University of Southern California Dissertations and Theses

Allocation of resources to improve student achievement

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Allocation of resources to improve student achievement

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ALLOCATION OF RESOURCES TO IMPROVE STUDENT ACHIEVEMENT

by
Nisha Bhakta Dugal

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

May 2011

Copyright 2011 Nisha Bhakta Dugal

ii
ACKNOWLEDGMENTS

There are numerous people who deserve my acknowledgement and thanks.
First, I would like to thank my dissertation chair Dr. Pedro Garcia for his guidance
and support through my coursework and the dissertation writing process; as well as
Dr. Rudy Castruita and Dr. Laurie Love for serving on my committee. I’m fortunate
to have had the opportunity to learn from such experts in the field.
I’m extremely appreciative of my fellow graduate students with whom I was
fortunate to have shared my experience with at USC. I have learned much from you
all, and I’m so glad to know you.
Finally, the most significant source of support, love and true inspiration
comes from my family. To my parents, I thank you for providing me unconditional
support as I maneuvered through my career, education, and life. To my sisters, you
are my “rock stars.” And to my amazing husband and beautiful daughter your love,
patience, and understanding have allowed me to get this done. This is for you!

iii
TABLE OF CONTENTS

Acknowledgements ii
List of Tables iv
List of Figures v
Abstract vi
Chapter One: Introduction 1
Chapter Two: Literature Review 12
Chapter Three: Methodology 35
Chapter Four: Findings 43
Chapter Five: Conclusion 67
References 78
Appendices:
Appendix A. School Expenditure Structure and Resource Indicators 81
Appendix B. Qualitative Interview Protocol 82
Appendix C. Data Collection Protocol 84
Appendix D. Data Collection Definitions 88

iv
LIST OF TABLES
Table 2.1: School Resource Indicators 28
Table 2.2: School Expenditure Structure 29
Table 2.3: Recommendations for Adequate Resources for Prototypical
Elementary, Middle and High Schools 32
Table 3.1: School Achievement Data for Sample Schools 38
Table 3.2: School Resource Indicators 40
Table 4.1: School Achievement Data for Sample Schools 45
Table 4.2: School Demographic Data 45
Table 4.3: XYZ Unified School District Success Indicators in Algebra
(2007-2010) 50
Table 4.4: Unified School District Success Indicators for Subgroups
(2007-2010) 52
Table 4.5: Staffing and Class Size-Evidence Based Model Compared to Actual 60

v
LIST OF FIGURES
Figure 2.1: National School District Expenditure Averages 25
Figure 4.1: API Scores for All Students at Sample Schools 47
Figure 4.2: English CST Scores-4 Year Trend 48
Figure 4.3: Math CST Scores-4 Year Trend 49
Figure 4.4: Percentage of 8
th
Grade Students Enrolled in Algebra 51
Figure 4.5: Percentage of 8
th
Grade Students Scoring Basic or Above on the
Algebra CST 51
Figure 4.6: Students with Disabilities Scoring Proficient or Advanced on the
Math CST 53
Figure 4.7: English Learners Scoring Proficient or Advanced on the ELA CST 53

vi
ABSTRACT
One of the most important decisions made by school officials is deciding how
to allocate funding resources to ensure high student performance. The history of
school funding over the last century has been both an economic and political issue.
With the authorization of No Child Left Behind (NCLB) and the current budget
crisis, school accountability is at the forefront of debate. California is heading into a
massive budget crisis. The Governor is proposing to spend $2.6 billion less on K-12
education with an additional $2 billion reduction for the 2011-2012 fiscal year. The
reality is that school budgets will be cut drastically over the coming months and
perhaps years. This study suggests that efficient research-based strategies can used
with the existing resources to improve student performance. It is imperative that
California continue to explore every possible way to do better with the current
resources. Some research focuses on how much money schools receive and other
focuses on how fairly the funds are distributed. A more relevant study is whether
schools in California have the resources to meet California’s demanding academic
goals. California schools are attempting to educate the most diverse and challenging
school population.
This study analyzed three middle schools in California using the Evidence
Based Model. This study discovered that these schools have had steady
improvements in student performance even with reductions in K-12 funding.
1
CHAPTER ONE: INTRODUCTION
There is a well-documented crisis in education and school funding. The
history of school funding over the last century has been both an economic and
political issue. With the authorization of No Child Left Behind (NCLB) and the
current budget crisis, school accountability is at the forefront of debate. NCLB’s
overall purpose was to ensure that students in every classroom had the benefits of
well-prepared teachers, a standards-based curriculum, and a safe learning
environment. The emphasis on standards-based education led to a heavy reliance on
student achievement test scores and multiple measures of adequate yearly progress.
One of the main discussions in education around the standards movement is
whether there is adequate funding to enable school districts to meet NCLB. The shift
to a standard based reform movement and increased accountability measures has
forced school districts to focus on insuring that students meet the new standards. In
an attempt to implement these mandates, the question arises whether schools are
receiving ample funding. To understand the complexity of resource allocation in
California, it is helpful to start with the school finance history focusing on court
decisions, laws, and ballot measures which impact the school budgets. How
California compares nationally in terms of finances and student achievement is
important in understanding adequacy in school funding. While there has been a
general increase in spending, there are huge disparities across districts leaving a very
unequal allotment of funds per pupil. This study examines how schools have used
their resources to promote student achievement.
2
Background of the Problem
California’s school finance system has changed significantly since 1968 due
to a combination of court decisions, laws, and ballot measures. California’s school
finance system started from one based on local property taxes and moved to a system
mainly funded and controlled by the state. This transition from local property taxes
to state funding started in 1968 with the Serrano v. Priest court case. The California
Supreme Court found the existing system of financing schools unconstitutional
because it violated the equal protection clause of the state Constitution (Timar,
2006). The court ruled that property tax rates and per-pupil expenditures need to be
equalized and that by 1980 the difference in revenue limits per pupil should be less
than $100 (Serrano band). In 1978, California voters approved Proposition 13 which
limited property tax rates to 1% of a property’s assessed value. Proposition 13 also
limited how much local tax revenues go directly to school districts. Because schools
were stripped of a large portion of their revenues after the passage of Proposition 13,
the state increased its share of funding schools and became the primary source of
funding for schools. The Serrano v. Priest court decision and Proposition 13 were
the beginning of the shift from local to state control of school finance.
Proposition 13 was just the first of many voter initiatives in California aimed
at streamlining funds directly to schools and also limiting the budgetary discretion of
state lawmakers in regards to education. In 1979, voters approved Proposition 4
which set a constitutional limit on government spending at every level of the state.
This meant that agencies could not exceed their Gann Limit, which is adjusted
3
annually for changes in population and the less of either the national Consumer Price
Index (CPI) or California’s per capita personal income. The Gann Limit capped the
amount of revenue districts could bring in from property taxes. In 1984, the lottery
initiative authorized a California State Lottery which would guarantee that a
minimum of 34% of total lottery receipts be distributed to public education
(EdSource, 2006). This funding is to supplement, not replace, funding provided by
the state. The funding is limited to be used exclusively for the education of students
and not to obtain property, build new construction, or any other non-instructional
purposes. Currently, proceeds from the lottery add less than 2% to school districts’
revenues.
Because the state budgeting process is political and dependent on the
economy, school funding is volatile. As a response to this, in 1988 Proposition 98
was approved which guarantees a minimum funding level from the state and
property taxes for K-14 public schools using a formula based on state tax revenues.
Basically, about 40% of the state’s general fund is used for public education.
Proposition 98 also requires each school to prepare and publicize an annual School
Accountability Report Card (SARC) that includes test scores, dropout rates, and
teacher qualifications. A two-thirds vote of the Legislature and a signature from the
governor are required to suspend Proposition 98 for a year. The establishment of the
Gann Limit, Lottery Initiative, and Proposition 98 has streamlined funding to schools
and has also limited the budgetary discretion of state lawmakers in regards to
education.
4
Considering the state’s annual allocation of billions of dollars towards public
education, state lawmakers have acted to hold school districts more accountable for
their decisions. Often this means creating categorical programs that earmark funds
for specific uses, but the state has also passed measures that provide oversight and
support related to financial management. Assembly Bill 1200 established a system
for accounting practices that specifies how districts must track and report their
revenues and expenditures. This law requires that districts project their fiscal
solvency for two years in advance. The Williams v. California lawsuit charged that
the state had failed to give thousands of students the basic tools necessary for their
education. The 2004 settlement included accountability measures, extra financial
support and other help for low performing schools. To implement the settlement and
hold districts accountable, the Legislature enacted bills pertaining to facilities,
instructional materials and teacher credentialing.
As a result of court decisions and ballot propositions, the amount California
spends on its schools is largely determined by state policymakers rather than local
voters and school districts. Despite the growth in school age population and the
student diversity within the state, the system has looked about the same for more
than 25 years. The federal government contributes about 10% of the education
budget, while about 60% of the funds are from the state generated by business and
personal income taxes, sales taxes, and some special taxes (EdSource, 2009). Local
property taxes account for a little less than 23% of all funds and less than 2% is from
the California State Lottery (EdSource, 2009). Currently, about two-thirds of the
5
money distributed to local districts is for general purposes and almost one-third is
earmarked for special purposes or categories of students. The amount of funding
depends on average daily attendance (ADA), the general purpose money the district
receives for each student (revenue limit) and the support for specific programs for
which it qualifies (categorical aid). The miscellaneous and lottery revenues provide
less than 8% of funding statewide, but this money is important because few
restrictions are placed on its use.
For some districts whose property taxes exceed the revenue limit, the state
provides no additional state aid. These districts are basic aid districts who receive all
of their general purpose funding from the local property tax. These districts have no
control over the revenues they receive from property taxes from year to year. The
volatile economy has a direct impact on their revenues since property sales
(commercial and residential) and land reassessments can vary greatly. Since basic
aid districts’ revenues are not based on district enrollment, the economy can have an
even greater impact on the funding. The district income is determined by the growth
and decline of property tax revenues and not by the population served. At times, this
may mean serving more students although revenue is decreasing. Since basic aid
districts receive funding directly from local property taxes and schools are a major
factor in determining the local property tax values, the link between the local
community and its schools is strengthened which allows tax payers to hold their
schools more accountable for the quality of educational services they provide.
6
National comparisons provide a perspective on the process by which
California funds its schools, how much the state invests, how those funds are spent
and how it impacts student achievement. In 2007-2008 the state ranked 39
th
in the
nation in K-12 school expenditures per $1000 of personal income, spending $37 for
every $1000 of personal income (Edsource, 2010). Another way to look at a state’s
investment in education is to compare its spending on schools to its expenditures on
other public services. Californians pay more taxes than the national average, yet the
state spends a smaller proportion of personal income on schools. On a per-resident
basis, the state’s spending on K-12 education has been above the national average.
This does not necessarily translate into above-average expenditures per student.
California has been consistently below the nation average in per-pupil spending,
ranking 28
th
in 2007-2008 spending $9,706 per pupil (EdSource, 2010). One reason
for this ranking is that California has such a high proportion of children to adults
compared to other states. Further, California ranked 49
th
in terms of student-teacher
ratios but first in teacher salaries with an average salary of $65,808 (EdSource,
2010). In California, about 85% of a school district’s general fund is spent on staff
salaries and benefits. The primary assessment that provides comparable state-by-
state analyses of K-12 student achievement is the National Assessment of
Educational Progress (NAEP) results. California performed poorly based on NAEP
tests compared to other states, ranking in the bottom six states on every test its
students took. In 2009, half of fourth graders and 40% of eighth graders scored
below basic in reading and 29% of fourth graders and 43% of eighth graders scored
7
below basic in math (EdSource, 2010). Relatively low achievement levels lead to a
discussion of funding adequacy for California schools.
Statement of the Problem
The history of school funding over the last century has been both an
economic and political issue. With the authorization of No Child Left Behind
(NCLB) and the current budget crisis, school accountability is at the forefront of
debate. The NAEP scores are an indictment of the state’s success in educating its
students. There are ways to improve practice and be more effective. School districts
could also spend their funds more efficiently. It is imperative that California
continue to explore every possible way to do better with the current resources. Some
research focuses on how much money schools receive and other on how fairly the
funds are distributed. A more relevant study is whether schools in California have
the resources to meet California’s demanding academic goals. California schools are
attempting to educate the most diverse and challenging school population. A
particular focus is the extra investment that may be necessary to improve the
achievement of the state’s English Learners, low-income students, and students with
disabilities.
Purpose of the Study
The purpose of this study is to identify how schools are spending their
monies in relation to research-based recommendations for high achieving schools.
Resource allocation patterns are analyzed and compared to conclude what practices
and strategies improve student achievement and to add to the body of knowledge on
8
how successful schools are actually using their resources. The following research
questions guided this study:
1. What are the current instructional improvement strategies at the school
level?
2. How are resources used to implement the school’s instructional plan?
3. How does the availability of resources impact the development and
implementation of the school plan?
Significance of the Study
Given the current fiscal crisis facing California and its impact on school
funding, it is crucial to examine the relationship between the allocation of resources
and reform initiatives designed to improve student achievement. Schools cannot
continue to spend money on programs that do not demonstrate measurable gains in
student achievement. Findings from this study will inform schools in California on
how to effectively use their limited resources to improve their instructional
strategies. These findings will guide administrators in making data driven decisions
around scarce resources to best meet the needs of California’s diverse student
population. Furthermore, results may be used to inform policymakers in making
decisions around legislation and mandates regarding issues of school finance to
promote a more efficient use of resources.
Limitations and Delimitations
First, given the nature of studies in education, it is not possible to impose a
random experimental design. It would be impossible and impractical to randomly
9
assign resources to one school and hold others as a control group. Second, because
of the small sample size of one school district and the geographical considerations of
the sample, the ability to generalize the results of the study is limited. This study
examined only 1 of over 1000 school districts in California. Third, the study is not a
longitudinal study since data were only collected in a short time frame. Finally, as a
mixed methods study the ability to conclude definitive cause and effect relationships
in the findings is limited.
Assumptions
It is assumed that all information provided during interviews is honest and
truthful. It is also assumed that any documentation provided by the district/school
was accurate as it pertained to resource allocation. Statistics and achievement data
from the state website were used to ensure consistency and accuracy.
Definition of Terms
1. Accountability: The idea that people and organizations should be held
responsible for improving student achievement and should be rewarded or
sanctioned for their ability to inability to do so (EdSource, 2004).
2. Adequate Yearly Progress (AYP): A set of annual academic performance
benchmarks that states, school districts, schools, and subpopulations of students
are supposed to achieve. In California, the measures are specified percentages of
students scoring “proficient” or “advanced” on the CST in language arts and
math, participation rate of at least 95%, specified API scores or gains, and for
high schools a specified graduation rate or improvement in rate.
10
3. Average Daily Attendance (ADA): The total number of days of student
attendance divided by the total number of days in the regular school year. A
school district’s revenue limit income is based on its ADA.
4. Basic Aid District: A district funded primarily by property tax revenues. Basic
aid districts do not receive any revenue limit income based upon attendance other
than this constitutionally guaranteed basic aid allotment. Basic operational costs
for these districts are supported entirely by local property taxes.
5. California Standards Test (CST): Standards test in the core content areas of
English/language arts, mathematics, history/social science and science. These
tests make-up the core of California’s Standardized Testing and Reporting
Program (STAR).
6. Categorical Funds: State and federal funds allocated in addition to revenue limit
income and earmarked for special populations of students.
7. English Language Learner (ELL): Designation for students not yet sufficiently
proficient in English.
8. General Fund: An accounting term referring to all general use expenditures not
required by law to be accounted for in a separate accounting category.
9. No Child Left Behind (NCLB): “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
11
all significant subgroups. In California, those sanctions currently apply only to
schools and districts that accept Title I funding (EdSource, 2010).”
10. Revenue Limit District: A school district that receives general purpose funding
based on ADA, local property taxes, and state taxes.

12
CHAPTER TWO: LITERATURE REVIEW

This chapter details current literature pertaining to resource allocation and the
impact on student achievement. The review is divided into four major sections:
(1) educational adequacy; (2) best practices for improving student performance;
(3) resource use; and (4) models to track resources. The first section will further
define educational adequacy and review four models to determine adequate
expenditure levels. The second section explores the wealth of information on best
practices for improving student achievement. The third section synthesizes
information on why researchers have struggled to analyze school resources and how
to best allocate school resources to be tied to student achievement. Finally, the
fourth section focuses on the use of the Evidence Based Model developed by Odden
and Picus (2008) as a way to cost out resources required to fund an adequate
education.
Educational Adequacy
The courts, school districts and policy makers have tried to define adequacy
in terms of school resources for the last 20 years. Historically, the amount of money
given to public schools has been based on a politically determined amount of funding
available for education. This made funding based on the distribution of wealth and
political power rather than on the needs of the students. The first movement towards
adequacy began in the 1990s as the standards movement gained momentum and the
achievement gaps became glaring. The idea of equity shifted towards adequacy.
13
This shift towards adequacy was in response to allocating more funding to schools
without results in terms in achievement:
Adequacy dovetails directly with accountability…An ubiquitous outcome of
accountability systems is an explicit statement of performance deficit – that
is, how many students have not reached proficiency by the state’s standards.
The natural extension of this finding of low student performance is an
assessment of why this might be. And the answer is asserted in the new
round of court cases dealing with adequacy that resources are insufficient to
support the achievement standards. (Hanushek, 2006, p. xvi)

This shift from equity to adequacy means that school finance must
encompass fiscal inputs and their direct linkage to educational services,
compensation, and student achievement (Ladd & Hansen, 1999). As more funding is
allocated to schools, there is an expectation of achievement results. Since the state
holds students and schools accountable for meeting the state content standards, states
need to align their resources with meeting the state standards. Adequacy is the cost
of providing educational programs and services so all children have an equal
opportunity to achieve high academic standards and learning goals (Odden,
Archibald, Fermanich, & Gross, 2003; Baker, 2005; Rebell, 2007).
The adequacy model has forced policymakers to question whether or not
revenues are adequate enough to offer every child an appropriate educational
program. States are now challenged to design a school finance system that can
identify adequate expenditure levels for a typical student, modifications for students
with special needs, and how to manage these resources so all students learn towards
a high achievement level (Odden, 2003). Designing an adequate funding system is
both controversial and challenging. Hanushek (2006) claims that adequacy studies
14
are unreliable because it is impossible to identify exactly what combinations of
resources will improve student performance. Contrary to this thought, other
researchers claim that using the adequacy models to determine school funding is
better than the existing political methods of funding (Baker, 2005). The focus on the
level of funding along with the standards movement has resulted in a development
frenzy of “costing out” models to determine the amount of funding that is actually
needed to provide all students with a meaningful opportunity for an adequate
education (Rebell, 2007). There are four different models that attempt to determine
adequate expenditure levels for schools resources. These models are: (1) the
successful district approach; (2) the cost function analysis; (3) the professional
judgment approach; and (4) the evidence based approach.
In successful district approach studies, the researcher chooses a definition of
“success” and identifies school districts that are meeting this definition. This
approach identifies school districts that are meeting the goals of the state standards
and uses their resources to estimate the cost of providing an adequate education.
This approach is often referred to as the “beating the odds” approach since the
identified districts usually spend below the state average. John Augenblick
developed this approach based on school districts that are meeting state standards
and used their expenditure data to estimate the actual cost of an adequate education
(Augenblick, 1997). There are two main shortcomings to this approach. First, most
of these districts are small, rural districts and it is difficult to itemize these
expenditures for large, urban districts (Odden & Picus, 2008). Secondly, this model
15
does not identify specifically which strategies led to improved student performance
making it difficult to transfer this model to similar districts.
The cost function analysis is a statistical take at education finance which
attempts to determine how much a school district would need to spend to obtain
specific student achievement targets. This analysis requires extensive data on district
expenditures, student outcomes, and demographics. Research shows that there is a
significant variation in adequacy levels due to student and district demographics
(Loeb, 2007). This rigorous analysis approach attempts to determine how spending
levels impact student outcomes based on various student demographics. The main
limitation to this approach is that it requires a significant amount of data analysis on
expenditures per pupil, district demographics, and student achievement. This data is
also generated at the district level and not at the school level. Similar to the
successful district approach, this analysis makes it difficult to identify specific
instructional strategies which generated the improved student achievement levels.
The professional judgment approach uses a panel of educators to determine
the necessary resources for an adequate education. The business analysts then
calculate the total costs based on the panels’ decisions. This approach focuses on
research-based strategies to increase student achievement that are then assigned a
cost to determine per-pupil expenditures. The panel of experts is asked to determine
the resources necessary to meet the predetermined performance targets. After the
strategies are determined, each strategy is assigned a cost, determined by school size
and population, and the total expenditure level is calculated. This approach has been
16
widely used in education because it allows for the adjustment of costs based on
district size and for students with special needs (Odden, 2003). There are still
shortcomings with the use of this approach. The studies only rely on the opinions of
the panel, and panels vary widely in determining what school reform strategies will
best serve a school or district (Hanushek, 2006; Loeb, 2007). The panel is usually
compromised of educators from different backgrounds, with different experiences
and agendas causing resources to be allocated based on professional opinion rather
than what the district or school actually needs.
The evidence based approach uses research to identify educational strategies
and allocation of resources that have been proven effective in increasing student
achievement. This model uses the strategies of a comprehensive school design
model, with research-based best practices incorporated into school-wide educational
strategies, to serve as a guide to assist schools with allocating resources in the most
effective manner (Odden, 2007). The major advantage of using this approach is that
it identifies proven educational strategies to assist schools and districts in using their
resources more effectively and efficiently (Odden, 2007). By identifying key
components of a high quality instructional program, assigning costs to these
identified elements, and aggregating the costs to a per-pupil expenditure level this
model allows for linking fiscal resources to student performance. A shortcoming of
this approach is that researchers create a fictitious model school and then determined
the allocations to implement the strategies without analyzing the actual spending and
17
achievement experiences of districts in their study (Hanushek, 2006). This approach
will be the focus of this study.
Best Practices for Improving Student Performance
While there are many pre-packaged models for school reform that combine
research-based elements into improving student performance, there are critical
structural features that have been successful in implementing the reform initiatives to
improve student performance. Research on high-performing schools shows that
there are many ways to organize time, staff, and funding to improve student
achievement. Research supports that as districts hold schools accountable for their
student achievement results, the need for more core instructional time, help for
struggling students, resources for professional development and instructional
materials is increasing (Miles, 2000).
Miles (2000) claims that to begin this process of accountability there must be
clearly defined instructional goals and a reorganization of resources to meet the
goals. Her study provided research-based strategies for reorganizing resources based
on rethinking school staffing, time, and class size; district spending on professional
development; teacher salaries; and sources of funding (Miles, 2000). In regards to
staffing, research supports the reduction of specialist teachers and increasing core
teachers in the classroom. This will support a more integrated curriculum and
instructional model for student learning, especially English learners, students with
disabilities, and remedial students (Miles & Darling-Hammond, 1997). With more
18
core teachers, students will receive the additional support they need to meet the
performance standards.
Another common element in relation to improving student performance is
professional development. Research supports that professional development must be
sufficient in duration, have a specific focus, and incorporative active learning.
According to Gusky (2000), districts must identify the guiding philosophy that drives
professional development and establish goals and objectives. The goals and
objectives should address the need for improving student achievement. Gusky’s
analysis did not find “one right way” of professional development but that it must
center on student achievement. It is apparent that quality professional development
requires intensive resources, and districts must effectively allocate resources to
support successful professional development.
Restructuring the weekly school schedule to include a common planning time
gives teachers the opportunity to collaborate. This collaboration not only improves
instruction but has also shown to increase staff motivation and interdepartmental
relationships (Miles, 2000). This implementation of professional learning
communities (PLC) enhances teacher content knowledge and builds leadership
capacity around classroom instruction. The teams in a PLC engage in inquiry into
best practices in both teaching and learning. PLC members must work together to
build shared knowledge on the best way to achieve goals and meet the needs of the
students (Dufour, Dufour, Eaker, & Many, 2006). Providing time for collaborative
groups to identify strategies that are working, solve problems, and determine the best
19
use of resources is essential in developing a plan to close the achievement gap
(Johnson, 2002). Professional learning communities have the potential to become a
powerful vehicle for ongoing professional development that encompasses many of
the effective characteristics of staff development.
With the use of professional learning communities, a coherent standards-
based curriculum with a focus on data is needed to assist with improving student
achievement. Marzano (2003) identifies key factors at the school level for increasing
student performance: guaranteed and viable curriculum, challenging goals and
effective feedback, and collegiality and professionalism. A viable curriculum, in the
era of standards-based curriculum, means ensuring that the articulated curriculum
content can be adequately addressed in the time available (Marzano, 2003).
Successful schools must implement a curriculum that is both guaranteed and viable.
Teachers must “unpack” the benchmark standards and determine how much time it
would take to adequately address the essential content. Challenging goals and
effective feedback refers to high expectations and pressure to achieve said goals and
tracking the extent to which the goals are met. Schmoker (1999) suggests that goals
themselves lead not only to success but also to the effectiveness and cohesion of a
team. The act of establishing goals has strong support as a significant factor in
successful schooling. In addition, effective feedback must be timely and specific to
the content being learned (Marzano, 2003). Collegiality and professionalism deals
with how staff members interact with each other and to the extent in which they
approach their work as professionals (Marzano, 2003). Collegiality is not just about
20
teachers planning together. Fullan (2005) characterizes collegiality as teachers
openly sharing failures and mistakes, demonstrating respect for each other, and
constructively analyzing and criticizing practices and procedures. Professionalism
deals with the perception that they can impact change at their schools (Marzano,
2003). Teachers must be valued and empowered as a critical part of the school’s
policy setting process.
Although many schools have created time for collaboration, staff discussions
are not always centered on data analysis or collective inquiry, which will not support
the goal of student achievement (Johnson, 2002). Data provides the benchmark
measure of student progress toward attaining identified learning goals. PLC research
supports that schools need to create an intensive focus on learning by identifying
specifically what students are to learn and monitoring each student’s learning in a
timely manner (DuFour et al., 2006). Schools must begin looking at data as a reality
of where they are in comparison to where they want to be to make decisions about
what needs to change. Data is not just teachers in the classroom making instructional
decisions. Use of data also includes evaluation of reform strategies to determine if
the school-wide or district-wide efforts are in fact impacting student achievement
(Schmoker, 2006). Just as teachers must look at student data to improve practice,
schools and districts must also examine data to monitor progress towards their
identified goals.
This continuous learning cycle of looking at data to determine needs,
providing effective instruction for students or professional development for teachers,
21
monitoring progress and adjusting strategies to ensure growth is at the heart of most
successful reform strategies (Fullan, 2005; Johnson 2002; Schmoker, 2006). The
key to determining the needs of the school or district is the evidence of a clearly
articulated standards-based curriculum. If teachers lack the time or skills for
collaboration around data analysis and improved practice, it is challenging to create a
standards-based curriculum that holds teachers accountable for the progress of all
students. At successful schools there is evidence of attention to standards as the
driving force behind directing professional development, collaborative time, and data
analysis (Fullan, 2005; Schmoker, 2006).
Effective leadership is a necessary condition for successful school reform and
influences every aspect of school reform. In fact, Marzano (2003) claims that
leadership is the single most important factor of school reform. It is the
responsibility of the school leadership to create a place where research-based
strategies can be implemented, monitored, and adjusted to increase student
achievement. Leadership plays a critical role in ensuring the proper systems are in
place for professional development, monitoring the implementation of a standards-
based curriculum, establishing collaboration time, and utilizing data analysis.
Leadership makes the necessary resource allocation decisions to fund professional
development, collaboration time, and staffing. With the importance of teacher
efficacy and the direct role teachers play in impacting student learning outcomes,
leadership must play a crucial role in monitoring the quality of classroom instruction.
Research states that improved classroom instruction is the prime factor to produce
22
student achievement gains (Schmoker, 2006). Leadership is most effective when
carried out by a team of educators with the principal functioning as a strong cohesive
force (Marzano, 2003). Other administrators, teacher leaders, and support personnel
play a crucial role in implementing successful school reform. Teachers must be
especially involved in making decisions that impact classroom instruction. Building
leadership capacity at a school site becomes fundamental to the success rate of
implementing school reform.
Resource Use
With all the research supporting what works in schools, an overwhelming
number of schools have failed to implement effective strategies to any significant
degree. The usual excuse has been that schools are underfunded. While this may be
true for some cases, there are still several schools that are able to cite student
achievement gains without a huge influx of additional resources. The majority of
schools though are not able to show the academic gains.
Despite an increase in school funding, student achievement has not
significantly improved. Even after controlling for inflation and rise in student
population there has still been an increase in expenditure per pupil by three and half
percent since 1950 (Hanushek & Rivkin, 1997). Research cites many inefficient
uses of resources and the difficulty of measuring how school-level expenditures are
used as reasons for schools failing despite the increase in revenues. In most schools,
less than 50% of the school’s resources are allocated to core academic areas (Odden
& Picus, 2008). Funds have been used for non-instructional purposes or to support
23
students with disabilities, low income students or English learners (Hanushek &
Rivkin, 1997). Although support programs seem to be a high impact investment of
funding, the money for support programs has shown little impact on student
achievement. In most districts a declining proportion of funding allocated to
instruction is actually going to core academic subject instruction. More funding has
also been allocated towards non-core or elective courses. Beginning in the 1960s,
schools funded additional teachers for non-core academic courses to provide core
teachers with planning time (Odden & Picus, 2008). While students took physical
education, art, or other electives, core teacher had the time to plan. At the secondary
level, this has restructured the typical school day and expanded the offering of
electives. This new structure decreases the amount of time students spend in core
classes. This helps to explain why there has been minimal growth in student
achievement while total expenditures have increased over time (Odden & Picus,
2008).
As NCLB has mandated drastic improvement in student achievement and as
the standards-based movement has increased awareness and accountability of how
educational dollars are spent, researchers have worked on identifying how resources
should be allocated to impact student performance. Currently, there is a lack of a
consistent fiscal reporting method that can assist policymakers and educators in
making informed decisions about the allocation of resources (Odden & Picus, 2008).
There has also been minimal effort to analyze fiscal data in relation to student
outcomes. With the shift towards adequacy over equity, recent studies have
24
analyzed what resources schools are using and whether or not these funds are
improving student performance. Over the last 50 years school districts have
typically spent about 60% of funds 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 2.1
(Odden, 2007). With the evidence based model, which will be discussed in detail
below, Odden and Picus (2008) recommend that 30 to 40 percent of expenditures go
to core classroom teachers, a principal and professional development. An additional
30 to 40 percent should be spent on specialist teachers for non-academic courses
(electives), for support services, to assist struggling students, and other instructional
supports. The remaining 20 to 30 percent should be used on operational necessities
including central office support, personnel services, maintenance and operations,
transportation and food services. This is a more direct approach to linking resource
use to student achievement.

25
Figure 2.1: National School District Expenditure Averages

Source: Odden, 2007
Schools can be successful in allocating resources to improve student
achievement. Schools have been successful when they break away from the way
they have always done things in order to restructure resources to improve student
achievement, especially for low income students, English learners, and students with
disabilities (Odden, 2007). The most common strategies that have shown
improvement in student achievement have been increasing the time students spend
on core academic subjects, lowering class size in core academic subjects, increasing
investment in professional development for staff, and providing additional assistance
for students (Odden, 2007).
Model to Track Resources
The evidence based model was developed in response to the lack of
fiscal reporting systems that allow school-level comparisons of resource use (Odden
26
et al., 2003). This model identifies the elements of a school-wide instructional
program that is effective in increasing student performance. This model can be used
to “cost out” each element to determine an adequate level of funding (Odden, 2003).
It improves upon previous models in two significant ways. First, the model can be
used to report school-level expenditures rather than district level expenditures.
Second, it allows for the examination of specific instructional strategies and how
resources impact student achievement (Odden et al., 2003). Without school-level
expenditure data, it is almost impossible to conclude the impact that various
instructional strategies of resource allocation have on student learning (Odden &
Picus, 2008).
The evidence based model works with a prototypical school model which
adjusts for school size and demographics. The prototypical high school would have
a total of 600 students with an average class size of 25 students (Odden & Picus,
2008). The model is staffed with 24 full time core teachers, eight specialist teachers,
three instructional facilitators or coaches, and a technology coordinator. The role of
the personnel will be discussed further below. Odden and Picus (2008) have
identified the following five key components of resource use data that must be
analyzed to make the correlation between school-level expenditures and student
performance:
1. Staffing and expenditures by program: this includes the regular
instructional program, programs for special needs students (English
27
learners, compensatory, and special education), administration, staff
development and instructional materials
2. Staffing and expenditures by educational strategy: this includes class size,
professional development, resource room, tutoring, etc.
3. Staffing and expenditures by content area: mathematics, language arts,
science, social science, foreign language, art, and physical education
4. Interrelationships among the staffing and expenditure patterns
5. Relationship of staffing and expenditure pattern to student performance
As this type of information becomes readily available, the ability to study the
correlation between allocation of schools resources and student performance will
increase, and schools can begin to make more informed decisions about the most
effective use of school resources (Odden & Picus, 2008).
Odden et al. (2003) created the fiscal reporting system which incorporates the
following two components: (1) identifies a set of school resource indicators that
provide insight into a school’s priorities and instructional strategies, and (2)
categorizes school expenditure data according to nine elements that are classified as
instructional or non-instructional. The school resource indicators and expenditures
structures are provided in Table 2.1 and Table 2.2.

28
Table 2.1: School Resource Indicators
Indicator Definition
School building size Total student enrollment of the school
School unit size
Student enrollment of each
instructional unit within a school
(school within a school)
Percent low income
Percent of enrolled students who are
eligible for the federal free and reduced
lunch program
Percent special education
Percent of students in the school with
an individualized education program
(IEP)
Percent ESL/Bilingual
The number (percent) of students
eligible to receive services through the
English as a second language (ESL)
program or bilingual program
Expenditure per pupil
Calculated by dividing the total school
operating expenditures from all funds
by the total student enrollment
Professional development expenditures
per teacher
Calculated by dividing total school
expenditures for professional
development by the total number of
licensed teachers
Special academic focus Identifies any academic program focus
Length of instructional day
The number of hours per day that
students receive instruction
Length of class periods The number of minutes per class period
Length of core class periods
Length of mathematics, English,
science, and social studies classes
Core class size
The average number of students per
teacher in mathematics, English,
science and social studies classes
Non-core class size
The average number of student per
teacher of classes other than
mathematics, English, science and
social studies classes
Percent core teachers
The percent of all certificated staff who
are mathematics, English, science or
social studies teachers
Source: Odden et al., 2003
29
The school expenditure structure is the second component of the evidence
based model’s framework for tracking school resources. The school expenditure
structure consists of seven instructional elements and two non-instructional elements
and is based on definitions provided by Odden et al. (2003).
Table 2.2: School Expenditure Structure
Instructional Elements
Indicator Definition
Core academic teachers The number of full time equivalent
(FTE) teachers that are teaching
mathematics, English, science or
social studies
Specialist and elective teachers Licensed teachers who provide
instruction in non-core academic
classes (physical education, foreign
language, music, vocational education
etc)
Extra help Represents teachers who work in the
capacity of helping struggling students
or students with special needs to learn a
school’s regular curriculum (includes
tutors, mathematics and English
support class teachers, inclusion
teachers, etc)
Professional development The cost of teacher time in professional
development and all the elements of
providing professional development
(materials, trainers, transportation,
registration fees, etc)
Other non-classroom instructional staff Includes certificated and non-
certificated staff that works in a
support role
Instructional materials and equipment Supplies needed for all instructional
programs
Student support Represents a school’s support staff and
includes counselors, psychologists,
attendance monitors, parent liaisons,
etc. as well as expenditures for athletics
and extra-curricular activities

30
Table 2.2, Continued
Non-instructional Elements
Indicator Definition
Administration Administrators and all support and
clerical staff, equipment, supplies,
technology, and discretionary funds
Operations and maintenance Custodial services, maintenance staff,
security, food services, etc.
Source: Odden et al., 2003

As discussed earlier, the evidence based model works with a prototypical
school model which adjusts for school size and demographics. The prototypical high
school would have a total of 600 students with an average class size of 25 students
(Odden & Picus, 2008). The model is staffed with 24 full time core teachers, eight
specialist teachers, three instructional facilitators or coaches, and a technology
coordinator. The coaches would coordinate the instructional program and provide
staff development.
The evidence based model includes resources for extra support and staff for
disadvantaged students. The model funds one credentialed tutor for every 100
students on free or reduced lunch. The credentialed tutors are trained on specific
instructional strategies and the tutoring is used to support the regular school
curriculum (Odden & Picus, 2008). The model also funds one FTE teacher for every
100 English learner students to provide additional support classes for English learner
students. The model also funds programs outside the regular school day for
struggling students. The model funds one teacher for an extended day program for
every 15 free and reduced price lunch students (Odden & Picus, 2008). An extended
31
school year program (summer school) is funded for 50 percent of the number of
students in the free or reduced lunch program. The summer program is
recommended to be eight weeks in length with class sizes of 15 students for six
hours per day (Odden & Picus, 2008). For special education students, the model
funds four special education teachers for mild and moderately disabled students. The
evidence based model provides additional support for struggling students.
The model funds professional development in two ways. First, the model
funds a ten day summer institute for all teachers. The professional development is
also on going with on-site coaching. An additional five percent of all teacher
resources are used for substitute teachers to allow for teachers to receive on-going
professional development (Odden & Picus, 2008). The master schedule is also
developed to allow for teacher collaboration during common preparation periods.
Professional development strategies are funded at $100 per pupil for both the
summer institute and on-going staff training (Odden & Picus, 2008).
The remaining funding impacting instruction is based on technology and
instructional materials. The model funds technology and equipment at a rate of $250
per student for computers and upgrading and maintaining software and equipment
(Odden & Picus, 2008). Instructional materials are funded at the rate the $25 per
student for library books and $150 per student for textbooks and consumables.
Table 2.3 provides an overview of how the evidence based model allocates resources
in prototypical elementary, middle and high schools.
32
Table 2.3: Recommendations for Adequate Resources for Prototypical Elementary,
Middle and High Schools
School Element
Elementary
School
Middle School High School
School
Characteristics

School
configuration
K-5 6-8 9-12
School size 432 450 600
Class Size
K-3: 15
4-5: 25
25 25
Number of teacher
work days
200 with 10 day
summer training
200 with 10 day
summer training
200 with 10 day
summer training
% of students with
disabilities
12% 12% 12%
% of students with
free or reduced
lunch
50% 50% 50%
% of English
learners
10% 10% 10%
% of minority
students
30% 30% 30%
Personnel
Resources

Core teachers 24 18 24
Specialist teachers 4.8 3.6 8
Instructional
facilitators
(coaches)
2.2 2.25 3
Tutors 2.16 2.25 3
Teachers for EL
students
.43 .45 .60
Extended day 1.8 1.875 2.5
Summer school 1.8 1.875 2.5
Additional School
Characteristics

Students with
disabilities
3 3 4
Teachers for gifted
students
$25 per student $25 per student $25 per student
Substitutes 5% of budget 5% of budget 5% of budget
Support staff 2.16 3.25 5.4
33
Table 2.3, Continued
School Element
Elementary
School
Middle School High School
Non-instructional
aides
2 2 3
Librarians 1 1
1 plus 1 library
tech
Principal 1 1 1
Clerical 2 2 4
Professional
Development
See above plus
$100 per pupil
See above plus
$100 per pupil
See above plus
$100 per pupil
Technology $250 per pupil $250 per pupil $250 per pupil
Instructional
material
$140 per pupil $140 per pupil $175 per pupil
Student activities $200 per pupil $200 per pupil $250 per pupil
Source: Odden & Picus, 2008
The school expenditure structure and resource indicators provide a powerful
tool for analyzing and comparing resource allocation at the school level. By
comparing resource indicators and expenditure elements, a more detailed analysis
can be made of how schools are using their resources on specific strategies and how
that impacts student performance. This expenditure model has been tested, and
Odden et al. (2003) concluded that it was successful in providing an analysis of how
resources were actually used at the school level.
Conclusion
Research shows the need to collect school-level expenditure data and analyze
how it impacts instructional strategies that are research-based and demonstrate
improvements in student performance. This chapter detailed current literature
pertaining to resource allocation and the impact on student achievement. The first
section defined educational adequacy as the cost of providing educational programs
34
and services so all children have an equal opportunity to achieve high academic
standards and learning goals (Odden et al., 2003; Baker, 2005; Rebell, 2007). After
reviewing different models of costing out resources, it is apparent that the evidence
based model provides the most comprehensive framework for collecting school
expenditure data and analyzing what instructional and expenditure improvements
schools can make to improve student performance. Best practices for improving
student performance revealed the need for reorganizing resources to focus core
instructional time, helping struggling students, and professional development with
the key component of leadership capacity. The third section synthesized information
on why researchers have struggled to analyze school resources and how to best
allocate school resources to be tied to student achievement. The evidence based
model provides a research-based approach to allocating resources to directly impact
student performance. The following chapter will outline the methodology of using
the evidence based model in conducting this research study.

35
CHAPTER THREE: METHODOLOGY
The purpose of this study is to provide a school-level analysis of resource
allocation in relation to research-based recommendations for high achieving schools.
As described earlier, the shift in focus from equity to issues of adequacy requires an
in-depth analysis of resource allocation. Increases in funding over time have not
necessarily resulted in improvements in student achievement (Hanushek, 2006). The
specific goals of this study aim to develop a better understanding of what resources
schools use to improve learning and the link between resources and student
performance.
To explore these issues, three research questions guided the analysis:
1. What are the current instructional improvement strategies at the school
level?
2. How are resources used to implement the school’s instructional plan?
3. How does the availability of resources impact the development and
implementation of the school plan?
The first research question will describe the current improvement strategies in
practice to increase student achievement. It has been difficult to monitor the
connection between resource allocation and school improvement. Although all
schools have identified goals, few schools link school spending directly to the
attainment of the identified goals. The second research question provides insight on
how school sites actually allocate their resources to improve student achievement.
With the shift towards accountability and adequacy, it is important to analyze how
36
schools allocate resources to implement their improvement strategies and how they
monitor the resulting impact on student achievement. Finally, the third research
question provides critical information to schools, districts, and policymakers around
improving student achievement using resources in the most effective way. Given the
current context of California’s budget and the cuts in educational funding,
stakeholders can use this research to determine more effective ways to allocate
resources to improve student achievement.
Design Summary
This is a mixed methods study, collecting data both quantitatively and
qualitatively. Quantitative data associated with school allocation of current
resources and student achievement was collected to determine how personnel and
other resources are allocated to support the instructional improvement plan.
Qualitative data providing information about the school’s instructional plan was
collected through interviews with school and district personnel. Interviews with
open-ended questions were used to focus on understanding the school’s instructional
plan and how that plan was implemented. The use of the mixed methods approach
of interviews and collection of multiple types of data will allow stakeholders to link
instructional improvement strategies and resource allocation practices to make
improvements in student learning.
Participation and Setting
The focus of this study will be an analysis of resource allocation toward
identified improvement strategies at the school site level with three California
37
secondary schools. The sample of secondary schools was drawn from XYZ Unified
School District in Southern California. XYZ Unified schools accommodate more
than 10,000 students. This district is compromised of nine elementary schools, three
middle schools, and one comprehensive high school. This study will focus on the
three middles schools. XYZ Unified is a basic aid district which means the property
tax exceeds the revenue limit, so the state provides no additional state aid. XYZ
District has no control over the revenues it receives from property tax from year to
year. The district’s income is determined by the growth and decline of property tax
revenues and not by the population served. At times, this may mean serving more
students although revenue is decreasing. Since basic aid districts receive funding
directly from local property taxes and schools are a major factor in determining the
local property tax values, the link between the local community and its schools is
strengthened which allows taxpayers to hold their schools more accountable for the
quality of educational services they provide.
The three middle schools were a non-random sample and were chosen to
support the study’s goal of understanding what schools are doing to impact student
performance and to examine what these schools could be doing differently to
increase student performance. Table 3.1 displays each school’s overall API scores,
similar schools rankings, and percentage of students scoring advanced or proficient
in mathematics and English-Language Arts from school year 2006-2009.

38
Table 3.1: School Achievement Data for Sample Schools
School
Year
#
Tested
API Statewide
Rank
Similar
Schools
Rank
% Proficient
or Advanced
in English
% Proficient
or Advanced
in Math
School X
2006-07 820 875 10 4 76% 66%
2007-08 879 878 10 6 77% 66%
2008-09 883 875 10 4 76% 61%
2009-10 974 881 9 4 77% 64%
School Y
2006-07 464 848 9 7 67% 62%
2007-08 530 843 9 9 70% 60%
2008-09 538 854 9 7 72% 53%
2009-10 570 834 9 9 67% 56%
School Z
2006-07 1032 812 9 7 60% 55%
2007-08 987 826 8 4 64% 57%
2008-09 967 847 8 5 70% 59%
2009-10 933 875 9 7 73% 65%
Source: California Department of Education

Instruments and Data Collection
Information will be gathered through interviews and document reviews to
evaluate school-level resource allocation based on the evidence based model. This
framework includes school characteristics, non-fiscal resource patterns, staffing
allocation, and various types of support for students. The complete School
Expenditure Structure and Resource Indicators (Appendix A) includes all the
elements of the framework developed by Odden et al. (2003), which will be the
protocol for this study.
The interview protocol (Appendix B) is an open-ended format. The objective
of the interview questions is focused on gathering factual information about the
instructional strategies and allocation of school resources at each school. An
39
additional interview will be conducted with the Business Manager of XYZ Unified
School District to gather factual information about resource allocation and
instructional improvement strategies at the district level. The general interview
categories for the qualitative data collection include:
1. Curriculum and Instruction: curriculum used, content focus, assessment
strategies, instructional strategies
2. Resources: class size reduction, professional development, intervention,
technology
3. Nature of School Improvement: school, district, or state driven
4. Instructional Leadership: type of instructional leadership
5. Accountability: accountability in program, monitoring of progress
The quantitative data to be collected at each school site is based on the
Secondary School Resource Indicators (Table 3.2) developed by Odden et al. (2003).
These indicators provide basic information about the school and what resources are
available, as were described in Chapter 2.

40
Table 3.2: School Resource Indicators
Indicator Definition
School building size Total student enrollment of the school
School unit size
Student enrollment of each
instructional unit within a school
(school within a school)
Percent low income
Percent of enrolled students who are
eligible for the federal free and reduced
lunch program
Percent special education
Percent of students in the school with
an individualized education program
(IEP)
Percent ESL/Bilingual
The number (percent) of students
eligible to receive services through the
English as a second language (ESL)
program or bilingual program
Expenditure per pupil
Calculated by dividing the total school
operating expenditures from all funds
by the total student enrollment
Professional development expenditures
per teacher
Calculated by dividing total school
expenditures for professional
development by the total number of
licensed teachers
Special academic focus Identifies any academic program focus
Length of instructional day
The number of hours per day that
students receive instruction
Length of class periods The number of minutes per class period
Length of core class periods
Length of mathematics, English,
science, and social studies classes
Core class size
The average number of students per
teacher in mathematics, English,
science and social studies classes
Non-core class size
The average number of student per
teacher of classes other than
mathematics, English, science and
social studies classes
Percent core teachers
The percent of all certificated staff who
are mathematics, English, science or
social studies teachers
Source: Odden et al., 2003
41
The Data Collection Protocol (Appendix C) includes 13 categories of
information and school resources. Appendix D provides definitions of each data
item to be analyzed.
Data Analysis and Reporting
The quantitative data will provide insight on each school’s resources and how
those resources are allocated, using the evidence based model. The interview
protocol will give detailed information on the school’s instructional goals and the use
of resources as reflected in those goals. Both sets of data will be sorted and
categorized based on the templates for the protocol to reflect general trends from the
data. The evidence based model will provide a consistent criteria from which to
examine and categorize the data for analysis. Along with this, student performance
data will also be analyzed. The next step of the analysis is to compare the school
resource indicators to find commonalities and areas of differences among the three
middle schools. How each school uses its resources is the primary concern of the
study. In depth reporting will occur on how expenditure structures are similar
among schools and how expenditures align with the school’s instructional goals. As
state funding declines, the decisions school leaders need to make about instructional
priorities will be discussed.
Summary
The methodology of this research study is to provide a school-level analysis
of resource allocation in relation to research-based recommendation for high
achieving schools. The specific goals of this study aim to develop a better
42
understanding of what resources schools use to improve learning and the link
between resources and student performance. To do this, a mixed method approach
of qualitative and quantitative data will be used. Interviews with school site officials
and data regarding school resources will be analyzed. The next chapter will present
the results of the qualitative and quantitative data and discuss the findings.
43
CHAPTER FOUR: FINDINGS
The focus of this study was an analysis of resource allocation toward
identified improvement strategies at the school site level with three California
secondary schools. The sample of secondary schools was drawn from XYZ Unified
School District in Southern California. XYZ Unified schools accommodate more
than 10,000 students. This district is compromised of nine elementary schools, three
middle schools, and one comprehensive high school. This study focused on the three
middle schools. XYZ Unified is a basic aid district which means that property taxes
exceed the revenue limit, so the state provides no additional state aid. XYZ District
has no control over the revenues it receives from property taxes from year to year.
The district’s income is determined by the growth and decline of property tax
revenues and not by the population served. At times, this may mean serving more
students although revenue is decreasing. Since basic aid districts receive funding
directly from local property taxes and schools are a major factor in determining the
local property tax values, the link between the local community and its schools is
strengthened which allows taxpayers to hold their schools more accountable for the
quality of educational services they provide.
Given the volatile economy, the district’s basic aid status, the growing
reliance on local property taxes, and the fluctuating nature of student enrollment, it is
necessary for XYZ Unified School District to set aside a larger reserve. For the
fiscal year 2009-2010, XYZ Unified School District’s general fund (unrestricted and
restricted) expenditures exceeded revenues by $1,749,345. The district was able to
44
maintain the required reserve levels with $2.6 million designated for economic
uncertainties, which is 3% of the total spending budget. California requires districts
to maintain a 3% reserve but additional reserves are recommended particularly for
districts such as XYZ that depend heavily on local property tax.
This chapter presents the findings and results of the three schools that
participated in this study. The purpose of this study was to identify how schools are
spending their monies in relation to research-based recommendations for high
achieving schools. Resource allocation patterns were analyzed and compared to
conclude what practices and strategies improve student achievement and to add to
the body of knowledge on how successful schools are actually using their resources.
The following research questions guided this study:
1. What are the current instructional improvement strategies at the school
level?
2. How are resources used to implement the school’s instructional plan?
3. How does the availability of resources impact the development and
implementation of the school plan?
This chapter begins with a summary of the study schools’ characteristics and
performance data followed by the findings of each of the three research questions
and a comparison to the Evidence Based Model.
Study Schools’ Characteristics and Performance Data
The three middle schools were a non-random sample and were chosen to
support the study’s goal of understanding what schools are doing to impact student
45
performance and to examine what these schools could be doing differently to
increase student performance. Table 4.1 displays each school’s overall API scores,
similar schools rankings, and percentage of students scoring advanced or proficient
in mathematics and English-Language Arts from 2007-2010. Table 4.2 displays
each school’s demographic information.
Table 4.1: School Achievement Data for Sample Schools
School
Year
#
Tested
API Statewide
Rank
Similar
Schools
Rank
% Proficient
or Advanced
in English
% Proficient
or Advanced
in Math
School X
2006-07 820 875 10 4 76% 66%
2007-08 879 878 10 6 77% 66%
2008-09 883 875 10 4 76% 61%
2009-10 974 881 9 4 77% 64%
School Y
2006-07 464 848 9 7 67% 62%
2007-08 530 843 9 9 70% 60%
2008-09 538 854 9 7 72% 53%
2009-10 570 834 9 9 67% 56%
School Z
2006-07 1032 812 9 7 60% 55%
2007-08 987 826 8 4 64% 57%
2008-09 967 847 8 5 70% 59%
2009-10 933 875 9 7 73% 65%
Source: California Department of Education
Table 4.2: School Demographic Data
Income
Indicator
Language
Skills
Student Ethnicity
School Grades Reduced
Lunch
English
Learners
African
American
Asian Hispanic White/
Other
X 6-8 18% 6% 3% 9% 16% 72%
Y 6-8 24% 7% 5% 10% 27% 58%
Z 6-8 31% 10% 1% 5% 31% 62%
Source: California Department of Education
46
The free or reduced prices meal subsidy goes to students whose families
earned less than $40,793 a year (based on a family of four). At each of the three
middle schools, the percentage of students qualifying for this program was
considerably less than the state average of 55% and the county average of 50%
qualifying for this program. This information is collected in October through the
Free and Reduced Price Meal application through the National School Lunch and
School Breakfast Program.
At each of the middle schools, over 90% of the students were considered to
be proficient in English, compared to the state average of 81% and the country
average 80%. The most common home language for classified English learners is
Spanish. Less than 2% at each school reported Vietnamese or Korean as the home
language.
For the ethnicity data, the state of California allows citizens to choose more
than one ethnic group, or to select “multiethnic,” or “decline to state.” As a
consequence, the sum of all the responses may not necessarily equal 100%. Most
students at School X identify themselves as White/Other. In fact, there are about
five times as many White/Other students as Hispanic student, the second largest
ethnic group at School X. At School Y, there are about two times as many
White/Other students as Hispanic students. And at School Z, over half the student
population is identified as White/Other.
47

760
780
800
820
840
860
880
900
School X School Y School Z
School
API Score
2007
2008
2009
2010
Figure 4.1 illustrates the API growth trends of all three schools from 2007-
2010. School X has made minor gains each year and School Z has made steady
progress each year. School Y saw a 34 point loss on the API scores in 2010.
Figure 4.1: API Scores for all Students at Sample Schools

Source: California Department of Education
Figure 4.2 (English CST Scores – 4 Year Trend) and Figure 4.3 (Math CST
Scores – 4 Year Trend) presents the performance data on the California Standards
Test (CST) for all grades 6-8. Although all schools are above the state average for
both English and Math, there has not been significant progress in English scores.
School X teetered between 76% and 77% proficient or advanced during the last 4
years. School Y declined to 67% proficient or advanced in 2010, which was the
same data as 2007. School Z did make a 13% improvement, with a jump to 73%
scoring proficient or advanced in 2010 compared to 60% in 2007.
48
In Math, School Z has been the only school that has made progress in the last
four years. School Z increased by 10 percentage points with a gain from 55% to
65% of students scoring proficient or advanced. School X’s scores decreased by 10
percentage points with a drop from 66% proficient or advanced in 2007 to only 56%
of students scoring proficient or advanced in 2010. School Y took a drop of 6
percentage points from 2007 to 2010, with 62% scoring proficient or advanced in
2007 and only 56% reaching that same level in 2010.
Figure 4.2: English CST Scores – 4 Year Trend
Source: California Department of Education

49
Figure 4.3: Math CST Scores – 4 Year Trend
Source: California Department of Education
XYZ Unified School District’s Goal and Success Indicators
XYZ Unified School District’s yearly goal and success indicators are aligned
with funding to support them and are organized by cluster area, strategies, costs
allocated and identification of funding sources. Since the 2007-2008 school year, the
goal of the district has been “every student makes significant yearly progress toward
achieving appropriate and meaningful standards.” The goal is further broken down
into success indicators in various areas. For this research, only the instructional
indicators will be utilized.

50
Table 4.3: XYZ Unified School District Success Indicators in Algebra (2007-2010)
Success Indicator
2007 -The percentage of students enrolled in 8
th
grade Algebra or above will
increase to 50% with 89% scoring at Basic or above on the Algebra CST
2008 -The percentage of students enrolled in 8
th
grade Algebra (or above) will
increase to 90%
-90% of the students enrolled in 8
th
grade Algebra will score Basic or
above on the Algebra CST
2009 -95% of 8
th
grade students will be enrolled in Algebra or above
-The percentage of 8
th
grade students scoring Basic or above on the CST
will remain at 90%
2010 -Enroll 95% of 8
th
grade students in Algebra or above

The push to enroll 95% of 8
th
grade students in Algebra or above is a strategy
to meet AYP targets in Math. Figure 4.4 illustrates the actual data at each school of
students enrolled in Algebra and Figure 4.5 shows the percentage of students scoring
at the Basic or above level for the last four years. From Figure 4.4, only School Z
met the district goal of enrolling 95% of 8
th
grade students in Algebra for the 2009-
2010 school year. School X & School Y are still aiming to meet this goal. From
Figure 4.5, it is apparent that a higher percentage of students scored basic or above
on the Algebra CST when less students were enrolled in the course. With the district
goal of enrolling 95% of 8
th
grade student in Algebra, the percentage of students
scoring basic or above on the Algebra CST has decreased. School Z did surpass the
district goal in 2010, with 92% of students enrolled in Algebra scoring at basic or
above.

51
Figure 4.4: Percentage of 8
th
Grade Students Enrolled in Algebra

Source: California Department of Education
Figure 4.5: Percentage of 8
th
Grade Students Scoring Basic or Above on the
Algebra CST

Source: California Department of Education
52
XYZ Unified School District is also aiming to improve the student
achievement data for two main subgroups: students with disabilities and English
Learners. Since 2007, these two subgroups have been included in the success
indicators matrix outline in Table 4.4: XYZ Unified School District Success
Indicators for Subgroups (2007-2010).
Table 4.4: XYZ Unified School District Success Indicators for Subgroups (2007-
2010)
Students with Disabilities English Learners
2007 Percentage of students scoring
proficient or advanced on the
Math CST will increase to
46%
Percentage of EL students
scoring proficient or advanced
on the ELA CST will increase
to 45%
2008 Percentage of students scoring
proficient or advanced on the
Math CST will increase to
50%
Percentage of EL students
scoring proficient or advanced
on the ELA CST will increase
to 45%
2009 Percentage of students scoring proficient or above on the ELA
CST will be at least 56.4% district wide, by school, by
subgroup
2010 Meet all AYP targets in ELA & Math district wide, by school
and by subgroup.

All three schools have been unsuccessful in meeting the subgroup success
indicators. Figure 4.6 and Figure 4.7 illustrate the lack of improvement in student
achievement for students with disabilities and English Learners. All of the schools
are more than 20 percentage points away from meeting the success indicators for
these two subgroups.

53
Figure 4.6: Students with Disabilities Scoring Proficient or Advanced on the Math
CST
Source: California Department of Education

Figure 4.7: English Learners Scoring Proficient or Advanced on the ELA CST
Source: California Department of Education

54
The most gains have been made with the English Learner population. Most
schools have seen a steady increase in the scores, but have yet to meet the success
indicator. XYZ Unified School District’s yearly goal and success indicators are
aligned with funding to support them and are organized by cluster area, strategies,
costs allocated and identification of funding sources.
Findings for Research Question 1:
What are the Current Instructional Improvement Strategies at the School Level?
The common strategies used by all three schools in relation to instructional
improvement strategies can be categorized into school leadership, data analysis,
collaboration and intervention. School leaders are central to shaping and
maintaining the school culture and are responsible for gaining and sustaining
momentum for instructional improvements (Symonds, 2004). Each school was led
by a principal and leadership team that discussed the importance of developing a
shared vision with the staff and all three principals were directive in nature towards
instructional practices. Spending time in the classrooms was cited as a key strategy
used by the leadership team. The principals promoted specific instructional
strategies and created rubrics to use when observing classes.
Shared leadership was evident at all three school sites. Marzano (2003)
argues that leadership should be carried out in a small group of trusted individuals
with the principal as the strong cohesive force. These principals believed in this type
of distributed leadership and the leadership teams consisted of teacher leaders.
These teacher leaders were empowered to make important decisions for the school
55
and school community. Each principal was able to build relationships with teachers
to ensure confidence, build leadership qualities, and monitor each teacher’s sense of
well being as part of the school culture. These principals’ abilities to create a culture
that is simultaneously demanding to specific principles while allowing for autonomy
for the teachers to decide how to go about daily matters ensured a spirit of trust
(Dufour et al., 2006).
Another common theme with all the schools was the importance of analyzing
data. The use of data to drive instructional decisions provides the opportunity to
have accountability, monitor the implementation and quality of instructional
programs, and mobilize schools to action (Johnson, 2002). Accountability ensures
that school personnel fulfill their expected duties. One of the district’s success
indicators for 2010 is to implement protocols for data analysis and instructional
adjustment. Monitoring the implementation of the instructional programs provides a
measure to ensure that resources are being utilized efficiently. Finally, having the
appropriate data allows schools to make appropriate instructional decisions.
All the schools used the CST and benchmark data to provide specific and
appropriate support to their students. School Z shared the previous year’s scores
with each student to raise student awareness of their performance and to serve as
motivators. School Z also used pacing guides in all core curricular areas to maintain
an intensive focus on learning. The teachers created classroom, grade level, and
school-wide goals based on the previous year’s data and aligned instruction to meet
those goals. School X used initial CST scores to place students in intervention
56
programs to address areas of deficiency. School X teachers focus on maintaining
high levels of rigorous instruction across all classrooms. They engage in dialogue
related to student data in staff and department meetings. All schools used
benchmark assessment data to monitor and gauge student progress. This data
allowed teachers to provide appropriate interventions in the classroom. All schools
used DataDirector as their tool for analyzing student performance data.
The use of benchmark assessments and DataDirector are a part of the
district’s success indicators. In the 2008-2009 school year, the success indicator was
to have 95% of students in grades 6-12 complete two XYZ Unified School District
benchmark assessments in ELA, Math, Social Science, and Science and have the
results entered into the DataDirector system. This success indicator was met that
school year. The following year, the success indicator was to have 95% of teachers
in grades K-8 demonstrate evidence in quarterly conferences and/or observations of
instructional adjustments made as a result of benchmark data analysis. This change
is a result in meeting the needs of the subgroup populations and adjusting instruction.
The use of this data in DataDirector varied according to the school and
subject area. School X used the school leadership team to analyze data and share
with the staff through department meetings. School Y & School Z used whole staff
meetings to share school-wide data and department meetings to review subject
specific data. All three schools are beginning to create both summative and
formative common assessments. These assessments will allow teachers to review
the data immediately and adjust instruction as needed. Although assessments cannot
57
improve student performance alone, it provides a summary of student performance
and allows for schools to plan and improve student learning. The use of both
formative and summative assessment data is necessary and each assessment type
serves a distinct and unique purpose (Fullan, 2005). The use of these assessments
will further inform instruction.
Collaboration is an essential component of each school’s academic plan.
Each Thursday students are dismissed early to allow for collaboration time with
teachers. The collaboration time is used to ensure that the curriculum is aligned and
each teacher is pacing appropriately. This time is also used to develop common
assessments and to analyze the results. The Professional Learning Community
(PLC) approach was used at all three school sites. Dufour et al. (2006) states that the
PLC model ensures that all students learn when teams of professionals work together
to create common essential learning standards, pacing guides, and assessments.
School Z furthers the idea of the PLC with their organization into interdisciplinary
teams referred to as the Village System. This organizational structure reflects a
school within a school concept and is designed to help students make a successful
transition from elementary to middle school. Each village includes an English,
mathematics, science and social science teacher. The village concept has allowed
for additional collaboration among teachers to provide the necessary instructional
supports for the students.
All three schools have been working on a comprehensive intervention
program for English learners. The middle school CELDT data revealed that 67.3%
58
of the English Learners made at least one level or more of growth on the CELDT
exceeding the target by 15.7%. Unfortunately, neither the district nor the middle
schools in this study have met the 45% of all English Learners needing to score
proficient or advanced in the ELA CST. School Y had the highest percentage with
28% of English Learners scoring proficient or advanced on the ELA CST. Of the
6
th
-8
th
graders who scored at the Intermediate and English Proficient Levels on the
CELDT, all the students scored Below Basic or Far Below Basic on the ELA CST.
School principals and district officials concluded EL students at XYZ Unified have
been unable to show progress for a two main reasons. First, English Language
Development is delivered inconsistently throughout the schools. Only School Y had
an additional time allotment for ELD and used the core material. There was an
overall lack of structure in the ELD program at all three schools. Second, additional
instruction in reading is inconsistent and not standards-based. According to CELDT
data, students are achieving proficiency in listening and speaking but not in reading.
School X and School Z provided 20 minutes of silent sustained reading time during
the school day. School Y targeted reading through an after-school tutoring program.
The inconsistent delivery of reading intervention has become a focus of change.
The district has identified the essential standards in ELA and has worked on
the development of district-wide benchmark assessments giving special attention to
target the needs on EL students. The five ELD Specialists have provided
professional development to the classroom teachers working with EL students. Part
1 of the professional development focused on building academic vocabulary and Part
59
2 focused on developing literacy skills. The instructional focus of the district and at
the three schools is to fully implement consistent standards-based ELD, targeting
identified essential ELD standards for the EL students. This is followed with
providing students with the appropriate reading instruction and strategic intervention
based on the implementation of a comprehensive Response to Intervention (RtI)
program. There is a push to focus on academic language development in the core
content areas. The ELD Specialists have provided professional development
opportunities that will enhance teacher skills in providing research-based
instructional practices.
Alignment to the Evidence Based Model
As discussed earlier, the evidence based model works with a prototypical
school model which adjusts for school size and demographics. The prototypical
middle school would have a total of 450 students with an average class size of 25
students (Odden & Picus, 2008). The model is staffed with 18 full time core
teachers, 3.6 specialist teachers, 2.25 instructional facilitators or coaches, and a
technology coordinator. Table 4.5 illustrates how the Evidence Based Model would
staff a school in comparison to how the schools in this study are actually staffed.
The class sizes for all the schools are larger than the recommended 25 students per
teacher in the core classes. Only School X and School Y come close to meeting the
recommendations of the Evidence Based Model in regards to staffing. None of the
schools have instructional facilitators or a technology coordinator.

60
Table 4.5: Staffing and Class Size – Evidence Based Model Compared to Actual
Core Class Size Core Teachers
(FTE)
Specialist Teachers
(FTE)
School Enrollment EBM
Suggests
Actual
School
EBM
Suggests
(75%)
Actual
School
EBM
Suggests
(25%)
Actual
School
X 919 25 30 37 36 12.25 10
Y 569 25 30 24 22 8 8
Z 1016 25 30 41 31 13.5 10

The support staff at each school site is also significantly less than
recommended by the Evidence Based Model of three support staff for the school site.
All XYZ District school sites are serviced by two full-time nurses and five English
Language Development specialists. The support of psychologists, technology
specialists, etc. is handled by the district. Each school has one full-time equivalent
academic/guidance counselor for all the students.
The model funds professional development in two ways. First, the model
funds a ten day summer institute for all teachers. The professional development is
also on going with on-site coaching. An additional five percent of all teacher
resources are used for substitute teachers to allow for teachers to receive on-going
professional development (Odden & Picus, 2008). The Evidence Based Model
suggests 200 works days per teacher including 10 days for intensive training. None
of the schools meet the requirements of yearly professional development according
to the Evidence Based Model. Per the teacher’s union and district agreement, each
teacher did receive three days of professional development each year ending with the
2008-2009 school year. With the start of the 2010 school year, the new contract
increased to a 184 day work year, with two professional development days. This
61
translated to one official buy back day and seven extended staff meeting days. This
day is usually used prior to the start of the school year and is primarily used to allow
teachers to set-up classrooms and handle operational activities and not necessarily
used as professional development. The master schedule is developed to allow for
teacher collaboration during common preparation periods and each Thursday.
Findings for Research Question 2:
How are Resources used to Implement the School’s Instructional Plan?
Given that the actual school resources are substantially less that the
recommendations of the Evidence Based Model, the schools in this study have had to
use their resources efficiently to target the needs of the school. The common
strategies used by all three schools include distributed leadership, use of data to drive
instruction, collaboration time for teachers, and intervention for struggling students.
Most of these strategies do not necessarily depend on specific resources being
implemented but rather the staff working together to use instructional time
effectively.
Distributed leadership was a common theme across the three middle schools.
Elmore (2000) refers to distributed leadership as multiple sources of guidance and
direction, following the contours of expertise in an organization, made coherent
through a common culture. At these schools, distributed leadership was not just
about accountability but also working on creating common culture among the staff.
The teachers and administrators worked together to develop instructional plans. The
leadership team was responsible for facilitating professional development, analyzing
62
data, and discussing instructional strategies. The three school principals felt
supported by the district with the development of overall goals, but the school site
distributed leadership provided the opportunity to develop staff buy-in for the
various instructional strategies.
All three schools used the district provided DataDirector to provide teachers
with performance data. DataDirector is used to organize and access state and local
data and demographic information. Although the teachers did not fully utilize the
tools or frequently enough, it is an effective part of the reform process. The data
component is directly linked to teacher collaboration. None of the schools have the
resources to provide a ten day summer institute as recommended by the Evidence
Base Model. Each school recognizes the importance of having teachers collaborate
by looking at data, adjusting instructional practices, developing common
instructional plans, and developing best practices. XYZ Unified School District and
the teacher’s union agreed to an early dismissal day each Thursday. Each school
allocated 1 hour each Thursday for collaboration. The development of Professional
Learning Communities was utilized at all schools. Teachers were expected to use
Thursdays to develop curricular material, common formative assessments, and
review data. Teachers at all three schools were just beginning to visit each other’s
classrooms and share best practices. Collaboration around data is a strategy being
used at all three school sites.
Schools in this study have engaged in various strategies to meet the needs of
their struggling students by providing intervention. Each school has protocols in
63
place to identify struggling students and provide intervention. School X and School
Z provide a 7-period day for students and provide students with a double period of
Math or ELA to allow for additional instructional time. Although no specific
program is in place for the additional period, many teachers utilize the additional
minutes to cover standards in depth. School Y used a 20-minute advisory period to
target their main intervention during the school day and after-school programs
beyond the school day.
To improve the language proficiency and academic achievement of English
Language Learners the three schools have been focused on two main objectives. The
first is to provide EL consistent standards-based ELD, targeting essential ELD
standards. Since the district did not have any benchmark assessments to measure
acquisition of ELD essential standards, the teachers worked on developing the
benchmarks. Release time was granted from the district’s Title II funds to do this
work. The professional development and portfolio reviews have been done through
the collaboration time on Thursdays. The second objective is that EL have access to
appropriate reading/language arts instruction. This means that reading/language arts
curriculum is based on their assessed needs and the curricular materials will have
appropriate modifications. To do this, each school identified students who were
Below Basic and Far Below Basic on the CSTs for ELA and placed them in
appropriate intervention. At School X and School Z the intervention was the 7-
period day. Each student had an additional period of ELA instruction on a daily
basis. At School Y the intervention was after-school tutoring and summer school.
64
The funding source for supplemental intervention material, specifically the Read 180
program, was through Economic Impact Aid (EIA) and limited Title I funds.
Since the actual school resources are substantially less that the
recommendations of the Evidence Based Model, the schools in this study have had to
use their resources efficiently to target the needs of the school. The common
strategies used by all three schools are distributed leadership, use of data to drive
instruction, collaboration time for teachers, and intervention for struggling students.
The first three of these strategies do not necessarily depend on specific resources
being implemented but rather the staff working together to use instructional time
effectively.
Findings for Research Question 3:
How Does the Availability of Resources Impact the Development and
Implementation of the School Plan?

The Evidence Based Model provides resources well above what any of the
schools in this study receive. Research Question 2 described how the schools in this
study have used their resources to improve student achievement. This section will
detail how the schools have worked with the limited resources they have to continue
to improve student achievement.
With the Evidence Based Model each school should have 2.25 instructional
facilitators to provide professional development and coach teachers. None of the
schools in this study had any instructional facilitators. The schools instead used their
Thursday collaboration time and the expertise of the leadership team to work on
curriculum mapping, data analysis, and peer-coaching. The five district-funded ELD
65
specialists provided additional support, as well. With the limited amount of funding
for professional development, the schools were not able to cover the 10 days of an
intensive summer institute but continued to collaborate and share classroom best
practices through the Thursday collaboration time. With the increase to the 184 day
work year, essentially teachers are guaranteed two professional development days.
This translated to one official buy back day and seven extended staff meeting days
leading to a 1.18% salary increase for the 2010-2011 school year. Although these
schools are not funded according to the Evidence Based Model, they have worked
with their resources.
Each middle school reported different strategies for funding instructional
programs. School X used the Friends of School X Foundation in conjunction with
the PTSA to raise funds to support reading, drama and science labs. This fundraising
also helped with fieldtrips and to support technology for students. School Site
Council at School X also approved EIA funds to support the double block of English
for English Learners. School Y used funds to pay for after-school tutors but they
were not credentialed teachers. They have also partnered with Kids Care and North
County Lifeline to supplement afterschool services. School Z allocated their school
improvement funds towards both English and Math support through the double block
of classes. This provided intervention during the school day.
Summary of Findings
This chapter presented the findings and results of the three schools that
participated in this study. The purpose of this study was to identify how schools are
66
spending their monies in relation to research-based recommendations for high
achieving schools. Resource allocation patterns were analyzed and compared to
conclude what practices and strategies improve student achievement. The following
research questions guided this study and the findings were presented in this chapter:
1. What are the current instructional improvement strategies at the school
level?
2. How are resources used to implement the school’s instructional plan?
3. How does the availability of resources impact the development and
implementation of the school plan?
The first research question described the current improvement strategies in
practice at each school site. The second research question provided insight on how
each school site actually allocated their resources. The three schools used a
combination of distributed leadership, data analysis, collaboration among teachers,
and intervention to document student achievement. The third research question
described how each school improved student achievement with limited resources.
The final chapter of this study addresses the conclusions, recommendations, and
implications of the entire study.

67
CHAPTER FIVE: CONCLUSION
This final chapter presents a brief overview of the study, implications of the
study, and thoughts on future research. The purpose of this study was to identify
how schools are spending their monies in relation to research-based
recommendations for high achieving schools. Resource allocation patterns were
analyzed and compared to conclude what practices and strategies improve student
achievement. The following research questions guided this study:
1. What are the current instructional improvement strategies at the school
level?
2. How are resources used to implement the school’s instructional plan?
3. How does the availability of resources impact the development and
implementation of the school plan?
Summary of the Study
Chapter One provided a brief overview of the study. This chapter focused
on school finance history in California including court decisions, laws, and ballot
measures which impact the school budgets. This was followed by a comparison of
how California compares nationally in terms of finances and student achievement.
While California ranks 39
th
in the nation spending $37 for every $1000 of personal
income, it ranks 1
st
in terms of average teacher salary at $65,808 (EdSource, 2010).
In California, about 85% of a school district’s general fund is spent on staff salaries
and benefits. In 2009, half of fourth graders and 40% of eight graders scored below
basic in reading (EdSource, 2010). The history of school funding has been both an
68
economic and political issues. With the authorization of NCLB and the current
budget crisis, school accountability is at the forefront of the debate.
Chapter Two reviewed the literature around resource allocations and the
impact on student achievement. The first section explored educational adequacy and
reviewed four models to determine adequate expenditure levels. The second section
reviewed the best practices to improve student achievement including defining
instructional goals, professional development, data analysis, and effective leadership.
The third section synthesized information on why researchers have struggled to
analyze school resources and how to best allocate school resources to be tied to
student achievement. The last section of Chapter Two focused on the use of the
Evidence Based Model as a way to cost out resources required to fund an adequate
education.
Chapter Three described the methodology of this study. This was a mixed
method study, collecting both quantitative and qualitative data. Quantitative data
associated with school allocation of resources and student achievement data were
collected. Qualitative data were collected through interviews with open-ended
questions focusing on understanding the school’s instructional plan and how it was
implemented.
Chapter Four presented the findings of the study along with a comparison
with the Evidence Based Model. This section began with a summary of each
school’s characteristics and performance data. Following this, the findings related to
each of the research questions was presented, providing detailed information about
69
the instructional improvement strategies at each school, resource allocation, and
impact of resources on the instructional plan. A comparison with the Evidence
Based Model was also presented.
The remaining sections of this chapter will present conclusions of the study
and suggestions for further research. The conclusions and suggestions for further
research are crucial to this district. Given the volatile economy, the district’s basic
aid status, the growing reliance on local property taxes, and the fluctuating nature of
student enrollment it is necessary for XYZ Unified School District to set aside a
larger reserve. For the fiscal year 2009-2010, XYZ Unified School District’s general
fund (unrestricted and restricted) expenditures exceeded revenues by $1,749,345.
The district was able to maintain the required reserve levels with $2.6 million
designated for economic uncertainties, which is 3% of the total spending budget.
California requires districts to maintain a 3% reserve, but additional reserves are
recommended particularly for districts such as XYZ that depend heavily on local
property tax.
Conclusions
Best practices for improving student performance were summarized in the
review of literature section of this study. Schools setting instructional goals,
providing professional development for staff, data analysis and effective leadership
along with Odden’s 10 Steps for Doubling Student Performance led to three main
conclusions for this study.
70
The first conclusion is that actual resource use is significantly less than the
Evidence Based Model. None of the school’s resource allocation patterns compared
favorably to the Evidence Based Model. Only School X and School Y come close to
meeting the recommendations of the Evidence Based Model in regards to staffing.
None of the schools used certificated tutors to work with struggling students, the
afterschool programs were inadequately staffed, and there was a lack of guidance
counselors based on the prescribed levels of the Evidence Based Model. Despite the
gap between what the Evidence Based Model recommends for professional
development, each school has found creative ways to develop their staff and find
time for them to meet. Professional Learning Communities have provided structure
for a collaborative school culture focused on data and improving student learning.
These schools have found creative ways to meet the needs of their students.
The second conclusion is the need for quality intervention programs at XYZ
Unified School District. Although the schools had various forms of intervention,
none of them were strategic and intensive. All schools identified students needing
intervention but had various approaches to meeting their needs. School X and
School Z offered a double period of English Language Arts or Math; while School Y
offered extended day tutoring. Unfortunately, it was not clear exactly how the
additional time was being utilized and how these classes were taught differently.
Each of the schools needs to develop quality intervention programs for English
Language Arts and Math. Struggling EL students need to be offered programs that
will build their skill and enable them to master the appropriate standards. The
71
district’s use of Read180 is not enough to improve acquisition of English Language
Arts standards. The program is designed to improve reading levels, but it does not
help raise other related areas such as writing. All three schools need to take a closer
look at the alignment of curriculum and the role of certificated-tutors to assist with
intervention programs. Darling-Hammond’s (2006) research documents that the
adoption and implementation of authentic curriculum is correlated to higher student
performance. It is not enough to just give students more time to acquire skills
without authentic curriculum and instruction in place. Teachers also need to be
provided with the necessary training on how to use the curriculum. Overall, students
who are not performing at grade level need to be offered programs that will build
their skills and enable them to master the appropriate content standards.
Each school used data to make decisions and to enhance teacher
collaboration. The methods for analyzing and using data varied at each school, but
each school is progressing towards looking at data in small groups and identifying
areas of improvement. This data and collaboration should also be used to identify
and enhance the intervention programs in place. Having timely, small group support
to help struggling students is a concept that has not been fully explored at any of the
school sites. The concept of having tutors to help students who fall behind get
caught up quickly and return to the regular classroom is a type of intervention that
can be used at the school sites. Teachers can use formative assessment data to
regroup students on a consistent basis. Enhancing the current practices of PLCs to
72
develop common achievement goals and assessments will help struggling students
progress towards grade level achievement.
The final conclusion from this research is that the financial crisis has had
minimal impact on student achievement. In each of the schools studied, determining
whether or not the budget reductions had a direct impact on student achievement is
difficult in part due to the use of the Evidence Based Model as a framework. Even
though budget reductions have taken place at the schools and the resource allocation
levels at each school are still far below the recommendations of the Evidence Based
Model, the schools have shown progress towards increasing student achievement.
Earlier, Hanushek (2006) generalized that there is no systematic link between the
amount of money spent and student achievement because it is impossible to identify
exactly what combination of resources will improve student performance. This
research confirms that the effective use of funding combined with a focus on student
achievement is what makes the true difference. The Evidence Based Model provides
the tool to utilize resources to improve student achievement.
The focus on student achievement can be targeted through (1) understanding
the problem and challenge, (2) setting ambitious goals, (3) using formative
assessments and data, (4) using instructional time efficiently and effectively, (5)
creating a collaborative, professional culture, and (6) distributed leadership (Odden,
2009). These targets are not directly impacted by district funding and can continue
to be implemented. To gain a current understanding of the performance situation at
the school site and district wide, each school year must begin with an analysis of the
73
standardized testing data. The state testing data gives specific information about
overall student achievement data and achievement levels of each of the main
subgroups. The data should be used to understand where the district’s students stand
on performance and to use the results to identify areas of improvement. The analysis
should be based on the framework of what schools do largely impacts student
academic performance. This analysis then leads to curriculum mapping and the
alignment of curriculum, state standards, and assessments (Odden, 2009). In short,
XYZ Unified School District can double student performance by taking a closer look
at student performance data. The goal is to understand the performance situation for
the district and the school sites, to see where students are performing well and where
they are not, to understand the performance levels of the main subgroups, and to
calculate how far or near the student’s performed to the proficient level.
The next focus is to set high and ambitious goals. Marginal improvements
are not enough to increase student achievement. The goals must also apply to all
students, including the EL and students with disabilities. The goals should not be
made for just a specific demographic of students or the students “on the bubble” to
proficiency. All students need to be moved to the proficient and advanced level. If
the district operates under the idea that all students can learn, regardless of
demographics, then these ambitious goals become more than just “stretch” goals but
can be seen as attainable.
The continued use of formative assessments and data can only be
implemented once schools have taken ownership of everything that happens at the
74
school site. This includes the assignment of teachers, the organization of curriculum
and instruction, and academic expectations. From this sense of “ownership” comes
the use of formative assessments which provide detailed information about what
students know and do not know based on a given unit of study. Teachers can use the
data from formative assessment to design their instructional activities to reach the
goals and objectives of that particular unit of study. Instruction in the classroom
becomes more efficient by specifically targeting the learning goals.
Although the instructional time during the school day is a fixed resource,
schools need to use this time more efficiently and effectively. At two of the middle
schools, students were given a double dose of mathematics or English language arts
instruction. The second period needs to be used to provide targeted assistance to the
struggling students. This additional period cannot be more of the same, the
instruction needs to be targeted and strategic to help students understand material
they did not understand the first time around. Since the daily instructional minutes
are a fixed resource, the effective use of instructional minutes is crucial.
By using the steps above, a collaborative professional school culture can be
created. This is not a stand-alone target, but rather a product of the activities detailed
above. The collaborative culture begins with the first idea of understanding the
problem and challenge. Leaders of the district and school sites build a collaborative
culture through the goal setting and development of the formative assessments and
analysis of data. By de-privatizing instruction, everyone is involved in moving the
students forward. The continued implementation of professional learning
75
communities is part of the collaborative culture. Teachers regularly observing other
teachers, data shared openly among colleagues, and informal coaching among peers
will strengthen the collaborative professional culture.
In this case distribute leadership also involves instructional leadership.
Leadership shapes school culture, and it is essential to shaping and maintaining
student achievement models (Symonds, 2004). Creating change and improving
student achievement form the bottom up is crucial to overcome teacher isolation.
In summary, this research revealed three main ideas. First, the actual
resource use in XYZ Unified School District is significantly less than the Evidence
Based Model. Second, there is the need for quality intervention for struggling
students in XYZ Unified School District. And finally, the financial crisis in
California has had minimal impact on student achievement in XYZ Unified School
District. These three conclusions directly link to the implications of this study.
Implications
From conclusions above, it is apparent that the efficiency of how resources
are used is more crucial than the amount of resources available (Hanushek & Rivkin,
1997). This study further indicates that even with limited resources schools can
work efficiently to implement proven strategies and improve student achievement.
Policy makers should be advised to consider research on effective improvement
strategies when providing more resources to education. Funding that is directly
linked to these strategies will prove more beneficial than discretionary funds that
could be used to raise teacher salaries or reduce class size.
76
The analysis of the resource use patterns and instructional improvement
strategies implemented at each school site lends support to the literature on
improving schools. The schools need to continue to focus on distributed leadership,
collaboration, data analysis and targeted intervention. Instead of being distracted by
the latest “quick fix” strategy, the staff and leadership focus needs to be on the
instruction in the classroom towards improving student performance. Collaboration
about student data and instructional intervention, along with leadership support, has
yielded student performance results.
Recommendations for Future Research
This study adds to the numerous school-level resource use studies using the
Evidence Based Model. Additional studies are needed to conclude larger
implications and to better inform practice and policy. This study was limited to three
middle schools in XYZ Unified School District. It would be valuable to collect
school-level resource use and instructional improvement strategy data from all the
schools in the district. This would add a comprehensive look at the entire district’s
allocation of resources and links to student performance. This study should also be
extended to all basic aid districts in California. The additional studies will lend
themselves to comparisons between the basic aid districts on how scarce resources
are allocated to improve student performance.
Concluding Comments
As this study is completed, California is heading into a massive budget crisis.
The Governor is proposing to spend $2.6 billion less on K-12 education with an
77
additional $2 billion reduction if voters do not approve an extension of existing taxes
in a ballot measure this summer. The reality is that school budgets will be cut
drastically over the coming months and perhaps years. This study shows efficient
research-based strategies can used with the existing resources to improve student
performance. The Evidence Based Model provides policymakers with a framework
for rethinking how schools can be funded using a research-based approach to
resource allocation. Hopefully, a new model of school finance that efficiently
utilizes resources with a focus on adequacy will be implemented.
78
REFERENCES
Augenblick, John. (1997). Recommendations for a Base Figure and Pupil-Weighted
Adjustments to the Base Figure for Use in a New School Finance System in
Ohio. Columbus, OH: Ohio Department of Education.

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

Darling-Hammond, L. (2006). Constructing 21
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Century Teacher Education.
Journal of Teacher Education, 57(2), 1-15.

Dufour, R., Dufour, R., Eaker, R. & Many, T. (2006). Learning by Doing: A
handbook for professional learning communities at work. Bloomington, IN:
Solution Tree.

EdSource. (2004, May). Rethinking how California funds it schools. Retrieved
March 8, 2010 from www.californiaschoolfinance.org

EdSource. (2005, November). How California ranks: A national perspective.
Retrieved March 12, 2010 from www.californiaschoolfinance.org

EdSource. (2006, October). Proposition 98 guarantees a minimum level of funding
for public schools. Retrieved March 15, 2010 from
www.californiaschoolfinance.org

EdSource. (2009, January). The basics of California’s school finance system.
Retrieved April 15, 2010 from www.californiaschoolfinance.org

EdSource. (2010, September). How California ranks: Demographics, resources,
and student achievement. Retrieved January 11, 2010 from
www.californiaschoolfinance.org

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

Fullan, M. (2005). Leadership and Sustainability. Thousand Oaks, CA: Corwin
Press.

Gusky, T. (2000). Evaluating professional development. Thousand Oaks, CA:
Corwin Press.

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Hanushek, E. (2006). Courting Failure: How school lawsuits exploit judges’ good
intentions and harm our children. Stanford, CA: Education Next Books.

Hanushek, E. & Rivkin, S. (1997). Understanding the twentieth-century growth in
the US school spending. Journal of Human Resources 32(1), 35-68.

Johnson, R. (2002). Using data to close the achievement gap: How to measure
equity in our schools. Thousand Oaks, CA: Corwin Press.

Ladd, H. & Hansen, J. (1999). Making money matter. Washington, DC: National
Academy Press.

Loeb, S. (2007). Getting down to facts: School finance and governance in
California. Stanford, CA: Stanford University.

Marzano, R. (2003). What works in schools: Translating research into action.
Alexandria, VA: Association for Supervision and Curriculum Development.

Miles, K. (2000). Critical issue: Rethinking the use of educational resources to
support higher student achievement. North Central Regional Educational
Laboratory.

Miles, K. & Darling-Hammond, L. (1997). Rethinking the allocation of teaching
resources: Some lessons from high performing schools. Educational
Evaluation and Policy Analysis, 20(1), 9-29.

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

Odden, A. (February, 2007). Redesigning school finance systems: Lessons from
CPRE research. (CPRE Policy Brief RB-50).

Odden, A (2009). 10 Strategies for Doubling Student Performance. Thousand
Oaks, CA: Corwin Press.

Odden, A., Archibald, S., Fermanich, M. & Gross, B. (2003). Defining school-level
expenditure structures that reflect educational strategies. Journal of
Education Finance 28(3), 323-256.

Odden, A. & Picus L. (2008). School finance: A policy perspective (4
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New York, NY: McGraw Hill.

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Rebell, M. (2007). Professional rigor, public education, and judicial review: A
proposal for enhancing the validity of education adequacy studies. Teacher
College Record 109(6) ID Number 12743, Available at www.tcrecord.org

Schmoker, M. (1999). Results: The key to continuous school improvement.
Alexandria, VA: Association of Supervision and Curriculum Development.

Schmoker, M. (2006). Results now. Alexandria, VA: Association of Supervision
and Curriculum Development.

Symonds, K.W. (2004). After the test: Closing the achievement gaps with data.
Naperville, IL: Learning Point Associates and Bay Area School Reform
Collaborative.

Timar, T. (2006). How California funds K-12 education. Stanford University, CA.:
Institute for Research on Education Policy and Practice. Retrieved April 15,
2010 from cap-ed.ucdavis.edu/publications.
81
APPENDIX A: SCHOOL EXPENDITURE STRUCTURE AND RESOURCE
INDICATORS

School Resource Indicators
School Building Size
School Unit Size
Percent Low Income
Percent Special Education
Percent ESL
Expenditures Per Pupil
Professional Development
Expenditures Per Teacher
Length of Instructional Day
Length of Class Periods
Length of Core Class Periods
Core Class Size
Non-Core Class Size
Percent Core Teachers
Core: math, ELA, science and social
studies

School Expenditure Structure
Instructional 1. Core Academic Teachers
-Math
-ELA
-Science
-Social Studies
2. Specialist and Elective Teachers
-Arts, music, physical education, etc.
-Vocational
-Driver’s education
-Librarians
3. Extra Support/Help
-Tutors
-Resource rooms (pull-out programs)
-Inclusion teachers
-ESL classes
-Special Education self-contained
classes
-Extended day or summer school
4. Professional Development
-Teacher time (stipends and
substitutes)
-Trainers and coaches
-Administration
-Materials, equipment, and facilities
-Travel and transportation
-Conference fees
5. Other non-classroom
instructional staff
-Coordinators
-Instructional aides
6. Instructional materials
and equipment
-Supplies, materials, and
equipment
-Computers (hardware,
software)
7. Student Support
-Counselors
-Nurses
-Psychologists
-Social workers
-Extra-curricular
-Athletics
Non-
Instructional
1. Administration

2. Operations and
maintenance
-Custodial
-Utilities
-Security
-Food Services
82
APPENDIX B: QUALITATIVE INTERVIEW PROTOCOL
The following are open-ended questions to capture a school’s strategies for
improving student performance.

Curriculum and Instruction
I. Tell me about how your school improved student performance.
a. What were the curriculum and instructional components of your
strategy for improvement?
i. What content area did your improvement focus on?
ii. What curricula have you used for your instructional
improvement effort?
1. Is it aligned to the state content standards?
2. How do you know it is aligned?
iii. Have assessments been used as part of your instructional
improvement effort?
1. If so, what types of assessments have been integral?
2. How often are those assessments used?
3. What actions were taken with the data results?
iv. What types of instructional strategies have been implemented
as part of your reform efforts?
1. Were teachers trained on the instructional strategies?
2. How did you know the instructional strategies were
being implemented?
Resources
II. What were the resources allocated to this strategy?
a. Was class size reduction a focus?
i. If so, what reduction strategy did you implement?
b. Was professional development a focus?
i. If so, when are professional development days scheduled?
ii. What is the focus of professional development?
iii. Do you have instructional coaches in the school? Were there
enough coaches?
c. Was intervention a focus?
i. If so, what intervention strategies were implemented?
(Tutoring, ESY, extended day, master schedule)
d. Was technology a focus?
i. If so, what types of resources were allocated to technology?

Nature of School Improvement Efforts
III. Was the instructional improvement effort driven by the school or the central
district?

83
Instructional Leadership
IV. What type of instructional leadership was present?

Accountability
V. What type of accountability was built into the instructional improvement
plan?
84
APPENDIX C: DATA COLLECTION PROTOCOL
School Profile
School Name

Address

Phone Fax

Website

Contact Person Email

Notes

85
School Resource Indicators
Current Student Enrollment
Number of ELL students
Number of students eligible for free and reduced
lunch

Total number of special education students
(IEPs)

Number of special education students (self-
contained class)

Total length of the school day
Length of the instructional day
Length of mathematics class
Length of ELA class
Length of science class
Length of social studies class
Length of foreign language class
Core Academic Teachers FTEs
Mathematics
ELA
Science
Social studies
Foreign language
Specialist/Elective Teachers FTEs
Arts
Music
Physical education
Drama
Technology
Other specialist or elective teachers
Description of other specialist or elective
teachers

Library Staff FTEs
Librarian
Library media specialist
Library aide
Extra Help I FTEs or Dollars ($)
Certified teacher tutors
Non-certified tutors
Title I aides
ELL class teachers
Aides for ELL
86
Gifted program teachers
Gifted program funds
Other extra help teachers
Other extra help classified staff
Extra Help II FTEs
Special education teacher (severely disabled)
Special education inclusion teachers
Special education resource teachers
Special education aides (severely disabled)
Special education inclusion aides
Special education resource room aides
Extra Help III
Number of extended day students
Minutes per week of extended day program Minutes
Teacher contract minutes per week Minutes
Extended day teachers
Extended day classified staff
Minutes per week of summer school Minutes
Length of session (# of weeks) Weeks
Number of students enrolled in summer school
Summer school teachers
Summer school classified staff
Other Instructional Staff FTEs or Dollars ($)
Consultants
Other teachers
Other instructional aides
Funds for daily substitutes
Professional Development FTEs or Dollars ($)
Number of professional development days
Substitutes and stipends
Instructional facilitators/coaches
Trainers/Consultants
Travel
Materials, equipment, and facilities
Conference registration fees
Other professional development
Student Services FTEs
Guidance counselor
Attendance/dropout
Social workers
Nurse
Parent liaison/community representative
87
Psychologist
Speech/OT/PT
Health assistant
Non-teaching aides
Administration FTEs
Principal
Assistant principal
Secretary
Clerical staff
Technology coordinator
Security
Custodians
Average Class Size
Grade 6
Grade 7
Grade 8

88
APPENDIX D: DATA COLLECTION DEFINITIONS

School Profile
A. School name: official school name
B. Address: street address, city, and zip code of school
C. Phone: main office phone number of school
D. Fax: main office fax number of school
E. Website: official school website address
F. Contact Person: main contact at school site
G. Email: email address of contact person
H. Notes: additional notations

School Resource Indicators
A. Current student enrollment: number of students enrolled at the school based
on 2009 CBEDs data
B. Number of ELL students: number of students eligible for services as ELL
C. Number of students eligible for free and reduced lunch: number of enrolled
students who are eligible for the federal free and reduced priced lunch
D. Total number of special education students: number of students in the school
with an IEP indicating their eligibility for special education services
E. Number of special education students (self contained): number of students in
the school with an IEP indicating their eligibility for special education
services
F. Total length of the school day: number of minutes per day that students are
required to be present at school
G. Length of the instructional day: number of minutes per day that students are
present for instruction (subtract nutrition, lunch, passing periods)
H. Length of mathematics class: number of minutes of mathematics class
periods per day
I. Length of ELA class: number of minutes of ELA class periods per day
J. Length of science class: number of minutes of science class periods per day
K. Length of social studies class: number of minutes of social studies class
periods per day
L. Length of foreign language class: number of minutes of foreign language
class periods per day

Core Academic Teachers
A. Mathematics: number of full time equivalent (FTE) licensed subject
teachers who teach mathematics
B. ELA: number of full time equivalent (FTE) licensed subject teachers who
teach ELA
C. Science: number of full time equivalent (FTE) licensed subject teachers who
teach science
89
D. Social studies: number of full time equivalent (FTE) licensed subject
teachers who teach social studies
E. Foreign language: number of full time equivalent (FTE) licensed subject
teachers who teach foreign language

Specialist/Elective teachers: teachers who teach non-core academic classes
A. Arts: number of full time equivalent (FTE) licensed subject teachers who
teach art
B. Music: number of full time equivalent (FTE) licensed subject teachers who
teach music
C. Physical education: number of full time equivalent (FTE) licensed subject
teachers who teach physical education
D. Drama: number of full time equivalent (FTE) licensed subject teachers who
teach drama
E. Technology: number of full time equivalent (FTE) licensed subject teachers
who teach technology
F. Other specialist or elective teachers: number of full time equivalent (FTE)
licensed subject teachers who are not specifically listed above
G. Description: indicate the subject area that the “other” specialist teacher(s)
instruct

Library Staff
A. Librarian/library media specialist: number of FTE licenses librarians or
medial specialist who instruct students
B. Library aide: number of FTE library aides who help instruct students

Extra Help Staff: supplemental to the instruction in the regular classroom
A. Tutors: number of FTE tutors to help students one-on-one or in small group
B. Title I aides: number of FTE non-special education aides who provide
groups of students with extra help
C. ELL class teachers: number of FTE licensed teachers of ESL classes who
work with non-English speaking students to teach them English
D. Aides for ELL: number of FTE aides of ESL classes who work with non-
English speaking students to teach them English
E. Gifted program teachers: number of FTE teachers who instruct students in
the gifted program
F. Gifted program funds: dollar amount budgeted for the gifted program for the
2009-2010 school year
G. Other extra help teachers: number of FTE teachers who provide
supplemental instructional assistance to students to learn the school’s core
curriculum
90
H. Other extra help classified staff: number of FTE classified staff who provide
supplemental instructional assistance to students to learn the school’s core
curriculum
I. Special education teacher (severely disabled): number of FTE licensed
teachers who teach in self-contained special education classrooms and work
with “severely” disabled students
J. Special education inclusion teachers: number of FTE licensed teachers who
assist regular classroom teachers with mainstreamed students who have
learning disabilities
K. Special education resource teachers: number of FTE licensed teachers who
provide small groups of special education students with extra help
L. Special education aides (severely disabled): number of FTE aides who assist
in self-contained special education classrooms and work with “severely”
disabled students
M. Special education inclusion aides: number of FTE aides who assist regular
classroom teachers with mainstreamed students who have learning
disabilities
N. Special education resource room aides: number of FTE aides who provide
small groups of special education students with extra help
O. Number of extended day students: number of students who participate in the
extended day program
P. Minutes per week of extended day program: number of minutes per week
that the extended day program is offered
Q. Teacher contract minutes per week: number of work minutes per week in the
teacher contract
R. 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
S. 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
T. Minutes per week of summer school: number of minutes per week that
students attend summer school
U. Length of session (# of weeks): number of weeks that summer school is in
session
V. Number of students enrolled in summer school: number of students enrolled
in summer school
W. Summer school teachers: number of FTE teachers who worked summer
school
X. Summer school classified staff: number of FTE staff who worked summer
school

91
Other Instructional Services
A. Consultants: dollar amount for all consultants other than professional
development contract services
B. Other teachers: number of FTE teachers who instruct, but were not included
in the above categories
C. Other instructional aides: number of FTE aides who instruct, but were not
included in the above categories
D. Funds for daily substitutes: daily rate for certified teacher substitutes who
replace sick teachers

Professional Development
A. Number of professional development days: number of days the teacher
contract specifies for professional development
B. Substitute and stipends: dollar amount budgeted for substitutes and stipends
that cover teacher time for professional development
C. Instructional facilitators/coaches: number for FTE instructional facilitators or
coaches
D. Trainers/consultants: dollar amount for outside consultants who provide
training or other professional development services
E. Travel: dollar amount of the costs of travel for off-site professional
development
F. Materials, equipment, and facilities: dollar amount for professional
development including the cost of classroom materials, equipment needed for
professional development, and rental or other costs for facilities
G. Conference registration fees: dollar amount for fees for conferences related
to professional development
H. Other professional development: either FTE or dollar amount for other
professional development not included in the above categories

Student Services
A. Guidance counselor: number for 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 social workers
D. Nurse: number of FTE registered nurses or nurse practitioners
E. Parent liaison/community representative: number of FTE staff members who
serve as parent liaison/community representative
F. Psychologist: number of FTE licensed school psychologist
G. Speech/OT/PT: number of licenses speech, occupational, and physical
therapists who provide services to students at the school site
H. Health assistant: number of FTE health assistants
I. Non-teaching aides: number of FTE non-teaching aides

92
Administration
A. Principal: number of FTE licensed principals
B. Assistant principal: number of FTE licensed assistant principals
C. Secretary: number of FTE secretaries
D. Clerical staff: number of FTE clerical staff
E. Technology coordinator: number of FTE technology coordinators
F. Security: number of FTE security staff
G. Custodians: number of FTE staff who provide custodial services

Average Class Size
A. Grade 6-8: average class size in the core academic courses

Abstract (if available)

Abstract One of the most important decisions made by school officials is deciding how to allocate funding resources to ensure high student performance. The history of school funding over the last century has been both an economic and political issue. With the authorization of No Child Left Behind (NCLB) and the current budget crisis, school accountability is at the forefront of debate. California is heading into a massive budget crisis. The Governor is proposing to spend $2.6 billion less on K-12 education with an additional $2 billion reduction for the 2011-2012 fiscal year. The reality is that school budgets will be cut drastically over the coming months and perhaps years. This study suggests that efficient research-based strategies can used with the existing resources to improve student performance. It is imperative that California continue to explore every possible way to do better with the current resources. Some research focuses on how much money schools receive and other focuses on how fairly the funds are distributed. A more relevant study is whether schools in California have the resources to meet California’s demanding academic goals. California schools are attempting to educate the most diverse and challenging school population.

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Asset Metadata

Creator Dugal, Nisha Bhakta (author)

Core Title Allocation of resources to improve student achievement

School Rossier School of Education

Degree Doctor of Education

Degree Program Education (Leadership)

Publication Date 03/07/2011

Defense Date 03/01/2011

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

Tag budget crisis,OAI-PMH Harvest,school finance

Place Name California (states), USA (countries)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Garcia, Pedro E. (committee chair), Castruita, Rudy M. (committee member), Love, Laurie (committee member)

Creator Email nbhakta@usc.edu,nisha.dugal@lausd.net

Permanent Link (DOI) https://doi.org/10.25549/usctheses-m3683

Unique identifier UC1454048

Identifier etd-Dugal-4399 (filename),usctheses-m40 (legacy collection record id),usctheses-c127-442124 (legacy record id),usctheses-m3683 (legacy record id)

Legacy Identifier etd-Dugal-4399.pdf

Dmrecord 442124

Document Type Dissertation

Rights Dugal, Nisha Bhakta

Type texts

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

Repository Name Libraries, University of Southern California

Repository Location Los Angeles, California

Repository Email cisadmin@lib.usc.edu