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Educational resource allocation at the high school level: a case study of high schools in one California district

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Educational resource allocation at the high school level: a case study of high schools in one California district

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Content Running Head: HIGH SCHOOL EDUCATIONAL RESOURCE ALLOCATION 1
EDUCATIONAL RESOURCE ALLOCATION AT THE HIGH SCHOOL LEVEL:
A CASE STUDY OF HIGH SCHOOLS IN ONE CALIFORNIA DISTRICT

by

Sarah Ragusa

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

May 2013

Copyright 2013 Sarah Ragusa

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Dedication
This dissertation is dedicated to Tim Ragusa, my loving husband whose unending
support has been invaluable throughout this process.

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Acknowledgements
I would like to thank my dissertation chair, Lawrence O. Picus, who supported me
and the rest of my thematic group through a long and arduous process. We couldn’t have
done it without him.
I would also like to thank Dr. Kent Bechler for mentoring me and inspiring me to
embark on the journey of obtaining a doctoral degree. His advice and encouragement
prompted much self-reflection which helped me to grow both personally and
professionally.
Thank you, as well, to both of my parents for their belief in my ability to
accomplish any endeavor. Their confidence in me throughout my lifetime has created the
pathway which has led me here.
Finally, I would like to acknowledge the deep friendships that were forged
amongst eight strangers who joined USC’s doctoral class of 2013 with no idea what they
were in for. Together we laughed, argued, supported, and pushed one another. It was an
honor to share this experience with the “OC-8;” may we feed and nurture these
friendships for a lifetime.

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Table of Contents
Dedication 2

Acknowledgements 3

List of Tables 6

List of Figures 7

Abstract 8

Chapter 1: Overview of the Study 10
Brief History of School Finance 11
Statement of the Problem 17
Purpose of the Study 17
Research Questions 18
Importance of the Study 18
Summary of Methodology 19
Limitations 19
Delimitations 19
Assumptions 20
Definitions 20

Chapter 2: Review of the Literature 23
School Improvement Strategies 23
Allocation of Human Resources 31
Effects of Fiscal Crisis on Education in California 45
Gap Analysis 54
Summary 59

Chapter 3: Methodology 61
Overview of Methodology 61
Research Questions 62
Sample and Population 62
Instrumentation and Data Collection 64
Data Analysis 66
Summary 68

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Chapter 4: Study Results 69
Overview of the District 69
Research Question #1: What Research-based Human Resource Allocation
Strategies Improve Student Achievement? 74
Research Question #2: How are Human Resources Allocated across the
Sample School District? 80
Research Question #3: Is there a Gap between Current Resource Allocation
Strategies and Research-Based and Desired District Allocations? 92
Research Question #4: How Can Resources be Reallocated to Align
with Strategies that Improve Student Achievement? 101
Summary 107

Chapter 5: Conclusions 108
The Sample 108
Limitations 109
Summary of Findings 109
Implications for Practice 113
Recommendations for Future Research 115
Summary 116

References 118

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List of Tables
Table 1: Percentage Share of Public School Revenues 32

Table 2: Expenditures by Function for the United States, 1969–2008 34

Table 3: Recommendations for Adequate Resources for Prototypical
Elementary, Middle and High Schools 43

Table 4: Demographics for Comprehensive High Schools in Sample District 70

Table 5: Demographics for Alternative High Schools in Sample District 70

Table 6: Student Achievement Data for Comprehensive High Schools 72

Table 7: Student Achievement Data for Alternative High Schools 72

Table 8: Management Staff, All High Schools 81

Table 9: Certificated Teaching Staff, All High Schools 84

Table 10: Certificated Staffing: Adjunct or Specialized Services, All High Schools 87

Table 11: Pupil Support Staff, All High Schools 88

Table 12: Classified Staff, All High Schools 91

Table 13: Gap Analysis: High School Certificated Teachers 95

Table 14: Gap Analysis: High School Certificated Teachers, Adjunct
or Specialized Services 97

Table 15: Gap Analysis: High School Pupil Support Staff 98

Table 16: Gap Analysis: High School Positions Overstaffed Compared to EBM 100

Table 17: High School Tradeoff Summary 106

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List of Figures
Figure 1: Percentage Distribution of Revenues for Public Education in the U.S.,
Fiscal Year 2006 33

Figure 2: Elements of the Evidence-Based Model 42

Figure 3: California’s Education Revenue System, Fiscal Year 2008 48

Figure 4: Percentage of District Revenues by Funding Type as of 2010 49

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Abstract
This study utilized the Evidence-based Model (EBM) from the research on school finance
to evaluate the high school level human resource spending patterns of one California
school district. The purpose of this study was to determine whether the district’s
spending patterns were aligned with those patterns which have been shown by the
research to boost student achievement. An additional objective of the study was to
recommend staff reallocation to more closely align the district’s current spending
strategies with strategies that have the potential to increase student achievement. Data on
staffing allocations were collected from the Educational Services and Human Resources
departments of the study district, and a gap analysis was conducted to analyze the nature
of the differences between the district’s spending patterns and those suggested by the
EBM.
Findings from the study indicate that the EBM’s suggestions could not be fully
implemented in the study district given that the district’s high schools do not have
adequate funding to hire as many staff as recommended by the EBM for almost every
position. However, findings also indicate that some human resource reallocation is
possible and, when performed in conjunction with school restructuring strategies,
provides the study district with avenues for making spending decisions in support of
student achievement. Specific reallocation suggestions for the study district include
gaining additional core teachers, instructional coaches, guidance counselors and
academic extra help staff by reducing special education instructional aides and
transitioning assistant principals of athletics and activities to teacher salaries.
Organizational suggestions for the study district include gaining more academic extra
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help staff by reorganizing the school schedule to include a homeroom period, gaining
additional core teachers by transitioning appropriately credentialed specialist teachers
into the teaching of core subject areas, and gaining additional special education teachers
by converting extra planning time into teaching time. This study contributes to the
growing body of school finance research by illuminating the spending challenges and
opportunities specific to the high school level and providing suggestions for revamping
existing human resource allocation practices accordingly.

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Chapter 1: Overview of the Study
In the 1990s, a standards-based reform movement swept over the United States
revolutionizing the educational landscape. The expectation was that all students would
learn similar content and master similar objectives such that the academic experience
could be comparable from classroom to classroom and from school to school.
Subsequently, the Federal No Child Left Behind act (NCLB) of 2002 mandated that
states set minimum performance levels wherein all students could and would become
proficient by the year 2014. NCLB spawned the current two-pronged accountability
system that provides both federal (Adequate Yearly Progress [AYP]) and state
(Academic Performance Index [API]) targets against which to measure the progress made
by schools, both individually and in comparison to one another. Never before have
schools felt such pressure to demonstrate effectiveness through the attainment of specific
student performance outcomes as demonstrated on a battery of state standardized tests.
Failure to meet minimum performance levels in terms of AYP and API triggers a host of
sanctions, the consequences of which can range from damaged school reputations to full-
blown state takeovers (EdSource, 2005).
The burden and accompanying stress of accountability is felt especially strongly
in California where demographic challenges present roadblocks along the pathway to
proficiency. California educates more students than any does other state (EdSource,
2008), the highest proportion of which live in households where the primary parent has
not obtained a high school diploma (EdSource, 2011). Approximately 56% of
California’s students live near or below the nation’s poverty line and qualify for the
federal free and reduced-priced meals program. Additionally, 24% of California’s
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students are designated as English Learners (EL) compared to 10% nationally, while 44%
speak a language other than English at home compared to the national average of 20%
(EdSource, 2011).
In addition to demographic challenges, California also faces distinct academic and
fiscal challenges. California has adopted a set of content standards that are considered to
be among the most rigorous in the nation (EdSource, 2008). Though the teaching of
arduous content standards might suggest the need for heightened levels of fiscal and
human resources, California’s per-pupil funding rate is well below the national average
(EdSource, 2008) and its staff-to-pupil ratios are at or near the bottom of national
rankings (EdSource, 2011). How, then, can schools in California expect to make gains in
student achievement with ever diversifying student populations and limited fiscal
resources? This study provides some answers to this important question, focusing on
strategies for resource allocation at the high school level.
This chapter first presents a brief history of California school finance, describing
the difference between equity and adequacy as theoretical models for funding schools. A
concise statement of the problem, followed by a description of the purpose of the study
and its importance are also be presented. Finally, the study’s limitations, delimitations
and assumptions are disclosed, along with a list of definitions for key terms that appear
throughout the study.
Brief History of School Finance
Schools have been witness to various changes over the years in how they receive
their funding. Prior to 1976, schools were funded largely through local property taxes.
That process was called into question when a landmark legal decision was made for the
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plaintiff in Serrano v. Priest, where it was found that existing school funding
mechanisms inadvertently perpetuated inequities between students. Because wealthier
communities were able to raise more revenue from property taxes, students in less
affluent communities did not have access to the same education as their wealthier peers,
and the court decided that such spending disparities must be eliminated. Following this
important decision, voters passed Proposition 13, a constitutional amendment that set a
ceiling on the amount of property taxes that could be levied. This proposition flipped the
ratio of state to local funding, where most of the funding previously collected from
property taxes was now expected to be backfilled by contributions from the state. Thus
the 1980s saw the rise of individual states taking on primary responsibility for the
funding of public education. In 1988, Proposition 98 guaranteed schools a minimum
funding level based upon a formula (EdSource, 2011), and in California 59% of
education funding is generated from the state’s general fund (EdSource2009).
Despite this minimum guarantee California was, and still remains, underfunded
compared to the national average in terms of per pupil spending (EdSource, 2008). The
current recession has depleted funds in such a way that California has been challenged to
do more with less. While old approaches to funding schools focused only on the
resources or inputs they received, new approaches are more concerned with how those
inputs are used to meet student learning targets, or produce specific outputs. The next
section of this chapter explores the differences between equity and adequacy as
theoretical frameworks for school funding models, and a rationale for the selection of one
particular adequacy model as the conceptual basis for this study is described.
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From equity to adequacy. Equity models of school finance were developed as a
direct response to an inequitable funding system where students in middle and upper
class neighborhoods were more likely than their lower class peers to benefit from
revenues collected from property taxes. In theory, equity models had the potential to
level the playing field by distributing funds across schools in an equal manner, such that
no school or district could benefit or be disadvantaged by an unequal share of revenue.
While this originally seemed to be a fair answer to inherent school funding inequalities,
there are two fundamental problems with equity models. First, they do not take into
account that schools in varying socioeconomic circumstances are also in various states of
need, such that equal sums of money distributed evenly across schools might produce
very different results depending upon each school’s financial, cultural, and academic
foundation. Thus, the question arises whether equal funding across schools does much to
eradicate the disparity in the quality of education from one school to the next. Second,
being concerned only with how much funding is bestowed upon schools and districts
leaves the spending of those funds up to individual school and district discretion. There
is no accountability for how the money is spent, and thus the effective use of funds is
random, up to the intuition of school leaders, and sometimes even a result of chance
(Odden, 2005; Walter & Sweetland, 2003).
As a reaction to the shortfalls of equity models, adequacy models began to
develop as the need for accountability and attention to results became more pervasive.
Unlike equity, adequacy does not suggest an equal distribution of funds across all
schools. Rather, it defines the starting point for each school and then determines what
level of additional funding is necessary to educate the students in each school such that
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they have an equal opportunity to meet performance standards. In other words, an
adequacy framework would not advocate giving schools in low income communities and
schools in affluent communities the exact same sums of funding because their existing
resource levels are quite different and their students’ proximity to proficiency targets are
likely dissimilar as well. Unlike equity, adequacy is concerned with both inputs and
outputs (Baker, 2005; Odden, 2003). The questions that adequacy studies ask are: how
much funding is required to ensure that all students meet performance standards? Are
those funds being spent on programs and strategies that are both aligned with school
goals and proven by the research to bring about the desired outcomes?
There are four distinct methods for estimating adequacy. They are 1) the
successful district approach, 2) the cost function approach, 3) the professional judgment
approach, and 4) the evidence-based model. What follows is a brief description of each
approach, including their strengths and weaknesses, and an explanation for the selection
of the evidence-based model as the theoretical framework for this study.
Successful district approach. The successful district approach to estimating
adequacy examines funding levels in districts where all students are currently meeting or
making gains toward meeting proficiency targets for the purposes of replicating those
results elsewhere. The successful district approach is convenient and user friendly;
finding schools that are meeting performance goals is straightforward, requiring only
time and research. Where the successful district approach falters is in its
oversimplification of the effects of diverse populations which vary from school to school.
For example, factors such as socioeconomic status and parent education level may be
more strongly associated with school success or failure than are school funding strategies.
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When schools whose demographics or cultural dynamics are unlike the schools within the
studied district, their replication of similar strategies is likely to result in outcomes which
do not mirror the studied district’s successes (Odden, 2003; Rebell, 2007).
Cost function approach. In contrast to the simplicity of the successful districts
approach, the cost function approach is a complex statistical model which examines
current spending patterns across a state and then estimates, based on a single district’s
student population, what level of funding is required for that district’s students to meet
performance standards. A cost function study, then, is a comparison between a single
district’s needs and the needs across a state overall. The benefit of the cost function
approach is its technical and mathematical accuracy. Its shortcomings, however, include
its difficulty level and labor intensiveness, the fact that it can only estimate costs based on
one or two performance outcomes, and that it is only effective in estimating adequacy at
the district, and not the school level (Rebell, 2007).
Professional judgment approach. The professional judgment approach, the
most commonly used educational adequacy model, consists of soliciting the opinions of
highly qualified teachers, principals, and other educational practitioners through the use
of either a focus group or a survey. These individuals are asked which strategies they
believe are most effective in bringing about gains in student achievement, and then a cost
is assigned to each of their recommendations. Advantages to this approach are its ease of
use, its singular focus on strategies that inspire student performance, and its origination
from professionals within education who understand the nuances of the system. Its
limitations include its subjectivity and its potential financial disconnect with reality.
Professionals who are asked their opinion about strategies which are connected to student
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achievement may not be mindful of costs and may propose recommendations which are
visionary but unrealistic given financial constraints. Additionally, the professional
judgment approach is not as precise or dependable as a statistical model (Odden, 2003,
Rebell, 2007).
Evidence-Based Model. Like the professional judgment approach, the evidence-
based model pinpoints several strategies that produce student achievement and then
assigns a cost to each of those strategies. The difference between the two models,
however, lies in the fact that the evidence based model is less susceptible to subjectivity
or opinion: it recommends only those strategies which have been identified by the
research as effective for helping students meet performance targets. Additionally, it
functions as a precise and user-friendly statistical model which suggests a method for
prioritizing research-based strategies. Thus, schools are given suggestions for the
instructional tools they need to succeed without surpassing cost ceilings. Unlike other
adequacy models, the evidence-based model is able to take into account spending
patterns at both the district and school level, determining whether current spending is
aligned with district and school goals (Odden et. al, 2005). For these reasons, the
evidence-based model exhibits a significant advantage over the other three models
previously discussed and thus functions as the theoretical framework for this study.
Of the existing studies of educational adequacy, many have been conducted
outside of California. Those with origins in California have studied only state or district
level expenditures (Rebell, 2007). There has been very little adequacy research
conducted at the school level in California, and this study fills that gap by concentrating
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on expenditures in five comprehensive high schools and three alternative high schools in
one school district in Southern California.
Statement of the Problem
As California continues its fight through the current recession its school leaders
need guidance in the strategic allocation and reallocation of scarce resources. These
leaders face the overwhelming challenge of reaching 100% student proficiency by 2014
while navigating threats in the form of additional cuts to funding over the coming years.
Not only will California’s schools need to determine the effectiveness of their current
practices, they will also inevitably need to decide which programs and services to cut and
which to preserve and augment. Explicit tools for differentiating the value of resources
will become essential and the Evidence-based Model’s strength lies in its provision of
these tools. After examination of the distribution of resources at the studied schools,
specific strategies are proposed for allocating and reallocating existing resources in ways
which are both fiscally sound and supportive of growth in student achievement.
Purpose of the Study
The purpose of this study was to collect resource allocation data from schools to
determine whether current fiscal practices support school and district visions and are
conducive to improving student achievement. This data was collected from five
comprehensive high schools and three alternative high schools and compared to the
research-based resource allocation strategies of the Evidence-based Model. The
outcomes of this study provides policy makers, district administrators, and school site
leaders with an indication of the effectiveness of current practice and with
recommendations for making improvements where gaps exist between present spending
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patterns and those proposed by the Evidence-based Model. Armed with this knowledge,
stakeholders are empowered to make decisions which have the potential to positively
impact student achievement.
Research Questions
This study asked the following questions:
 What research-based human resource allocation strategies improve student
achievement?
 How are human resources allocated across the sample school district?
 Is there a gap between current resource allocation strategies and research-
based and desired district allocations?
 How can resources be reallocated to align with strategies that improve student
achievement?
Importance of the Study
This study contributes to the existing bank of adequacy studies in two ways.
First, it increases the now scant knowledge of how adequacy is calculated in California.
Second, it is one of few studies that narrows the focus to examine how adequacy is
estimated solely at the high school level. In addition, it may inform policy makers’
decisions by increasing their awareness of effective practices so that they might make
sound judgments about mandates or funding streams they wish to advocate. It also serves
as a resource for district administrators who are choosing between competing district-
wide interventions to implement at the high school level. Finally, this study informs site
administrators who wish to streamline their funding patterns in ways which support
school goals and bolster student achievement.
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Summary of Methodology
A mixed methods approach has been utilized to study five comprehensive high
schools within a single suburban district in Southern California. Interviews were
conducted with school principals and district personnel to gather information regarding
instructional practices and school and district mission, vision and goals. Additionally,
artifacts such as master schedules, staff rosters, single plans for student achievement, and
school budgets were examined. All site-based human resource expenditures were input
into a database which was utilized to generate funding recommendations as proposed by
the Evidence-based Model. For each school and across schools, a gap analysis was
performed where the Evidence-based Model’s recommendations were compared to
current practices.
Limitations
One limitation of this study was the size of its sample. The results obtained from
an examination of eight schools are not generalizable to other settings, especially those
where demographics are dissimilar. Another limitation of this study was the relatively
short period of time in which it was conducted. A five month study such as this one is
susceptible to the volatility of any immediate circumstances present at the time of the
study.
Delimitations
This study was conducted in five high schools within one school district in
southern California. It examined resource allocation data for one school year only.

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Assumptions
This study assumed that all data collected were in fact accurate, that interviewees
spoke freely and truthfully, and that the documents chosen for analysis were reflective of
the schools’ cultures and practices.
Definitions
Academic Performance Index (API)—California’s numerical system for comparing levels
of student achievement in schools to one another statewide.
Achievement Gap—The difference in performance between minority and low socio-
economic student groups and that of more privileged groups.
Adequacy—the level of funding necessary to allow each student the opportunity to
achieve growth targets (Odden, 2003).
Adequate Yearly Progress (AYP)—federal accountability system resulting from the 2001
No Child Left Behind (NCLB) law which mandated that all students must demonstrate
proficiency in Math and English language arts by the year 2014 (EdSource 2005).
American Recovery and Reinvestment Act (AARA)—Commonly called “the stimulus
package,” this act gave over $100 billion one time monies to education.
Average Daily Attendance Rate (ADA)—A funding formula calculated by multiplying the
per pupil minimum guaranteed by Proposition 98 by a district’s total enrollment.
Class Size Reduction (CSR)—A movement to drop class sizes in K-3 in response to state
funding incentives for doing so.
Collaboration—Teachers working together in teams to build formative assessments,
share best practices, create lesson plans, and create plans for intervention.
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Cost Function Approach—A statistical model which estimates adequacy by comparing
individual schools to state averages (Rebell, 2007).
Data-based Decision Making—The practice of utilizing data to determine how to make
improvements to school systems which foster improvements in student achievement.
Equity—the practice of allocating identical resource levels across all schools and districts
(Walter &Sweetland, 2003).
Evidence-Based Model (EBM)—a research-based adequacy estimator which provides
recommendations for sufficient funding levels to ensure that all students have the
opportunity to meet achievement targets (Odden et. al, 2005).
Gap Analysis—A tool for measuring the distance between actual and desired
performance, diagnosing causes, and proposing solutions (Clark & Estes, 2002).
Instructional Coaches—Teachers released from the classroom for the purposes of team-
teaching, modeling, and coaching their peers in specific instructional strategies.
No Child Left Behind (NCLB)—2001 reauthorization of the federal Elementary and
Secondary Education Act (ESEA) which requires schools in all states to demonstrate
ongoing progress toward meeting student achievement targets. Schools that fail to
exhibit progress face a tiered system of sanctions, the most extreme consequence of
which could be a state takeover (EdSource, 2005).
Performance Targets—Goals set by the state regarding performance levels students need
to meet to be considered “proficient.” In California, all students are expected to reach
proficiency by the year 2015.
Per Pupil Funding—A specific monetary allotment that is given to school systems for
each student that is currently enrolled.
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Professional Development—Training of teachers in specific strategies for the purposes of
instructional improvement.
Professional Judgment Approach—an adequacy model which relies on the expertise of
educational professionals for recommendations regarding effective use of funds (Odden,
2003).
Proposition 13—California initiative passed in 1978 which limited property tax rates and
provided a cap for increases in assessed property values (EdSource, 2011).
Proposition 98—passed in 1988, this proposition guaranteed schools a minimum level of
funding as determined by a formula (EdSource 2011).
Research-based Instructional Practices—Educational practices that have a research base
that attests to their effectiveness in improving student achievement.
Resource Allocation—Describes the practices of categorizing money to be spent on
various school needs and considers all inputs and the various ways they are spent (Nakib,
1995).
Resources—Includes the money, personnel, time, materials, and facilities required to run
schools.
Senate Bill (SB) 90—Imposed a revenue limit system which placed a ceiling on the
amount of income districts could raise through property taxes (EdSource, 2009).
Successful Districts Approach—an adequacy estimation model which involves studying
successful districts with the goal of emulating their practices (Rebell, 2007).
State Fiscal Stabilization Fund (SFSF)—A division of AARA which allotted $48.6
billion to states to backfill budget deficits.

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Chapter 2: Review of the Literature
This chapter outlines the existing literature on school finance strategies with a
particular emphasis on their relationship to school reform efforts. The chapter is divided
into the following four sections: 1) an overview of research-based school improvement
strategies, 2) an examination of resource allocation patterns through the lens of
educational adequacy, 3) a discussion of California’s specific fiscal challenges and
constraints, and 4) an overview of gap analysis as this study’s chosen methodological
structure.
School Improvement Strategies
In an era of increased accountability, school reform movements have been widely
studied in order to inform school leaders and policy makers of research-based strategies
for improving student achievement. The following is a synthesis of studies and meta-
analyses that have made an important contribution to the body of research on school
improvement strategies (Odden, 2009; Duke, 2006; Reeves, 2003; Togneri & Anderson,
2003; Fermanich, Mangan, Odden, Picus, Gross, Rudo, 2006; Darling-Hammond, 2002).
These studies have been chosen for discussion based on their overall representation of the
larger body of literature and their demonstration of common, recurring themes. These
themes are examined after a short summary of the research.
Darling-Hammond (2002) conducted a study that looked at small New York
schools opened in response to declining academic success, low attendance and high
dropout rates. Of the newly opened schools, four were identified as successful in that
they produced over 90% graduation and college-going rates with at-risk populations. The
study of these schools focused on common practices that were implemented with the
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opening of each school which required them to do business differently than in previous
schools. The common practices implemented across all four of the successful schools
were: 1) the use of portfolio assessment, 2) regular collaboration among faculty, 3) the
formation of interdisciplinary teacher teams, 4) the implementation of class size
reduction, 5) the provision of guidance by teachers acting as counselors, 6) opportunities
for shared decision-making, 7) the use of peer evaluation, 8) inclusion of professional
development, and 9) the involvement of the community in school matters.
Similarly, Reeves (2003) coined the now prolific 90/90/90 concept in a study of
schools in Milwaukee and Wisconsin whose demographics included over 90%
participation in the free and reduced lunch program, over 90% belonging to minority
groups, and over 90% of students meeting district or state performance targets. In an
effort to identify how these schools defied the odds and achieved academic success with
their at-risk populations, the study identified common characteristics shared across all
excellent schools and found that each school had placed a singular focus on academic
achievement and had made clear and specific choices in regards to its curriculum.
Additionally, each school conducted frequent assessments of student progress and offered
multiple opportunities for intervention and improvement. Each school also enjoyed a
school-wide emphasis on nonfiction writing and its teachers worked collaboratively to
score students’ work.
In a parallel study of schools beating the odds, Togneri and Anderson (2003)
identified schools and districts making gains in student achievement in a manner
dissimilar to their neighbors, describing these places as “islands of excellence.” They
examined schools and districts in California, Texas, Maryland, Minnesota, and Rhode
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Island with poverty rates of at least 25%, with three-year trajectories of improved scores
in math and reading and with evidence of progress toward closing the achievement gap.
The study aimed to expand these pockets of success by illuminating successful practices
for other schools and districts to emulate. The islands of excellence schools and districts
shared the following six attributes: 1) poor performance was initially acknowledged and
solutions were sought, 2) a system-wide approach to instructional improvement was
implemented which included articulated curriculum and support structures, 3) their vision
was focused on learning and instructional improvement, 4) data-based decision making
was the norm, 5) new approaches to professional development were implemented and 6)
leadership roles were redefined.
In a meta-analysis of five studies conducted between 1995 and 2004, Duke (2006)
reported on initially low performing schools that executed turnaround efforts leading to
significant increases in student achievement. The purpose of the study was to inform a
training program for school reform specialists in Virginia. Findings of similar
characteristics across all schools in the five studies included the use of frequent formative
assessments, alignment of those assessments with the curriculum, and prompt assistance
for students experiencing difficulties learning content. Additionally, school staffs had
high expectations for student achievement and their bell schedules reflected prioritization
of the core in the form of increased time for math and English language arts. Each school
exhibited efficient organizational structures with opportunities for staff collaboration and
professional development. Effective leadership practices were documented in each
turnaround school where staff used data to drive decision-making and held an expectation
of parent involvement.
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In an effort to identify the practices of successful schools in Washington,
Fermanich, Turner, Mangan, Odden, Picus, Gross, and Rudo (2006) performed a
successful district study by first conducting a state level analysis and then selecting 31
successful schools in nine districts across the state. The study identified a set of criteria
for success and then examined how resources were distributed in those schools that met a
high percentage of those criteria. The authors found that the key elements of successful
schools were a focus on the ability of all students to meet performance targets, the use of
data-based decision making, adoption of a rigorous curriculum aligned to state standards,
effective professional development practices, and extended learning opportunities for
struggling students.
In a meta-analysis and synthesis of work done by 13 researchers, Odden (2009)
compiled a list of ten strategies utilized by schools that were able to double student
performance as demonstrated by state standardized test scores. The identified strategies
included: 1) understanding the performance problem, 2) setting ambitious student
performance goals, 3) creating a new instructional vision, 4) implementing formative
assessments and data-based decision making, 5) providing ongoing professional
development, 6) restructuring the instructional day to provide additional time for reading
and math, 7) extending learning time for struggling students, 8) creating a collaborative,
professional culture, 9) providing strong instructional leadership, and 10) sharing best
practices and consulting the research on effective instructional techniques.
Recurring themes in the literature. A thorough review of these important
studies and meta-analyses reveals recurring themes. Across all schools studied, those that
focused on the critical components of leadership, assessment and data-based decision
HIGH SCHOOL EDUCATIONAL RESOURCE ALLOCATION 27

making, collaboration, and professional development enjoyed success in terms of meeting
or exceeding their student performance targets. The following is an in depth discussion
of each of these themes and what the research suggests about their influence on school
improvement and student achievement.
Leadership. Much research has been conducted to show the ways in which
leadership influences the operations of successful schools (Marzano et. al, 2005; Bolman
& Deal, 2008; Northouse, 2010; Hallinger & Heck, 2002). The properly channeled
influence of school administrators, teachers, and staff members can shape a positive and
productive school culture which supports ongoing student achievement. Specifically,
school leaders who express a clear vision, set incremental goals, and maintain the focus
on those goals tend to experience success in the form of student achievement (Odden,
2009; Duke, 2006; Togneri& Anderson, 2003; Reeves, 2006). In addition, redefining
leadership roles in new creative ways and involving school staff in shared decision-
making are effective strategies for creating a culture of staff engagement, which in turn
bolsters student achievement (Odden, 2009; Togneri& Anderson, 2003; Darling-
Hammond, 2002). When seeking to effect change in the form of student performance,
the importance of leadership, of both the grass-roots and top-down nature, cannot be
overlooked.
Assessment and data-based decision making. Another component of successful
schools is their focus on the importance of assessment (Black & William, 1998; Baker,
2005) and implementation of data-based decision making (Tilly, 2006; Hamilton et. al,
2009; Datnow et. al, 2007; Williams et. al, 2005). The research shows that schools which
move from purely summative assessment models to models which incorporate more
HIGH SCHOOL EDUCATIONAL RESOURCE ALLOCATION 28

frequent, formative assessments often experience dramatic increases in student
performance (Duke, 2006; Reeves, 2006). In this way, assessment is used as a tool to
inform future teaching and re-teaching rather than simply as an indicator of what was or
was not learned at the conclusion of a lesson or unit. In addition to frequent formative
assessment, schools are also likely to experience gains in student achievement if they
incorporate alternative assessments, such as performance-based or portfolio assessments,
as part of their testing repertoire (Darling-Hammond, 2002). This gives students
opportunities to engage with the material in new ways and to express what they have
learned in nontraditional formats.
The frequent use of formative and alternative assessments provides teachers with
the data they need to make informed decisions about what to teach next, how to change
their instructional approaches, and what to re-teach. Schools that use data, whether
gathered from assessments at the classroom level or from state standardized tests, to
guide the instructional decisions they make tend to experience improvement in student
progress toward meeting performance targets (Odden, 2009; Duke, 2006; Togneri&
Anderson, 2003; Fermanich et. al, 2006). Using data to guide decision-making drives an
ongoing cycle of improvement where assessment data are collected and analyzed,
struggling students are identified and provided with intervention, instruction is changed
in response to overall data trends, and assessment occurs again, retriggering the cycle.
The continuous nature of this system helps schools to resist stagnation as they
consistently reach toward higher levels of student performance. For these reasons,
frequent alternative assessments coupled with data-based decision making are important
strategies for consideration as schools aim to increase student achievement.
HIGH SCHOOL EDUCATIONAL RESOURCE ALLOCATION 29

Collaboration. The research shows that professional collaboration between teams
of teachers is linked to student performance improvements (Bensimon & O’Neil, 1998;
O’Day, 2002; Langer et. al, 2006). Collaboration gives teachers the opportunity to
transcend the isolation of the individual classroom and interact professionally with their
peers (Odden, 2009; Duke, 2006). One form of productive interaction includes the
sharing of best practices, where teachers teaching similar subjects can glean from one
another what works and replicate those practices across classrooms so that more students
are impacted by strong teaching models (Odden, 2006). Another effective use of
collaboration time is to analyze student work, both for the purpose of norming grading
practices and for identifying areas of weakness in student comprehension so that
instruction might be modified accordingly (Reeves, 2003). In terms of the structure of
teacher teams, there is evidence that both subject-specific and interdisciplinary teams can
be effective vehicles for boosting student achievement (Darling-Hammond, 2002). In
subject-specific groups, teachers benefit from the sharing of best practices and
standardizing their instruction and grading. In interdisciplinary teams where teachers
share the same students, teachers have access to holistic information about students such
that they are able to intervene where needed early and often. Professional collaboration
in all of its forms is a useful tool which should be considered by schools seeking to make
positive changes in student achievement.
Professional development. Much research has been conducted regarding the
impacts of professional development (Birman et. al, 2000; Desimone et. al, 2002; Garet
et. al, 2001; Joyce & Showers, 2002; Suppovitz & Turner, 2000). This is due in part to
the fact that effective professional development can change instruction, which in turn can
HIGH SCHOOL EDUCATIONAL RESOURCE ALLOCATION 30

lead to higher levels of student learning. Professional development is needed for the
interpretation of state test data, for exposure to newly adopted curriculums, for the
implementation of new instructional practices, and for interpreting and acting upon
formative assessment data (Odden, 2009). Schools are most successful when they make
professional development a priority in terms of providing both ample time and funding to
carry out a quality, comprehensive program (Darling-Hammond, 2002; Togneri&
Anderson, 2003; Fermanich et. al, 2006; Odden, 2009). Additionally, professional
development programs are most effective when they continue over several years and
require between 100 and 200 hours of training in a single school year (Odden, 2009). It
is also important that professional development be system-wide and connected to district
goals (Togneri& Anderson, 2003) and that there be an expectation for implementation of
the strategies learned (Odden, 2009).
Successful programs are subject matter specific (Odden, 2009). They derive their
content from needs illustrated by the data (Togneri& Anderson, 2003) and impart only
those instructional strategies which are proven by the research to be most effective
(Fermanich et. al, 2006). To keep strategies learned in professional development at the
forefront of a school’s agenda, instructional coaches are critical for mentoring struggling
teachers, modeling sample lessons, and team-teaching core concepts (Togneri&
Anderson, 2003; Fermanich et. al, 2006; Odden, 2009). Coaches ensure the necessary
follow up after training and help to enforce the expectation that instruction will change as
a result of training. Therefore, a school’s reform efforts should include a systematic plan
for professional development along with a follow up component consisting, in part, of the
utilization of instructional coaches.
HIGH SCHOOL EDUCATIONAL RESOURCE ALLOCATION 31

Summary. This section synthesized the research on the practices of effective
schools which have been able to make significant gains in student achievement. The
practices found to recur most often in the literature were the implementation of focused
leadership techniques, the use of frequent, formative, and alternative assessments and
data-based decision making, the formation of subject based and/or interdisciplinary
professional collaboration teams, and the institution of a long-term, ongoing professional
development plan to include the use of instructional coaches for follow up. As the
foundation for examination of schools in this study, this information also provides school
leaders and decision makers with research-based strategies for increasing student
achievement so that they might make sound choices as they determine how to organize
their scarce resources.
Allocation of Human Resources
When schools are aware of which practices are most effective for increasing
student achievement, they can begin to allocate their resources in ways which support
those practices. Unfortunately, this can be a challenging task in times of fiscal stress.
The following is a brief discussion of the fluctuations in education spending that have
occurred over time and how adequacy has been used as a framework for addressing those
fluctuations. Specific properties of the Evidence-based Model (EBM) (Odden & Picus,
2003), the adequacy tool which will provide the conceptual framework for this study, are
also explored.
History of expenditures. Although it is common public perception that
education's fiscal resources have been steadily dwindling over time, schools and districts
are actually working with bigger budgets than ever before. In fact, per pupil spending is
HIGH SCHOOL EDUCATIONAL RESOURCE ALLOCATION 32

up (Odden & Picus, 2008), reflecting a 3.5% increase from 1890 to 1990 (Hanushek &
Rivkin, 1997). During that time, local, state, and federal roles have repeatedly shifted as
changes in policy created new funding ratios. Between 1960 and 1980 the federal share
of education funding rose while the local share continued to drop. Then, in the 1970s and
1980s, the states took the lead as the primary funders of education until the early 1990s
when state and local roles were equalized (Odden et al., 1995) (see Table 1 and Figure 1).
Table 1
Percentage Share of Public School Revenues
Year Federal State Local
1959-60 4.4 39.1 56.5
1969-70 8.0 39.9 52.1
1979-80 9.8 46.8 43.4
1989-90 6.1 47.3 46.6
1990-91 6.2 47.2 46.7
1991-92 6.6 46.4 47.0
1992-93 6.9 46.8 46.3
1993-94 7.0 45.7 47.3
Source: National Center for Education Statistics, Digest of Education Statistics 1994 (Washington, D.C.:
U.S. Department of Education, 1994); and 1993-94 Estimates of School Statistics (Washington, D.C.:
National Education Association, 1994)

HIGH SCHOOL EDUCATIONAL RESOURCE ALLOCATION 33

Figure 1. Percentage Distribution of Revenues for Public Education in the U.S., Fiscal
Year 2006
Changes in resource allocation patterns. To obtain a clear picture of education
funding over time, it is important to learn not only where the funds have come from but
also how they have been spent. Odden and Picus (2008) note that there are six categories
for which nationally reported data on spending patterns exist. They include instruction,
instructional support, student support, administration, operations and maintenance, and
food and transportation. One might reasonably assume that as both per pupil spending
and accountability for student performance have increased over time, changes in
spending patterns across these different categories must have also occurred.
Interestingly, this has not been the case.
Hanaway et al. (2002) performed a study of the data to find out whether
accountability and standards-based reform had any impact on resource allocation patterns
and found that there were few, if any, changes to the ways in which schools and districts
spent their money over time. They found that regardless of changes in state and federal
accountability requirements, schools continued to allocate their resources in the same
HIGH SCHOOL EDUCATIONAL RESOURCE ALLOCATION 34

ways they had always done. Similarly, Odden and Picus (2008) noted that the
percentages of expenditures across each of their six categories have remained relatively
stagnant from 1969 to 2008 (see Table 2).
Table 2
Expenditures by Function for the United States, 1969–2008
Function 1969-70 1979-80 1989-90 1999-2000 2007-2008
Instruction 57.2% 55.5% 53.4% 52.4% 51.7%
Administration 3.9 4.4 7.7 6.6 6.4
Plant operation 6.3 10.2 9.5 8.2 8.3
Plant Maintenance 2.4 * * * *
Fixed Charges 8 12.3 ** ** **
Other School Services 6.3 8.3 17.9 17.7 18.6
Other Current
Expenditures
2.6 0.6 1.4 1.4 1.4
Capital Outlay 11.5 6.8 8.4 11.4 11.0
Interest on School Debt 2.9 2.0 1.8 2.4 2.6
Note: Totals may not equal 100 percent due to rounding.
*: Plant Operation and Plant Maintenance report together.
**: Data not available for Fixed Charges during these years.
Source: National Center for Education Statistics, 2010, Table 183. Retrieved from
nces.ed.gov/programs/digest/d10/tables/dt10_183.asp, on May 7, 2012.

If overall funding has increased and spending patterns have remained the same,
where has the additional money gone? This question is a critical one, not only for
taxpayers to whom local, state, and federal agencies are accountable, but also for leaders
in education who, if made aware of how additional dollars have been spent, can find out
whether those practices have had any impact. In answer to this question, a review of the
research reveals that there are four areas where this pattern of stagnation has been broken
and increased spending has taken place over time. These areas are: 1) teacher salaries, 2)
special education, 3) instructional aides and support staff, and 4) elective teachers. The
following is a short discussion of each of these components with an examination of their
impact on the overall educational program.
HIGH SCHOOL EDUCATIONAL RESOURCE ALLOCATION 35

Teacher salaries. Public perception may hold that teacher salaries are low,
especially when compared to the level of responsibility they shoulder and the amount of
work they are expected to put in to be effective. However, while it is in fact true that the
level of teacher earnings have declined over time when compared to those of other
careers (Hanushek & Rivkin, 1997), it is also true that the cost of teacher salaries in
actual dollars has steadily risen over time (Hanushek & Rivkin, 1997; Odden & Picus,
2008). For this reason, teacher salaries account for a portion of the increase in education
funding that has been spent over time.
Special education. Multiple studies have documented significant increases in
spending on resources and programs for students with special needs (Hanushek & Rivkin,
1997; Odden & Picus, 2008; Monk et al., 1996; Hannaway et al., 1992; Langford &
Wycoff, 1995). This is mainly due to growth in the number of students identified to
receive special education services. To demonstrate, special education students
represented 8.7% of the general school population in 1978 but grew to represent 11.6%
by 1990 (Hanushek & Rivkin, 1997). Reasons for this growth may be explained by the
passage of the Education for All Handicapped Children Act of 1975, which expanded the
offerings of special education programs. Also, the provision of additional categorical
funding for special education students may have inadvertently provided incentives for
over-identification of students to receive these services (Hanushek & Rivkin, 1997).
Since the cost to educate a student with special needs is approximately twice the cost of
educating a general education student, these increases in special education enrollment
account for a significant portion of the expenditures of additional dollars over time.
HIGH SCHOOL EDUCATIONAL RESOURCE ALLOCATION 36

Instructional aides and support staff. Instructional aides are those who assist
teachers with tasks ranging from translation to dissemination of the curriculum to student
discipline, and they are most often found in classrooms which service English learners or
students with special needs. Support staff such as clerks, counselors, and security assist
with the smooth functioning of the school. Hanushek and Rivkin (1997) document a
steady rise in clerical and support staff between 1960 and 1980 and Odden and Picus
(2008) report a similar trend with instructional aides. While an argument can be made
that these positions are non-instructional and therefore only of peripheral significance,
there is also some evidence that these roles take on enhanced importance in communities
with high poverty rates (Hannaway et al., 2002). Either way, the fact remains that dollars
spent on these positions has been on the rise, thereby accounting for a portion of
additional educational expenditures over time.
Elective teachers. Odden and Picus (2008) document that non-core teachers
provide preparation time to elementary teachers and expanded offerings to secondary
students, where they comprise over 50% of the teaching staff. They assert that the
biggest portion of additional per pupil dollars have gone to teachers in these roles. In a
study of New York schools, Monk et al. (1996) also found that more money was spent on
the combination of special education and vocational teachers than was spent on the
teaching of academics. These findings indicate that elective teachers have been the
beneficiaries of a rising trend to allocate additional dollars away from academics.
As a result of the additional spending on teacher salaries, special education,
instructional aides, support staff, and elective teachers, the number of core academic
teachers and their percentage of the overall school staff is on the decline. In terms of the
HIGH SCHOOL EDUCATIONAL RESOURCE ALLOCATION 37

allocation of human resources, emphasis is currently not being placed on the academic
core and student performance is not being considered as a primary factor in hiring and
staff placement decisions (Odden & Picus, 2008; Monk et al., 1996).
Adequacy. When student performance outcomes are not the driving force behind
the allocation of human resources, there is no way to measure whether current spending
practices are effective. For this reason, it is imperative that schools and districts find
ways to reformulate their spending strategies such that they reflect a focus on student
achievement and can be tested for efficiency. The traditional approach to the allocation
of resources considers what an appropriate education should look like and then allocates
accordingly. In other words, the traditional approach is a service delivery model with no
emphasis on learning objectives (Baker, 2005). As discussed in Chapter 1, adequacy is a
departure from the traditional model in that it allows for the organization and
reorganization of resources in support of helping all students meet learning objectives.
This section on adequacy discusses the importance of critically examining fiscal
decision-making systems, the definition of an adequate education, and the findings of
recent adequacy studies.
Examining fiscal systems. Even in an era of high stakes testing and increased
accountability, it appears that schools and districts are still utilizing traditional
approaches to allocate resources. For example, in a study of New York schools that were
identified as either best or worst in the state, Steifel (2004) investigated the relationship
between the schools’ ratings and their resource allocation practices. Not only was there
no relationship between school ratings and spending strategies, but often schools rated as
“worst” were strategic in their spending and schools rated as “best” were inefficient
HIGH SCHOOL EDUCATIONAL RESOURCE ALLOCATION 38

spenders. These findings reflect the lack of strategy behind school and district spending
and resulting haphazard student performance outcomes.
But how do school and district leaders make the leap from traditional resource
allocation models to adequacy models focused on helping all students meet achievement
targets? The research reveals some recommendations for starting this journey. District
and school officials must first choose and employ diagnostic tools for assessing their
current fiscal conditions before they can know what they might like to change.
Examples of such tools include the Financial Condition Indicator System (FCIS)
developed for New York schools (Mead, 2004) or the Evidence-based Model (EBM)
developed for use across seven different states (Odden et al., 2003). These tools aid in
producing a clear picture of a district’s or school’s starting point so that realistic goals
may be set. Additionally, Miller (2004) suggests that districts must measure how
resources are allocated not just at the district level, but also at the site level, pointing out
the disparity between the fact that monies are reported as amounts dispersed to the district
but are mainly spent at the site. Examining site level expenditures is a relevant endeavor
in that it aids in identifying school to school inequities and helps to explain the
relationship between inputs and outputs (Miller, 2004). These initial steps are the
foundation for moving districts from traditional to adequate spending models, as is a solid
understanding of educational adequacy.
Educational adequacy defined. Baker (2005) defines educational adequacy as
the cost of educating all students such that they are enabled to meet performance
standards. Its two components are absolute standards of adequacy and relative standards
of adequacy. Absolute standards describe the overall financial support which is
HIGH SCHOOL EDUCATIONAL RESOURCE ALLOCATION 39

associated with the overall performance of students, while relative standards refer to
differences in the costs of helping students with different needs to achieve the same
performance standards. Baker’s (2005) definition is based on the following six
assumptions: 1) the cost of meeting targets varies depending upon the target, 2) an
adequate education may cost more in smaller districts, 3) adequacy costs vary by student
needs, 4) adequacy costs vary from district to district, 5) student characteristics, district
size, and resource costs have multiplicative effects on the cost of adequacy, and 6) the
cost of adequacy increases and decreases as performance targets increase and decrease.
Baker (2005) also asserts that there are two ways to measure educational
adequacy. One is the Education Cost Function, a top-down model that statistically
estimates the relationship between district spending and student outcomes. The other is
the Resource Cost Model, a bottom-up model that identifies and costs out the set of
inputs that constitute an adequate education. The Resource Cost Model has been the
method widely in use since the 1980s but it is important to note that neither model is free
from error. Because of fluctuation in performance targets and variance in student
populations, there is no absolute answer for what it costs to adequately educate all
students. The cost of an adequate education is an estimate that is district-specific and is
always in flux.
Adequacy studies. Because of the elusive nature of adequacy, several researchers
have taken on the task of examining what it costs to adequately educate students in
California’s schools. Sonstelie (2007) recruited 568 randomly selected public school
teachers, principals, and superintendents to simulate ideal resource allocation practices
that were then compared to existing practices. Findings were that 40% more funding
HIGH SCHOOL EDUCATIONAL RESOURCE ALLOCATION 40

would be required to help students meet achievement targets and most of it would need to
go to schools in low socioeconomic communities. Imazeki (2006) also examined the cost
of an adequate education by utilizing a statistical method to analyze per pupil spending,
student performance, and student characteristics across all districts in the state. The study
found that districts would need an additional $1.7 to $5.7 billion to achieve performance
standards and that these costs are partially a result of the additional needs of students
qualifying for free or reduced lunch and special education students.
In 2005, the Governor’s Committee on Education Excellence requested a series of
adequacy studies which it entitled the “Getting Down to Facts” studies. In one of these
studies, Perez (2007) compared 103 high performing schools with 113 low performing
schools and found that higher performing schools did not necessarily receive more money
but allocated the money they did receive differently than the low performing schools.
They had lower class sizes in Kindergarten, a higher percentage of staff in administrative
positions and a lower percentage of staff in pupil support positions. Another “Getting
Down to Facts” study conducted by Chambers (2007) used a professional judgment
approach to find that districts in California in 2004 would have needed an additional
$24.14 to $32.01 billion to adequately educate all students, a 53 to 71% increase over
actual allocations in 2004.
What these studies have in common is their suggestion that additional funding is
needed in California to ensure that all students meet performance targets. What some of
them also share is the susceptibility to bias in terms of the nature of their design. For
example, findings from the professional judgment studies were a result of the opinions of
panelists and recommendations may or may not have been reflective of strategies proven
HIGH SCHOOL EDUCATIONAL RESOURCE ALLOCATION 41

by research to be effective (Sonstelie, 2007; Chambers, 2007). As an alternative to the
methodologies of these studies, the next section will examine the Evidence-based Model
and its potential for the strategic estimating of adequacy in California schools.
Evidence-Based Model. The Evidence-based Model (EBM) looks exclusively at
school improvement strategies that have been shown by the research to be most effective
in raising student achievement. It recommends resource allocation and reallocation
patterns which support the full utilization of those specific strategies. The EBM is an
expenditure structure developed by Odden et al., (2003) which allows for the close
examination of school level spending. Items in the structure are drawn from research on
high performing schools and the structure reflects a commitment to the core subjects and
to supporting the learning of all students in those subjects. Thus, the EBM is
characterized by minimal time spent in low-level and elective classes, especially at the
high school level.
The EBM has been used in seven states to estimate the cost of educational
adequacy (Picus & Odden, 2009). Elements of the EBM include smaller class sizes in
core subjects and specialist teachers for art, music and physical education who provide
planning time for other teachers. The EBM also includes strategies for helping struggling
learners and returning them quickly to the core curriculum as well as resources for
professional development to include instructional coaches, summer workshops, the hiring
of experts, and options for conference travel. Resources for distinct programs like special
education, gifted and talented, and career and technical education are provided for in the
EBM as are resources for school and district administration, and for maintenance and
operations costs (see Figure 2)
HIGH SCHOOL EDUCATIONAL RESOURCE ALLOCATION 42

Figure 2. Elements of the Evidence-Based Model. Borrowed from Odden and Picus,
2009.
Rooted in the principles of the EBM, Odden, Goetz, and Picus (2007) have
developed prototypes for elementary, middle, and high schools which detail the needed
level of resources, based on a standard level of enrollment, to help schools provide an
adequate education for all students. These prototypes can serve as guides for schools
who wish to compare existing spending patterns with those suggested by the EMB
prototypes (See Table 3).

HIGH SCHOOL EDUCATIONAL RESOURCE ALLOCATION 43

Table 3
Recommendations for Adequate Resources for Prototypical Elementary, Middle and High
Schools
School Element Elementary
Schools
Middle Schools High Schools
School Characteristics
School configuration K-5 6-8 9-12
Prototypical school size 432 450 600
Class size K-3: 15
4-5: 25
6-8: 25 9-12: 25
Full-day kindergarten Yes NA NA
Number of teacher work
days
190 teacher work
days, so an increase
of 5 days
190 teacher work
days, so an increase
of 5 days
190 teacher work
days, so an increase
of 5 days
Percent of students with
disabilities
13.7% 13.7% 13.7%
Percent poverty (free
and reduced price lunch)
36.3% 36.3% 36.3%
Percent ELL 10.6% 10.6% 10.6%
Personnel Resources
1. Core teachers 24 18 24
2. Specialist teachers 20% more assuming
a 6 period day with
each FTE teaching 5
periods:
4.8
20% more assuming
a 6 period day with
each FTE teaching 5
periods:
3.6
20% more assuming
a 6 period day with
each FTE teaching 5
periods:
8.0
3. Instructional
facilitators/coaches
1/200: 2.2 1/200 students: 2.25 1/200 students 3.0
4. Tutors for struggling
students
1/100 poverty
students: 1.57
1/100 poverty
students: 1.63
1/100 poverty
students: 2.18
5. Teachers for ELL
students
An additional 1
teacher/100 ELL
students:
0.46
An additional 1
teacher/100 ELL
students:
0.48
An additional 1
teacher/100 ELL
students:
0.64
6. Extended day 1.31 1.36 1.74
7. Summer school 1.31 1.36 1.74
8. Students with mild
disabilities
Additional 3
professional teacher
positions and 0.5
aides for each
special education
teacher.
Additional 3
professional teacher
positions and 0.5
aides for each
special education
teacher.
Additional 4
professional teacher
positions and 0.5
aides for each
special education
teacher.
9. Students with severe
disabilities
100% state
reimbursement
minus federal funds
100% state
reimbursement
minus federal funds
100% state
reimbursement
minus federal funds

HIGH SCHOOL EDUCATIONAL RESOURCE ALLOCATION 44

Table 3, continued
10. Resources for
gifted/talented
students
$25/student $25/student $25 student
11. Substitutes 10 days/FTE 10 days/FTE 10 days/FTE
12. Pupil support staff 1/100 poverty
students: 1.32
1/100 poverty
students plus 1
guidance/250
students: 3.18 total
1/100 poverty
students plus 1
guidance/250
students: 4.25
13. Supervisory aides 2 2 3
14. Librarians/media
specialists
1 1 1 librarian
1library technician
15. Principal 1 1 1
16. School site secretary 1 secretary and
1 clerical
1 secretary and
1 clerical
1 secretary and
1 clerical
Dollar per Pupil
Resources

17. Professional
development
Included above:
Instructional
facilitators
10 summer days.
Additional:
$100/pupil for other
PD expenses-
trainers,
conferences, travel,
etc.
Included above:
Instructional
facilitators
10 summer days.
Additional:
$100/pupil for other
PD expenses-
trainers, conferences,
travel, etc.
Included above:
Instructional
facilitators
10 summer days.
Additional:
$100/pupil for other
PD expenses-
trainers,
conferences, travel,
etc.
18. Technology and
equipment
$250/pupil $250/pupil $250/pupil
19. Instructional
materials, including
textbooks, formative
assessments
$165/pupil $165/pupil $200/pupil
20. Student activities $250/pupil $250/pupil $250/pupil
Other Expenditures
21. Operations and
maintenance
$890/pupil $890/pupil $890/pupil
22. Transportation $375/pupil $375/pupil $375/pupil
23. Food services Self supporting Self supporting Self supporting
Borrowed and adapted from Odden, Goetz and Picus, 2007.
Because the EBM recommends only research-based school improvement
strategies and explicitly links those strategies to school spending, it has served as the
conceptual framework for this study. Chapter 3 discusses how the EBM was utilized to
measure current spending levels and to propose alternatives for resource allocation.
HIGH SCHOOL EDUCATIONAL RESOURCE ALLOCATION 45

Effects of Fiscal Crisis on Education in California
Utilization of a strategic fiscal model like the EBM is more important than ever as
California’s schools continue their financial struggle through the current recession. As
state and national resources continue to dwindle, a thoughtful approach to the allocation
of those resources is vital. The economic reality facing the nation has been deemed a
“fiscal emergency” by Superintendent of Public Instruction Tom Torlakson who pointed
out that the last three years of budget cuts have left 30% of our nation’s students
attending schools facing serious financial jeopardy (EdSource, 2011). These districts are
either already experiencing the effects of large scale debt or are preparing for impending
revenue cuts which will encumber them with new debt. Additional cuts to education
funding may render many of them unable to provide even the most basic educational
services that the public has come to expect from its schools.
As the financial atmosphere has worsened, accountability requirements for
student achievement have increased. Under the No Child Left Behind Act, schools are
expected to steadily improve student achievement each year, culminating in a goal of
100% proficiency by the year 2014. Though this may seem a daunting task, districts
have undertaken the work of implementing NCLB’s standards, partly because
compliance is tied to Title I funding which districts desperately need in light of the
current fiscal climate. Though Title I funding comprises only 3% of the education
budget, it is still a motivating factor when so many are struggling to stay afloat. This is
demonstrated by the fact that no state has chosen to resist compliance and thus forfeit
funding even though an argument can be made that the accountability demands are
unrealistic at best (EdSource 2005). The next section of this literature review provides an
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overview of the recent history of school finance in California and describes the ways in
which the federal and state governments have responded to the current fiscal crisis.
California school finance overview. Three events in California’s recent past
have played a part in contributing to the economic predicament it now faces. They are
the Serrano v. Priest I and II court decisions of 1971 and 1976, the passage of
Proposition 13 in 1978, and the passage of Proposition 98 in 1988. What follows is a
brief description of each event, to include an explanation of their individual influences on
California’s current fiscal state.
Serrano v priest. Prior to the Serrano v. Priest decision of 1971, local districts set
their own property tax rates and used that income as their main funding source for
schools. The constitutionality of that practice was challenged when the court ruled for
the plaintiff in Serrano v. Priest, asserting that the practice of funding schools primarily
through property taxes perpetuated inequities across communities of differing
socioeconomic privilege and thus violated the “equal protection” clause of the
constitution (EdSource, 2009). As a result, districts were no longer be able to rely
primarily on property taxes for funding, and Senate Bill (SB) 90 was passed to impose a
revenue limit system placing a ceiling on the amount of income districts could raise
through property taxes.
This crippling of the existing system led to a shift from local to state sources as
the primary funders of education. While the intent of this shift was to equalize funding
across districts, ascertaining the measurable positive effects of Serrano v. Priest is
problematic given the complex nature of state education funding. For example,
approximately 40% of state monies were dispersed to districts in the form of categorical
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funding which only allowed for allocation toward specified programs, students, or
materials (EdSource, 2009). Since Serrano v. Priest’s requirements did not apply to
categorical funds, only roughly 60% of state education monies were subject to the
mandates intended to equalize spending across districts, leaving little assurance that those
mandates actually fulfilled their purpose.
Proposition 13. The trend of scrutinizing property taxes and their financial
contribution to education continued with the passage of Proposition 13 in 1978.
Proposition 13’s provisions set the property tax rate at 1% of assessed value and capped
the amount by which it could increase to 2% or the percentage of growth in the state’s
Consumer Price Index, whichever was lower. Though property tax revenues had already
been reduced with the passage of SB 90 after the Serrano v. Priest ruling, Proposition 13
further dropped those revenues by almost half, thus requiring additional state aid in the
form of income and sales taxes just to help fund schools to the revenue limit.
The effects of Proposition 13 were felt both in schools and in communities at
large. While Californians experienced the responsibility of funding schools through their
income and sales tax contributions, school and district leaders simultaneously
experienced a new lack of control over the receipt and allocation of funds in their own
schools. Since about 59% of monies for education were now produced by the state’s
general fund, school boards, district and school leaders were no longer the major
decision-makers in terms of expenditures in their own districts and schools (EdSource,
2009). Proposition 13’s limitations on revenue growth were reflected in the decline of
California’s investment in education compared to the national average. In 2005-2006,
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California’s per pupil allocation was $614 below the national average and its schools
were, and continue to be, subject to the state’s often volatile budgetary processes.
Proposition 98. With the aim of improving education’s worsening financial
condition in California, Proposition 98 was passed in 1988. Proposition 98 proposed a
revised system for education funding, and it is still the state’s fiscal system in use today.
Proposition 98 guarantees a minimum amount of per pupil funding that is to be generated
by both state and property taxes. This minimum level is used to calculate the Average
Daily Attendance rate (ADA) by multiplying enrollment by the per pupil minimum to
arrive at the minimum guaranteed funding level for schools and districts. Districts
receive 72% of their total funding from Proposition 98 (see Figure 3). Under this system
approximately 70% of district funding can be spent as needed while 30% of district and
school funding is restricted or categorical in nature, only to be spent on categories as
specified by the state (see Figure 4).

Figure 3. California’s Education Revenue System, Fiscal Year 2008
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Figure 4. Percentage of District Revenues by Funding Type as of 2010
Under Proposition 98, if districts fall below their minimum guaranteed funding
levels, the state is required to make up the difference. Proposition 98 only determines the
funding amounts that must be allocated to K-14 districts; it is at the discretion of the
governor and the legislature to choose how those amounts actually get allocated to
districts (Timar, 2006). In the current fiscal crisis, districts have found themselves being
expected to operate with less than their minimum guaranteed funding levels as it has
become customary for the state to miss its promised deadlines for disbursement. Many
districts are also finding themselves in dire straits as they struggle to deal with mid-year
budget cuts that may have been unanticipated (EdSource, 2009).
This is not to assert that the financial quandaries of schools and districts have
gone completely ignored by government agencies. To the contrary, both federal and state
governments have attempted to implement intervention programs designed to reduce the
amount of fiscal stress placed on districts by the current recession. What follows is a
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description of these federal and state programs along with a discussion of their
effectiveness in alleviating some of the pressure districts are currently facing.
Federal response to fiscal crisis. In response to the national fiscal crisis,
President Obama signed the American Recovery and Reinvestment Act (AARA) in 2009,
commonly termed “the stimulus package.” This act boosted federal spending by over
$800 billion and provided tax cuts meant to encourage additional spending to jumpstart
the economy. Over $100 billion of these monies went to education, which made it the
largest one-time increase ever allotted to education (Mead et al., 2010). The intention
was that monies would be used to save teachers’ jobs and supplement districts’ gaping
budget deficits.
Accompanying this new legislation was a school reform agenda which included
advancement in each of four areas: implementing standards and assessments aimed at
producing career and college-ready students, increasing teacher effectiveness, creating
data systems equipped to track students from preschool to college, and reforming
consistently low performing schools. This reform agenda, driven by incentives rather
than mandates, was carried out through the State Fiscal Stabilization Fund (SFSF), a
division of the AARA which allotted $48.6 billion to states in order to backfill state
budget deficits in the areas of public education and government services. States that
committed to taking immediate action in each of the four reform areas were allotted one-
time stimulus funds which were given directly to districts to be spent at the local level.
While the money allocated to states and districts through AARA and its SFSF
fund provided some relief, it was not as effective as was originally envisioned. One
problem with AARA was a function of its design: it featured the competing goals of short
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term monies for a promise of long term reform (Mead et al., 2010). Additionally, though
the funds were enough to make up for immediate budget shortfalls in many states, they
weren’t enough to allow states to plan for fiscal longevity; the one-time monies mostly
allowed states to maintain the status quo (Roza, 2010). For this reason, many states used
the funds received through AARA and SFSF to manipulate their own education funding
formulas, supplanting rather than supplementing existing funding with the new monies
from AARA. This explains why 75% of the largest urban districts in the nation reported
that AARA funds were insufficient in compensating for state and local budget cuts
(Center of Education Policy, 2010).
State level response to fiscal crisis. In addition to attempts made by the federal
government to alleviate financial strain, the state also made an effort to reduce the burden
the fiscal crisis placed on California’s schools. It instituted policy changes in six
different areas aimed at providing districts with short-term relief from budget deficits.
They were: 1) increased flexibility in funding, 2) flexibility with class size reduction, 3)
waivers from instructional materials adoptions, 4) reductions in the number of school
days, 5) flexibility in the funding of maintenance projects, and 6) flexibility in financial
reserves requirements. None of these changes produced new money, but rather allowed
districts to use existing money in new ways to help maintain minimal district-level
operations with less revenue. The following sections describe each of these six policy
changes and their impact on districts’ ability to cope with the fiscal crisis.
Funding flexibility. In order to allow districts the financial creativity they needed
to keep schools open as budgets dwindled, the state approved increased flexibility of
funding originally intended for categorical programs in exchange for additional cuts
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(Weston, 2011; Shambaugh et al., 2011). This initiative, which began in 2008 and will
expire in 2013, allowed the monies generated by 39 categorical grant programs such as
school safety, libraries, technology, and music to be swept into the general fund so that it
could be used for any needed purposes (California Education Code 42605). The fact that
this flexibility was granted in exchange for new cuts, some as large as 20% in 2007-2008,
suggests that it did little to remediate districts’ financial struggles but served instead to
keep districts operating at the most basic level (Weston, 2011).
Class size reduction flexibility. Under the assumption that smaller class sizes
promote student achievement, California has offered funding incentives to districts with
reduced class sizes since 1996. 98% of districts have taken advantage of this incentive by
reducing their class sizes to less than 20 students in kindergarten through third grade
(CDE, 2009). To provide relief to struggling districts, California’s budget compromise
allowed districts to continue to receive funding for class size reduction without meeting
the 20 student requirement up until 2013. For example, a district could still receive 70%
of its class size reduction funding with K-3 classes over 25 students. This helped districts
absorb some of its losses in the short term.
Instructional materials adoptions. In California, new instructional materials and
textbooks are required to be adopted every three to four years in an effort to assure that
students are taught the most current and relevant content in each subject area. Part of the
state’s budget compromise included the forgiveness of the materials adoption
requirement until 2013, allowing districts the opportunity to funnel money that might
otherwise have been spent on textbooks into other areas which they determined may be
more critical (California Education Code 60200.7).
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Reduction of school days. Up until 2007, California’s requirement for the
amount of time students must spend in school was 180 days (California Education Code
46200). To lessen the fiscal burden on districts, policymakers reduced this number by
five in 2008. This meant that districts could now close their doors for five more days
each school year, saving money on both staffing and operating costs. In most districts,
these five days became furlough days where teachers took a reduction in salary in the
form of five unpaid days off work. The challenge with this particular budgetary
compromise was the fact that districts had to negotiate with teachers’ unions to
implement it, which was a smooth process in some districts but difficult in others
(EdSource, 2011).
Funding of maintenance projects. Prior to 2009, California required districts to
use between 1% and 3% of its funds for maintenance to include such items as roofing,
plumbing, heating, air and electrical systems. The state would then match that amount
dollar-for-dollar (Shambaugh et al., 2011). To lessen the financial pressure on districts,
California removed this requirement in 2009, still contributing to districts’ maintenance
funds without expecting districts to match their share.
Financial reserves requirements. Traditionally, California required districts to
maintain a reserve account where, depending upon district size, they were expected to
save between 1% and 5% of their overall budget (California Education Code 33128.3).
However, in 2009 California revised this expectation and reduced the amount previously
required by two-thirds, such that a district that used to reserve 3% of their revenues
would only need to reserve 1% under this new change. This allowed districts the ability
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to spend down some of their reserves and utilize them to cope with losses in revenue due
to the fiscal crisis.
Summary. Though they did not reverse or remediate fiscal problems, most of
these budgetary compromises provided a degree of short-term relief to school districts in
California. As a result, most districts have been able to cover, if only by a small margin,
basic operating costs where some of them may have otherwise failed. However, given
the state’s history of fiscal practices and the impending likelihood of additional cuts to
funding, it is unclear how much longer districts will be able to tread water. California is
likely to remain a bottom state in terms of per pupil funding, and given that likelihood,
strategic resource allocation may very well become the deciding factor in the future
health of schools and districts. It is therefore crucial for districts to make sacrifices and
tradeoffs, prioritizing their staffing, services, and programs in ways that both cut costs
and promote student achievement.
Gap Analysis
Districts can start the process of resource reallocation by obtaining a clear picture
of their fiscal status quo, and then determining what changes are needed to meet future
goals. This portion of the chapter reviews the literature on gap analysis, the genre of
methodology that will be utilized in this study to measure the distance between ideal and
actual spending patterns. A rationale for utilizing gap analysis is presented in the
discussion of methodology in Chapter 3. In this chapter, a description of gap analysis to
include its processes and analysis structures is presented.
In this study, differences between current district spending patterns, district ideals,
and spending patterns proposed by the EBM were measured and analyzed using gap
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analysis. Gap analysis is a conceptual tool designed to increase the effectiveness of
systems within organizations. It determines which human influences are contributing to
differences between desired and actual performance, and then proposes solutions
appropriate to the particular causes of those differences (Clark & Estes, 2002). The gap
analysis utilized in this study allowed the researcher to propose solutions for resource
reallocation that directly addressed the causes of problematic spending patterns.
Clark and Estes (2002) developed gap analysis as a tool for helping businesses
improve their effectiveness. Their process consists of six steps: 1) Identifying key
business goals, 2) identifying individual performance goals, 3) determining performance
gaps, 4) analyzing gaps to determine causes, 5) identifying and implementing appropriate
solutions, and 6) evaluating the results to tune the system and revise goals as needed.
What follows is a discussion of each of these steps.
Identify key business goals. Identifying key business goals occurs at the level of
the organization as a whole and is akin to setting and clarifying mission or vision
statements. This means each member of the business team understands the direction that
the company is heading and understands his or her own contribution to that overarching
goal. It is important that these goals be both relevant and flexible such that they can be
changed as needed to meet day-to-day demands.
Identify individual performance goals. Once all members of a team are clear
on the direction an organization is moving, they must then understand how their own
individual contributions influence that momentum. They must have an understanding of
the specific expectations for the role they play in advancing the company’s mission.
Clark and Estes (2002) assert that individual performance goals must be concrete,
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challenging, and current in order for each employee to fully realize their potential and
maximize their contribution to the organization.
Determine Performance Gaps. According to Clark and Estes (2002), an
organization can begin determining its performance gaps by first specifying desired
performance levels, which can be done by either examining existing goals or by
benchmarking the industry leader’s performance. Next, current performance must be
quantified and then subtracted from the goal or benchmark. Finally, clear and specific
team and individual objectives that will close the gap must be set and communicated.
Analyze gaps to determine causes. Once an organization has determined how
big the gaps are between desired and actual performance, it can begin to diagnose the
causes of those gaps with the aim of choosing pertinent effective solutions. Clarke and
Estes (2002) assert that gaps between desired and actual performance are a result of a
lack of knowledge or skills, a lack of motivation, the existence of organizational barriers,
or the combination of any of these three deficits.
Knowledge and skills. Sometimes people do not fulfill performance goals simply
because they lack the knowledge and/or skills needed to meet those goals. Often in these
cases they are unaware of their knowledge or skill deficits, making the importance of
timely and specific feedback paramount. Knowledge and skill deficits can sometimes be
identified by their tendency to accompany poor communication and the withholding of
information. Similarly, poor performance of a similar task in the recent past may indicate
an insufficient level of knowledge or skills to be able to execute the next task with
success.
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Motivation. Another potential cause of performance gaps is a lack of motivation.
People who are capable of accomplishing a task may deliberately choose not to if they
don’t believe it is valuable. Unlike gaps caused by knowledge or skill deficits,
motivation-based gaps are more difficult to diagnose. As well, a lack of motivation has
adverse effects on critical work processes like choosing to work toward a particular goal,
persisting in the face of adversity, and putting forth significant mental effort to
accomplish the goal.
Organizational barriers. Organizational barriers are work-related processes,
bureaucratic structures, or resource deficiencies that stand in the way of the completion of
a work task. When motivation and knowledge/skills are ruled out as contributors to a
performance gap, organizational barriers are often the cause. Organizational barriers are
a result of misalignment between an organization’s systems and its goals, as when the
formalities required for completion of a task stand in direct opposition to the goal of
completing that task efficiently and successfully.
Identify and implement solutions. Once the causes of the performance gaps
have been assessed, appropriate solutions should be selected and put into action.
Categorizing the causes of each gap is crucial because there are no “one size fits all”
solutions for performance problems. Solutions must directly address the root causes of
the problem, and Clark and Estes (2002) recommend separate solutions for
knowledge/skill gaps, motivation gaps, and organizational barriers.
Solutions for closing knowledge and skill gaps. Clark and Estes (2002)
recommend four types of possible solutions for intervention when team members lack the
knowledge or skills to complete a task or reach a goal. They are information, job aids,
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training, and education. Giving information consists of simply illuminating facts that
may have been otherwise unknown but which may have an impact on the
accomplishment of the task. Job aids are more sophisticated than information in that they
guide an individual toward the appropriate completion of a task, like in the case of a
rubric or checklist. Training is appropriate when one needs to learn how to do
something, and it should include opportunities for practice and feedback. Education is
required when people need to learn how to be strategic problem-solvers across a range of
situations and it should not consist of “how to” information. Instead, it should be
comprised of current, research-based theoretical information about emerging patterns in
practice or why things happen the way they do.
Solutions for closing motivation gaps. Motivation for the performance of any
given task is a fusion of experience and beliefs about oneself, one’s coworkers, and one’s
potential for actually being successful. Motivation exists when a person chooses to take
on a task, persists at the task through difficulties, and exerts substantial mental effort in
the process (Clark & Estes, 2002). Solutions to motivation-based problems include
helping people develop confidence in themselves and in their team, being alert and
removing perceived organizational barriers, creating a positive emotional work
environment, and suggesting reasons and values for performance tasks.
Solutions for organizational barriers. When people are knowledgeable and
motivated to execute a task but are still unable to be successful, the culprit is often an
organizational barrier. Often people are aware of these barriers and can articulate exactly
what they are. For this reason, removing organizational barriers involves maintaining
close relationships with team members and keeping lines of communication open to
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become aware of which organizational barriers are impeding success. It also involves
spending the necessary time and effort to change policy, restructure a bureaucracy, or
acquire resources that people need to complete their performance tasks efficiently and
successfully.
Evaluate Results. After the appropriate solutions for closing performance gaps
have been identified and implemented, it is important to find out whether those solutions
are, in fact, effective. This final step of a gap analysis involves measuring the results of
the solutions that have been put into practice to determine not only whether they have
solved the initial problem but also whether they have proven to be cost effective. Once a
judgment is made regarding the effectiveness of implemented solutions, revisions to
company goals should be made to reflect either a continuance of these new solutions or a
redirection in favor of trying a new set of solutions. Evaluation is a critical component
of gap analysis as it is the only way for organizations to continually improve.
Summary
The preceding literature review provided the foundation for this study by
synthesizing the existing research in four key areas. First, what is known about strategies
for increasing student achievement was summarized in order to shed light on how those
strategies may or may not inform the work being done by schools in this study. Then,
human resource allocation practices were explored, revealing snapshots of how monies
allocated for these resources have been spent over time and ultimately providing
perspective for the spending patterns which have been discovered and analyzed in this
study. Also, the literature on recent state and federal policy changes was discussed in
order to establish the fiscal context from which this study emerges. Finally, gap analysis
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was introduced and surveyed as the methodological tool which was used in this study to
compare actual spending patterns with more desirable ones. The next chapter explores
the methodology of this study, featuring specific details regarding how the study was
organized and executed.

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Chapter 3: Methodology
This chapter provides a description of the methodology of this study, including
the research questions, design of the study, sample and population, instrumentation, data
collection and processes for data analysis. The purpose of the study was to inform policy
makers as well as school and district leaders of the extent to which current resource
allocation patterns support effective school improvement strategies. School and district
level data was examined to identify gaps between existing spending patterns and what
has been proposed by the Evidence Based Model (EBM) (Odden et al., 2003).
Recommendations for reallocation of resources are proposed to ensure that resources are
used efficiently in an effort to give all students the opportunity to meet achievement
targets.
Overview of Methodology
This was a multi-method study of five comprehensive high schools and three
alternative high schools within a single suburban school district in Southern California.
Both numerical and qualitative data was gathered for analysis. The numerical data
consisted of actual expenditures in various categories at both the district and individual
school levels. The qualitative data told the story of how those expenditures are actually
utilized in practice. This multi-method approach was appropriate because it allowed for
the analysis of expenditure data while simultaneously examining the human impact of
those dollars within and across schools.

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Research Questions
This study sought answers to the following research questions:
 What research-based human resource allocation strategies improve student
achievement?
 How are human resources allocated across the sample school district?
 Is there a gap between current resource allocation strategies and research
based and desired district allocations?
 How can resources be reallocated to align with strategies that improve student
achievement?
Sample and Population
The subject of this study was a school district in California that had been selected
as a finalist for the 2012 Broad Prize for Urban Education. The Eli and Edythe Broad
Foundation selects American school districts as finalists for this award based on evidence
of gains in student achievement for traditionally underrepresented populations. This
district is a purposive and critical sample and was selected because it is both high
achieving and located in an urban community, thus having the potential to inform reform
efforts in school districts with similar demographics. Additionally, the 2012 Broad
Foundation finalist status may increase the likelihood of this study’s utility, in that policy
makers as well as school leaders who are interested in the practices of a district that has
earned such an honor will likely find the results and recommendations presented useful.
The chosen district is located in Southern California and as of 2011 its
demographic data reflects a population of 50% Hispanic, 31% White, 7% Asian, 6%
Black, 3% Filipino, less than 1% Pacific Islander, American Indian, and two or more
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races, and 2% unreported (California Department of Education, 2012). It consists of 31
elementary schools, eight middle schools, five comprehensive high schools, and three
alternative high schools. At just over 53,000 students, it is the largest district in its
county and the tenth largest district in the state of California (retrieved from district
website, 2012). At the time the study was conducted, the chief researcher was employed
in the district, and the design of the study reflects methodologies which facilitated
objectivity as described in the Data Collection and Data Analysis sections of this chapter.
The study specifically examined the district’s high schools with the aim of
comparing actual spending patterns with ideal patterns as envisioned by district personnel
as well as with those proposed by the Evidence-based Model. The district’s high schools
consisted of five comprehensive schools and three smaller alternative schools. For the
2010-2011 school year, enrollments at the traditional, comprehensive high schools ranged
from 2,195 to 3,767 students and their ratings on the Academic Performance Index (API)
ranged from 758 to 799. The 2010 graduation rates at these schools ranged from 92.4%
to 97.1% and the A-G college eligibility rates ranged from 46.4% to 60.2% (California
Department of Education, 2012).
In terms of the district’s three alternative high schools, one is a middle college
program, one provides opportunities for credit recovery, and one provides placement
options for disciplinary infractions. Their 2010-2011 enrollments ranged from 215 to
846 students with APIs ranging from 419 to 834. Their 2010 graduation rates ranged
from 19.7% to 98.1% and their A-G college eligibility rates ranged from 0% to 50%
(California Department of Education, 2012).

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Instrumentation and Data Collection
This study began with an informal meeting with the district’s superintendent
where authorization for conducting the research was obtained. Next, a training session
took place where the researcher received expert instruction on the creation of interview
protocols, data analysis techniques, and case study preparation. Additionally, the Internal
Review Board was consulted for approval of the methodology and the study was
exempted from the IRB process. Plans for instrumentation were made with the goal of
obtaining valid answers to the research questions by triangulating the collected data. To
that end, the three primary forms of data collected for this study were: 1) numerical data
on staffing ratios, 2) school and district documents, and 3) data gathered in interviews.
Numerical data. A quantitative data collection strategic budgeting tool was used
to collect information on the allocation of school staff across all high schools in the
district. This tool was developed as an extension of successful adequacy studies that have
been conducted in various states (see for example Odden, Picus, et al., 2008). It was
chosen as the framework for this portion of the study’s methodologies because, as was
discussed in the literature review, it reflects a strategic plan for improving student
achievement. To collect data for input into the strategic budgeting tool, the assistant
superintendent of business services was contacted and asked to provide a detailed list of
staff and student characteristics across the high school sites in the district. To the extent
that was possible, each staff member’s role was aligned with the definitive roles
established by the budgeting tool. The following information was entered into the
database:

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 Enrollment data by grade
 Student demographic data, to include participation in special programs
 Class sizes
 Staff roles, to include instructional aides, specialist teachers, instructional
coaches, tutors, LEP teachers, special education teachers, special education aids,
librarians, library technicians, pupil support staff, principals, assistant principals,
and secretaries
 Information about extended day programs
 Information about summer school programs
 Fiscal data about expenditures in the form of technology, instructional materials,
assessment, student activities, professional development, substitutes, and teacher
compensation
Once actual allocations based on these categories were entered into the budgeting tool’s
database, comparisons were generated between the actual allocations, the district’s
desired allocations, and those allocations recommended by the EBM.
Documents. Specific school and district documents were collected and analyzed
to determine whether current allocation patterns aligned with the district mission and
vision and to identify potential areas for reorganization of resources to better support
student achievement. The 2011-2012 budget, plans for professional development, and
mission and vision statements were collected at the district level. At the school level,
Single Plans for Student Achievement, School Accountability Report Cards, mission and
vision statements, master schedules, staff rosters, and school budgets were collected.
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Interviews. To tell the story of spending patterns and how those relate to the
district’s spending goals, interviews were conducted with district office and some school
staff. The first interview was conducted with the assistant superintendent of Business
Services. The interview questions sought to gain insight on the district’s instructional
priorities and the extent to which resource allocation patterns are aligned to those
priorities. In addition to interviewing the assistant superintendent of Business Services,
there was also a need to interview school site assistant principals to gain perspective on
how individual school sites further allocate the resources apportioned to them. The
questions for these interviews concentrated on topics such as curriculum focus,
definitions of effective teaching, professional development, intervention, instructional
leadership and accountability. Once all interviews were conducted and field notes taken,
interview data was summarized and written into a case study for further analysis.
These three data collection methods were chosen because they lent themselves to
answering this study’s research questions, specifically providing the researcher with
information about the sample district’s current resource allocation patterns and what gaps
exist between those patterns, the district ideal, and the EBM’s proposals. One further
reason for choosing to collect numerical data and data from school and district documents
is the potential for painting a clear and objective picture of the sample district’s fiscal
reality. Once collected, this data was combined with the interview data and analyzed as
described in the next section of this chapter.
Data Analysis
Collected data was analyzed to generate information that assisted in answering
each of this study’s four research questions. This section details which specific
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conceptual approaches and data analysis techniques were utilized. It is organized in the
order of the study’s four research questions.
First research question. The first research question asked which research-based
human resource allocation strategies improve student achievement. To answer this
question, the Evidence Based Model was reviewed and employed as a conceptual model
for examining resource allocation patterns across the sample district.
Second research question. The next research question asked how resources are
allocated across the sample district. A strategic budgeting tool served as the structure for
determining into which particular categories the staff members at each school were
arranged, ultimately generating a comprehensive listing of staffing positions at each
school. Interview data and data generated from school site master schedules were also
examined to glean additional information about staffing patterns and to corroborate the
data generated from the strategic budgeting tool.
Third research question. The third research question was answered by utilizing
gap analysis (Clarke & Estes, 2008) as a conceptual framework. Gap analysis is a
theoretical tool for identifying gaps between current performance and performance goals,
and it attributes the reasons for those gaps to one of three categories: 1) lack of
knowledge, 2) lack of skill, or 3) lack of motivation. The third research question for this
study focused on whether there are gaps between current resource allocation patterns and
the district ideal as well as those proposed by the EBM. Use of Clark and Estes’
framework not only helped to identify the magnitude of those gaps, but it will also
assigned causes to the gaps, allowing the researcher to better propose recommendations
for future reorganization of fiscal resources.
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To illuminate gaps, the strategic budgeting tool was programmed to make
automatic comparisons of current spending, district ideal spending, and spending deemed
most efficient by the EBM. This was performed utilizing the formulas in the strategic
budgeting tool’s database. Then school site plan data, district and school mission and
vision statements, and interview data was analyzed to substantiate or disprove the
numerical gaps illuminated by the strategic budgeting tool.
Fourth research question. To answer the last research question about how
resources can be reallocated to align with strategies that improve student achievement,
the researcher studied the nature of the gaps between current allocations, district ideals,
and the EBM to determine areas of weakness in spending as they relate to student
achievement. In response, spending tradeoffs are proposed which both close the gaps
between current practices and the district’s ideal practices as well as those practices
deemed most effective by the EBM.
Summary
This chapter provided an overview of the methodology of this study and it
outlined the four research questions this study answered. The chapter also provided a
description of the study’s sample district and its population and included the specifics on
the data collection process. Each type of data collected and analyzed was discussed and
reasons for selecting those particular data types were provided. Lastly, the conceptual
frameworks and methodological tools for data analysis were presented. The findings of
this study are delineated in the next chapter.

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Chapter 4: Study Results
This chapter reports the study’s findings. An overview of the study’s sample
district is included and each of the study’s research questions is addressed individually.
Those questions are:
 What research-based human resource allocation strategies improve student
achievement?
 How are human resources allocated across the sample school district?
 Is there a gap between current resource allocation strategies and research-based
and desired district allocations?
 How can resources be reallocated to align with strategies that improve student
achievement?
Results for each research question are analyzed and contributing causes are discussed.
Overview of the District
This study examined only the high schools, both comprehensive and alternative,
from the sample district. This section provides information about the demographics,
achievement, and funding conditions for these schools in order to give context to the
study’s findings.
Demographics. The sample district is located in Southern California, serves
53,000 students, and is comprised of 31 elementary schools, eight middle schools, five
comprehensive high schools, and three alternative high schools. The comprehensive high
schools average 4% English Learners, 3% Special Education students, and 42% of
students qualifying for the Free or Reduced Lunch program (see Table 4).

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Table 4
Demographics for Comprehensive High Schools in Sample District
Grade Level ELL SPED FARL
High School
# Total 9 10 11 12 # % # % # %
1 3318 870 832 785 831 13 0.4% 89 2.7% 1370 41.3%
2 3041 872 773 644 752 211 6.9% 108 3.6% 1518 49.9%
3 3107 795 814 706 792 286 9.2% 126 4.1% 1756 56.5%
4 2179 614 571 471 523 90 4.1% 87 4.0% 814 37.4%
5 3683 956 929 887 911 81 2.2% 79 2.1% 977 26.5%
Subtotal for
High Schools 15328 4107 3919 3493 3809 681 4% 489 3% 6435 42%

The alternative high schools represent a range of student service options: the first
provides credit recovery, the second provides a middle college option, and the third
provides behavior intervention. Demographic averages for these schools are 10%
English Learners, 4% Special Education students, and 49% of students qualifying for the
Free or Reduced Lunch program (see Table 5). It should be noted that one reason for the
low percentage of Special Education students (most schools average 10%) is the
existence of a separate school for students with severe disabilities. Because the school
services students of all ages it is not included in this study.
Table 5
Demographics for Alternative High Schools in Sample District
Grade Level ELL SPED FARL
Alternative School # Total 9 10 11 12 # % # % # %
6 611 0 130 201 280 11 1.8% 55 9.0% 190 31.1%
7 903 10 30 362 501 104 11.5% 7 0.8% 512 56.7%
8 218 34 54 76 54 55 25.2% 13 6.0% 139 63.8%
Subtotal for
Alternative Schools 1732 44 214 639 835 170 10% 75 4% 841 49%

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Student achievement. The study’s sample district was nominated for the Broad
Prize in Education in 2011-2012 because of its steady improvement in student
achievement results over time and its success in narrowing the achievement gap. Though
this honor reflects the district’s work as a whole, the high schools have been instrumental
in maintaining an academic focus and forward momentum in the area of student
achievement. In terms of the California state accountability system, during the 2011-
2012 school year the comprehensive high schools averaged an Annual Performance
Index score of 797 while the alternative high schools averaged a score of 646. In the last
three years, the comprehensive high schools have seen an average positive gain of 30.2
points on this scale while the alternative schools have averaged a 50 point gain in that
same period of time. In terms of closing the achievement gap, the district average growth
for its ethnic and socio-economic subgroups in its comprehensive high schools over a
three year period has been between 25.8 and 46.8 points, and the alternative high schools
have experienced even larger gains over three years with their at-risk populations. In
terms of federal accountability, only one school of the eight high schools was able to
meet its Annual Yearly Progress (AYP) target in 2011-2012 (see Tables 4.3 and 4.4).

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Table 6
Student Achievement Data for Comprehensive High Schools

Table 7
Student Achievement Data for Alternative High Schools

Funding conditions. Between the 2007-2008 and 2011-2012 school years, the
sample district cut over $90 million from its budget. This manifested itself in the form of
353 lost jobs and a 5% pay cut across the board. Additionally, students go to school five
fewer days than they did prior to 2007, and teachers and support staff have taken a total
of nine furlough days to offset cuts. Because of high costs, bus transportation has been
virtually done away with as has transportation to and from games for some sports teams.
Additionally, many programs such as science fairs, history days, and spelling bees have
3 Year Growth Over Time: Subgroups
High
School #
2012
Met
AYP
?
API
2010
API
2011
API
201
2
3 Year
Change
African-
America
n Hispanic
English
Learners
Student
s with
Disabili
ties
Socio-
economically
disadvantage
d
1 N 767 798 812 +45 +78 +53 +52 +123 +53
2 N 772 793 806 +34 +22 +35 +9 +56 +22
3 N 757 758 769 +12 +15 +12 +10 -7 +12
4 N 749 771 789 +40 +41 +39 +34 +48 +52
5 N 789 799 809 +20 +32 +22 +24 +14 +44
Average
All
Schools N 766.8 783.8 797 +30.2 +37.6 +32.2 +25.8 +46.8 +36.6
3 Year Growth Over Time: Subgroups
Alternative
School #
2012
Met
AYP?
API
2010
API
2011
API
2012
3 Year
Change
African-
American Hispanic
English
Learners
Students
with
Disabilities
Socio-
economically
Disadvantaged
6 Y 787 864 866 +79 +63 +89 +225 N/A* +78
7 N 575 625 640 +65 +103 +66 +10 +232 +54
8 N 426 419 432 +6 N/A* +1 -123 N/A* +1
Average
All Schools N 596 636 646 +50 +83 +52 +37.3 +232 +44.3
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become unpaid events for participating staff and have thus been reduced or eliminated
(Straehley, 2011).
Some schools within the sample district are experiencing thinner budgets than
others. Though the current budget crisis affects districts on the whole, districts do have
some flexibility in how they allocate per-school funding. The sample district has chosen
to extend the 60% Free and Reduced Lunch funding cutoff to 43%, making up this gap
by supplementing Title I funds with non-Title I sources such as Investing in Innovation
(i3) grants, Economic Impact Aid (EIA) funds and State Compensatory Education (SCE)
funding. Thus, all schools at or above 43% Free and Reduced Lunch participation
receive funding at Title I levels even though they are technically not considered Title I
schools (B. Taylor, personal communication, September 3, 2012). For schools between
43% and 60% Free and Reduced Lunch participation, the funds currently being used to
supplement Title I are those that would have otherwise been divided amongst all schools,
including those with lower Free and Reduced Lunch populations. This commitment to
schools with higher at-risk populations comes at a price to schools with less at-risk
students, inadvertently creating an equity gap between schools that fall above and below
the 43% dividing line. As a result, schools in more affluent neighborhoods are struggling
for resources, while their sister schools in less affluent neighborhoods are more than
equipped with the resources they need.
This description of the sample district’s demographics, student achievement levels
and funding conditions is meant to supply important background information to assist
with interpretation of the answers to this study’s research questions. These questions and
the study’s findings are explored in the next section of this chapter.
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Research Question #1: What Research-based Human Resource Allocation Strategies
Improve Student Achievement?
This section of the study revisits the strategies reviewed in chapter two, all of
which have been found by this study to improve student achievement. The link between
each strategy and related human resource allocation practices is explicated and a
description of the ways in which the sample district is or is not implementing each
strategy is included.
Leadership. Research shows a link between student achievement and specific
leadership practices such as articulation of vision, goal setting, shared decision making,
and creative redefinition of leadership roles. Human resource allocation strategies which
support a district’s capability to execute these practices include hiring a highly qualified
administrative staff who have experience and a natural inclination for implementing these
higher level leadership practices, as well as hiring adequate numbers of staff such that the
focus can be maintained and daily managerial duties do not usurp the importance of the
organization’s vision and goals. Also, providing professional development, both for
administrative staff and for teachers, on how to increase opportunities for teachers to take
on leadership positions and be included in decision-making increase a district’s capacity
for empowering its teachers and staff.
The sample district employs some of these important leadership strategies but also
shows room for growth. For example, district leadership utilizes a multi-step process
when hiring new administrators or moving existing administrators from site to site. The
comprehensive process places priority on matching administrators’ skills and talents with
the needs of the site, ensuring that each school is equipped with an administrative staff
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that will project a vision and set site goals. To make sure that all administrators are
versed in communicating that vision and setting goals, the district not only provides
professional development on vision and goal setting, but it also employs an evaluation
system which requires each administrator to draft a mission statement and set personal
goals for which they are held accountable.
The sample district’s room for growth lies in the areas of teacher empowerment
and creative redefinition of leadership roles. For example, although teachers who lead
small collaborative groups which the district terms Professional Learning Communities
(PLCs) have received three days’ worth of professional development to hone their
leadership skills, the training has not been ongoing and there is no system in place to
check for implementation of the strategies learned. Additionally, the training is the only
one of its type and teachers who function as PLC leaders are the only staff members
eligible to take advantage of it. The only other formalized teacher leadership role
occurring in the sample district at the high school level is the position of department
chair, which comes with a small stipend, no release time, and no training. Without
guidance or specific performance expectations, this is a teacher leadership position whose
potential to make a difference in terms of student achievement remains largely untapped.
The need for ongoing professional development with built-in accountability for
implementation of learned strategies is one that keeps all types of teacher leaders from
reaching their capacity for impacting student achievement.
Assessment and data-based decision making. This study’s research shows that
practices such as using formative assessment to inform teaching and re-teaching,
implementing alternative assessments, identifying struggling students early for the
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purposes of intervention, and adjusting instruction to address trends in student
performance data help to boost student achievement. Resource allocation strategies
which support the implementation of these practices include investing in a user friendly
student data information system, funding the development of district-wide formative
assessments, and prioritizing intervention staff which can work with students during the
school day with the aim of swiftly returning them to the regular instructional program.
The sample district has devoted time and resources to creating district-wide
assessments in the core subject areas of math, English language arts, science, and social
science. Teachers were recruited for subject-specific curriculum committees that
examined district pacing guides and created shared assessments. For science those
assessments are given at the high school level quarterly and science teachers have the
opportunity to collaborate often to review their results and plan accordingly. However,
math, English language arts, and social science teachers only give assessments at the end
of each semester, which makes those assessments more summative than formative in
nature and leaves those teachers with the need for establishing their own formative
assessment systems at the school site or even at the PLC team level.
To assist teachers with this kind of work and to report important information to
students and parents, the sample district has invested in two programs for tracking data.
It purchased Data Director to house and report student data as it relates to performance on
both formative and summative assessments, and Zangle to house and report data on
student grades. While both programs offer a range of services, neither are intuitive
enough for users to easily find and extract the data they need without training. Though
the district has offered implementation workshops for small groups as requested by
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school sites, it has not made the financial commitment to ongoing, extensive district-wide
training. As a result, teacher access to data varies from school to school depending on
each site’s approach and prioritization of the process of pulling, interpreting, and acting
on student data. Thus, rather than being systematic district-wide, data informs instruction
in pockets across the district’s eight high schools.
Because of this lack of systemized identification of struggling students through
analysis of formative assessments, many are identified as struggling only after they have
completed their final, summative assessments at the end of the school year. Accordingly,
the district’s high schools have prioritized credit recovery options like summer school
programs and online course repetition opportunities. If the district were able to satisfy its
need for ease of use of reporting, inputting, and analyzing formative assessment data, it
could then redirect remediation resources toward one-on-one and small group in-school
intervention options for students who are struggling at the moment they are identified.
Those students could be supported for a short period of time and returned to the regular
instructional program, decreasing the number of students who ultimately fail and require
remediation at the end of the term.
Collaboration. Another practice research suggests boosts student achievement is
professional collaboration in the form of sharing best practices, analyzing student work,
norming grading systems, and standardizing instructional strategies. In terms of resource
allocation, the biggest contribution a district can make to collaboration efforts is through
freeing up chunks of time within the contracted school day specifically for the purposes
of collaboration. This can be done by either extending the school year or by adding a
small block of time to each teaching day.
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The sample district has prioritized collaboration by adjusting its calendar such
that every high school has time set aside for collaboration on either a biweekly or
monthly basis. To ensure the productivity of collaborative groups, the district has sent
almost all of its teachers to receive training in the DuFour model for Professional
Learning Communities (PLCs) (DuFour, 2004). Even after this training, however,
collaboration efforts often look different from site to site, and even sometimes from
group to group within the same site. This can be attributed to the lack of a system-wide
framework for expected outcomes and accountability. Since the district has already made
a substantial initial commitment to teacher collaboration by setting aside time and
providing training, the next steps should include the development and standardization of
expectations as well as an articulated method for holding teachers accountable for work
accomplished in collaborative groups. These additions to the existing collaboration
structure would not require the expenditure of near as many resources as the district’s
initial investment but would have the potential to make substantial improvements in the
district’s student achievement levels.
Professional development. The final element suggested by this research to
enhance student achievement is professional development that causes teachers to adjust
and improve their instruction. Professional development is needed for interpreting and
acting on data, as well as for implementing new instructional practices. The most
successful professional development programs are those that unfold over several years
and that include an expectation for implementation. Instructional coaches play a critical
role in the success of professional development programs by mentoring struggling
teachers, modeling lessons, team-teaching, and reinforcing the expectation for
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implementation of newly learned strategies. Resource allocation structures which allow
for the execution of successful professional development programs include setting aside
release time for trainings, providing substitute teachers as needed, and hiring instructional
coaches.
The sample district’s professional development strategy for the high school level
consists of the provision of a menu of options so that every school may customize
professional development to meet its own needs. Some high school principals, depending
upon the school’s level of focus on a single professional development initiative, develop
walk through tools which reflect the ideals of the school’s particular focus area in order
to provide teachers with feedback regarding the extent to which the school’s focus
strategies are observable in teachers’ classrooms.
These walk through tools, however, are non-evaluative in nature. In addition,
much of the professional development offered to high school teachers is voluntary, so
that often there is no common language among staff since not all have been trained in a
given professional development program. Additionally, the district does not employ
instructional coaches at the high school level so teachers who do attend training and
decide to implement what they have learned have no classroom level support when they
encounter obstacles. To expect its professional development programs to actually
improve instruction and boost student achievement, the sample district would need to
focus on one professional development initiative district-wide, require all teachers to be
trained, hire instructional coaches for support, and incorporate a check for
implementation of learned strategies into the teacher evaluation instrument. Enacting
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these steps gives teachers the incentive to change their existing instructional practices
with the end goal of raising student achievement.
Summary: Research Question #1. This study’s first research question asked
which research-based human resource allocation strategies improve student achievement.
In answer to this question, this section has demonstrated that leadership, assessment and
data-based decision making, collaboration, and professional development all have
significant impacts on student achievement. Accordingly, the sample district has been
shown to allocate resources in each of these four areas, though room for growth in each
area has also been identified. Most notably, the district’s growth areas include the need
for investment in professional development to train teacher leaders and to help staff pull,
interpret, and act on assessment data. Additionally, there is a need for an investment in
human resources in the form of intervention specialist positions and instructional
coaching positions at the high school level. Acting on these suggestions by spending
additional monies on professional development and new staffing positions may seem next
to impossible given the current climate for education funding in California. However,
this does not mean that these suggestions are out of the question. The remainder of this
chapter will discuss current resource allocation patterns and how trade-offs can be made
which would allow for some or all of these recommendations to be put into practice.
Research Question #2: How are Human Resources Allocated across the Sample
School District?
This section of the chapter examines how human resources are distributed across
the eight high schools in the sample district. Staffing trends are reported for
management, certificated teaching staff, certificated staff providing adjunct or specialized
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services, pupil support, and classified staff. Definitions are provided for each individual
position as characterized by the Evidence-based model (EBM) (Odden, Picus, & Goetz,
2010) and, in cases where the sample district utilizes or defines positions differently than
the EBM, an explanation is also provided.
Management. Management consists of each school’s principals and assistant
principals. Principals bear the chief responsibility for running the school and assistant
principals support the principal by managing site responsibilities, disciplining students,
and monitoring instruction. Assistant principals who do not fit this description are those
that oversee activities by managing the Associated Student Body (ASB) group and those
that function as athletic directors. The sample district has eight high school principals
and 32 high school assistant principals, with 10 of those 32 individuals functioning as
either activities or athletics directors. Every high school has one principal and assistant
principals are allocated based on enrollment. The average ratio of students to assistant
principals in the sample district is 533 to one (see Table 8).
Table 8
Management Staff, All High Schools
High School Enrollment Principals Assistant Principals
1 3318 1.00 6.00
2 3041 1.00 6.00
3 3107 1.00 6.00
4 2179 1.00 4.00
5 3683 1.00 7.00
6 611 1.00 1.00
7 903 1.00 1.00
8 218 1.00 1.00
Total 17060 8.00 32.00
Average per
Site 2132.5 1.00 4.00
Student Ratio N/A 2133 : 1 533 : 1
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Certificated teaching staff. This section reports the sample district's staffing
information for core teachers, specialist teachers, special education teachers, and teachers
of English language learners.
Core teachers. Core teachers are those who teach in the academic areas of math,
English language arts, social studies, science, and world languages. Teachers at the high
school level often teach more than one subject, and it is not uncommon for a teacher’s
caseload to consist of both core and non-core (such as elective or co-curricular) courses.
During the data collection phase of this study, cases like these were counted as portions
of a whole. For example, a teacher who teaches math for eighty percent of his day and
coaches track for twenty percent is counted as eight tenths of a core teaching position and
2 tenths as a specialist.
The sample district has 395.4 core teachers spread across its eight high schools,
with a ratio of approximately one core teacher for every 43 students. Approximately one
hour of time is built into each core teacher’s schedule daily for the purposes of
preparation and instructional planning. The exception to this rule occurs at the two high
schools that run on block schedules. At these schools core teachers receive 1.5 to two
hours of preparation time every other day. Core teachers make up 62% of certificated
teaching staff in the sample district (see Table 9).
Specialist teachers. Specialist teachers are those that teach courses outside of the
five core subject areas. Often referred to as elective teachers, these individuals
commonly teach courses in the areas of art, music, physical education, career-technical
education, or co-curricular activities. The sample district has 174.1 specialist teachers
across its eight high schools, with an average ratio of 98 students to every specialist
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teacher. Specialists make up 27% of the certificated teaching staff in the sample district
and, like core teachers, they receive an average of one hour of preparation time per day
(see Table 9).
Special education teachers. Special education teachers are those that teach
students with documented disabilities and provide accommodations and modifications for
students based on their Individual Education Plans (IEPs). These teachers are often
assisted by instructional aides who can work one-on-one with students or with students in
small groups as needed. In the sample district, there are 64.8 special education teachers
at the high school level. For every one special education teacher there are 263 regular
education students and 3.7 special education students.
Unlike core and specialist teachers, special education teachers receive double the
amount of preparation and planning time. They average two hours of release time per
day, and the district’s rationale for this additional time is to provide ample opportunity
for holding meetings with parents, completing paperwork, and monitoring caseloads of
students. In the sample district, special education teachers make up 10% of all teachers
(see Table 9).
English learner teachers. English learner (EL) teachers are those that provide
instruction in English as a second language. EL teachers are often assisted by
instructional aides who can provide translation of content to students in large and small
groups. In the sample district, there are 3.4 EL teachers at the high school level. In terms
of student-teacher ratio, there are 5,018 regular education and 355 EL students to every
EL teacher. Like core and specialist teachers, EL teachers receive an average of one hour
of preparation and planning time per day, with the exception of one EL coordinating
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teacher at each school site who may receive an additional one to two hours per day for
running the school’s EL program. EL teachers make up .5% of the district’s overall high
school teaching staff (see Table 9).
Table 9
Certificated Teaching Staff, All High Schools
High School Core Specialist Special Ed EL
1 79.00 29.00 11.60 1.20
2 75.20 29.60 11.20 0.60
3 74.60 35.20 13.00 0.60
4 47.20 27.00 9.40 0.40
5 84.20 38.00 9.60 0.40
6 12.88 4.05 5.00 0.00
7 16.59 7.88 3.00 0.20
8 5.70 3.40 2.00 0.00
Total 395.37 174.13 64.80 3.40
% of
Teaching
Staff 62.0% 27.3% 10.2% 0.5%
Average per
Site 49.42 21.77 8.1 0.425
Student
Ratio 43 : 1 98 : 1 263 : 1 5018 : 1

Certificated staff providing adjunct or specialized services. This sections
reports information as it relates to those teachers who support students’ academic
achievement by providing services outside the context of traditional classroom
instruction. These teachers include instructional coaches, academic extra help staff,
librarians, and extended day and summer school staff.
Instructional coaches. Instructional coaches provide in-class coaching to
teachers who need support with the implementation of professional development
strategies. They can model lessons in their own or a colleague’s classroom, observe a
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colleague’s teaching and provide feedback, or team-teach lessons with colleagues, all
with the aim of assisting in the incorporation and regularization of new instructional
practices.
The sample district makes little use of instructional coaches at the high school
level. District-wide there are only 2.4 instructional coach positions, two of which are
employed by the district to go out to all eight high schools and .4 of which has been
established by one high school which releases a teacher for two periods, raising class
sizes in other teachers’ classrooms (see Table 10). This .4 of a coaching position is not
supported through funding by the district.
Academic extra help staff. Academic extra help staff consists of those teachers
who function as tutors, intervention specialists, or reading teachers for struggling
students. Instead of teaching traditional classes during the school day, they work with
students one-on-one or in small groups to remediate gaps in their learning. Academic
extra help staff members often execute their work through a pull-out model where
students are removed from their general program to receive targeted instruction, and then
promptly returned to their regular schedule.
The sample district has 7.8 academic extra help staff members district-wide at the
high school level, which averages out to almost one full time staff member providing
these services at each high school, or one for every 2,184 students (see Table 10). The
most common intervention provided by this type of staff in the sample district is
remediation of basic skills in preparation for the California High School Exit Exam
(CAHSEE). Passage of this test is required by the state in order to receive a high school
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diploma, and targets for intervention include those students whom the data suggest are at
risk of failing the exam.
Librarians. Librarians are certificated staff members who do not teach classes
but instead are assigned to maintain and facilitate the functioning of the school’s library.
They maintain the school’s card cataloguing system and train teachers and students on
library research techniques. In the sample district, there are 1.8 librarians district-wide at
the high school level and this is because librarian positions have been cut and all eight of
the sample district’s librarians have been returned to the classroom (see Table 10). There
are two high schools, however, which have chosen to keep their librarians by way of
raising class sizes in all other teachers’ classes and absorbing the librarians’ resulting
release periods into the school’s master schedule. This site-level choice is not fiscally
supported by district administration.
Extended day and summer school staff. Extended day teachers are those who
teach programs or tutor after school in order to provide additional academic support to
struggling students. Summer school teachers are those who do the same but do so in the
summer months when school is out of session, always for the purposes of remediation.
In the sample district, high school summer school teachers teach the same curriculum
they do during the school year to students who performed poorly in the subject the first
time, giving them another opportunity at a passing grade and the accompanying
graduation credits. The sample district typically offers a summer school program at three
of its eight high schools, and the students who attend the other five schools are expected
to arrange transportation to attend. There is less than one extended day staff member in
the sample district at the high school level and there are 127 summer school staff
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members. When adjusted based on number of actual teaching hours, this number is
equivalent to 14.5 full time teachers (see Table 10).
Table 10
Certificated Staffing: Adjunct or Specialized Services, All High Schools
High
School
Instructional
Coaches
Extra
Help
Staff Librarians
Extended
Day
Summer
School
1 2.00 1.00 1.00 0.24 3.77
2 0.00 1.00 0.00 0.21 0.00
3 0.00 1.00 0.00 0.15 5.83
4 0.00 1.50 0.00 0.00 0.00
5 0.40 1.00 0.80 0.23 4.91
6 0.00 1.47 0.00 0.00 0.00
7 0.00 0.84 0.00 0.02 0.00
8 0.00 0.00 0.00 0.00 0.00
Total 2.40 7.81 1.80 0.85 14.5
Average
per Site 0.30 0.98 0.23 0.11 1.81
Student
Ratio 7108 : 1 2184 : 1 9478 : 1 17060 : 1 1177 : 1

Certificated pupil support staff. This section reports staffing data at the sample
district for certificated positions that provide non-academic support for students.
Included in this category are school nurses, guidance counselors, and school
psychologists.
School nurses. Nurses provide health care to sick or injured students and their
expertise is relied upon in times of health emergencies. The sample district has one full
time nurse at the high school level district-wide (see Table 11). The amount of time the
nurse spends at a given high school site averages two to three hours per week. The
sample district has structured this individual’s role such that the main function is to check
in with the school’s health assistant paraprofessional, who administers virtually all of the
HIGH SCHOOL EDUCATIONAL RESOURCE ALLOCATION 88

school’s health care to students. The nurse supports the health assistant paraprofessional
by completing paperwork, providing counsel on specific student cases, and addressing
areas of concern.
Guidance counselors and school psychologists. Guidance counselors are
certificated staff members who provide socio-emotional, academic, and career and
college counseling. School psychologists also provide socio-emotional counseling in
some cases, but their main function in the sample district is to provide eligibility testing
and consultation for special education services. There are 53.7 counselors and school
psychologists across the sample district’s eight high schools, which is an average of one
for every 318 students (see Table 11).
Table 11
Pupil Support Staff, All High Schools
High School Nurses Guidance/ Psych
1 0.20 9.40
2 0.10 9.00
3 0.10 10.40
4 0.10 8.20
5 0.10 12.00
6 0.30 1.53
7 0.00 2.20
8 0.20 1.00
Total 1.10 53.73
Average per Site 0.14 6.72
Student Ratio 15509 : 1 318 : 1

Classified staff. This section reports staffing data for classified staff members.
Included in this group are instructional aides, special education aides, supervisory aides,
library technicians and paraprofessionals, and secretaries and clerks.
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Instructional aides. Instructional aides assist teachers in working with large
groups, small groups, or individual students in either regular classes or classes for
English learners. In the sample district, instructional aides work in English learner
classrooms but are not utilized in regular classrooms. Across the eight high schools in
the sample district, there are 4.4 instructional aides (approximately half an aide per
school site). In terms of student to aide ratios, there are 3,877 regular education students
for every instructional aide and 193 EL students for every aide (see Table 12).
Special education aides. Special education aides provide the same kinds of
services as instructional aides but are utilized exclusively in classrooms servicing special
education students. Depending upon students’ Individualized Education Plans (IEPs),
aides might be contracted to work with one particular student exclusively or with small
groups or whole classrooms as needed. The sample district employs 102.4 special
education aides across its eight high schools. With 241 special education students in the
district at the high school level, the student to aide ratio is one aide for every 2.4 special
education students and one aid for every 167 regular education students (see Table 12).
Supervisory aides. Supervisory aides are those that provide supervision for
students outside of the classroom during non-instructional times like lunch, passing
periods, recess, and before and after school. At the high school level in the sample
district, supervisory aides are referred to as security guards and they work closely with
campus police and assistant principals to monitor student behavior and keep school
campuses safe. The sample district utilizes 43 security guards across its eight high
schools. Their average representation at each high school is 5.4 guards and their student
to guard ratio is one to every 397 students (see Table 12).
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Library technicians and paraprofessionals. Library technicians as those who
keep the school library running by maintaining the library’s technological equipment,
while library paraprofessionals are those who perform general library upkeep tasks
including checking books in and out to students and staff. The sample district has only
one library technician who works at one of the alternative schools which is bookless by
design. This staff member manages a virtual library in a computer lab setting. In
addition, the sample district employs four individuals as library paraprofessionals across
its eight high schools, supplying an average of half a staff member for the purposes of
library upkeep at each high school (see Table 12). Since all but two of the high schools
in the sample district have cut their librarian positions, some schools’ libraries are
without full time staffing and thus unable to keep their doors open all day.
Secretaries and clerks. Secretaries and clerks are those who perform
administrative tasks to support the smooth operations of the school. This includes
standard positions like the school’s secretary, but at the high school level in the sample
district it also includes those who work in special departments such as attendance offices,
registrar’s offices, student services and counseling offices, athletic offices, and career
centers. The sample district employs 89 secretaries and clerks across its eight high
schools, which averages out to approximately 11 such individuals at each school.

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Table 12
Classified Staff, All High Schools
High
School Aides
Special
Ed
Aides Supervisory
Library
Tech.
Library
Paraprof.
Secretaries/
Clerks
1 0.00 13.40 8.00 0.00 0.00 14.00
2 1.60 18.40 8.00 0.00 1.00 14.00
3 1.60 23.00 7.50 0.00 1.00 16.00
4 0.80 18.70 5.00 0.00 0.00 15.00
5 0.00 18.20 7.50 0.00 1.00 18.00
6 0.00 6.40 1.00 1.00 0.00 3.00
7 0.40 2.90 4.00 0.00 1.00 5.00
8 0.00 1.40 2.00 0.00 0.00 4.00
Total 4.40 102.40 43.00 1.00 4.00 89.00
Average
per Site 0.55 12.80 5.38 0.13 0.50 11.13
Student
Ratio 3877 : 1 167 : 1 397 : 1
17060 :
1 4265 : 1 192 : 1

Summary: Research Question #2. This study’s second research question asked
how the sample district allocates human resources. This section of the chapter has
reported staffing information in answer to this question, demonstrating total counts, per
school counts, and student-to-staff ratios for positions under the umbrellas of
management, certificated teaching staff, certificated staff providing adjunct or specialized
services, pupil support, and classified staff. These reported amounts will provide the
foundation for the forthcoming analysis of gaps between the sample district’s staffing
patterns, its desired staffing patterns, and those staffing patterns deemed by the Evidence-
based Model (EBM) to be most effective for increasing student achievement. After the
gap analysis, specific tradeoffs will be proposed with the intent of creating more
alignment than currently exists between the sample district’s actual staffing, its desired
staffing, and staffing as proposed by the EBM.
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Research Question #3: Is there a Gap between Current Resource Allocation
Strategies and Research-Based and Desired District Allocations?
This section of the chapter explores the gaps between the sample district’s current
resource allocation patterns, its desired allocations, and the research-based allocation
strategies proposed by the Evidence-based Model (Odden, Picus, & Goetz, 2010). First
described are the negative gaps, where the EBM proposes more staffing than the sample
district’s current or desired allocations. These are followed by a discussion of positive
gaps, where the sample district is overstaffed in comparison to the staffing allocations
proposed by the EBM. Examination of gaps includes a discussion of potential causes,
utilizing as a framework Clarke and Estes’ (2002) gap analysis structure which attributes
the causes of performance gaps to either a lack of knowledge or skills, a lack of
motivation, or to the existence of organizational barriers.
Negative gaps between current allocations and the EBM. The results of this
study illuminate far more negative than positive gaps between current and desired district
allocations and the allocations proposed by the Evidence-based Model. It should be
noted that this result is not surprising given California’s inadequate per-pupil
expenditures. Currently California has the second largest gap in the nation between its
current per-pupil expenditures and what it would need to spend to fully fund the EBM.
More specifically, California would need to spend an additional $2,814 per pupil per year
in order to staff its schools to the levels suggested by the EBM (Odden, Picus, & Goetz,
2010). For this reason, only the sample district’s largest and most disproportionate
negative gaps between current spending and the EBM’s proposals are the subject of this
gap analysis.
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Certificated teachers. In the sample district, certificated teachers represent the
largest gaps revealed by this study. More specifically, the EBM proposes substantially
more core and special education teachers than the district’s current or desired allocations.
Core teachers represent the largest gap of the study with a difference of 465.2
teachers between current district allocations and those allocations proposed by the EBM.
Evidence of this gap is reflected in the district’s large class sizes. The contractual class
size limit at the high school level is 42 students to one teacher, and most core classes are
within a few students of reaching this maximum limit. Reasons behind this core teacher
shortage emerge when a comparison is made between core teacher gaps and specialist
teacher gaps. Specialist teachers are those who teach elective classes like art or physical
education, and the gap between the current allocation of specialist teachers and those
proposed by the EBM is only 28 teachers across the district (see Table 13). It should be
noted that because of low per pupil funding in California and thus the sample district,
there is no way to fully close either of these gaps. Findings of interest emerge, however,
when the size of the relative gaps are compared. The sample district is currently funding
core teachers at only 46% of the levels proposed by the EBM, while funding specialist
teachers at 86% of the levels proposed by the EBM. Whether deliberately or not, the
district is offering a relative abundance of elective classes, possibly at the expense of
smaller core classes. In terms of Clarke and Estes’ (2002) gap analysis framework, the
core teacher shortage may be due to motivational barriers: the district may feel obligated
to provide ample opportunities for access to the arts, athletics and co-curricular activities,
and may be using this philosophy as the basis for resource allocation across its high
schools. That said, the number of core teachers the district desires to have mirrors the
HIGH SCHOOL EDUCATIONAL RESOURCE ALLOCATION 94

EBM’s recommendation, still suggesting a strong need to reallocate resources in an effort
to narrow this gap.
Special education teachers also demonstrate a sizable gap. The EBM
recommends 37 more special education teachers than the district currently has allocated
at the high school level, though the district’s desired number is roughly the same as its
current allocation (it has 64 special education teachers and desires to have 61) (see Table
13). Hence the district is funding 63% of what the EBM suggests should be allocated
toward special education teachers. It should be noted that one reason for this large gap is
the existence of a separate school for severely handicapped students in the sample district
that pulls special education enrollment numbers away from the eight high schools. This
does not mean, however, that this gap should be ignored, as there may be ways to address
it that don’t require additional spending. In analyzing the causes of the gap, this study
found that special education teachers receive an additional hour of planning time beyond
what is received by core and specialist teachers, indicating that the number of special
education teachers as calculated by actual teaching time is much lower than the number
of actual teachers on site at any given time. The cause of the gap, then, is both
organizational and motivational in nature. Providing the additional planning time creates
an organizational barrier preventing the district from effectively utilizing its existing
staff. As well, the lack of motivation on the part of teachers who are unwilling to give up
the additional time presents a roadblock to closing this gap.

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Table 13
Gap Analysis: High School Certificated Teachers
District Total
Gap Revenue Difference
Position Counts
Current
-
Desired
Current
-
EB
Position
Current -
Desired
Current -
EB Title Current Desired EB Cost

Core
teachers 395.4 860.5 860.5 (465.2) (465.2) $72,800 ($33,865,000) ($33,865,000)
Specialist
teachers 174.1 202.3 202.3 (28.2) (28.2) $72,800 ($2,052,931) ($2,052,931)
SPED
teachers 64.8 61.3 102.2 3.5 (37.4) $72,800 $253,926 ($2,721,749)
* Parentheses in "Gap" and "Revenue Difference" columns indicates current staffing below district desired
levels or EBM
proposals.

Certificated staff providing adjunct or specialized services. There are also
sizable gaps between the number of teachers presently working in non-traditional roles in
the sample district and those numbers proposed by the Evidence-based model. In
particular, the EBM calls for more instructional coaches and academic extra help staff
than what the district currently funds.
Instructional coaches are those who support the implementation of new
instructional strategies by modeling, team-teaching, and providing feedback. The district
only funds 2.4 coaches across all high schools as compared to the EBM’s
recommendation of 76.6 (see Table 14), which means they fund only 3% of the EBM’s
recommendation for instructional coaches. This gap is caused by organizational barriers.
The sample district does not require its high schools to implement a common professional
development focus, but rather offers a variety of professional development options from
which each high school selects one or more to address. Professional development, also,
is mostly voluntary at the high school level. Both of these factors make utilizing a force
of instructional coaches near impossible; not only would such staff have no particular
HIGH SCHOOL EDUCATIONAL RESOURCE ALLOCATION 96

strategies of focus to help teachers implement, but there would also be no accountability
for implementation of those practices. Since the district’s desired number of instructional
coaches is aligned with the number proposed by the EBM, this gap will be in need of
addressing in the next section where trade-offs for resource reallocation are proposed.
Academic extra help staff, or those who function as tutors, intervention
specialists, or reading teachers, represent another gap between the EBM’s
recommendations and the sample district’s allocations. The district has 7.8 staff
members working in this capacity at the high school level district-wide, and the EBM
recommends 64.4, revealing a funding level of only 12% of the amount proposed by the
EBM for academic extra help staff (see Table 14). In terms of reasons for this gap, there
are organizational barriers, knowledge and skill gaps, and possibly motivational causes
that prevent the district from utilizing these types of staff to a higher degree. First, in
terms of full time staff working as academic extra help support, though a structure exists
for employing these staff to assist students who need support to pass the California High
School Exit Exam, administrators may be unaware of other models of intervention. Also,
in terms of part-time academic extra help staff, though two schools have a homeroom
period where teachers act as tutors, not all schools have implemented this model,
suggesting either a lack of motivation or awareness of the benefits of such a model.
Though the sample district does not value academic extra help staff as strongly as does
the EBM (its desired allocations of this staff are 51.5 and the EBM recommends 64.4),
there is still a substantial gap between what the district wants and what it currently
employs (7.8) (see Table 14). Thus, this gap will be addressed when resource allocation
tradeoffs are proposed.
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Table 14
Gap Analysis: High School Certificated Teachers, Adjunct or Specialized Services
District Total
Gap Revenue Difference
Position Counts
Current -
Desired
Current
-
EB
Position
Current -
Desired
Current -
EB Title Current
Desire
d EB Cost

Instructional
coaches 2.4 76.6 76.6 (74.2) (74.2) $72,800 ($5,404,672) ($5,404,672)
Academic extra
help 7.8 51.5 64.4 (43.7) (56.5) $72,800 ($3,179,176) ($4,116,112)
* Parentheses in "Gap" and "Revenue Difference" columns indicates current staffing below district desired
levels or EBM proposals.

Pupil support staff. The final substantial negative gap between the sample
district’s current allocations and those allocations recommended by the EBM is for non-
academic pupil support staff. These are guidance counselors and school psychologists
who support students in areas other than academics. The EBM recommends 125.7 pupil
support staff for the high schools in the sample district and the district actually employs
53.7 such staff, evidencing a current funding level of only 43% of the EBM’s suggested
allocations (see Table 15). The reasons for this gap are motivational in nature as the
district does not demonstrate a drive for building or even sustaining pupil support staff.
Counseling positions district-wide have been cut through attrition since 2006 such that
caseloads hover at 500 students to one counselor, even though the National Standards of
the Counseling Profession recommend caseloads of 250 to one (American School
Counselors Association, 2011). Additionally, many of the attrition cuts have been made
at the elementary level, and elementary counselors have been moved up to the high
school level without formal training for this shift. These facts suggest that the sample
district undervalues the role of school counselors, even though the desired allocations of
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this group are not far removed from what the EBM recommends (104.2 versus 125.7)
(see Table 15).
Table 15
Gap Analysis: High School Pupil Support Staff
District Total
Gap Revenue Difference
Position Counts
Current
- Desired
Current
-
EB
Position
Current -
Desired
Current -
EB Title Current Desired EB Cost

Pupil support 53.7 104.2 125.7 (50.5) (71.9) $72,800 ($3,675,090) ($5,236,650)
* Parentheses in "Gap" and "Revenue Difference" columns indicates current staffing below district desired levels or
EBM proposals.

Positive gaps between current district allocations and the EBM. Though
fewer in number, this study did illuminate some positive gaps where the sample district
actually funds more positions than what the Evidence-based model recommends. These
are findings of interest given the substantial nature of the negative gaps discussed in the
previous section. Positive gaps represent a severe departure from the sample district’s
pattern of underfunding described thus far and therefore illustrate the district’s
commitment to and value of specific position types. These include assistant principals
and special education instructional aides.
Assistant principals. Assistant principals support school principals by managing
the day-to-day operations of schools. The sample district currently allocates 32 assistant
principals across its eight high schools, which is 6.5 or 25% more than is recommended
by the EBM. Even though these numbers are high in comparison to the EBM, the district
still desires to have 4.5 more assistant principals than they currently do (see Table 16).
While staffing schools with so many assistant principals might suggest an allegiance to
the importance of school leadership, one notable cause of this gap is organizational in
HIGH SCHOOL EDUCATIONAL RESOURCE ALLOCATION 99

nature. The structure the district uses to hire its athletic directors who organize the
schools’ sporting programs and activities directors who supervise the schools’ student
leadership programs calls for hiring them as assistant principals. In other words, they are
on the same salary schedule and hold the exact same title and position as traditional
assistant principals. This is not standard practice in all districts; other models include
hiring a part-time teacher who still teaches classes for a portion of the school day or
hiring a teacher on special assignment who is released from teaching completely but is
still paid a teacher’s salary. The sample district currently employs one athletic director
and one activities director at each comprehensive high school for a total of 10 such
positions across the district.
Special education instructional aides. Special education instructional aides assist
teachers in classrooms by working with special education students in small groups or
one-on-one. The sample district has 102.4 of these staff working across its eight high
schools, which is 51.3 or 100% more than what the EBM recommends. Special
education aides represent the larger positive funding gap of this study, with $1,836,779
being spent beyond what the EBM would fund (see Table 16). Interestingly, even though
they fund a significant number over and above what the EBM suggests, the sample
district still desires to fund 20.2 more of these positions. This suggests that the large
positive gap is due to a lack of knowledge and skills. The district may be over assigning
one-on-one aides which, in addition to monetary costs, may also be impeding students’
access to the least restrictive environment. The district may also be unaware of its
potential to function just as efficiently while funding fewer of these positions.

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Table 16
Gap Analysis: High School Positions Overstaffed Compared to EBM
District Total
Gap Revenue Difference
Position Counts
Current
- Desired
Current
-
EB
Position
Current -
Desired
Current -
EB Title Current Desired EB Cost

Assistant
principals 32.0 36.5 25.5 (4.5) 6.5 $104,800 ($476,491) $676,309
SPED aides 102.4 122.6 51.1 (20.2) 51.3 $35,800 ($724,019) $1,836,779
* Parentheses "Gap" and "Revenue Difference" columns indicate current staffing below district desired levels or
EBM proposals.

Summary: Research Question #3. This section has identified key areas of need
in terms of human resource allocations in the sample district. This study demonstrated
severe negative gaps between the sample district’s current allocations and what the EBM
recommends with regard to five position types: core teachers, special education teachers,
instructional coaches, academic extra help staff, and pupil support staff. Together, these
negative gaps represent $51,344,183 that the district would need to spend to fund these
positions at the levels proposed by the EBM. Conversely, the positive gaps created by
overages of assistant principals and special education instructional aides represent
$2,513,088 that the sample district is spending beyond what the EBM would recommend
for these position types. Unfortunately, because of low per pupil funding levels in
California, the negative gaps are far too exorbitant to be closed, or even significantly
narrowed, by reallocating the overages from the positive gaps. However, the next section
illustrates the exercise of addressing the overages and proposing recommendations for
resource reallocation with the aim of bringing the sample district a few steps closer to
aligning its practices more closely with what has been deemed by the research to be most
effective for increasing student achievement.
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Research Question #4: How Can Resources be Reallocated to Align with Strategies
that Improve Student Achievement?
This section proposes tradeoffs that help to narrow key gaps between the sample
district’s current resource allocations and what the Evidence-based Model recommends.
An explanation for how to enact each tradeoff is included, as are recommendations for
organizational restructuring which can assist in closing the gaps without resource
reallocation. The proposed tradeoffs reflect two principles of strategic budgeting that
have been shown by the research to help districts reallocate resources for the betterment
of student achievement (Odden & Picus, forthcoming). They are 1) the importance of
prioritizing first best instruction in the core subject areas and 2) the value of providing
support for struggling students so that they can meet rigorous performance standards.
First best instruction. An examination of the negative gaps between the sample
district’s resource allocation patterns and those recommended by the EBM reveals that
staffing deficits are impeding the district’s ability to improve the delivery of first best
instruction in the core subject areas. More specifically, the district is severely lacking in
its numbers of instructional coaches, core subject area teachers, and special education
teachers. Reallocating resources to increase the number of instructional coaches provides
teachers with support for implementing effective instructional strategies in their
classrooms. Additionally, expanding the number of core and special education teachers
lowers class sizes, allowing teachers to work more closely with each student. This
section proposes that resources be drawn from positive gaps between the EBM’s
recommendations and current allocations in the sample district, and reallocated toward
these staff.
HIGH SCHOOL EDUCATIONAL RESOURCE ALLOCATION 102

More instructional coaches. The district’s current allocation of Special
Education instructional aides is over what the EBM proposes by 51.3 positions, which is
equivalent to roughly 25 teaching positions. The first tradeoff proposal is to reduce 51.3
of these Special Education aides and reinvest the savings into first best instruction in the
form of instructional coaches. It should be noted that the district’s current system for
professional development would also need to be revamped to include a singular focus and
system for implementation accountability. The sample district should hire one
instructional coach per high school who could assist teachers in implementing new
instructional strategies learned. Though this is still far below what the EBM recommends
and the district could optimally benefit from hiring closer to five per site (one coach for
each core subject area), given the shallow nature of overages for reallocation, it is more
fiscally realistic that the district could afford to hire one new instructional coach per site.
Doing so would produce eight new instructional coaching positions across the sample
district’s high schools (see Table 17).
More core teachers. If the previously discussed tradeoff is enacted and 51.3
Special Education instructional aides, or the equivalent of 25 teaching positions, are
reduced while eight instructional coaches are hired, that leaves a positive gap of 17
remaining positions to be reallocated. For this tradeoff, 12 of those positions should be
utilized to hire core teachers who are dispersed across the sample district’s high schools
in the most appropriate manner for reducing class sizes in the core subject areas (see
Table 17).
Another strategy recommended for adding core teachers is to conduct
credentialing analysis to find out which elective teachers are also qualified to teach core
HIGH SCHOOL EDUCATIONAL RESOURCE ALLOCATION 103

courses. The sample district should then place those teachers who can teach both core
and specialty subjects into a full load of core courses, converting its specialist teachers
into core teachers. Since credentialing analysis is not a function of this study, the number
of core teachers the sample district has the potential to acquire this way is unknown and
depends entirely upon the number of teachers holding both credentials. It is likely,
however, that the EBM’s proposed funding for core teachers would still far exceed what
the sample district is fiscally and organizationally capable of gaining through
reallocation, but the aim of these recommendations is to arm the sample district with
practical options it could execute absent new or additional funding.
More special education teachers. Rather than cutting salaries, the tradeoff to
acquire more special education teachers involves reallocating the resource of time. As
discussed previously in this chapter, the special education teachers in the sample district
currently receive two hours of planning and preparation time per day. This stands in
contrast to their peers teaching core and specialty courses who receive only one hour
daily for planning and preparation. The sample district should remove the extra hour,
converting it back into teaching time. Doing so would generate the equivalent of 16
additional special education teaching positions across the district, which would lower
class sizes, allowing teachers to work more closely with the sample district’s special
needs students (see Table 17).
Support for struggling students. Resources also need to be reallocated so that
the sample district can provide proper support to its struggling students, enabling them to
meet rigorous performance standards. Currently, staff deficits are hampering the
district’s ability to accomplish this goal. Specifically, the district needs more academic
HIGH SCHOOL EDUCATIONAL RESOURCE ALLOCATION 104

extra help staff and pupil support staff in the form of guidance counselors. Academic
extra help staff can be used in a formative nature to work with students who are identified
as struggling early on, remediating their skill gaps and then quickly returning them to the
regular instructional program. Guidance counselors can support struggling students by
addressing their non-academic needs which may be prohibiting them from benefiting
from their instructional program. They can also provide an important service to students
and the district by closely monitoring progress toward graduation and college eligibility.
This section proposes that resources be reallocated such that these staff are increased and
prioritized, giving students in the sample district a better chance at unfettered access to a
rigorous instructional program.
Academic extra help staff. Should the previous tradeoff recommendation of
reducing 51.3 special education instructional aides and hiring eight instructional coaches
and 12 core teachers be fulfilled, then the remaining savings from reducing the aides
would equate to five teaching positions. This proposed tradeoff involves reallocating
those five positions toward academic extra help staff, giving each comprehensive high
school in the district one such staff member (see Table 17). The rationale for excluding
the alternative schools from this opportunity is twofold. First, their enrollments are much
lower and their class sizes much smaller, suggesting the possibility of a lower level of
need for external intervention than what is demonstrated by their comprehensive peers.
Second, because of the creative and flexible nature of master scheduling at the alternative
schools, they may be more apt to take advantage of the next recommendation, which
involves gaining academic extra help by way of utilizing existing teachers.
HIGH SCHOOL EDUCATIONAL RESOURCE ALLOCATION 105

The next proposed tradeoff for increasing academic extra help staff involves the
trading of time as opposed to salaries. This recommendation converts every teacher into
academic extra help for a portion of the school day by restructuring the bell schedule to
include a homeroom period where intervention can occur. The sample district currently
has two such schools utilizing this model, but would benefit from spreading this
methodology to its other sites. Should the previous recommendation of hiring academic
extra help at the comprehensive sites come to fruition, this strategy would be ideal for
adding extra help at the alternative schools without increasing spending. Both of these
tradeoffs ensure that struggling students are identified and given extra help early and
often so that they have every opportunity to meet their academic potential. Enacted
together, they still do not allow the sample district to close the gap between current
practices and the EBM’s recommendations, but they are feasible and practical ways for
the district to begin to address and narrow the gap.
Pupil support staff: guidance counselors. One discrepancy between the sample
district’s allocations and those proposed by the EBM is the district’s overage of assistant
principals, due in part to the fact that athletic and activities directors are included in this
category. A recommended tradeoff to acquire more guidance counselors entails
converting athletic and activities directors to teachers’ salaries and spending the savings
on counselors. Given that the sample district has 10 athletic and activities directors, the
revenue generated by transitioning these to the equivalent of teaching positions would
equate to roughly four additional guidance positions (see Table 17). Therefore, the
sample district should hire these guidance counselors and distribute them in ways to
either lower caseloads or to work specifically with at-risk students.
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Table 17
High School Tradeoff Summary
Position
Position
Cost Tradeoff Type
Number
cut/added Savings
CUTS
SpEd Instructional Aides $35,800 Position Reduction 51.3 $1,836,540
SpEd Teachers $72,800
Convert 1 hour planning
time 16 $1,164,800
Assistant Principals $104,800
Transition Activities &
Athletics to teacher salary 10 $320,000
Total Savings $3,321,340
TRADES
Instructional Coaches $72,800 New Hires 8 $582,400
Core Teachers $72,800 New Hires 12 $873,600
SpEd Teachers $72,800 Additional teaching periods 16 $1,164,800
Academic Extra Help $72,800 New Hires 5 $364,000
Guidance Counselors $72,800 New Hires 4 $291,200
Total Expenditures $3,276,000

Summary: Research Question #4. Enacting these proposed tradeoffs would not
only bring the district’s spending patterns into closer alignment with the research-based
recommendations of the Evidence-based Model, but it would maximize the effectiveness
of the district’s first best instruction and its ability to intervene on behalf of at risk
students. Trading special education instructional aides and athletic and activities assistant
principals for instructional coaches, core teachers, academic extra help staff, and
guidance counselors puts the district in a position for increasing student achievement
without increasing spending. Additionally, making structural changes such as adding a
homeroom period to the school day and putting special education teachers back into the
classroom during planning time gives students the attention and support they need to be
successful while costing the sample district no additional revenue.

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Summary
This chapter revealed the results of this study, beginning first with an overview of
the sample district’s demographics and student achievement data and then answering
each of the study’s four research questions. The sample district’s current resource
allocation patterns were examined, as were the gaps between those existing patterns, the
district’s desired patterns, and the proposed patterns of the Evidence-based Model. Areas
of positive gap, where the district spends more than the EBM recommends, were utilized
to propose reallocation tradeoffs to close negative gaps, where the district spends far less
than what the EBM proposes. The next chapter will address the implications of these
findings and how they might inform future research.

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Chapter 5: Conclusions
The purpose of this study was to determine the gaps between a sample California
school district’s current human resource allocation practices, its desired practices, and a
set of research based practices deemed effective for increasing student achievement. An
additional objective of this study was to determine whether resources in the sample
district could be reorganized in ways to better promote student achievement without
spending additional revenue. The Evidence-based Model (EBM), a strategic template
that translates research on student achievement into optimal human resource allocation
patterns for prototypical schools (Odden & Picus, 2010), was used as the guiding
framework for a comparison with the sample district’s current and desired human
resource allocation systems. In order to measure the gaps between the sample district’s
staffing patterns, it’s desired patterns, and those suggested by the EBM, Clarke and Estes’
(2008) gap analysis was utilized as a methodological tool for both assessing the nature
and size of the gaps as well as revealing the underlying causes of those gaps. Finally,
tradeoffs were proposed to allow the sample district options for closer alignment of their
current resource allocation techniques with research-based approaches shown to boost
student achievement.
The Sample
The sample district is one that serves 53,000 students in an urban community in
Southern California. This study focused on the district’s five comprehensive and three
alternative high schools. In terms of demographics, the comprehensive schools averaged
42% Free and Reduced Lunch participation and the alternative schools averaged 49%
participation in 2011-2012. In terms of student achievement, the comprehensive schools
HIGH SCHOOL EDUCATIONAL RESOURCE ALLOCATION 109

averaged an Annual Performance Index (API) of 797 and the alternative schools averaged
646, and only one school met its Annual Yearly Progress (AYP) target in 2012. A
nomination for the Broad Prize in Urban Education in 2011-2012 highlighted the sample
district’s progress in closing the achievement gap: in the previous three years, the district
had produced an average growth of 63 points on the API scale for its demographic
subgroups.
Limitations
This study’s limitations included its small sample size that made the findings less
generalizable to other districts, especially districts with different demographics. In
addition, this study did not inform the human resource allocation practices of elementary
or middle schools as those school types were excluded from the sample entirely. Finally,
the time constraints of this study made its findings susceptible to volatility. The study
was conducted over a seven month period of particular budgetary uncertainty where
substantial cuts had become the norm and school districts across the state were waiting in
suspense to find out whether Proposition 30 would pass and save districts from having to
enact even deeper cuts. For these reasons, the study is likely not a reflection of the
sample district’s sustaining human resource allocation patterns over time.
Summary of Findings
This study sought and obtained answers to four research questions about the
relationship of human resource allocation strategies to student achievement in the sample
district and how to reorganize current practices in support of improved student
achievement.
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Research Question #1. What research-based human resource allocation
strategies improve student achievement? Research in response to this question revealed
the importance of four principles for improving student achievement. They are
leadership, assessment and data-based decision-making, collaboration, and professional
development.
Leadership. Findings related to leadership and human resource allocation
strategies showed that the sample district’s strengths were its tendency to hire sufficient
quantities of high quality site administrative staff to allow for the accomplishment of
school and district goals. Its room for growth included its need to empower teacher-
leaders by investing in systematic training for those staff members and then holding them
accountable for implementation of the newly learned leadership practices.
Assessment and data-based decision making. Findings regarding assessment and
data-based decision making revealed the sample district’s strengths to include the
utilization of common assessments in math, English, and social science once per
semester, and quarterly for science. Though it had purchased programs for data reporting
and analysis, its room for growth included the software’s lack of ease of use and the
accompanying need for more intense user training. Another area for growth included a
need for more formative assessments so that intervention for struggling students could
occur early and often.
Collaboration. In terms of collaboration, this study found one of the sample
district’s strengths to be its adjusted calendar reflecting built-in time for professional
collaboration. The district had accomplished this goal by reallocating time from
instruction and from other sources like lunches and passing periods to allow for the
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implementation of staff collaboration. Another of the sample district’s strengths was the
training for many of its teachers in the DuFour model for Professional Learning
Communities (DuFour, 2004). Its area for growth was found to be its need for a district-
wide system of expectations and accountability for the outcomes of collaboration.
Professional development. The sample district’s professional development
strengths were found to be the existence of training options at the high school level and
the utilization of non-evaluative walk-through protocols designed for observing the use of
newly acquired instructional strategies. The district’s areas for growth were its lack of
focus on a single district-wide professional development initiative, the voluntary nature
of its existing professional development programs, and its failure to implement
instructional coaches to support those programs.
Research Question #2. How are human resources allocated across the sample
school district? Research in response to this question revealed that management,
certificated teachers, instructional aides, security guards and secretaries were allocated to
each school site based mainly on student enrollment. There were some positions,
however, which were subject to such an acute lack of staffing that there was only one, or
less than one, position per school. For example, the district only employed one academic
extra help staff member at each high school, and it only staffed 1.8 total librarians, 2.4
instructional coaches, and one singular nurse across all eight of its high schools. Low
staffing levels for these positions suggested the sample district’s lack of confidence in
their value, providing the researcher with an area of focus for the reallocation phase of
this study.
HIGH SCHOOL EDUCATIONAL RESOURCE ALLOCATION 112

Research Question #3. Is there a gap between current resource allocation
strategies and research-based and desired district allocations? Findings revealed that
there were several severe and pervasive gaps between the district’s human resource
allocation practices and the staffing patterns suggested by the EBM. One explanation for
these gaps stems from the fact that the EBM was created as a generic model for allocating
resources in support of student achievement, and was not specifically developed for the
depressed fiscal conditions currently present in California, where per-pupil funding levels
are among the lowest in the nation (Odden, Picus, & Goetz, 2010). Thus, a majority of
the sample district’s position counts fell far below those proposed by the EBM. There
were two positions, assistant principals and special education instructional aides, which
were overstaffed by the sample district in comparison to the EBM, and these overages
were used to propose reallocation tradeoffs. In terms of the district’s desired staffing
patterns, in some cases what the district desired to staff and what it actually staffed were
the same, and in other cases the district’s desired position counts aligned more closely
with the suggestions of the EBM. Those areas of close alignment between the district’s
desired staffing and the EBM’s proposals became the subject of close scrutiny when
tradeoffs for reallocation were analyzed and presented.
Research Question #4. How can resources be reallocated to align with
strategies that improve student achievement? A small number of positive gaps were
revealed by the research for the previous question, where the sample district was actually
shown to be overstaffed in comparison to the EBM’s suggestions. These gaps were
treated by this study as funding overages to be reallocated to supplement the district’s
efforts to improve student achievement. Given the areas for growth revealed in the first
HIGH SCHOOL EDUCATIONAL RESOURCE ALLOCATION 113

research question as well as the position deficits revealed in the third question, this study
determined that the most cost effective reinvestment of the money saved from
transitioning some assistant principal positions to the equivalent of teaching positions,
reducing special education instructional aides, conducting credentialing analyses,
converting additional preparation time to teaching time for special education teachers,
and restructuring the school day to include a homeroom period would strengthen the
district’s first best instruction and provide more support for struggling students.
Specifically, this study’s recommendations for the sample district were to
strengthen first best instruction by hiring more instructional coaches, hiring more core
academic teachers, and providing more teaching time for special education teachers..
Additionally, this study recommended the provision of support for struggling students by
hiring more academic extra help staff, providing additional academic extra help through
the incorporation of a homeroom period, and by hiring more guidance counselors.
Though these proposed tradeoffs did not serve to eliminate the gaps between the
district’s current staffing patterns and the suggestions of the EBM, they did illustrate the
possibility of making changes within existing structures and without additional funding in
order to make an impact on student achievement.
Implications for Practice
Implications for the sample district. There are many ways in which the sample
district may choose to use the information presented in this study. First, since the study
provided a list of structures, policies and practices which are identified by the research to
improve student achievement outcomes, the sample district can benchmark its current
practices to find out if it is in fact doing everything possible to enable its students to meet
HIGH SCHOOL EDUCATIONAL RESOURCE ALLOCATION 114

rigorous state and district performance standards. In terms of resource allocation, the
district can examine how closely their current practices match their desired practices and
explore the reasons for those areas with large gaps. In like fashion, the district can also
examine the gaps between their current practices and the EBM’s recommendations,
determining whether it would like to consider narrowing those gaps through resource
reallocation. If it would like to consider tradeoffs, it can use the suggestions presented in
this study as a starting point and examine the EBM’s suggestions for prototypical schools
to prioritize which staff they would like to reduce and which they would like to add.
Finally, should California’s current fiscal condition improve and the district find itself
with new or additional funding, it can utilize the findings of this study as a tool for
prioritizing spending. Since this study provides a clear picture of the sample district’s
areas of need, those needs can become systematically addressed as the means to do so
become available.
Implications for other California districts. Other school districts can make use
of this study’s findings by benchmarking themselves against both the sample district’s
practices and those recommended by the EBM. Districts with similar demographics and
in similar communities may find the findings especially useful, as might districts looking
to close the achievement gap as successfully as the sample district has done. These
districts can examine the identified school improvement strategies that help students to be
successful, compare those to their own strategies, and use this information to set goals
and make long term district plans for their human resources and curriculum departments.
Implications for policy makers. This study can be useful for policy makers
looking to make fiscal educational change in the state of California. By providing a
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snapshot of one district’s fiscal circumstances, this study has shown policy makers the
ways in which California’s limited per pupil funding inevitably ties the hands of school
leaders, rendering them incapable of guaranteeing that all students will have the
opportunity to meet their full potential. That said, this study, along with other similar
studies and additional relevant information, can provide a starting point for policy makers
interested in devising new legislation to revise or revamp California’s existing
educational funding structures. Because it exposes a specific list of research-based
spending practices tied to student achievement, policy makers can view this study as a
roadmap for the development of incentives and sanctions that they might then attach to
forthcoming legislation. For example, districts which choose to utilize school funding in
support of strategic human resource allocation practices might experience incentives
whereas those who choose to spend their funds in other ways might encounter sanctions
or be unable to apply for new funding initiatives altogether.
Recommendations for Future Research
Sample district. The researcher recommends two areas for future research and
exploration on the part of the sample district. First, the district’s next steps should
include a credentialing analysis of its high school staff to determine how many specialist
teachers could be reallocated to become core teachers. Given that the study’s largest gap
between current practice and the EBM’s proposals was for core teachers, and given that
investment in first best instruction is a key principal in allocating human resources to
boost student achievement, this endeavor may make a significant contribution to closing
this important staffing gap. Once the district has completed its reallocations at the high
school level, the researcher also recommends that further research be conducted to study
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staffing patterns at the elementary and middle school level. The district should determine
whether similar reallocations could also benefit its schools at the lower levels such that
students of all ages have the opportunity to reach their full potential.
School finance researchers. It is recommended that school finance researchers
build on the findings of this study by conducting an in-depth comparison of similar
California studies utilizing the EBM and studies conducted in other states where the
EBM was successfully implemented. From there the researcher recommends that a
scaled down version of the EBM, focused on the premise of severe fiscal constraints, be
developed specifically for use in the state of California. This innovation would prove
particularly useful to California districts interested in the implementation of a
customized, research-based formula for their own human resource allocation practices.
Summary
The current national and state fiscal crisis requires that every penny spent on
education be scrutinized carefully for return on investment. The Evidence-based Model
provides a framework for that scrutiny, ensuring that human resources are carefully
allocated to best support student achievement. While California’s low levels of per pupil
funding bar it from fully implementing the criteria of the EBM, lessons can still be
learned by measuring the gaps between current spending patterns and those proposed by
the EBM. This study has illuminated the human resource allocation patterns of one
sample urban district in California, revealing deep deficits in spending on most staffing
positions. It proposed resource allocation tradeoffs by drawing from areas where the
district was shown to be overspending and reallocating those funds to areas of need. In
addition to enacting those proposed tradeoffs, the district has been encouraged to conduct
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teacher credentialing analysis which is likely to reveal further options for resource
reallocation which, if enacted, would more closely align its practices with those deemed
by the research to improve student achievement. Other districts can learn from this study
by comparing their own practices with the sample district’s systems and using those
results to drive future human resource decision-making. Finally, policy makers can
utilize this study’s findings to create a system of incentives and sanctions attached to
future funding initiatives. Such initiatives would be likely to spread the use of strategic
human resource allocation methodologies, with the ultimate goal of ensuring that all
children have the opportunity to meet their full potential.

HIGH SCHOOL EDUCATIONAL RESOURCE ALLOCATION 118

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serving low-income students. Mountain View, CA: EdSource.

Abstract (if available)

Abstract This study utilized the Evidence-based Model (EBM) from the research on school finance to evaluate the high school level human resource spending patterns of one California school district. The purpose of this study was to determine whether the district’s spending patterns were aligned with those patterns which have been shown by the research to boost student achievement. An additional objective of the study was to recommend staff reallocation to more closely align the district’s current spending strategies with strategies that have the potential to increase student achievement. Data on staffing allocations were collected from the Educational Services and Human Resources departments of the study district, and a gap analysis was conducted to analyze the nature of the differences between the district’s spending patterns and those suggested by the EBM. ❧ Findings from the study indicate that the EBM’s suggestions could not be fully implemented in the study district given that the district’s high schools do not have adequate funding to hire as many staff as recommended by the EBM for almost every position. However, findings also indicate that some human resource reallocation is possible and, when performed in conjunction with school restructuring strategies, provides the study district with avenues for making spending decisions in support of student achievement. Specific reallocation suggestions for the study district include gaining additional core teachers, instructional coaches, guidance counselors and academic extra help staff by reducing special education instructional aides and transitioning assistant principals of athletics and activities to teacher salaries. Organizational suggestions for the study district include gaining more academic extra help staff by reorganizing the school schedule to include a homeroom period, gaining additional core teachers by transitioning appropriately credentialed specialist teachers into the teaching of core subject areas, and gaining additional special education teachers by converting extra planning time into teaching time. This study contributes to the growing body of school finance research by illuminating the spending challenges and opportunities specific to the high school level and providing suggestions for revamping existing human resource allocation practices accordingly.

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University of Southern California Dissertations and Theses

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Asset Metadata

Creator Ragusa, Sarah (author)

Core Title Educational resource allocation at the high school level: a case study of high schools in one California district

School Rossier School of Education

Degree Doctor of Education

Degree Program Education (Leadership)

Publication Date 04/01/2013

Defense Date 02/11/2013

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

Tag adequacy,evidence-based model,OAI-PMH Harvest,resource allocation,school finance

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Picus, Lawrence O. (committee chair), Donavan, Frank (committee member), Escalante, Michael F. (committee member)

Creator Email sragusa@cnusd.k12.ca.us,sragusa@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c3-229487

Unique identifier UC11292699

Identifier usctheses-c3-229487 (legacy record id)

Legacy Identifier etd-RagusaSara-1500.pdf

Dmrecord 229487

Document Type Dissertation

Rights Ragusa, Sarah

Type texts

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

Access Conditions The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the a...

Repository Name University of Southern California Digital Library

Repository Location USC Digital Library, University of Southern California, University Park Campus MC 2810, 3434 South Grand Avenue, 2nd Floor, Los Angeles, California 90089-2810, USA