

213

In preparation for the CAHSEE exam, a CAHSEE Academy is offered for four to
six Saturdays before each test administration. The Academy classes are targeted to
students who are below basic according to CST scores or who have attempted but have
not passed the CAHSEE. All students are welcome and encouraged to attend. Over 200
students typically attend the academy sessions. A similar academy is offered prior to the
CST exams with two Saturdays devoted to Math, two to Science and one each to Social
Science and English. Typically, 200 students attend these sessions. The Measuring Up
curriculum is used for CAHSEE prep. As an informal mentoring program, each teacher
in the school is assigned two to three students to focus on. Currently, Class Size
Reduction is only offered in the support classes for Math and English. It was phased out
of ninth grade English and Algebra I last year.
Collaboration and Professional Development
A variety of collaboration opportunities provide teachers with time to analyze the
standards and student work, develop common assessments and share strategies. In
addition to the collaboration time, the district provides six days of pupil free professional
development, the most of any school in this study. About 15 to 20 teachers per year
participate in outside conferences for professional development, otherwise professional
development is limited to staff meetings and is mostly provided by the school’s staff with
some support from the district office.
There is one late start day each week where students come late and teachers have
time for collaboration or professional development. In addition to the weekly morning
meetings, departments meet once per month after school. An additional hour after school

214

per month is allocated to staff meeting time and is typically used for professional
development. The collaboration time is organized as Professional Learning Communities
where the focus is developing common formative and summative assessments and
discussing strategies for differentiating instruction. Teachers use common assessments
and district benchmarks in addition to standardized test scores to analyze data.
Focus on Student Achievement
From the beginning, there has been a culture of high standards nurtured by the
commitment of the staff. An analysis of the master calendar indicates that the focus of
the school’s curriculum is on core classes with very few electives. About 75% of all
sections are in the core content areas of English, History, Math, Science and Foreign
Language. The lowest course offered in Math is Algebra I and support classes are
provided to struggling math students to facilitate their success in a rigorous curriculum.
In place of a nutrition break, the whole school works on writing for ten minutes per day
with writing activities developed by a group of teachers. Because it is teacher developed,
there is more buy-in to the program. Although 160 students are classified as EL only 25
are actually in EL classes, the rest are mainstreamed into regular classes. The results of
this commitment to mainstreaming are clear in the standardized test data where 80% of
the EL students passed the English portion of the CAHSEE last year.
The Silver Baccalaureate program was developed three years ago for the highest
achieving students and has seen a steady rise in enrollment. Students must apply to the
program and once admitted participate in a rigorous course of study that is modeled after
the International Baccalaureate program.

215

Resource Comparison to Evidence Based Model
At three times bigger than the prototypical school of the Evidence Based Model
(EBM), SRHS is one of the smallest schools in this study and one of only two with less
than 2,000 students. In some areas SRHS comes the closest of all the schools in this
study to achieving the proportions recommended in the Evidence Based Model. With the
most Professional Development days built into the calendar, six throughout the year,
SRHS is still short of the ten recommended by the Evidence Based Model. Table F15
shows how the resources at SRHS compare to the Evidence Based Model. The last
column indicates the difference between the Evidence Based Model and SRHS or
indicates how the Evidence Based Model would staff a school of 1,815 students with the
demographics of SRHS.
Table F15 – Comparison of actual resources at SRHS to Evidence Based Model
School Element
EBM Prototypical
High School
Actual SRHS
Resources
Difference
between EBM
and SRHS or
EBM
suggested
amount for
SRHS
School Characteristics
School Configuration 9-12 9-12
School Size 600 1815 3 times bigger
Core Class Size 25 30
5 more than
EBM
Number of teacher work
days
200, including 10
days for intensive
training
188 including 6
Prof. Devel. days
4 less Prof.
Devel. days, 8
less school
days
Number Disabled
(w/IEP)
132 (7.3%)

216

Table F15 – Comparison of actual resources at SRHS to Evidence Based Model
(continued)
Number Poverty (free &
reduced lunch)
527 (29%)
Number English Learner 160 (8.8%)
% Minority (non-white) 59%
Personnel Resources
1. Core Teachers
24 per 600 students
(75% of FTEs)
55
(74% of FTEs)
EBM suggests
72.6 for 1815
students
2. Specialist Teachers
8.0
(25% of FTEs)
19.4
(26% of FTEs)
EBM suggests
24.2
3. Instructional
Facilitators/Mentors
3
(1 for every
200 students)
0
EBM suggests
9
4. Tutors for struggling
students
One for every 100
poverty students
0
EBM suggests
5.27
5. Teachers for EL
students
An additional 1.0
teacher for every 100
EL students
0.2
EBM suggests
1.6
6. Extended Day
1 teacher for every 15
poverty students
(based on half the
number of poverty
students), 15 hours
per week @ 25% of
salary
0
EBM suggests
4.4 FTE
extended day
teachers
7. Summer School 6.25 FTE
EBM suggests
4.4 FTE
Teachers
School Characteristics
8. Learning & mild
disabled students
Additional 4
professional teacher
positions for 600
students
6.4 FTE
EBM suggests
12.1 teachers
for 1815
students
9. Severely disabled
students
100% state
reimbursement minus
federal funds
1 FTE teachers and
4 aides for 19
students
Based on need

217

Table F15 – Comparison of actual resources at SRHS to Evidence Based Model
(continued)
10. Resources for gifted
students
$25 per student
91 sections of
honors or AP
courses plus Gate
budget of $3,000
EBM suggests
funds of
$45,375
11. Vocational
Education

1/3 more per student
enrolled
4.6 FTE
EBM suggests
8.3 FTE
12. Substitutes 10 days per teacher 10 days per teacher
13. Pupil support staff
1 for every 100
poverty students plus
1.0 guidance per 250
students
6 Counselors
5 clerical
attendance
0.5 Nurse, 1 Psych,
0.1 Speech, 1
health clerk (13.6
FTE)
EBM suggests
12.5 FTEs
14. Non-Instructional
Aides
3.0 to relieve teachers
and provide
supervision
0
EBM suggests
9
15. Librarians/media
specialists
1.0 Librarian
1.0 Library Tech
1 Librarian &
1 library aides
EBM suggests
3 Librarians
and 3 Library
techs
16. Principal 1 Principal
1 Principal, 4
Assistant Principals
EBM suggests
1 Principal and
3 Assistant
Principals
17. School Site
Secretary
1.0 Secretary and 3.0
Clerical
2 Secretaries &
10 clerks
EBM suggests
3 secretaries &
9 clerks
18. Professional
Development
Included above:
Instructional
facilitators, Planning
and prep time, 10
summer days
Additional: $100 per
pupil for other PD
expenses - trainers,
conferences, travel,
etc.
6 PD days in
calendar. 1 hour
each week for
collaboration plus 2
hours per month
after school = 6.9
days, $9,500 for
conferences and
travel.
EBM suggests
10 days PD in
summer and
$181,500 for
other PD
expenses.

218

Table F15 – Comparison of actual resources at SRHS to Evidence Based Model
(continued)
19. Technology $250 per pupil
1 technology
coordinator. 5:1
computer to student
ratio, technology
throughout school
EBM suggests
$453,750
20. Instructional
Materials
$175 per pupil
EBM suggests
$317,625
21. Student Activities $250 per pupil
1 section ASB, 1
section Peer
Counseling
EBM suggests
$453,750

Lessons Learned
The success of SRHS begins with the high expectations of the staff for their
students. High expectations are balanced by strong support programs for struggling
students. The staff, working in a collaborative PLC model has adopted a rigorous
curriculum that focuses on the core content areas. With weekly collaboration time, the
staff analyzes student work, breaks down the standards, shares effective strategies and
develops common assessments. Professional Development is site based, tailored to the
needs of the staff and presented by colleagues from within increasing the level of buy-in.
Future Needs
In order to continue improving more resources are needed for professional
development in the areas of collaboration time (paying teachers for their time),
conferences and materials. In addition, lower class sizes and more resources to improve
and maintain the current technology resources are needed.

219

VB High School: A case study of Instructional Improvement
and Resource Use with a majority minority population
Victor Bustamante High School (VBHS) is located in a highly diverse, urban
community in southwest Los Angeles. VBHS is one of 3 comprehensive high schools in
a high school district that also contains an arts magnet school and a continuation school.
The school was reopened eleven years ago and has been going through an extensive
remodel for the last several years. A block bell schedule is used to provide longer class
periods.
VBHS stands out among the other schools in this study for several reasons. It has
the highest poverty rate with 65% of students participating in the free or reduced price
lunch program. It also has the highest percentage of non-white minority students at 94%,
the highest percentage of EL students at 15.6% (despite the placement of beginning EL
students at another school within the district) and the smallest student population with
only 1,400 students. It is the only school in this study that receives Title I funds.
Although VBHS is eligible to be a Title I school they chose to be only a partial Title I
school in order to avoid some of the mandates of being a 100% Title I campus. VBHS
has met AYP every year since 2003, but the district has been in program improvement for
three years, and the other two comprehensive high schools in the district have been in
program improvement for five years each. Even the arts magnet school is in its first year
of program improvement. VBHS is the only school in the district that is not in program
improvement.
The eight year growth in API scores, as shown in Table F16, are the most
impressive in this study with an overall gain of 252 API points since 2000 giving the

220

school a current API of 750. Because the white population of VBHS is so small, the
scores are not reported by the state so there is no achievement gap shown in table F16 as
it was in the other case studies.
Table F16 – VBHS API Scores 2000 to 2008 including subgroups
2000 2001 2002 2003 2004 2005 2006 2007 2008
Change
2000 to
2008
All Students 498 509 530 589 653 706 725 733 750 252
African American 487 476 495 543 607 676 693 695 724 237
Hispanic 486 505 520 597 660 707 733 734 746 260
Low SES 494 510 518 588 648 698 725 730 748 254

Figure F21 visually illustrates the rapid rise in API scores since 2000. Although
African American students seem to be performing a little lower than Hispanic students,
the gap seems to be closing and African American scores have increased 237 points since
2000.
Figure F21 – VBHS API Scores 2000 to 2008 including subgroups
400
450
500
550
600
650
700
750
800
850
900
2000 2001 2002 2003 2004 2005 2006 2007 2008
API Scores
All Students African American Hispanic Low SES

221

Student’s scores on CST tests have steadily improved over the last five years with
an almost linear increase in the percent of students scoring proficient or advanced in
English, flat and then rapid growth in Science scores and steady growth in History scores
(see Figure F22). Math scores have declined over the last four years from a high of 28%
of students scoring proficient or advanced in 2005 down to 21% in 2008.
Figure F22 – VBHS CST Scores 2003-2008, percent Proficient or Advanced
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
2003 2004 2005 2006 2007 2008
% Proficient or Advanced
English/LA History Math EOC Science EOC Science NCLB

Interestingly, Math scores began their decline after the pre-Algebra class was
phased out and all students began high school in Algebra I or higher. Figure F23 shows
that beginning in 2005, more and more students were enrolled in Geometry or higher, but
at the same time, student performance on the CSTs declined for students in Algebra I
(18% were proficient or advanced in 2008) and for students in higher levels of Math
(24% were proficient or advanced in 2008).

222

Figure F23 – CST Scores for students in Geometry and above vs. Algebra I or lower
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
90.00%
100.00%
2003 2004 2005 2006 2007 2008
% Prof/Adv in Alg or low er % Prof/Adv in Geom or higher % in Geom & Above

CAHSEE pass rates have shown some improvement over the last four years.
Table F17 shows scores for first time test takers in tenth grade of each year. Although
there is some fluctuation among each subgroup in pass rates, the overall trend is
increasing numbers of students are passing with 84% passing the English portion in 2008
and 82% passing the Math portion.
Table F17 – VBHS CAHSEE first attempt pass rates by subgroup 2005 – 2008
English % Passed Math % Passed

2005,
n=331
2006,
n=367
2007,
n=307
2008,
n=356
2005,
n=331
2006,
n=369
2007,
n=307
2008,
n=353
All 10th Grade 79% 83% 86% 84% 80% 83% 82% 82%
Hisp/Latino 78% 85% 87% 86% 81% 85% 83% 81%
Af. Amer 74% 80% 78% 79% 76% 76% 76% 79%
White 80% 80% 92% 74% 75% 88% 85% 94%
English Learner 71% 67% 50% 63% 71% 66% 50% 60%
Low SES 77% 83% 85% 85% 80% 82% 83% 82%
SPED 26% 24% 40% 24% 26% 50% 27% 28%

223

Master Schedule
An analysis of the master schedule helps in understanding the test data above. In
English, History and Science a balance of advanced, regular and remedial courses are
offered to provide the appropriate rigor and support for students as needed. As illustrated
in Figure F24, a disproportionate number of Math courses offered are either remedial or
below grade level. Out of the 58 sections of math in the master schedule 20 are Algebra I
- 35% of all math sections.
Figure F24 – VBHS Course Offering Levels by Subject Area
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
English History Math Science Foreign Lang Elective Overall
% Remedial % Regular % Advanced

Instructional Improvement Process
The impressive gains detailed above are the result of a small dedicated staff of
teachers and administrators working hard and innovating in the belief that all their
students can be successful. The next section details the important aspects of leadership,

224

curriculum, collaboration and interventions that have enabled the rapid rise in student
performance.
Leadership
At VBHS, the administrators are consistently in classrooms observing and
supporting teachers. For informal visits, administrators use a rubric in each classroom
they visit to document how the teacher is checking for understanding (and re-teaching as
appropriate), connecting the lesson to the state standards and district pacing guide,
instructing from bell to bell and nurturing a positive classroom environment. The
consistent presence of the administrators in the classroom promotes their value as
instructional leaders on campus. To help ensure that all the administrators have
opportunities to get into the classroom, the principal sometimes helps with handling
student discipline issues.
Because of the block schedule design, teachers are expected to engage all students
in meaningful activities with special emphasis on typically non-engaged students. For
some teachers, it was a longer process to get them to buy into the block schedule design
and how it can help engage students with more opportunities for active engagement. The
instructional coaches showed more reluctant teachers how other teachers were using the
block time effectively to help them buy into the process. Teachers have now bought in
and are working to engage all students. They are using formative assessments to check
for understanding and students are asking more questions.

225

The school district, which is in program improvement, provides many mandates
to VBHS, but because the school has shown such success there is some flexibility with
implementation.
Staff members have attended trainings by Rick Dufour on the Professional
Learning Community (PLC) model. The school took the idea of critical questions and
selectively chose other pieces that work for them in their own PLC model. They
eliminated some of the ideas that do not work for them.
Because the staff is small, the school is new and the principal was allowed to hire
almost all of his own teachers when the school opened eleven years ago, the Principal is
able to work with the staff effectively to get buy-in to the mission and vision of the
school. The two instructional coaches are key to this process as they were both teachers
at the school and are well respected by the staff. Many of the teachers have leadership
roles on the staff in moving the school forward and the entire staff feels a level of
ownership and internal accountability to innovate and improve. The staff is well
informed on how the school is performing and takes great pride in their accomplishments.
For many years the district was in disarray due to problems on the school board and rapid
turnover of superintendents, so the staff of VBHS took ownership of the school to move
it forward. The district is now recognizing the success of the school and wants to
increase the size by 150 students next year.
Curriculum
VBHS is the only school in this study to make use of instructional coaches. Two
FTE coaches analyze data and work with teachers on curriculum and pacing guides in

226

Math and English. English has been the instructional focus for the last several years with
help from California State University, Dominguez Hills to work on expository writing
skills. They have worked to incorporate writing across the curriculum school-wide. One
of the Program Improvement mandates is the training of staff in specific textbook use.
For English, this means a move away from a curriculum based on novels to one that more
closely follows a standards aligned textbook.
In Science, VBHS recently created a Marine Science Academy (MSA) program.
The hope is that the program helps focus students on the core curriculum by making it
relevant outside of school. Using a school-within-a-school design, the MSA students get
more individualized attention and have certain requirements for tutoring, community
service and outside of school learning opportunities at local aquariums.
In building the master schedule, the Principal and department leadership work to
ensure that teachers teach both low level and higher level classes so that the lowest
performing students benefit from the best teachers.
In Math, the Mastery Math program is used to help students gain proficiency in
all areas of Algebra. Algebra I is divided into four quads (one per quarter). For each
unit, students have three opportunities to demonstrate mastery of the concepts, but they
must do a certain amount of homework in order to qualify to take the tests. Students
must demonstrate mastery by scoring 80% on the assessment before they can move on to
the next quad level. Student progress in each quad is measured with benchmark
assessments and four mini assessments per quarter.

227

Collaboration
The district provides three staff development days per year, but the trainings are
driven by the district. This last year the focus of the three days was on benchmark testing
to measure progress toward meeting the standards. During the three prior years the focus
of the district professional development was on aligning the curriculum to content
standards.
Students are released early two days per month to allow time for teacher
collaboration in departments or for school-wide meetings to work on the WASC report or
to review the latest data. Twelve of the eighteen collaboration days are used in
departments to discuss data, instructional strategies and ways to check for understanding.
The other six collaboration days are school-wide meetings that are designed by the
administration team and instructional coaches to look at school-wide data.
Monthly after school faculty meetings are used to deal with the business of
running the school and to promote a positive school climate.
Using Data
Teachers review both internal and external data by using benchmark assessments,
textbook generated tests, action learning projects and data analysis of statewide measures
using Data Director. The district is more focused on external measures.
Interventions
For English, VBHS offers the Read 180 program as a double period along with
the grade level English class. The Read 180 program is supposed to help students
improve two grade levels per year, but due to problems of fidelity of the program, they

228

have not found great success with Read 180. The program is highly dependent on the
skill of the teacher with the program.
Students also have access to tutoring outside of school hours through the Title I
tutoring program. CAHSEE intervention classes are offered during the school day. The
summer school program is only for remediation and maintains high expectations for
students so that it is not seen as an easy way out for students.
Resource Comparison to Evidence Based Model
VBHS, at 1,400 students, is the smallest school in this study but is still 2.33 times
bigger than the size of the prototypical high school suggested by the Evidence Based
Model (EBM). Table F18 shows that, while in some areas VBHS is resourced similarly
to the Evidence Based Model, overall VBHS is understaffed. It is worth noting that 83%
of the teacher FTEs are in the core subject areas, the most of any school in this study and
8% above the Evidence Based Model recommendation of 75%. The last column of the
table indicates the difference between the Evidence Based Model and VBHS or indicates
how the Evidence Based Model would staff or fund a school of 1,400 students with the
demographics of VBHS.

229

Table F18 – Comparison of actual resources at VBHS to Evidence Based Model
School Element
EBM Prototypical
High School
Actual VBHS
Resources
Difference
between EBM
and VBHS or
EBM
suggested
amount for
VBHS
School Characteristics
School Configuration 9-12 9-12
School Size 600 1,400
2.33 times
bigger
Core Class Size 25 27.6
2.6 more than
EBM
Number of teacher work
days
200, including 10
days for intensive
training
183, including 3
inservice days
7 less inservice
days, 10 less
school days
Number Disabled
(w/IEP)
121 (8.6%)
Number Poverty (free &
reduced lunch)
909 (64.9%)
Number English Learner 219 (15.6%)
% Minority (non-white) 94%
Personnel Resources
1. Core Teachers
24 per 600 students
(75% of FTEs)
46.8 FTE
(83% of FTEs)
EBM suggests
56 for 1,400
students
2. Specialist Teachers
8.0 per 600 students
(25% of FTEs)
9.6 FTE
(17% of FTEs)
EBM suggests
18.7
3. Instructional
Facilitators/Mentors
3
(1 for every
200 students)
2
EBM suggests
7
4. Tutors for struggling
students
One for every 100
poverty students
0
EBM suggests
9.1
5. Teachers for EL
students
An additional 1.0
teacher for every 100
EL students
0.2 FTE
EBM suggests
2.2 FTE

230

Table F18 – Comparison of actual resources at VBHS to Evidence Based Model
(continued)
6. Extended Day
1 teacher for every 15
poverty students
(based on half the
number of poverty
students), 15 hours
per week @ 25% of
salary
0.4 FTE
(8 Teacher hours
per week)
EBM suggests
7.6 FTE
extended day
teachers
7. Summer School 6.3 FTE
EBM suggests
7.6 FTE
School Characteristics
8. Learning & mild
disabled students
Additional 4
professional teacher
positions for 600
students
0.2 FTE Resource
Room Teacher
EBM suggests
9.3 teachers for
1,400 students
9. Severely disabled
students
100% state
reimbursement minus
federal funds
1.2 FTE teachers
and 2 aids
Based on need
10. Resources for gifted
students
$25 per student
Gate budget of
$8,543
EBM suggests
funds of
$35,000
11. Vocational
Education
1/3 more per student
enrolled
2.6 FTE
EBM suggests
4.7 FTE
12. Substitutes 10 days per teacher
10 days per teacher
for illness and PN

13. Pupil support staff
1 for every 100
poverty students plus
1.0 guidance per 250
students
4 Counselors, 1
clerical attendance,
1 Psych, 1 Speech,
1 health clerk,
(8 FTE)
EBM suggests
14.7 positions
14. Non-Instructional
Aides
3.0 to relieve teachers
and provide
supervision
0
EBM suggests
7
15. Librarians/media
specialists
1.0 Librarian
1.0 Library Tech
1 Classified
Librarian

EBM suggests
2.3 Librarians
and 2.3 Library
techs
16. Principal 1 Principal
1 Principal, 2
Assistant Principals
EBM suggests
1 Principal and
2.3 Assistant
Principals
17. School Site
Secretary
1.0 Secretary and 3.0
Clerical
7 Secretaries &
1 clerks
EBM suggests
2.3 secretaries
& 7 clerks

231

Table F18 – Comparison of actual resources at VBHS to Evidence Based Model
(continued)
18. Professional
Development
Included above:
Instructional
facilitators, Planning
and prep time, 10
summer days
Additional: $100 per
pupil for other PD
expenses - trainers,
conferences, travel,
etc.
$750,000,
including
3 PD days in
calendar, 18 hours
per year for
collaboration = 2.6
days per year per
teacher,
conferences,
substitutes, travel
& materials.
EBM suggests
10 days PD in
summer and
$140,000 for
other PD
expenses.
19. Technology $250 per pupil
0.6 FTE
technology
coordinator.
Resources vary
EBM suggests
$350,000
20. Instructional
Materials
$175 per pupil
EBM suggests
$245,000
21. Student Activities $250 per pupil 1 section ASB
EBM suggests
$350,000

Lessons Learned
At VBHS, the small dedicated staff, through their success, has demonstrated their
strong belief that all students can learn and they work hard to promote the success of all
students. The typical practice at VBHS is that teachers teach both low and high level
classes to ensure that the lowest students have the best teachers. Although VBHS does
not have as much collaboration time as some of the other schools in this study, they use
the time they have to analyze student data. A focus, as demonstrated by the
administrators’ informal observation forms, is on checking for understanding and re-
teaching as needed. All students are challenged to master standards in courses ranging
from the Mastery Math program to the large percentage of honors and AP courses to the
MSA program. Teachers have participated in professional development opportunities

232

and have developed a modified Professional Learning Community. The small dedicated
staff has taken ownership in promoting student success with the help of well respected
instructional facilitators and a strong administrative team.
Future Needs
The principal of VBHS feels that more funding and time for professional
development are needed. He would like to send teams of teachers to conferences that
may provide impetus for moving the school forward. In addition to more resources for
professional development he would like to have more resources for technology including
bringing technology into the homes of the students and for teachers to use in the
classroom. Additionally, more resources are needed to recognize the achievements of
individual students.
In order to allow him and the administrative team to focus more on issues of
teaching and learning he would like a dean of students to handle discipline issues and
more support staff to handle the day to day management issues.

Abstract (if available)

Abstract This study used a purposeful sample of six southern California high schools with demographic characteristics of at least 20% African American, Hispanic or low SES students that are outperforming similar schools to determine the instructional strategies and resource use patterns used during their improvement process. Case studies, which include interview data, performance data and information on school level resource use, were conducted, and the information was analyzed using the data entry system created by Lawrence O. Picus and Associates which is aligned with the expenditure structure model created by Odden, et al (2003). The Evidence Based Model, developed by Odden and Picus (2008), which identifies the elements of a school-wide instructional program that research has shown to be effective in improving student performance, was used as the framework for analyzing the resource use patterns of the study schools. The findings indicate that although the resources available to the study schools were significantly fewer than what the Evidence Based Model suggests, the improvement strategies showed many commonalities to those suggested in the body of literature on school improvement. Analysis of the case studies indicates that the schools used the following improvement strategies that are commonly seen in the literature on effective schools: high expectations for students, timely small group support, the use of data to make decisions and inform practice, distributed leadership that empowers teachers to improve student achievement, the protection of instructional time including maximizing the time spent on the core subject areas and continual professional development with coaches as a key strategy. Implications for practice and policy are discussed.

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Asset Metadata

Creator Coulter, Christopher David (author)

Core Title Allocation of educational resources to improve student learning: case studies of California schools

School Rossier School of Education

Degree Doctor of Education

Degree Program Education (Leadership)

Publication Date 04/16/2009

Defense Date 03/02/2009

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

Tag California school finance,closing achievement gap,data driven decision making,educational adequacy,evidence based model,instructional improvement,OAI-PMH Harvest,resource use,school level resource use

Place Name California (states)

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 cdcoulte@usc.edu,coulterc@gmail.com

Permanent Link (DOI) https://doi.org/10.25549/usctheses-m2090

Unique identifier UC1453543

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Document Type Dissertation

Rights Coulter, Christopher David

Type texts

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

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Repository Location Los Angeles, California

Repository Email cisadmin@lib.usc.edu