University of Southern California Dissertations and Theses

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

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

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Content Running Head: ALLOCATION OF HUMAN RESOURCES 1

Educational Resource Allocation at the Elementary Level:
A Case Study of One Elementary School District in California
by

Dominic Nguyen

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

August 2013

Copyright 2013 Dominic Nguyen
ALLOCATION OF HUMAN RESOURCES 2

Dedication
This dissertation is dedicated to my parents Nam and Mary Nguyen. You have risked
everything and left so much behind because you wanted to provide me with great opportunities
that this wonderful country of ours can provide. A special thank you to my fiancée, Jessica
Seglar, for believing in me and pushing me to continue when things got difficult. To my brother,
extended family and friends, thank you for understanding the time commitment required of this
journey. The person I am now and the person whom I hope to become is because of your love
and support.

ALLOCATION OF HUMAN RESOURCES 3

Acknowledgements
I would like to thank my dissertation chair, Dr. Lawrence O. Picus. Thank you for
accepting me into our wonderful dissertation group. Your support and insightful feedback has
made this experience such a positive one. I could not have asked for a better chair.
I would also thank the members of our dissertation group. You have provided so much
support and encouragement, I would not have been able to complete on time without you.

ALLOCATION OF HUMAN RESOURCES 4

Table of Contents
Dedication 2

Acknowledgements 3

Abstract 8

Chapter 1: Overview of the Study 10

Statement of the Problem 15

Purpose of the Study 15

Research Questions 16

Importance of the Study 16

Summary of Methodology 17

Limitations 17

Delimitations 17

Assumptions 18

Definitions 18

Chapter 2: Literature Review 22

School Improvement Strategies 22

Allocation and Use of Human Resources 27

Limited Resources/Fiscal Constraints 36

Gap Analysis 45

Summary 50

Chapter 3: Research Methodology 51

Research Questions 52

Sample and Population 52

Instrumentation 54

Data Collection 55

Data Analysis 57

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Chapter 4: Data Analysis and Interpretation of Findings 58

Overview of Districts and Schools 58

Research Question #1: What research based human resource allocation strategies
improve student achievement? 64

Summary: Research Question #1 71

Research Question #2: How are human resources allocated across Washington School
District and its schools? 72

Summary: Research Question #2 84

Research Question #3: Is there a Gap between Current Resource Allocation Strategies
and Researched-Based and Desired District Allocations? 85

Summary Research Question #3 88

Research Question #4: How Can Resources be Reallocated to Align with Strategies
that Improve Student Achievement? 88

Summary: Research Question #4 91

Summary 92

Chapter 5: Conclusions 93

The Sample District 93

Limitations 94

Summary of Findings 94

Implication for Practice 99

Recommendations for Future Research 101

Conclusion 102

References 103

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List of Tables
Table 1: Recommendations for Adequate Resources for Elementary,
Middle and High Schools 33

Table 2: Class Size Reduction Penalty 44

Table 3: Certificated Staff in 2011-2012 53

Table 4: Classified Staff in 2011-2012 53

Table 5: School Population Demographic in WSD 60

Table 6:WSD API by School 63

Table 7: Management Staff, Elementary School 73

Table 8: Management Staff, Middle School 73

Table 9: Number of Core, Specialist and Special Education Teachers 75

Table 10: Academic Help Staff, Instructional Coaches and Extended Day Staff 77

Table 11: Nurses, Counselors, Psychologists, Speech Teachers and TOSA 79

Table 12: Classified Staff 84

Table 13: Total Human Resource Allocation Gaps for Washington School District 86

Table 14: Number of Additional Academic Extra Help Staff per School 91

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List of Figures
Figure 1: Elements of the Evidence-Based Model 32

Figure 2: California K-12 Revenue Sources 38

Figure 3: The Three Tests of Proposition 98 39

Figure 4: California’s Actual Funding Level Compare to Long-Term Test 2 Projections 40

Figure 5: Share of Categorical Revenues, by Programs 2010-2011 43

Figure 6: Students by Race/Ethnicity 2011-2012.Source: ED-Data Partnership (2012) 54

Figure 7: Washington School District Student enrollment. 59

Figure 8: WSD Academic Performance Index 2005-20012. 61

Figure 9: WSD Percent Proficient and Advanced in English Language Arts. Source: 62

Figure 10: WSD Percent Proficient and Advanced in Mathematics. Source: Ed-Data 62

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Abstract
The purpose of this study was to examine the dispersion of human capital resources
within one school district in southern California and compare the use of personnel at each school
to the desired allocation informed by the district’s strategies and staffing formula. The district’s
resource distribution was also compared to that of the Evidence Based Model (EBM) to
determine how the district spent its funding in relation to the research-based recommendations
from the EBM. Gaps between the district’s allocation and the recommendation of the EBM were
unveiled. Causes for these gaps were determined and suggestions on the reallocation of human
resources that align with strategies proven to raise student achievement were presented.
The following four questions were addressed by the study: 1. What research based human
resource allocation strategies improve student achievement? 2. How are human resources
allocated across Washington School District and its schools? 3. Is there a gap between current
human resource allocation practices and what the research suggests is most effective? 4. How
can human resources be strategically re-allocated to align with strategies that improve student
achievement?
A mixed methods approach with a primacy on qualitative data was used to collect data
for this study. Quantitative data on the resource allocation of the sample school district was
gathered. Qualitative data on the district’s instructional vision, improvement plan, and
professional development plan were collected. Triangulation of the interviews, the district’s
resource allocation, and its philosophy was conducted to determine the congruency among how
the district is allocating their resources, how they perceive they are allocating their resources, and
how they want to allocate their resources.
ALLOCATION OF HUMAN RESOURCES 9

The Evidence-Based Model provides a framework for the allocation of human resources
that has been proven by research to increase student achievement. This study’s findings suggest
that schools in Southern California do not have the financial resources available to allocate
personnel to the recommendations of the Evidence-Based Model. Districts in California can use
this framework to identify areas of excess and strategically reallocate resources so that it can more
closely emulate the recommendation of the EBM and increase student achievement.

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Chapter 1: Overview of the Study
Keeping with the needs of a rapidly changing society, the American public education
system has been challenged with the task of finding innovative ways to allocate available
resources while searching for best practices to raise the quality of student achievement in an era
of high accountability. In 1983, National Commission on Excellence in Education’s path
breaking report, A Nation at Risk, outlined deficiencies within the public education system which
included the need for higher academic standards, increased student course requirements, longer
school days, and changes in the training and retention of teachers (Thomas & Brady, 2005).
Despite this, recent budget cuts have made it more difficult for schools to meet the academic
demands in place by an increasingly diverse student population and high stakes testing.
The public education system’s search for adequate funding has evolved into a system that
places a strong emphasis on accountability. Adopted in 1965, Title I of the Elementary and
Secondary Education Act (ESEA) sought to provide financial support to districts serving areas
with high concentrations of low-income families. The rationale driving this new structure was
that with more district funding, schools would be able to produce higher achieving students in
lower income areas, therefore closing the achievement gap. Since its passage, Title I has become
the single largest source of federal support for education, which in turn has strengthened the
federal government’s role in education. However, this led to the abuse of federal funding by
local districts which was stressed through the publication of the 1969 report Title I of ESEA: Is It
Helping Poor Children? The ESEA was amended four times between 1965 and 1980. In the
1980’s President Ronald Reagan reduced the financial support of the ESEA, citing the poor
academic performance of students in the American public school system as outlined by the
publication of A Nation at Risk (Thomas & Brady, 2005).
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On January 8, 2002, ESEA was reauthorized and retooled under President George W.
Bush and retitled as the No Child Left Behind Act (NCLB) of 2001. Currently, the NCLB act
requires greater accountability for test results as well as the need for research-based practices to
provide quality instructions. NCLB also enhances the school of choice movement in America
through a provision that allows parents more school site options to choose from. Additionally, a
set of criterion to determine teacher qualifications has been developed in order to ensure the
placement of highly qualified teachers in every classroom. Moreover, states have become ever
more accountable for educating their children because of sanctions placed upon low performing
districts that affect their access to federal funding. NCLB also requires individual states to
implement a data reporting system that provides information on state assessments that cover high
standards and serve as an indicator to determine if a school meets its Adequate Yearly Progress
(AYP). In turn, large demographic subgroups, including students of limited English proficiency,
racial/ethnic minority students, and students with disabilities within a school need also
demonstrate AYP on state achievement assessments. If a school fails to meet their AYP for two
consecutive years, the school is labeled a “needs improvement” school. An improvement plan is
then required from the school to help it reach its AYP for the following year. Parents of students
attending a “needs improvement” school may opt for their child to attend a nearby school that is
public or private and higher performing. Under NCLB, all children are expected to reach grade
level proficiency on state assessments by the 2013-2014 school year. There is the threat of
administrative expense reduction, school reorganization, state takeover, and the replacement of
staff members for those districts that fail to comply with these regulations. (Thomas & Brady,
2005)
ALLOCATION OF HUMAN RESOURCES 12

While adapting to NCLB, California, like many other states in the union, has had a
history of struggling to find the adequate amount of funding to provide students with a quality
education. Its public schools serve the country’s largest student population but only ranked 28
th

amongst all states in per-pupil expenditures (EdSource, 2011). In contrast, the state ranked 11
th

in per-pupil spending and spent 13% more than the average of the other states in 1970 (Glenn &
Picus, 2007). This substantial drop in funding is primarily due to legislations and court rulings
that have developed the financial structure of California’s school systems.
One such landmark court ruling, Serrano vs. Priest of 1971, determined that students
living in wealthier neighborhoods had an unfair advantage over those living in poorer
neighborhoods. School districts in wealthier neighborhoods were able to receive more funding
from its property taxes. The courts’ decisions ultimately took financial funding powers away
from local districts and gave the state control over the funding of its public schools.
On June 6
th
, 1978, California voters passed Proposition 13, which altered the property
taxes that the state utilizes for school funding. This piece of legislation reduced property tax
rates on homes, businesses, and farms by placing a 1% property tax cap on the assessed value of
homes. It also allowed for the assessed values of homes in 1978 to be rolled back to their
assessed values in 1976. The law allowed for a reassessment of the property value to be
completed for tax purposes once a change in ownership took place. Currently, state lawmakers
are responsible for allocating property tax revenues amongst local jurisdictions. Any changes
that allow for increased property tax rates must be approved by a two-thirds vote from each
house of legislature. Additionally, taxes raised by the local government must be approved by
two thirds of voters. Prior to Proposition 13, the averaged property tax rate was a little less than
ALLOCATION OF HUMAN RESOURCES 13

3% of the assessed value and there was no limit as to how much a property could be taxed.
Furthermore, there were no limits on increased tax rates for a property (EdSource, 2011)
Before Proposition 13, about two-thirds of education’s revenues came from property
taxes. The reduced revenues from lowered property tax lead to the increase reliance on state
funding for K-12 education in California. As a result of Proposition 13, Proposition 98 was
passed in 1988 to help stabilize funding and set a minimum amount of funding for K-12 and
education and community colleges (K-14). As it stands, 40% of the general fund revenues in
California must be set for K-14 education. This percentage is based on three testing formulas
that calculate the amount of financial funding allocated for education in California. Based on the
results of Test 1, which generates a percentage of general fund revenues, California was required
to spend 40% of the state budget for education. However in times of economic growth, Test 2
mandates that education must receive the minimum amount of dollars as in previous year, which
includes an adjustment based on statewide personal income and student enrollment. In times of
poor economic growth, Test 3, an adjustment based on available revenues tailors the amount of
funding education must receive in previous years plus adjustments for student enrollment and per
capita growth. A 0.5% increase of the general fund must be allotted for education. Proposition
98 also provided provisions to suspend the law with a two-thirds vote from state Legislature and
the approval of the governor. In 2010-2011 Proposition 98 was suspended to give policymakers
the ability to lower funding allotted for education (EdSource, 2011).
Limited resources in education have led to the formation of four methodologies for
determining the amount of resources needed to increase student achievement to the level
expected by NCLB. The four dominant approaches to estimating adequate funding levels
include: 1. Successful schools approach takes the findings learned from successful schools
ALLOCATION OF HUMAN RESOURCES 14

districts and applies the same model to another district, 2. Cost function approach statistically
estimates the cost of achieving specific levels of performance to the amount of dollars spent, 3. A
professional judgment approach that uses experts from the education field to make
recommendations to governments on how to best allocate resources and then estimates the cost
of those resources, and 4. Evidence-based approach that relies on a research to identify best
practices and determines the adequate amount of funding to support these practices (Policy
Analysis for California Education , 2000).
Although there has not been a model to obtain unanimous support from education
leaders, the evidence-based approach has advantages of being based on education practices that
have been identified as successful in the research literature. It has “advantages of simplicity,
transparency, and the ability to deal comprehensively with the full range of educational needs
and outputs” (Rebell, 2007). These benefits have led to its usage in several states including
North Dakota, Vermont, Arkansas, Wyoming, Kentucky, Arizona, and Washington (Picus,
2008).
As a consequence of increased pressures from NCLB and the diminishing financial
resources going to the California public school system, research based strategies need to be
implemented in order to efficiently improve student performance with the limited resources that
are provided. One of the primary advantages of the Evidence-Based Model is that it relies on
current educational research to estimate the resources needed to raise student achievement.
Allan Odden, a professor in the Department of Educational Leadership & Policy Analysis at the
University of Wisconsin–Madison and co-creator of the Evidence-Based Model, has provided
examples of proven strategies for improving student performance in his book 10 Strategies for
Doubling Student Performance. Odden states that school districts must first understand the
ALLOCATION OF HUMAN RESOURCES 15

performance problem and its challenges. They must then set ambitious goals and then provide
schools with the proper curriculum to achieve them. Instruction within individual schools must
also be driven by data provided from benchmark and formative assessments. In addition, a
strong professional development component is important to raising student achievement.
Struggling students need to be provided with more time. There must also be a collaborative
culture within the organization and time must be used efficiently and effectively. Specific details
of Odden’s strategies will be discussed later in chapter 2.
Statement of the Problem
California’s education budget continues to fall while accountability and expectations for
student achievement continue to rise. School districts’ quest to find the best way to allocate
limited resources to increase student achievements remains. The pressure to close the
achievement gap mandated by federal laws has educational leaders searching for answers.
Although there isn’t a consensus as to which educational funding model to implement in order to
adequately provide students with a high quality education, the Evidence-Based Model provides a
strategic example of how school districts can apportion its personnel to raise student
achievement. Further research needs to be done to determine how school districts can modify
their current allocations to match that of the Evidence-Based Model.
Purpose of the Study
As California continues its plan to decrease spending for education, school districts and
their schools need to determine the most effective and efficient way to allocate its resources to
meet the demands of increasing student achievement. This study will look at one elementary
district in southern California to examine the distribution of personnel at its sites. The researcher
will compare the current state in which the district is allocating its personnel to that of the
ALLOCATION OF HUMAN RESOURCES 16

Evidence Base Model. Using a gap analysis, the researcher will propose a plan to modify current
resources to mirror that of the Evidence Base Model.
Research Questions
The researcher will answer the following questions:
1. What research based human resource allocation strategies improve student achievement?
2. How are human resources allocated across Washington School District and its schools?
3. Is there a gap between current human resource allocation practices and what the research
suggests is most effective?
4. How can human resources be strategically re-allocated to align with strategies that improve
student achievement?
Importance of the Study
As the economic downturn continues, a cut in spending is the reality. Because education
is one of the highest costs a state endures, decrease in education expenditures will likely
continue. The Evidence-Based Model can be a viable resource to lawmakers and educational
leaders as a resource to determine how much and where cuts should be made.
With diminishing funding, school districts need to reallocate its resources and still meet
the needs of those they serve. Expectations of high student achievement must be met. The
Evidence-Based Model could be the guide to help districts determine alternatives to their current
staffing protocols. The information generated from this study can demonstrate to districts across
the nation how modifications can be made in personnel allocation and still achieve high student
learning.
This research provides a perspective that lawmakers can use to determine how much
funding is needed to provide students with a quality education. In turn, lawmakers would be able
ALLOCATION OF HUMAN RESOURCES 17

to set a minimum for education finance, as well encourage them to look at other avenues to
preserve an appropriate minimum.
Summary of Methodology
A mixed method approach will be use to study one elementary school district, in southern
California, consisting of 14 elementary schools and two middle schools. Interviews will be
conducted with site principals and district personnel to identify instructional practices that are in
place, the district’s mission and goals, the district’s staffing formula, and current staffing at each
school site. Data collected from the district will be entered into a pre-formulated model provided
to us by Dr. Picus. Using the pre-formulated model, gap analysis will be conducted for each site,
as current resource allocations will be compared to that of the Evidence-Based Model.
Limitations
One limitation of this study is the size of its sample. The findings may not be generalized
to other schools and student populations due to variations in student demographics. Another
limitation is the information gathered from interviews may include subjective opinions of
principals and district personnel. Therefore the information may not be representative of all
principals and district personnel. The length in which the study was conducted is also a
limitation due to its relatively short time period.
Delimitations
This study will be conducted within one elementary school district in southern California.
It will examine resource allocation data for the 2011-2012 school year only.

ALLOCATION OF HUMAN RESOURCES 18

Assumptions
This study assumes that all data collected are complete and accurate, that interviewees in
this study answered willingly and honestly, and that the documents chosen for analysis are
reflective of the school’s culture 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 that mandated that all students must demonstrate proficiency in
Math and English language arts by the year 2014 (EdSource 2012).
American Recovery and Reinvestment Act (AARA)—Commonly referred as the stimulus
package. Enacted by the 111
th
United States Congress in February 2009. This act gave over
$100 billion one-time monies to education.
Average Daily Attendance Rate (ADA)—A statistic representing total number of days of
attendance for all students divided by the total number of school days in a given period.
California Standards Test (CSTs)- A series California State tests that measure the degree which
students are achieving in the areas of English-language arts, mathematics, science, and history-
social sciences
Categorical Funds- Federal funds for schools that are assigned for specific purposes.
ALLOCATION OF HUMAN RESOURCES 19

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.
Cost Function Approach—A statistical model that 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 that foster improvements in student achievement.
Elementary and Secondary Education Act (ESEA) – The principal federal law affecting K-12
education. Originally enacted in 1965 to support the education of the country’s poorest children.
Congress must reauthorize it every six year. No Child Left Behind Act is the most current
reauthorization (Edsource, 2012).
Equity— The equalization of student access to educational opportunities.
Evidence-Based Model (EBM)—a research-based adequacy estimator that provides
recommendations for sufficient funding levels to ensure that all students have the opportunity to
meet achievement targets (Odden et. al, 2005).
Fulltime Equivalent (FTE)- The ratio derived by dividing the number of work hours required in a
part-time position by the number of work hours required in a corresponding full-time position.
Gap Analysis: A tool for measuring the distance between actual and desired performance,
diagnosing causes, and proposing solutions (Clark & Estes, 2002).
General Funds- Funds used by the state and school districts to differentiate general revenues and
expenditures for those placed in other funds for specific uses (Edsource, 2012)
ALLOCATION OF HUMAN RESOURCES 20

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, 2012).
Per Pupil Spending—Current expenditures for public school education in a state divided by
student enrollment.
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 and 111—Voter-approved initiative that amended the California Constitution in
1988 and 1990 to guarantee the minimum level of funding from property and state taxes for K-14
education (EdSource, 2012).
Research-based Instructional Practices—Educational practices that have been proven effective
in improving student achievement through research.
Resource Allocation—The practice in which an organization assigns its available resources to
meet the needs of the organization.
ALLOCATION OF HUMAN RESOURCES 21

Resources—The supply of money, materials, staff, and other assets that can be drawn by an
organization in order to function.
Senate Bill (SB) 90—Imposed a revenue limit system that placed a ceiling on the amount of
income districts could raise through property taxes (EdSource, 2012).
Successful Districts Approach—an adequacy estimation model that involves studying successful
districts with the goal of emulating their practices (Rebell, 2007).

ALLOCATION OF HUMAN RESOURCES 22

Chapter 2: Literature Review
This chapter provides an overview of literature regarding school finance and resource
allocation strategies as those topics pertain to school reform. The review focuses on four areas:
1) school improvement strategies, 2) allocation of human resources, 3) limited resources/fiscal
constraints, 4) and a synopsis of a gap analysis because of its methodological use this case study.
School Improvement Strategies
There has been much research done to identify strategies that have been successful in
raising student achievement. The following is an overview and then a synthesis of studies in this
area along with an examination of common themes that are the studies identified as essential for
school improvement.
Doug Reeves (2003) studied schools in Milwaukee and Wisconsin that have shown gains
in student achievement to identify successful strategies in turning around schools. Those which
he studied had a population of 90% or more of its students qualifying for free and reduced lunch,
belonging to minority ethnic group, and/or meeting district or state performance standards. He
concluded that all these successful schools had a clear focus on academic achievement and
aligned their curriculum to support the goal. The schools also frequently assessed student
progress and then provided intervention to students in need. Common characteristics of high
achievement schools also included an emphasis on non-fiction writing and teachers worked
collaboratively to score and assess student work (Reeves, 2003).
Togneri and Anderson (2003) conducted a study examining five high poverty school
districts showing improvement in their academic results. Their findings included seven key
factors that the school districts had adopted to improve instruction and increase student
achievement. All districts acknowledged their poor performance in efforts to find
ALLOCATION OF HUMAN RESOURCES 23

solutions. They also put in place a system-wide approach to improving instruction, one that
included instructional support focused in curricular content. A vision focusing on student
learning and guided instruction was also adopted. In addition, the districts used data to support
their decision-making. Professional development was strategically planned to improve
instruction. Leadership roles were defined and distributed to include assistant principals, teacher
leaders, central office staff, union leaders, and school board members. The study also found that
the successful districts were committed to sustaining reform over time, often maintaining
continuity with those in leadership roles (Togneri & Anderson, 2003).
Williams et al. (2005) conducted an extensive survey of California elementary schools
serving low-income students to determine why some elementary schools score much higher on
the on the California academic performance index (API) than other schools serving students with
similar demographics. An analysis of its findings determined that higher performing schools had
higher expectations for their students by setting them as a priority. Successful schools
implemented a coherent, standard-based curriculum and instructional program. They also used
data to drive instruction and improve student achievement. Instructional resources were also
readily available because the district provided the most up-to-date instructional materials along
with support on how to best implement them. The survey also found that schools with more
experienced principals and teachers were more likely to have higher achievement. It was
concluded that strong district and site leadership was influential in attaining high student
achievement (Williams, et al., 2005).
In a study of 31 successful schools in 9 school districts from Washington state,
Fermanich, Mangan, Picus, Odden, Gross and Rudo (2006) identified six key practices in raising
student performance. Successful schools had a focus on educating all students so that they
ALLOCATION OF HUMAN RESOURCES 24

would meet performance targets. In addition, they adopted data-driven decision-making
practices, as well as a rigorous curriculum that is aligned with state standards. The district and
its schools provided effective professional development to aid in the implementation of the
curriculum. They also extended learning opportunities for struggling students (Fermanich,
Mangan, Odden, Picus, Gross, & Rudo, 2006).
Daniel Duke (2006) examined multiple studies to identify key strategies for school
improvements. Duke evaluated five studies conducted between 1995 and 2004 to determine six
characteristics implemented by low performing schools to drastically increase student
performances. Prompt assistance was given to students who had difficulty learning the
curriculum. Teacher collaboration was another factor in turning around low performing
schools. The study also showed that the schools practiced using data to drive its decision-
making. Strong leadership from principals and teachers was recognized as an essential
component in turning around struggling schools. The organizational structure of the school in
terms of the roles of all stakeholders and planning process was reconfigured to align with the
goals of the organization. Finally, an effective staff development component was also
determined as essential (Duke, 2006).
Similar to Duke, Allan Odden (2009) compiled a list of ten strategies based on his
research, for districts and schools to use in doubling student performances. The ten strategies
include: Creating a sense of urgency and understanding the performance challenge, setting
ambitious goals, changing the curriculum program and implementing a new instructional vision,
using data-based decision making and implementing benchmark and formative assessments,
providing ongoing professional development, using time efficiently and effectively by
restructuring the instructional year or day, extended learning time for struggling students,
ALLOCATION OF HUMAN RESOURCES 25

establishing a collaborative culture with distributed leadership, providing outreach to
professionals in search of best practices, and the acquisition, development, and retention of
quality human capital (Odden A. R., 10 Strategies for Doubling Student performance, 2009).
A review of the studies revealed four common themes vital to successful school
reform: Strong leadership, the use of assessments and data-based decision making,
collaboration, and effective professional development.
The importance of school leadership in bolstering student achievement has been
emphasized throughout studies of school improvement. Literature has shown that leadership has
evolved into a shared practice where a team consisting of administrators, teachers, and staff
members has an integral role in developing the school culture where high student achievement is
cultivated. Effective leaders are capable of communicating a clear vision as well as establishing
goals and implementing strategies to help achieve them. Successful leaders have the ability to
assess the status of their organization and implement change by motivating others to support and
contribute to the process (Togneri & Anderson, 2003; Reeves, 2003; Marzano et al., 2005; Duke,
2006; Bolman and Deal, 2008; Odden, 2009).
The adoption of data based decision making is another theme implemented by
successful schools. Data provides schools with essential information needed to set goals, align
resources, and focus instruction to best move students to high achievement. Schools that have
experienced success in raising student achievements have fostered a culture where data is used to
set goals, align resources and drive instructions (Togneri & Anderson, 2003; Reeves, 2003;
Williams et al., 2005; Fermanich et al., 2006; Duke, 2006; Odden, 2009). Assessments that are
used as monitoring tools to gauge student understanding and identify gaps in their knowledge
provides pivotal information for educators to use in tailoring their instruction and aligning their
ALLOCATION OF HUMAN RESOURCES 26

resources to meet their students’ needs (Lezotte & Snyder, 2011). Furthermore, Datnow, Park,
and Wohlstetter (2007) identified six key strategies that need to be implemented to build a
performance-driven school system. One of these strategies focused on the necessity to build a
foundation for data-driven decision-making and establish a culture of data use and continuous
improvement. Schools organizations must invest in an information management system that can
help them select the right data. They must build the capacity for data-driven decision-making
and have the ability to analyze and act upon data to improve performance (Datnow, Park, &
Wohlstetter, 2007).
As data-driven decision-making becomes the cultural norm within an organization,
collaboration among colleagues is fostered. This creates an environment where teachers share
similar instructional goals, methods, problems, and solutions to bolster student performance
(Birman, Desimone, Porter, & Garet, 2000). Collaboration provides teachers with opportunities
to share best practices as they provide one another with pedagogy and support to make more of
an impact on student learning.
Effective professional development has become essential in providing quality teachers
to increase student achievement. A report from the National Center for Education Evaluation
and Regional Assistance concluded that teachers who receive considerable professional
development have the ability to increase students’ achievement by about 21 percentile points
(Yoon, Duncan, Lee, Scarlos, & Shapley, 2007). Professional development increases the
instructors’ knowledge and skills while bringing about change in teaching practices within the
classroom. The process of change makes teachers aware of new knowledge to be obtained,
provides opportunities for teachers to work and plan their curriculum, allows teachers to
implement new practices within a setting where they can be observed and obtain feedback, and
ALLOCATION OF HUMAN RESOURCES 27

delivers time to reflect on what does and does not work (Elmore & Burney, 1999). Research
shows that the duration of professional development should be at least 100 hours, and ideally 200
hours annually to be effective (Odden, 2009). According to research, effective professional
development should be school based and job embedded rather than a one-day workshop (Odden,
Archibald, Fermanich, & Gallagher, 2002). Being at the school site makes it more likely for
teachers to correlate their new information into everyday practice. Reforming types of activities
are more aligned to how teachers learn and therefore have a greater influence on changing their
instructional practice because it better meets their needs and goals. (Garet, Porter, Desimone,
Birman, & Yoon, 2001).
Activities such as mentoring and coaching have a lasting effect on classroom instruction
more than traditional forms of professional development. Teachers that receive mentoring or
coaching develop learned strategies more often and with greater skill than those who receive the
same training during a one-day workshop. They are also more likely to retain and increase their
skill over time because they are receiving ongoing support. Teachers who receive coaching also
have a stronger understanding of the purpose of the new strategies. They are able to collaborate
and discuss with their colleagues about the implementation in their lessons and materials design
(Joyce & Showers, 2002).
Allocation and Use of Human Resources
Understanding the best practices that have been proven to raise student achievement
enables educational leaders to make calculated decisions when allocating resources. In difficult
fiscal years, the appropriate allocation of resources becomes a challenging endeavor. The
following section examines the spending patterns in public education and how educational
adequacy has become the focus when determining the appropriate allocation of resources. This
ALLOCATION OF HUMAN RESOURCES 28

section concludes with a brief description of the Evidence-Based Model (EBM), the adequacy
framework used in this case study.
History of expenditures. Educating the youth of America is an expensive
undertaking. It is the largest portion of most state budgets. From 1940 to 2009, public school
revenues more than doubled during each decade. Public school revenues increased from two
billion dollars in 1890 to $611 billon in 2008-09. The national average per pupil rose from $40
in 1920 to $10,297 in 2008. (Odden & Picus, School Finance A Policy Perspective, 2008)
(Hanushek & Rivkin, 1997) (National Center for Education Statistics, 2012)
Historically the six typical categories of education have been: Instruction, instructional
support, student support, administration, operations and maintenance, and transportation and
food. Research indicates that increases in the cost of educating students have been linked to
teacher salaries, special education, instructional aids and support staff, and non-core
teachers (Adams, 1994; Lankford and Wyckoff, 1995; Hannaway et al., 2002; Odden & Picus,
2008).
With the increase in student enrollment, the need for instructional staff members has
grown. This expansion, coupled with higher rates of instructor compensation, has amplified the
cost of education. In 2010, the average annual salary for an elementary school teacher is
$51,380 and the average annual salary for a high school teacher is $53,230 (Bureau of Labor
Statistics, U.S. Department of Labor, 2012). The decrease in student to teacher ratio from 22.3
in 1970 to 15.4 2009 has also raised staffing expenditures by increasing the need for instructional
staff needed to educate students (National Center for Education Statistics, 2012). The need for
more instructional staff coupled with the rise in teacher salaries have accounted for some of the
increase in education expenditures (Hanushek & Rivkin, 1997).
ALLOCATION OF HUMAN RESOURCES 29

The increases in non-core teachers have also added to the expenditures in
education. Beginning in the mid 1960’s, core teachers were allowed more planning and
preparation time during the day by the addition of art, music, physical education, and library
teachers. Odden and Picus (2008) noted that only approximately fifty percent of the teaching
staff in secondary schools provides instruction in core subjects such as mathematics, science,
reading/English/language arts, history, and foreign language. Monk et al (1996) also concluded
that the cost of vocational teachers and special education exceeded the cost of core teachers.
Educating students with special needs has had a significant impact on the increased
amount of school expenditures (Hanushek & Rivkin, 1997). The estimated cost of educating
special education students is approximately 2.3 times more that regular education students. With
the enactment of the Education for all Handicapped Children Act in 1975, the resources offered
to those with special needs were expanded. The competition for additional categorical funding
then resulted in the over-identification of special education students. From 1980 to 2009, the
number of special education students grew from four million to approximately 6.4 million (US
Department of Education, 2011). The growth in instructional staff grew at an even more rapid
rate. From 1978 to 2010, the number of special education teachers increased from 194,802 to
459,600 (Bureau of Labor Statistics, US Department of Labor, 2012).
The increase in special education services also increased the amount of instructional
aides and support staff. This entry of more support personnel has added to the overall growth in
educational expenditure (Hanushek & Rivkin, 1997). Other special education instructional
personnel rose from 140,183 to 219,752. Hanushek and Rivken (1997) concluded that the rise in
instructional expenditures was consistent with the growth of clerical and support staff. The
ALLOCATION OF HUMAN RESOURCES 30

number of teacher aides grew from 57,000 in 1970 to 1,288,300 in 2010 (Bureau of Labor
Statistics, US Department of Labor, 2012).
The increase in teacher salaries, non-core teachers, cost of special education,
instructional aides, and support staffs have diverted education funding away from those
providing instructions in core academic subjects. As resources are taken away from the core
subject, it is more difficult for schools to increase student achievement. The focus needs
realigning, as student performance needs to be the primary factor in the hiring and placement of
staff members (Monk et al. 1996; Odden and Picus, 2008).
Adequacy. Because districts and their schools are measured by how well students
perform on state assessments, resources must be allocated appropriately to increase student
achievement. Traditionally, the allocation of resources has been similar to that of a service
delivery model where a one size fits all approach has been adopted. In a study conducted by
Steifel et al. (2004), they concluded that the traditional approach used in the New York schools
had no systematic method in the allocation of resources, and therefore resulted in inconsistent
student achievement outcomes. Recent court rulings have shifted the focus of school finance to
an adequacy model where the allocation of resources is strategically planned to meet the needs of
students.
Adequacy is the cost of educating all students to meet proficiency standards. It consists
of two components: absolute standards of adequacy and relative standards of
adequacy. Absolute standards of adequacy deal with the overall financial support associated
with student performance. Relative standards measure the difference in cost of helping students
with special needs reach the same performance standards of other students. This definition is
based on the following six assumptions: 1) basic costs vary by desired outcomes, 2) marginal
ALLOCATION OF HUMAN RESOURCES 31

costs of achieving outcomes vary by district scale, 3) marginal costs of achieving outcomes vary
by student needs, 4) marginal costs of producing outcomes vary by the prices districts must pay
for comparable resources, 5) scale, student needs, and input prices, and 6) marginal costs of
achieving desired outcomes increase as performance standards increase, and decrease as
performance standards decrease (Baker, 2005).
There have been studies conducted in California that examine the cost of educating
students under the framework of an adequacy model. In a budget simulation conducted with 568
randomly selected public school teachers, principals, and school district superintendents,
(Sonstelie, 2007) concluded that the cost to California’s public schools meeting the state’s
achievement standards is about 40 percent more than the expenditures of California schools in
2003-2004. Imazeki (2007) uses a cost-function approach to estimate the cost for California
districts to meet the achievement goals set by the state. She determined that California school
districts need up to $1.7 billion more to achieve its Academic Performance Index (API)
goals. Both these studies identified the need for California public schools to provide additional
funding for students to reach proficiency.
While both the Sonstelie (2007) and the Imazeki (2007) studies expressed a need for
more funding, Imazeki (2007) identified a flaw in the cost-function approach by acknowledging
a weak quantitative relationship between overall spending and student performance. As an
alternative to the methodologies used in these studies, this case study will use the Evidence-
based Model approach to determine adequacy. The following section will provide a brief
description of the Evidence-based Model and how it strategically allocates resources to provide
adequacy in public education.
ALLOCATION OF HUMAN RESOURCES 32

Evidence- Based Model. Unlike other adequacy methodology, the Evidence-Based
Model (EBM) strategically allocates resources to support school improvement strategies that
have been shown by research to be effective in raising student achievement. Developed by
Odden et al. (2003), EBM provides recommendation for the number of resources needed in a
given school based on its enrollment numbers. These figures provide a base point for schools to
compare its current allocation to determine the gap in resources. As shown on figure 2.1, the
EBM concentrates on core subjects such as math, science, and language arts. Layers of support
are added to ensure that all students are provided with the provisions they need to attain a high
level of achievement.

Figure 1. Elements of the Evidence-Based Model. Borrowed from Odden and Picus, 2009
Odden, Goetz, and Picus (2007) have detailed the number of resources needed in an
elementary, middle, and high school (Table 1). It serves as a guide for schools wanting to
compare their current allocation of resources to that of the EBM model. The figures are based on
a standard level of enrollment and can be adjusted accordingly to each site. The EBM suggests
ALLOCATION OF HUMAN RESOURCES 33

smaller class sizes for those teaching the core subjects. Planning and release time are provided
with the addition of specialist teachers for art, music, and physical education. The model also
supports full day kindergarten as a necessary means for providing a strong foundation for which
students can build upon. Extra support is also given to students and staff. One full time
credential tutor is provided for every 100 students on free or reduced-price lunch. For every 100
English language learner (ELL) students, one full time teacher is allocated to provide additional
support.
Table 1
Recommendations for Adequate Resources for 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%

ALLOCATION OF HUMAN RESOURCES 34

Table 1, continued
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
33% more assuming
a 90 minute block
schedule with each
FTE teaching 3
blocks a day: 8.0

Table 1, continued
3. Instructional
facilitators/coache
s
1/200 students: 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
1. Extended
day
1.31 1.36 1.74
2. Summer school 1.31 1.36 1.74
3. 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
4. Students with
severe disabilities
100% state
reimbursement
minus federal funds
100% state
reimbursement
minus federal funds
100% state
reimbursement
minus federal funds
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 total
13. Supervisory
aides
2 2 3
14.
Librarians/media
specialists
1 1 1 librarian
1 library technician

ALLOCATION OF HUMAN RESOURCES 35

Table 1, continued
15. Principal 1 1 1
16. School site
secretary
1 secretary and
1 clerical
1 secretary and
1 clerical
1 secretary and 3
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

Table 2, continued
19. Instructional
materials, including
textbooks,
formative
assessments
$165/pupil $165/pupil $200/pupil
20. Student
activities
$250/pupil $250/pupil $250/pupil
Other
Expenditures

22. Operations and
maintenance
$890/pupil $890/pupil $890/pupil
23. Transportation $375/pupil $375/pupil $375/pupil
24. Food services Self supporting Self supporting Self supporting
Borrowed and adapted from Odden, Goetz and Picus, 2007.
The EBM model allocates the appropriate number of resources needed to support
research based school improvement strategies. For this reason, it will serve as the conceptual
framework for this study. Further discussion as to how the EBM will be utilize to measure the
current spending of a district will be discussed later in Chapter 3.

ALLOCATION OF HUMAN RESOURCES 36

Limited Resources/Fiscal Constraints
In these challenging times of financial instability, the EBM has become a necessary tool
as it identifies the essential resources to support best practices to raise student achievement.
Although California schools are experiences financial cuts, expectations of student achievements
continue to grow. Under the No Child Left Behind Act (NCLB), students are expected to reach
100% proficiency by 2014. This next section of the literature review will provide an overview of
the history of school finance in California. It also identifies how the federal and state
government have responded to the changing climate in school funding.
School districts in California were primarily funded by local property taxes before the
mid-1970s. In 1968, a California court case, Serrano v. Priest challenged the policy, stating that
funding schools primarily through property taxes created inequities among school
districts. School districts in wealthier neighborhoods received more funding even though
property owners in those neighborhoods were being taxed at a lower tax rate. The difference in
revenue between districts was a representation of unequal opportunity. As a result of Serrano v.
Priest, legislators passed Senate Bill 90 in 1972. Senate Bill 90 placed a limit on the amount of
general-purpose revenue school districts could receive (Edsource, 2012).
After the Serrano v. Priest ruling, voters passed Proposition 13, an amendment to the
state Constitution in 1978. Proposition 13 limited the property taxes to 1% of full-assessed value
and capped the amount of annual increases to 2%. Local voters also had the right to attached
additional rate through the passing of bonds. They also allowed the right to levy a uniform dollar
tax per parcel of land. Individual properties would be reassessed once new construction was
done on the property or the sale of property occurred. Control over the allocation of local
ALLOCATION OF HUMAN RESOURCES 37

property taxes to schools, cities, counties and special districts were then effectively turned over
to the state (Edsource, 2012).
After the adoption of Proposition 13, there was a change in the landmark of California
school finance. Prior to the 1970s, local schools districts were financed primarily through
property taxes. About two-thirds of education’s revenues came from property taxes (Edsource,
2012). Proposition 13 reduced the amount of revenue school districts could receive from
property taxes. The state had to provide more financial support to districts to equalize funding
across districts, as regulated after the Serrano v. Priest ruling. As of 2009-10, California public
schools have been receiving 57% of their funding through the state. Property taxes and other
local sources have funded another 29%. The federal government has provided the remaining
14% of the revenue received for public schools (Figure 2). As a result, the state has gained more
control over the allocation of resources in California districts. Approximately 30% of funds are
restricted for categorical state and federal funding such as special education, class size reduction,
and the National School Lunch Program. The large number of restriction and categorical
programs has made the state one of the most controlled school finance system in the United
States (Weston, 2011).
ALLOCATION OF HUMAN RESOURCES 38

Figure 2. California K-12 Revenue Sources
In an attempt to improve school finance in California, voters approved amendments to the
California Constitution in 1988 and 1990. In 1988, Proposition 98 set a minimum amount of
state funding allocated for K-14 (kindergarten through community colleges) education. The
dollars K-14 education receives is based on three testing formulas (Figure 3). The third testing
formula was amended into the Constitution in 1990 with Proposition 111 (Timar,
2006). Proposition 98 also mandated that each school submit a School Accountability Report
Card (SARC) that included test scores, dropout rates and teacher qualification (Edsource, 2012).

ALLOCATION OF HUMAN RESOURCES 39

Figure 3. The Three Tests of Proposition 98. Copyright 2009 Edsource, Inc.
The recession of 2008 has made it difficult for the state to supply districts with the
appropriate funding set by Proposition 98. Although Proposition 98 has set the minimum for
funds allocated to K-14 education, the governor and the legislature has discretion as to how
much revenue each district receives. Under Test 1, at least 39% of the states General Fund tax
revenues need to be allocated for K-14 education. Test 1 has only been implemented in the first
year of Proposition 98. Under Test 2, California school funding must keep pace with ADA and
economic growth (Timar, 2006). California has not funded at the long-term Test 2 since 2005-
06 school year. Figure 2.5 shows a comparison between K-14 Proposition 98 funding estimates
from 2005-06 through 2011-12 and actual funding within that time span. In 2010-11, the actual
ALLOCATION OF HUMAN RESOURCES 40

funding level was approximately 9.1 billion less than the long-term Test 2. The state must
restore to the long-term Test 2 funding level once it is in better fiscal conditions. Considering its
current fiscal restraints, it is not likely to happen any time soon (Edwards, Terry, & Perry,
2011).

Figure 4. California’s Actual Funding Level Compare to Long-Term Test 2 Projections
To offset some of the fiscal pressure brought on by the recession of 2008, the federal
and state governments have taken various actions to reduce some of the pressures. The Federal
government has provided California with one time federal aid; the state has implemented a
deferral policy and reduced some of its restrictions on funding sources. Below are descriptions
of some of federal and state actions that have been implemented to help with the current
economic crisis in public education.
Federal actions. At the end of 2008, President Barack Obama and Congress passed the
federal stimulus plan known as the American Recovery and Reinvestment Act (AARA). The
ALLOCATION OF HUMAN RESOURCES 41

AARA allocated more than $100 billion for prekindergarten through 12th grade schools in the
United States. California received $6 billion in ARRA funding to be used from the 2008-09
through the 2010-11 school year. Another $1.2 billion could be used in the 2010-11 through the
2011-12 school year for Federal Education Jobs and Medicaid Act funding. The federal aid was
intended for school districts to avoid more personnel layoffs and retain vital school
operations. The funds were also intended to increase teacher and principal effectiveness,
establish a system that uses data to improve student achievement, adopt assessments that are
aligned with college and career ready standards, and aid in turning around low performing
schools (Edsource, 2012).
Critics of the AARA have cited that the incentive laden legislation have brought about
competing goals of short-term stimulus and long-term reform. They have also claimed that the
ambiguity of the legislation’s reform requirements have made it more difficult for districts to
decipher how they should use the funds to save jobs. Furthermore, it has been argued that this
one time federal aid was not enough for states to implement long-term solutions and implement
reform. It merely allowed states to fill the holes created by the recent budget cuts of the
recession, and districts to maintain their status quo (Mead, Vaishnav, Porter, & Rotherham,
2010). A report done by the Center on Education Policy (2010) found that districts were
reluctant to use the one time money on personnel because they were unsure that they would
receive the money the following years. Instead, they used the ARRA revenue to purchase
equipment, technology, and other non-personnel items (Center on Education Policy, 2010).
State actions. The states have also taken actions to help school districts cope with the
reduction in state funding for California public schools by giving them more flexibility on
spending the funds allotted to them. The state has also granted districts the ability to increase
ALLOCATION OF HUMAN RESOURCES 42

class sizes. Waivers were also given to districts from purchasing instructional materials to
reduce the impact of budget cuts. Additionally, the number of required school days has been cut,
along with malleable guidelines in the funding of maintenance projects. Districts have also been
given latitude in the amount of financial reserves they must keep.
Due to the slow economy of the Recession of 2008, which reduced state revenues, the
State Legislature in 2009 reduced restrictions on more than 40 categorical programs through the
2012-13 school year. This was later extended through the 2014-15 school year. California
school districts have been funded through unrestricted general funds and restricted categorical
funds. Unrestricted general funds, which make up approximately 70 percent of district revenues,
may be used for any educational purposes. Categorical funds have been used for special
programs such as special education, economic impact aid (EIA), and K-3 class size
reduction. Fifteen programs have made up 90 percent of all categorical funding (Figure 5). In
2009, Districts were given flexibility on approximately 30 percent of the categorical revenues in
exchange for large cuts (Weston, California's New School Funding Flexibility, 2011).
ALLOCATION OF HUMAN RESOURCES 43

Figure 5. Share of Categorical Revenues, by Programs 2010-2011
To help mitigate the pressures from California’s budget cuts, the state has given districts
leeway regarding K-3 class size reduction. Since 1996-97, districts were given categorical funds
to reduce their class sizes in grades K-3. They received funds for every K-3 classroom that had a
student to teacher ratio of 20:1 or lower. In 2004, Senate Bill 311 reduced the penalties districts
would accrue if they went over the 20:1 ratio (Table 2). This flexibility was initially applied
from 2010-2011 through 2011-12 but was extended through 2014 by Senate Bill 70. Districts
were given the decision to determine whether it was beneficial to accept K-3 class size reduction
funding and take on the penalties or forgo the categorical funds (Edsource, 2010).

ALLOCATION OF HUMAN RESOURCES 44

Table 2
Class Size Reduction Penalty
Under Senate Bill 311, 2004 New Flexibility: 2008-09 through 2001-12
Average number
of students per
class
Penalty Average number of
students per class
penalty
Up to 20.44 No penalty Up to 20.44 No penalty
20.45-20.94 20% penalty 20.45-21.44 5% penalty
20.95-21.44 40% penalty 21.45-22.44 10% penalty
21.45-21.84 80% penalty 22.45-22.94 15% penalty
21.85+ 100% penalty 22.95-24.94 20% penalty
24.95+ 30% penalty
The State also loosened restrictions on districts by suspending mandates that required
districts to purchase new instructional materials. On July 28, 2009, the Governor signed into law
Assembly Bill 2 of ABX4 2 stating that the State Board of Education is not to adopt K-8
instructional materials until at least 2013. The bill also states that Local Education Agencies are
not required to purchase the most recent instructional materials for their K-8 students. Prior to
2009, districts were required to adopt new instructional materials and textbooks every three to
four years. This change gave districts the ability to channel funds allocated for textbook
adoptions to other areas with more pressing need (California Department of Education, 2012).
Rules regarding the amount of required maintenance a district must complete to improve
its infrastructure have also been relaxed. The State has reduced the required contributions into
routine maintenance from 3 percent to 1 percent of a district’s general funds. The mandate that
required LEA to match the deferred funding for the maintenance program has also been
eliminated (Weston, California's New School Funding Flexibility, 2011).
In 2008, lawmakers reduced the number of required school days to lessen the fiscal
impact on school districts. Reducing the number of school days from 180 days to 175 days. By
operating 5 fewer days, districts were able to save on labor and physical plant costs. Most
ALLOCATION OF HUMAN RESOURCES 45

districts were able to negotiate with their labor unions and reduced the number of operating days
by providing staff members with furlough days (Edwards, Terry, Patel, Gonzales, & Perry,
2010).
The reductions on the amount of dollars districts must keep in their reserves have helped
districts manage with the current budget cuts. Before 2009, districts were required to keep 1
percent to 5 percent of their overall budget in a reserve account. The required reserve amount
was determined by the size of the district. In 2009, the state reduced the district’s required
reserve for economic uncertainty by two-thirds. For example, those who were required to keep 3
percent in their reserves before 2009 have only been required to keep 1 percent in their
reserves. This provision will be sustained through the 2012-13 school year. By reducing the
required amount of reserves, school districts will be immediately able to use the money and
apply it to its general fund.
Although provisions have been made to help districts and schools cope with the current
recession, it only acts as a Band-Aid. Districts struggle to make cuts in areas in which they
believe would make the least impact on student education. As California continues to struggle to
provide appropriate funding for its public schools, it is unclear how long districts and schools can
sustain continued reductions. It has become more critical for school districts and schools to have
a model to determine the essential resources needed to produce high achievements.
Gap Analysis
Districts are able to implement changes to resource allocation through clarification and
analysis of their current fiscal status, followed by implementing adjustments based on their
findings. The following chapter will draw together research that focuses on gap analysis
including the specific methodology that will be used to analyze the discrepancies between actual
ALLOCATION OF HUMAN RESOURCES 46

and idealized resource allocations. A summary of gap analysis processes and systems of analysis
will be presented in this chapter. The rationale for the use of gap analysis will follow in Chapter
3.
Using a gap analysis, this study will determine the differences between current district
allocation of resources, district ideals, and the EBM model. Gap analysis is an approach that
helps analyze an organization’s performance by comparing the district’s current performance
with the idealized performance. Clark and Estes (2008) argue that one’s knowledge, motivation,
and the organizational environment are the three components that influence all work
performance. Understanding each of the three components within an organization helps
determine causes for gaps and can in turn identify solutions to help achieve the desired
performances (Clark & Estes, 2008).
The gap analysis was developed by Clark and Estes (2008) as a guide for organizations to
select the appropriate performance solutions to increase productivity. Clark and Estes identified
six essential steps that organizations need in order to achieve results. The six essential steps are:
1) Identify key business goals, 2) identify individual performance goals, 3) determine
performance gaps, 4) analyzing gaps to determine causes, 5) identify solutions and implement,
and 6) evaluate the results to tune the systems and revise goals as needed. The following
discussion is an elaboration of each of the aforementioned steps.
Identify key business goals. Organizations must develop business goals that can be
clearly communicated to all stakeholders. Generally these goals are communicated in mission
statements and annual development plans. Clark and Estes (2008) describe the following six
procedural steps for setting business goals that are aligned with individual and team performance
expectations: 1) List the areas where one will set organizational goals and describe the indicators
ALLOCATION OF HUMAN RESOURCES 47

one will use to determine the achievement of each goal, 2) Benchmark and quantify the industry
leader’s achievement in each business area, 3) Quantify ones organization’s current achievement
in each business area, 4) Compute the gap by subtracting your achievement from the industry
leader, 5) Determine the economic benefit of closing the gap, 6) Identify individual and team
goals that will close each gap. The determined goals should be flexible so that adaptations can
be made to changing business conditions. These goals must be specific enough for all
stakeholders to comprehend the levels of performance required to achieve greater organizational
goals.
Identify individual performance goals. To support an organization’s overarching
business goals, every member of an organization needs individual performance goals that are
directly supportive of the organization’s goals. Clark and Estes (2008) state that goals must be
as concrete as they are clear, easily understandable, and measureable. The clarity of these goals
enables all stakeholders to understand what they must do in order for the organization to achieve
its goals. Goals provided to individuals must be challenging, maintaining a balance between
being difficult but achievable. Finally goals must be current. Research shows that short-term
daily or weekly goals are more motivating than longer-term monthly or annual goals.
Determine performance gaps. Once organizational goals or business goals are
determined, and current performance levels are analyzed, the organization can determine what
performance gaps exist. To quantify gaps in performances, Clark and Estes (2008) assert that
organizations must subtract the organization’s current performance level from its desired
level. By identifying these gaps, districts have a better understanding of the quantity of
performance increases needed to meet organizational goals.
ALLOCATION OF HUMAN RESOURCES 48

Analyze gaps to determine causes. By identifying the cause of the gap, an organization
would be able to implement the type of performance improvement program needed to close the
gap and achieve its goals. Clark and Estes (2008) concluded that the three main causes of
performance gaps are: 1) People’s knowledge and skills, 2) Their motivation to achieve the goal,
and 3) Organizational barriers such as lack of necessary equipment and missing or inadequate
work process.
Identify solutions and implement. Once the causes for the performance gaps have been
identified, appropriate solutions can be implemented. For performance gaps that are caused by
lack of knowledge and skill, Clark and Estes (2008) identified the following four possible
solutions: information, job aids, training, and education. Information is when an individual
shares any knowledge with other team members that will improve performance. Job-aids are
tools that assist employees, who have already acquired information, in job performance. An
example of a job-aid would be a reference manual where one can look to refresh their memory of
the steps and procedures needed to accomplish a task. Training is necessary when team
members need guidance on how to perform a task. Training provides them with opportunities to
practice and receive corrective feedback to help them achieve their goals. Education is required
when employees need to acquire knowledge and skills that would help them with future
challenges and problems. Education gives employees research based conceptual and theoretical
strategies that would allow them to be better problem solvers when a situation arises in the
future.
Performance gaps due to motivation are generally due to ones lack of direction,
persistence, and energy to accomplish the task at hand. Clark and Estes (2008) believes that
there are three types of motivational processes: active choice, persistence, and mental
ALLOCATION OF HUMAN RESOURCES 49

effort. Active choice is when someone actively pursues a goal. Persistence occurs when
someone continues no matter what distractions are in place of him or her. Mental effort is when
someone works smarter to find the appropriate solution. An individual’s mental effort is often
correlated with confidence in their abilities. To increase motivation, Clark and Estes (2008)
suggest adopting a culture where positivity, expectations and effective practices are
encouraged. A positive climate increases individual and team confidence. The correct climate
can foster trust among members of the organizations where team members work collaboratively
and value their work.
The last cause of performance gaps is organizational barriers that impede effective and
efficient work. With inadequate processes and materials, even those with the motivation and
knowledge will not be able to achieve their performance goals. Establishing an organizational
culture that aligns policies and procedures with the organizational goals results in diminished
organizational barriers. A culture that consistently communicates with all stakeholders about
plans and progress would reduce organizational barriers. Management’s involvement in the
improvement process would demonstrate a commitment to goals set forth by the organization as
well as reducing and eliminating barriers that can impede progress.
Evaluate Results, Tune System and Revise Goals
After identifying the causes of performance gaps and implementing appropriate solutions,
evaluation procedures need to be in place to determine the effectiveness of the
solutions. Evaluative procedures need to measure progress towards the organizational goals and
not just whether or not the goal was met. Once evaluations have been made, appropriate
adjustments can be implemented to ensure the success of the organization as it strives to meet its
goals.
ALLOCATION OF HUMAN RESOURCES 50

Summary
The literature review presented in this chapter represents four key areas of research that
form the basis for this study. First, existing strategies that have resulted in increased student
achievement were compared and contrasted for potential efficacy in relation to the schools
presented in this study. Secondly, an investigation of highly effective resource allocation
practices was used to illustrate budget allocations over time. The comparing and contrasting of
this highly effective resource allocation provides a framework to compare and contrast the
spending patterns of the schools in this study. Thirdly, research into state and federal policy
changes was used to describe the environmental conditions surrounding this study. Lastly, an
overview of gap analysis was provided as the context within which idealized and actual
budgetary allocations will be compared and contrasted. The following chapter will provide the
methodology to be utilized by this study, as well as procedures governing organization and
implementation.

ALLOCATION OF HUMAN RESOURCES 51

Chapter 3: Research Methodology
This study examined the dispersion of human capital resources within one elementary
school district in southern California and compared the use of personnel at each school to the
desired allocation informed by the district’s strategies and staffing formula. Current resource
distribution was compared to that of the Evidence-Based Model (EBM) to determine how the
district spent its funding in relation to the research-based recommendations from the EBM. This
rendered a research-based proposal to guide the district in aligning its allocation to that of the
EBM or an alternative, district-developed allocation strategy. By strategically allocating
personnel through research-based strategies, the district will likely be able to put into place best
practices to provide the necessary resources to raise student achievement.
This is a mixed methods study with a primacy on qualitative data. Quantitative data on
the resource allocation of one elementary school district were gathered. Qualitative data on the
district’s instructional vision, improvement plan, and professional development plan were
collected. Interviews of the district’s Assistant Superintendent of Human Resources, Assistant
Superintendent of Educational Services, and the Director of Curriculum and Instruction were
conducted. The district’s budget, policies and procedures on the allocated personnel, and its
strategic plan to improve student achievement were analyzed. Triangulation of the interviews,
the district’s current resource allocation, and its philosophy was conducted to determine the
congruency among how the district allocates resources, how leaders perceive they allocate the
resources, and how they want to allocate the resources.
A gap analysis was conducted to determine the difference between the district’s current
and desired allocation models as well as the difference between the district’s current allocations
to those of the EBM. This helped identify the gaps that needed to be filled to provide the proper
ALLOCATION OF HUMAN RESOURCES 52

resource allocation that supports best practices based on the EBM. In addition, an analysis of the
district’s knowledge, motivation and organizational barriers was conducted to identify why
current allocation did not meet the desired model or that of the EBM. This also helped identify
how the district could modify its current allocation to meet that of the EBM.
Research Questions
The following four questions were addressed by the study:
1. What research based human resource allocation strategies improve student achievement?
2. How are human resources allocated across Washington School District and its schools?
3. Is there a gap between current human resource allocation practices and what the research
suggests is most effective?
4. How can human resources be strategically re-allocated to align with strategies that improve
student achievement?
Sample and Population
This study focused on one elementary school district located in southern California. The
district was chosen based on the researcher’s interest in studying only elementary schools.
Pseudonyms were used to protect the anonymity of the district and its schools. Washington
School District was chosen upon the suggestion of Dr. Picus. At the time of this study, the
district consists of 13 elementary schools, three middle schools, and one Child Development
School. The Child Development School was not included in this study because it is a school that
serves primary students with special needs. For the 2011-2012 school year, there were 9,636
students enrolled in Washington School District. There were 405.5 equivalent teachers in the
district and a teacher-pupil ratio of 23.7. Hispanics or Latinos, who make up 42.1 percent of the
population, represented the largest group in the Washington School District. Students from
ALLOCATION OF HUMAN RESOURCES 53

Asian descent made up 39.3 percent and whites 13.3 percent of the population (ED-Data
Partnership, 2012). The tables below show the breakdown of certificated and classified staff
members employed in the Washington Elementary School District for the 2010-2011 school
year. It also shows how the district fared in relation to the county. Figure 6 indicates the
demographic analysis of students attending schools in the Washington Elementary School
District in comparison to the county.
Table 3
Certificated Staff in 2011-2012
Washington Elementary School District
District County
Number of
Staff
Full- Time
Equivalents
Per Pupil Ratio Per Pupil Ratio
Administrators 28 26 370.6 364.3
Pupil Services 54 47.2 204.2 296.4
Teachers 429 408.5 23.6 25.5
Source: ED-Data Partnership (2012).

Table 4
Classified Staff in 2011-2012
Washington Elementary School District
District County
Number of Staff Percent of Total Percent of Total
Paraprofessionals 177 32.1% 38.1%
Office/Clerical 59 10.7% 19.1%
Other 316 57.2% 42.9%
Source: ED-Data Partnership (2012)

ALLOCATION OF HUMAN RESOURCES 54

Figure 6. Students by Race/Ethnicity 2011-2012.Source: ED-Data Partnership (2012)
Instrumentation
To compare Washington School District’s resource allocation to that of the EBM, data
from the 2012-2013 school year were gathered from the district. This included enrollment
numbers along with the number of people within a position assigned to individual school sites.
The data were used to identify the gap between current personnel allocation within the district to
that which is recommended by the EBM.
Interviews of the district’s Assistant Superintendent of Human Resources, Assistant
Superintendent of Educational Services, and the Director of Curriculum and Instruction
identified goals, philosophies, and how they envisioned their resources’ being allocated. Staffing
formulas and strategies obtained within the interviews provided the numbers for desired staffing
allocations. These numbers were compared to that of the personnel actually allocated to the
ALLOCATION OF HUMAN RESOURCES 55

school sites. This comparison determined whether there was a discrepancy between the desired
and current allocations at the district’s school sites. Interviews with high-ranking district
personnel also identified organizational barriers that inhibited the district from allocating its
desired resources. A knowledge and motivation gap was also expressed as to why current
allocation and desired allocation differ from that of the EBM. The interviews also clarified titles
of positions and their duties and identified where each position fit into the EBM. This allowed a
direct comparison between the EBM and current allocation.
The EBM model created by Dr. Picus and his graduate student, David Knight, was used
to identify the gaps between current allocations of personnel to that of the district’s desired
allocation. Data collected from the district and each school’s School Accountability Report Card
(SARC) was applied to the EBM model. The model, with the appropriate formulas, computed
the necessary staffing based on the EBM. It also calculated the gap between the district’s current
allocation and that recommended by the EBM. In addition, a calculation of the gap between the
current allocation and the district’s desired allocation was made.
Data Collection
This research study was based on the framework that strategic resource allocation to
support research-based best practices is essential to increasing student achievement, and the
EBM is the best model that provides the appropriate allocation of resources. The initial process
will start with the researcher contacting prospective districts to request their participation. Once
a district is chosen, an introductory phone conversation was conducted with the district’s
Assistant Superintendent of Human Resources, wherein a detailed explanation of the research
methods and a list of required data was requested.
ALLOCATION OF HUMAN RESOURCES 56

In the summer of 2012, face-to-face interviews were conducted with the Assistant
Superintendent of Human Resources, Assistant Superintendent of Educational Services, and the
Director of Curriculum and Instruction to gather the data from the district. Information such as
the enrollment at each school and the personnel allocated at each school was collected.
Clarification of job descriptions and titles helped with the dissemination of the data to fit the
EBM. The interviewees were also asked to provide more descriptions of the district’s vision,
staffing formulas and strategies. This information determined the desired resource allocation of
the districts. Policies and procedures on how the district allocated resources needed to be
explained to help clarify how organizational changes could and could not be made within the
district.
After the interview, data were entered into the EBM simulation provided by Dr. Picus.
Anonymity of schools and interviewees were protected with false identification. Examples of
some of the data entered include the schools’ grade-by-grade enrollment, students’ demographic
characteristics, and personnel assignments such as teachers, coaches, tutors, and counselors.
This study also included open-ended interview questions. Being one of 18 studies
conducted in coordination with a thematic dissertation group at the University of Southern
California, all questions to interviewees were similar. Questions about how the district
responded to the decrease in funding and how this affected leadership’s plans to increase student
achievement were asked of the interviewees. How staffing was determined at the district level
and how much flexibility a site had when allocating resources was also clarified in the
interviews. Obstacles impeding the district’s progress towards goals was also discussed in the
interviews.

ALLOCATION OF HUMAN RESOURCES 57

Data Analysis
The data gathered from the interviews provided information on the district’s leadership’s
vision as to how allocation of personnel resources supports instructional strategies. Interviews
also helped to clarify the policies and procedures in place to help achieve the goal of improving
student achievement. The Evidence-Based Model was used to compare the district’s allocation
of resources to that of the researched base model.
After all interviews were conducted and all the data acquired, the data were entered into a
pre-formulated model provided by Dr. Picus. After the data were entered into the model, the
pre-formulated model calculated the gaps between how the district allocated resources and
leaders’ desired allocations based on their formulas and strategies. An analysis of the gap
between the desired model and the EBM will also be calculated. Additionally, the gaps between
how the district currently allocates their resources and the allocation suggested by the EBM were
configured with the same model.
A follow-up interview with the district’s Assistant Superintendent of Human Resources
was conducted to convey the study’s findings. Clarification from the interviewees about the
discrepancies between the district’s staffing formula and what is currently allocated helped
determine whether the gaps in the model were due to organizational, knowledge or motivational
reasons. An analysis of how the district’s leaders can modify their current staffing to meet the
EBM was made and recommendations to the district were based on the analysis.

ALLOCATION OF HUMAN RESOURCES 58

Chapter 4: Data Analysis and Interpretation of Findings
This chapter presents the findings of this study. The first section of this chapter provides
an overview of the district and the schools that participated in this study. The summary includes
the characteristics of the district and its schools, including resource allocation and performance
data. The second section of this chapter presents the findings as they relate to each of the
following four research questions:
1. What research based human resource allocation strategies improve student
achievement?
2. How are human resources allocated across Washington School District and its
schools?
3. Is there a gap between current human resource allocation practices and what the
research suggests is most effective?
4. How can human resources be strategically re-allocated to align with strategies that
improve student achievement?
Overview of Districts and Schools
This section provides an overview of the district and schools that participated in this
study. The Washington School District is a Kindergarten through eighth grade school district
located in northern Orange County, California. The district serves approximately 9,621 students
at 17 schools sites. Washington School District has 13 elementary schools, three middle schools,
and one Child Development school. The Child Development School was not included in this
study because it is a school that serves primary students with special needs. The diverse student
population of Washington school district comes from four different cities in the surrounding
area.
ALLOCATION OF HUMAN RESOURCES 59

Like many districts in California, Washington school district experienced declining
student enrollment for several years. Figure 7 shows Washington School District from 1996
through 2012.

Figure 7. Washington School District Student enrollment. Source: California Department of
Education
Washington School District serves an ethnically diverse population. The student
population is 41.5% Hispanic or Latino, 39% Asian, 13.7 White, 1% African American, 0.8%
Naïve Hawaiian or Pacific Islander, 0.6% Filipino, and 0.3% American Indian or Alaska Native,
and 2% students of two or more races.
Close to half the students attending the Washington School District are English Learners.
Fifty-three percent of the EL population consists of Spanish speakers and 44% of the EL
population speaks Vietnamese. Seventy-three percent of the students in the Washington School
district are socioeconomically disadvantaged. Table 4.2 presents the total population and the
percentages of English Language Learners, Special Education Students, and Socioeconomically
Disadvantaged students at each site.

ALLOCATION OF HUMAN RESOURCES 60

Table 5
School Population Demographic in WSD
School Total % ELL % SPED % SED
1. 673 88.0% 1.5% 87.0%
2. 536 40.0% 2.1% 51.0%
3. 478 80.0% 1.7% 84.0%
4. 521 22.0% 6.1% 30.0%
5. 437 81.0% 4.8% 91.0%
6. 453 67.0% 4.0% 77.0%
7. 896 82.0% 2.9% 78.0%
8. 724 79.0% 1.5% 80.0%
9. 511 84.0% 5.9% 88.0%
10. 598 26.0% 1.5% 32.0%
11. 415 46.0% 5.8% 55.0%
12 381 80.0% 4.2% 87.0%
13 400 83.0% 3.8% 93.0%
14 714 74.0% 18.2% 83.0%
15 824 49.0% 13.0% 61.0%
16 997 83.0% 7.0% 84.0%

Student achievement. The Washington School District made gradual growth
academically. Figure 8 shows the district’s steady rise in Academic Performance Index (API)
from 2005 to 2012. The API is an annual measure of test score performance of schools and
districts. Results of the Standardized Testing and Reporting (STAR) program and the California
High School Exit Exam (CAHSEE) are used to calculate the API.

ALLOCATION OF HUMAN RESOURCES 61

Figure 8. WSD Academic Performance Index 2005-20012. Source: California
Department of Education.
Under the No Child Left Behind Law, the district and its schools must show growth in
the percent of students scoring proficient or advance in English/Language Arts and Math.
Federal law requires schools, districts and the state to demonstrate this growth through its
Annually Yearly Progress (AYP). Annual Measurable Objectives (AMAOs) are targets that
California has set for districts and schools to achieve for it to meet its AYP. For the 2011-2012
school year, 78.4% of students must score proficient or advance in English/Language Arts on
state testing to meet AYP. In mathematics, 79% of students must score proficient or advance on
their state test to meet their AYP. Figures 9 and 10 below show the district’s growth in Annual
Yearly Progress (AYP) in both language arts and mathematics from 2002 to 2012. The graph
shows the percent of students who had scored proficient or advance in language arts and
mathematics for the given year. Although the district made some gains, it did not see enough
growth to meet its annual measurable objectives. At the time of this study, the district was in
700

720

740

760

780

800

820

840

860

2005
2006
2007
2008
2009
2010
2011
2012

API
Growth
2005-‐2012

ALLOCATION OF HUMAN RESOURCES 62

Program Improvement (PI) for not reaching annual yearly progress goals for two consecutive
years.

Figure 9. WSD Percent Proficient and Advanced in English Language Arts. Source:
Ed-Data

Figure 10. WSD Percent Proficient and Advanced in Mathematics. Source: Ed-Data
Washington School District’s vision states it aims to provide “High academic
achievement, health, safety and well-being for all Washington School District students.” The
ALLOCATION OF HUMAN RESOURCES 63

mission statement states that its goal is “to empower students to become lifelong learners and
fulfilled, productive citizens in a changing world.” Table 4.6 below provides the Academic
Performance Index (API) for each school in the sample district over the three years prior to this
study. Although the majority of schools within the sample district have experience gains on its
API over the last three years, it does not necessary mean that it would meet its AYP. Each
school must meet the AMOs in order to make AYP. Under NCLB, schools must also show
growth within its numerically significant subgroups to make AYP. Significant subgroups may
include ethnic groups, socioeconomically disadvantaged students, English learners and students
with disabilities.
Table 6
WSD API by School
School # 2012 Met
AYP?
API 2010 API 2011 API 2012 3 Year Change
1. No 829 789 794 -35
2. No 847 888 887 +40
3. No 817 793 798 -19
4. Yes 888 887 906 +18
5. No 763 773 796 +33
6. No 814 825 839 +25
7. No 858 872 888 +30
8. No 817 835 831 +14
9. Yes 765 808 828 +63
10. No 896 904 929 +33
11. No 860 865 868 +8
12 No 799 780 812 +13
13 No 752 753 N/A +1
14 No 794 772 788 -6
15 No 799 798 840 +41
16 No 851 846 864 +13

The description of the sample district’s demographic and student achievement was meant
to provide the reader with an understanding of the sample district. The information will also
help the reader have a firmer understanding to this study’s research questions and answers as it
ALLOCATION OF HUMAN RESOURCES 64

relates to the sample district. The following section of the chapter will present this study’s
findings
Research Question #1: What research based human resource allocation strategies improve
student achievement?
This section reviews the four common strategies found in research to improve student
achievement. As stated in Chapter 2, successful school reforms include strong leadership, the
use of assessments and data-based decision making, collaboration, and effective professional
development. This section also includes a description of how successfully the sample district has
implemented these strategies.
Leadership. The importance of strong leadership has been expressed throughout studies
as a vital component to the improvement of student achievement. A strong leader is one who is
capable of communicating a clear vision as well as establishing goals and implementing
strategies to help achieve them. Leaders are able to assess the organization and implement
change that will move the organization forward. Literature has also shown the evolution of
leadership as one of shared practiced where a team consisting of administrators, teachers and
staff members all play an integral role in assessing, developing, and implementing change within
the organization to cultivate a school culture with high student achievement (Togneri &
Anderson, 2003; Reeves, 2003; Marzano et. al, 2005; Duke, 2006, Bolman and Deal, 2008;
Odden, 2009).
The sample district employed some of these leadership strategies. At the time of this
study, one interviewee disclosed that administrators in the district participated in a three-day
summer program to plan for the future as well as to clarify the vision and goals for each site.
Leadership from the California School Employees Association (CSEA), Parent Teacher
ALLOCATION OF HUMAN RESOURCES 65

Association (PTA), and the Westminster Teacher Associations (WTA) were invited to help
ensure that the goals of the district were communicated and were aligned with those of the
participating stakeholders. Every Tuesday morning, the district conducted a meeting for all
Principals in the district meet and district administrators to review logistical plans. For the 2012-
2013 school year, the district implemented Principal Academies for principals within the district
to meet after school to receive professional development on instructional strategies and
curriculum. Throughout that year, principals also walked each other’s campuses to familiarize
themselves with how other schools within the district implemented the programs and strategies
to achieve their goals.
Washington School District also implemented programs that allow for teachers to take on
leadership roles. Each school implemented the philosophy of a Professional Learning
Community (PLC). A leadership team comprised of one teacher from each grade level or
department heads in the middle schools and the administrators made up the Schools Leadership
Team (SLT). At the time of this study, the SLT members met monthly to review data and make
decisions to move the school forward and achieve goals. By the end of the academic year, each
leadership team met with the Educational Service Team at the district office to deliver an hour-
long presentation regarding goals and the progress made towards them. The Educational Service
Team was made up of administrators in charge of Categorical Programs and Assessments, Child
Development, Safe and Healthy School, After School Programs, Special Education, along with
the director of Curriculum and Instruction. Teachers serving on the SLT received a $500 stipend
for their time.
Although the sample district implemented programs and a philosophy to enhance
leadership, it still saw need for improvement. One leadership area needing the most support was
ALLOCATION OF HUMAN RESOURCES 66

each site’s SLT. The SLT philosophy was implemented in the district in the 2008-2009 school
year as a corrective action for schools entering program improvement (PI). At that time, only
four schools in the district implemented the SLT concept, and those schools received two years
of training with Judy Cunningham, a Professional Learning Community expert. Teams met with
Ms. Cunningham four times a year for support in their implementation process. The district
implemented SLTs at schools within the district. Within two years, all schools in the district had
School Leadership Teams. The difference in the implementation was that the remaining schools
did not receive the support of Judy Cunningham. They were supported by district personnel. The
Director of Curriculum and Instruction indicated that each school’s SLT was different in
operation. Some schools were further along in the process and met more regularly. The strength
of SLT implementation relied on the principals’ ability to empower the team to work towards a
common goal. To ensure the fidelity of the SLT, the district needed to provide additional
coaching from Judy Cunningham. With her expertise, she would have been able to help the
principal empower the teachers to set goals, create a plan towards them, and implement a
monitoring process to gauge the team’s progress. The district also needed to make the SLT
meetings mandatory and more frequent. A system that trains SLT members was also needed
because new members often joined the team when the other members decided not to take on the
position.
Assessment and data-based decision making. Research has also shown that data based
decision making is essential to the success of school reform. Schools that were successful in
raising student achievement put in place a system where data was used to identify the current
state of a school, set goals for improvement, align resources and drive instructions. School
districts also invested in an information management system that allowed them to collect the data
ALLOCATION OF HUMAN RESOURCES 67

and help in the dissemination of the data. To build capacity, successful districts also provided
professional development to staff members to ensure everyone understood how to use the system
and correctly read the data it provides.
The sample district invested resources to move towards a data-based decision-making
culture. According to the Director of Curriculum and Instruction, the district and its schools
looked at multiple sources of data. The results from the California Standardized Test (CST),
district benchmark assessments, Dibbles, Read 180, and the scores on the Annual Measurable
Achievement Objectives were analyzed. Because it is a Positive Behavioral Intervention
Support (PBIS) district, leadership also looked at attendance and discipline data to identify areas
in need of improvement. During the 2009-2010 academic year, the district switched over from
using Edusoft and adopted School City as the assessment management system that collected its
data. The results from summative assessments such as state testing and the district benchmark
assessments were collected and desegregated using School City. The system also provided
teachers with the opportunity to create formative assessments. Aeries was the student
information software used by the district to store students’ attendance and grades. School Wide
Information System (SWIS) was the software that the district used to monitor students’
discipline and to collect information on students with Individualized Education Plans (IEP). To
help support the software the district implemented, each school site also had a classroom teacher
who served as the technology coordinator and another teacher who served as an assessment
coordinator. These teachers were paid an extra stipend for their positions.
The district made strides in becoming a district that used assessments and data to drive its
decision-making but it still had much room for growth. At the time of this study, the district had
benchmark assessments in the areas of English Language Arts and Math but needed to create
ALLOCATION OF HUMAN RESOURCES 68

them for Science and Social Science. These benchmark assessments were only given twice a
year at the end of the trimester, making them more summative assessments rather than formative
assessments. School City, the data gathering system, had the capacity to create formative
assessments, but teachers did not have the knowledge or skill to create these assessments on the
system. When School City was adopted in 2009, only the site principals received an overview
training of the system. More training was needed for all teachers at the site so that they could
use the system to create formative assessments for immediate feedback on the isolated standards
in which students required further scaffolding. The district was also in need of investing in a
system with the capacity to accumulate information from all its data sources or of replacing the
systems with one capable of gathering all the information. With enough training, such a system
would be more user friendly, and the teachers may be more motivated to use the technology at
hand.
Collaboration. As data based decision-making becomes the cultural norm within an
organization, collaboration among colleagues is cultivated. Sharing outcomes with one another
allows teams to identify strengths and weaknesses. Collaboration allows instructional leaders to
share best practices for the classroom in order to raise student achievement. Teams can build on
their strengths and realign resources to support areas that need further growth.
Time for teacher collaboration in the sample district was provided weekly at the time of
this study. Every Wednesday, students were dismissed approximately an hour and forty-five
minutes earlier at the elementary level. At the middle school level, there was an additional hour
and thirty minutes on Wednesday for teachers to collaborate. Each school site also had a
leadership team made up of grade level leaders or department chairs that met with the
administrators once a month.
ALLOCATION OF HUMAN RESOURCES 69

The district made a conscious effort to provide time for teachers to collaborate, but due to
the collective bargaining agreement between the teachers association and the district, teachers
were not required to meet with their teams during early release Wednesday. According to the
Director of Curriculum and Instruction, teachers were using the early release time to plan and
were not required to stay on campus to plan. They had the ability to leave campus early and plan
at home. Although he indicated that some teams collaborated during their time, many did not.
He also stated that some SLTs were stronger than others and collaborated more often than others.
Professional development. Another component that research has shown to have a
positive impact on raising student achievement is providing quality professional development, as
doing so increases the knowledge and skills of those within the organization so that they can
move the organization from where it is to where it wants to be. Effective professional
development should be school-based and job-embedded rather than consisting of one-day
workshops and the duration should be at least 100 hours annually. This ongoing process would
ensure that the change in practice that is needed to increase student achievement will be
sustainable and in time become a part of the culture of the organization.
Providing mentors or coaches is one strategy that has had a positive effect on the
instruction provided within the classroom. Teachers are more likely to retain and adopt the
learned strategy because they are receiving ongoing support and feedback throughout its
implementation. This type of collaboration model allows for dialogue among colleagues so that,
together, they can problem-solve and find ways to best adapt their current resources to meet the
needs of their students. Teachers are more likely to have a stronger understanding of the purpose
of the new strategies, as they are a part of the change process with the support of experts
(Showers, 2002).
ALLOCATION OF HUMAN RESOURCES 70

Like most district, the sample district made some changes as to how it provides
professional development to its teachers. Due to the budget cuts, the district took on additional
furlough days. The workdays that were taken off the calendar were generally days when the
district provided professional development to its teachers. School-wide professional
developments, at the time of this study, were provided four times a year on early release
Wednesday. The budget cuts also limited the district’s ability to contract professionals to
provide professional development. Staff members within the district provided the majority of
the trainings. Middle school teachers were also given the opportunity to receive Sheltered
Instruction Operation Protocol (SIOP) through an online training and were given stipends for
their time spent receiving the online training. A few times a year, principals also provided
professional development at their sites on non-workdays. Teachers who attended these trainings
received a stipend comparable to their one day of work.
Through a categorical grant that the district received, it hired eleven instructional coaches
to support all the schools within the district. These Instructional Support Specialist (ISS) were
classroom teachers within the district. They were paid on the same teacher salary schedule as
other teachers in the district and maintained their tenure status. Their goals were to support the
district in its transition to the common core, to support staff members in the use of technology,
and to support the implementation of instructional strategies adopted by the district. The ISS
team members started the year in a service delivery model of support for four schools within the
district. They worked closely with the schools’ SLT to help the school reach its goals. The
Director of Curriculum and Instruction chose these four schools because they were the four
schools that would most likely accept the assistance of the ISS team. He wanted the ISS team to
succeed before they were asked to help other school sites. As of March of the 2012-2013 school
ALLOCATION OF HUMAN RESOURCES 71

year, the ISS adopted the lesson study model. The ISS team members worked closely with a
teacher from each grade level at a school site to help plan and teach a lesson. The ISS member
taught the lesson to the class while the teacher observed. A debrief about the instructional
strategy used followed the lesson. Later in the day, the classroom teacher taught a lesson using
the same instructional strategy while the ISS team member observed. Feedback was given to the
classroom teacher at the end of the day. The following day, the same ISS team member met with
another teacher within the same grade level at the site and replicated the process. This coaching
model was repeated until all the teachers at that grade level received coaching.
With their Principal Academies and the ISS team, district leadership planned to provide a
great deal of support in the area of professional development to its teachers. To improve
instruction and raise student achievement, the sample district must require all teachers to be
trained during the non-work professional development days. This ensures that the district and its
teachers have the common knowledge and skills necessary to improve student achievement. The
ISS team would support with the implementation of the learned strategies from the professional
development.
Summary: Research Question #1
The first question of this study asks which research-based human resource strategies
increase student achievement. As mentioned in Chapter Two of the study, leadership,
assessment and data based-decision making, collaboration and professional development have a
great deal of impact in raising student achievement. This section identified how the sample
district allocated its resources in these four areas. Opportunities for growth in these four areas
were also identified and suggestions were also made for improvement. The following sections of
ALLOCATION OF HUMAN RESOURCES 72

this chapter discusses how the district allocated its resources at the time of this study and
presents recommendations for practice.
Research Question #2: How are human resources allocated across Washington School
District and its schools?
This section looks at the sample district and how it allocated its human resources across
the thirteen elementary schools and three middle schools. Staffing information is provided for
management, certificated teaching staff, certificated staff providing non-academic pupil support,
classified staff providing instructional support and classified staff providing non-instructional
support. Definitions are provided for each position as characterized by the Evidence-Based
Model (EBM) (Odden, Picus, & Goetz, 2010). In cases where the sample district categorizes
positions differently from the EBM, a description of the position is also provided.
Management. Management consists of site principals and assistant principals.
Principals oversee the day-to-day operation of the school, and, for the sample district, they
served as the primary provider of professional development. The assistant principal’s role was to
support the principal. Assistant principals were generally responsible for student discipline,
assessment and accountability, and monitoring of instruction. The sample district had one
principal at each site at the time of this study. At the elementary level, there was one assistant
principal. One elementary school had a Teacher on Special Assignment (TOSA) whose job
responsibility was similar to that of an assistant principal. Every middle school had one assistant
principal. Table 4.7 and 4.8 below present the management staff at the elementary and middle
schools in the sample district.

ALLOCATION OF HUMAN RESOURCES 73

Table 7
Management Staff, Elementary School
Schools Enrollment Principals Assistant Principals
1. 673 1.0 0
2. 536 1.0 0
3. 478 1.0 0
4. 521 1.0 0
5. 437 1.0 0
6. 453 1.0 0
7. 896 1.0 1
8. 724 1.0 0
9. 511 1.0 0
10. 598 1.0 0
11. 415 1.0 0
12 381 1.0 0
13 400 1.0 0
Total 7023 13 1
Avg. per Site 540.2 1.0 0.0625
Student Ratio N/A 540.2 :1 7023:1
Table 8
Management Staff, Middle School
Schools Enrollment Principals Assistant Principals
14. 714 1.0 1.0
15. 824 1.0 1.0
16. 997 1.0 1.0
Total 2535 3.0 3.0
Avg. per Site 845 1.0 1.0
Student Ratio N/A 845:1 845:1
Certificated teaching staff. Elementary teachers possess a multiple subject teaching
credential. A multiple subject teaching credential, as defined by the California Department of
Education, authorizes the holder to teach in self-contained classrooms and to serve in a core- or
team-teaching setting. The sample district had 363.5 teachers for its 13 elementary schools and
98 teachers in its middle schools. The average student to teacher ratio was 19.3 students per
teacher in the elementary grades and 25.9 students per teacher in the middle school grades.
ALLOCATION OF HUMAN RESOURCES 74

Specialist teachers. Specialist teachers are teachers who teach subjects that are outside
the core subject areas such math, English, science, and history. Specialist teachers generally
teach physical education, music, art, and woodshop. There are 19 specialist teachers currently
employed in the sample school district. All but one specialist teacher are at the three middle
schools. One elementary school site has a music teacher on its staff.
Special education teachers. In this study, special education teachers provided
instruction to students with mild to moderate learning disabilities who have trouble in one or
more areas of classroom learning. Special education teachers provide students with
accommodations and modifications for students based on their Individual Education Plan (IEPs).
Non- Severely Handicap Teachers and Resource Specialist Program (RSP) teachers worked with
students with special needs in the sample district. There were 11 non-severely handicapped
teachers and 21 RSP teachers providing services to students with special needs in the sample
district. Table 4.9 below presents the number of core, specialist and special education teachers at
each site.

ALLOCATION OF HUMAN RESOURCES 75

Table 9
Number of Core, Specialist and Special Education Teachers
School
Core
Teachers
Specialist
Teachers
Special
Education
Staff
1. 24 0 1
2. 20 0 1
3. 17 0 1
4. 18 0 3
5. 17 0 1
6. 16 0 1
7. 32 0 4
8. 27 0 1
9. 18 0 1
10. 21.5 0 1
11. 15 0 1
12 14 1 1
13 15 0 1
14 25 2 5
15 25 6 5
16 27 10 4
Total 330.5 19 32
% of Teaching
Staff 87% 5% 8%
Average per Site 20.65 1.19 2
Student Ratio 28.9:1 503.1:1 298.7:1
Academic help staff. Reading Teachers provided individual and/or small group reading
instruction to students by adapting the curriculum to meet the needs of these students. They
worked with the classroom teachers to evaluate students’ academic and social growth as related
to reading and developed a plan to help students recognize learning, heath, and attitude
problems. Reading teachers also communicated with parents through a variety of means. The
sample district employed 7.6 reading teachers who worked in 10 of their 13 elementary schools.
The sample district also employed a Child Development Program (CDP) Leader II. This
person was responsible for supervising, managing, and providing an education program for
children between the ages of eighteen months and five years and was also in charge of CDP
ALLOCATION OF HUMAN RESOURCES 76

Leader I. There were 1.38 people working as CDP Leader II at two elementary schools in the
district.
Instructional coaches. For the 2012-2013 school year, the district hired 11 instructional
coaches. These Instructional Support Specialist (ISS) provided support to all 16 schools within
the district. Their goals were to support the district in its transition to common core, to support
staff members with the use of technology, and to support the implementation of instructional
strategies that the district adopted. With a student population of 9,558, there were 0.69 full time
equivalent instructional coaches for every site.
Extended day staff. In the sample district, the staff included the Extended School
Program (ESP) Site Supervisor, the ESP Leader II, and the ESP Leader I. The ESP supervisor
supervised the activities of assigned personnel; planned and directed educational, recreational, and
child development programs for school-aged children; and managed a site budget. The ESP Leader
II was responsible for directing, managing, and providing both childcare and instructional
activities for students in the Extended School Program. They may also have been responsible for
directing other personnel in the Extended School Program. The ESP Leader I was responsible
for providing custodial care and the supervision of students in the Extended School Program.
In the sample district, there were 642 students attending the Extended School Program.
There were 7.49 ESP site supervisors working at eight elementary schools in the Extended
School Program and one ESP supervisor working at the district office to oversee the program.
There were 5.69 people in the ESP Leader II position and 8.175 people in the ESP Leader I
position in eight elementary schools. Table 4.10 below shows the number of academic help
staff, instructional coaches, and extended day staff at each site.
ALLOCATION OF HUMAN RESOURCES 77

Table 10
Academic Help Staff, Instructional Coaches and Extended Day Staff
School
Academic
Help Staff Instructional Coaches Extended Day Staff
1. 1 0.69 0
2. 1.44 0.69 2.35
3. 1 0.69 1.64
4. 0.44 0.69 2.91
5. 1 0.69 0.71
6. 0.4 0.69 3.07
7. 0.5 0.69 3.45
8. 0.5 0.69 1.76
9. 1 0.69 0
10. 0 0.69 3.53
11. 0 0.69 1.93
12 0.8 0.69 0
13 1 0.69 0
14 0 0.69 0
15 0 0.69 0
16 0 0.69 0
Total 9.08 11 21.35
Average per Site 0.57 0.69 1.33
Student Ratio 1053.2:1 868.9:1 447.7:1
Nurses. There were three district nurses who provided health service to the students at
the 16 sites in the district. They worked collaboratively with the health assistants at the school
site level to assess the health needs of students. They worked with students’ parents and
physicians to create emergency care plans and individual health plans for students with special
needs. They also served as a resource to parents and staff to help identify health problems for
referral for proper treatment.
Certificated non-academic pupil support staff. There were 7.6 psychologist providing
diagnostic, prescriptive, consultative and counseling services to students at six sites in the sample
district. They administered assessments to students to determine whether or not they had
learning disabilities that would qualify them for extra academic services.
ALLOCATION OF HUMAN RESOURCES 78

Counselors are other pupil support staff members who provide services to students in the
sample district. Counselors in the sample district attended Student Study Team (SST) meetings
to provide consultation to parents, teachers, and staff as to what intervention procedures were
need to support at-risk students. They were also available for immediate intervention in crisis
situations such as a death in a family, terminal illness, child abuse, rape, violent crimes involving
family members, and environmental disasters. Counselors coordinated services with district
nurses, district psychologists, and intervention program teachers. There were four counselors
employed in the sample district. Two of the counselors were assigned to two of the 16 sites in
the district and two are at the district office supporting the rest of the schools in the district.
Speech Teachers also provided non-academic support to students in the district. They
provided auditory training to students needing support with their communication skills and
language development. They worked with the teachers and parents in writing Individual
Education Plans (IEP) for children to whom they provided services. There were 10.6 speech
teachers working at 11 sites in the district. There was also a speech and language assistant with a
full time equivalent of 0.9375 working at one site in the sample district.
At one elementary school, there was one Teacher on Special Assignment (TOSA) who
performed all the duties of an assistant principal, with the exception of employee evaluations.
The TOSA helped with student discipline, coordinated assessments, gathered assessment data,
and supported the principal in running the school. Table 4.11 below shows the number of
nurses, counselors, psychologists, speech teachers and Teachers on Special Assignments at each
site.

ALLOCATION OF HUMAN RESOURCES 79

Table 11
Nurses, Counselors, Psychologists, Speech Teachers and TOSA
School Nurses Counselors Psychologists
Speech
Teachers
Teacher on
Special
Assignment
1. 0.19 0.14 0 0.8 1
2. 0.19 1 3 0 0
3. 0.19 0.14 1 1 0
4. 0.19 0.14 1 0.8 0
5. 0.19 0.14 0 0 0
6. 0.19 0.14 1 1 0
7. 0.19 0.14 0 0 0
8. 0.19 0.14 0 1 0
9. 0.19 0.14 0 1 0
10. 0.19 0.14 0.6 0 0
11. 0.19 0.14 0 1.94 0
12 0.19 0.14 0 1 0
13 0.19 0.14 0 0 0
14 0.19 1 0 1 0
15 0.19 0.14 0 1 0
16 0.19 0.14 1 1 0
Total 3 4 7.6 11.53 1
Average
per Site 0.19 0.25 0.48 0.72
0.06
Student
Ratio 3186:1 2389.5:1 1257.6:1 828.4:1
9558:1

Classified staff. Para educator/Specialized Health and Instructional Assistants assisted
teachers or specialists in providing instruction to students in a special education learning
environment.
Special education aides. Special education aides monitored and reported student
progress, behavior and performance. They also performed special physical health procedures for
students. Under the direction of a credentialed school nurse, they maintained health records and
files. There were 19.9125 Para educator/Specialized Health and Instructional Assistants
employed in the sample district at the time of this study.
ALLOCATION OF HUMAN RESOURCES 80

The sample district also employed 63.5 people with the titled of Para-educator
Instructional Support and 11 with the title of Instructional Support Special. Under the
supervision of a teacher or specialist, they provided instruction to students in a special education
learning environment. They also monitored and reported student progress, behavior and
performance. Para-educator Instruction Support and Instructional Support Special staff members
worked with students with mild to moderate disabilities.
Under the direction of a certificated Special Education Teacher experienced in autism,
the Lead Special Education Caseworker assisted with the coordination of the Discrete Trial
Training (DTT) program. This person coordinated with the preschool assessment team
regarding placement of students in the DDT program and obtained information to set up the
program from the Individual Education Plan. The lead special education caseworker also
conducted scheduling and other organizational duties necessary for the functioning of the
program and oversaw activities of Special Education Caseworkers while providing training and
instruction to them. The Special education caseworkers worked with students in a specialized
program such as the DTT. There was one Lead Special Education Caseworker working at one
elementary site in the sample district. There were 7.425 Special Education Caseworkers working
at two sites in the sample district.
Instructional aides. Instructional Computer Assistants provided instructional assistance
to individual or small groups of students in a learning environment that utilized computer
equipment. They provided instruction in the care and use of computer hardware and software.
Instructional Computer Assistants monitor and report student progress relative to students’
behavior and performance to teachers and school administrators. They also provided computer
ALLOCATION OF HUMAN RESOURCES 81

technology assistance to staff. There were 9.4375 Instructional Computer Assistants working at
16 sites in the sample district.
The person holding the title of Child Development Program Leader (CDP) II was
responsible for supervising, managing, and providing an education program for children between
the ages of 18 months and five years. This person was responsible for providing
developmentally appropriate educational programs and activities for pre-school aged children.
The Child Development Program Leader II also directed the activities of the Child Development
Program Leader I. A Child Development Program Leader I assisted the CDP II by providing
developmentally appropriate education programs and activities for children of pre-school age.
They also ensured that discipline and safety procedures were maintained in an appropriate
manner. There were 1.375 CDP II working at two sites in the district and 11.101 CDP I working
at 10 sites in the sample district.
Library technicians and paraprofessionals. Library and Media Assistants assisted
students in the acquisition, distribution and collection of library books, resource materials and
textbooks. They assisted students in learning library skills and research skills. Library and
Media Assistants also scheduled use of libraries and kept inventory of the resources available
from the library. There were 10.566 Library and Media Assistants working at 16 sites in the
sample district.
Non-Instructional Aides. The Instructional Assistant for Community Based English
Tutoring (CBET) supervised small groups of infants and children of Adult Education students
attending CBET classes. They communicated with families in a designated second language and
assisted the classroom teacher in the adult English as a Second Language (ESL) class. There
were 1.0375 FTE Instructional Assistant (CBET) working at two sites in the sample district.
ALLOCATION OF HUMAN RESOURCES 82

Health Service Assistants worked under the direction of the site administrator and the
technical support of the District nurse. They provided health services to students at their school
site as well as maintained health records, referrals and reports. The Health Service Assistants
administered routine first-aid and assisted in screening ill or injured students. They also assisted
with health testing programs and other health services. There were 5.40625 Health Service
Assistants working at 12 sites in the sample district.
Community Liaison workers coordinated communications and dissemination of
information among the school, home, and the community. They facilitated home and community
understanding of school programs and objectives and secured parent involvement in school
activities. Community Liaisons worked to develop and maintain effective working relationships
with individuals, community groups and social service agencies. They were under the direction
of the site administrators. There were 10.56 Community Liaison workers working at the 16 sites
in the sample district.
Office managers, secretaries, registrars and clerks. Office Managers worked under
the direction of the site administrators. They performed a variety of secretarial and
administrative aide duties relative to the organization and management of school activities at a
school site. Office managers facilitated communications between faculty, students, parents,
administrators and the community. There was one office manager at each school site in the
district.
Staff Secretaries, Senior Clerk Typists, Intermediate Clerk Typists, and Clerk Typists
supported the Office Managers. They assisted with secretarial and clerical duties and helped
plan and organize office activities and relieve the supervisor of administrative and clerical
details. Secretaries and clerks typists answered phones, filed, and maintained records. There
ALLOCATION OF HUMAN RESOURCES 83

was one Staff Secretary working at one middle school in the district. There were 2.45 Senior
Clerk Typists working at five school sites, 2.9875 Intermediate Clerk Typists at three sites and,
and 0.7 clerk typist at one elementary school in the sample district.
Intermediate Account Clerks performed a variety of accounting clerical duties. They
maintained financial records and prepared reports. Account Clerks also prepared and processed
financial and statistical documents, reports, and materials. There was only one intermediate
account clerk at the school site level in the sample district.
The Registrar worked under the direction of the site administrator. This person
performed a variety of duties related to attendance, accounting, and record-keeping. Registrars
contact parents or guardians relative to excused and unexcused student absences. They also
maintained cumulative files on all students and operated the District’s computerized records
management system to enter and update attendance data. There were three Registrars working in
the sample district, one at each middle school site. Table 4.12 below shows the number of
classified staff members and their positions at each site.

ALLOCATION OF HUMAN RESOURCES 84

Table 12
Classified Staff
School
Special
Ed.
Aides
Instructional
Aides
Library Techs.
Paraprofessional
Non
Instructional
Aides
Secretaries/
Clerks
1. 5.05 2.24 0.74 1.19 1
2. 4.94 1.23 0.61 0.38 3.64
3. 6.68 1.53 0.61 0.38 2.18
4. 3.95 0.49 0.61 0.81 1
5. 4.74 1.36 0.68 1.19 1
6. 6.58 2.1 0.61 1.19 1.39
7. 4.31 1.86 0.74 1.93 1.25
8. 4.94 1.36 0.68 0.75 1
9. 8.31 2.24 0.61 1.49 1
10. 2.84 1.23 0.61 0.81 1
11. 11.33 0.49 0.61 0.81 1.7
12 7.45 1.36 0.61 1.19 1
13 5.3 1.36 0.61 1.12 1.25
14 9.63 0.49 0.7375 1.24 2
15 7.04 0.49 0.7375 1.3 4
16 3.35 0.73 0.7375 1.24 2.74
Total 85.51 31.54 10.56 17 27.14
Average per
Site 5.34 1.97 0.66 1.06
1.7
Student Ratio 111.8:1 303.1:1 905.4:1 562.2:1 352.2:1

Summary: Research Question #2
This section of the chapter answered the study’s second research question of how the
sample district allocated its human resources. Management, certificated staff, and classified staff
were accounted for. This section of the chapter also broke down the human resource allocation
per school site in the sample district as well as provided the total count and student-to-staff
ratios. The numbers reported from the sample district were used to compare the district’s
allocation to that of the district’s desired allocation and to the Evidence-Based Model (EBM) in
the following section of the chapter.
ALLOCATION OF HUMAN RESOURCES 85

Research Question #3: Is there a Gap between Current Resource Allocation Strategies and
Researched-Based and Desired District Allocations?
This section of the chapter discusses how the sample district allocated its human
resources at the time of this study and compares the allocation to that prescribed by the
Evidence-Based Model. A gap analysis was conducted to compare current allocation with the
district’s desired allocation. The district’s desired allocation were based on the figures that the
Assistant Superintendent of Human Resources had provided to the researcher. Due to
California’s low per-pupil funding, it is not surprising that the data show negative gaps between
the sample district’s current allocation and the EBM. This section addresses the most significant
gaps between the sample district and the EBM. The positive gaps will be presented in the
section regarding research question four. Table 4.13 displays the human resource allocation gaps
between the district’s current and desired allocation as well as the gap between current allocation
and the recommendations of the Evidence-Based Model. Clark and Estes 2002 gap analysis
framework was utilized to determine whether or not these negative gaps were due to lack of
knowledge/skills, to issues related to motivation, or to organizational barriers within the sample
district.

ALLOCATION OF HUMAN RESOURCES 86

Table 13
Total Human Resource Allocation Gaps for Washington School District
District Total

Position Counts
Gap
Title Current Desired EB
Current-
Desired
Current-
EB

Principals 16.0 16.0 16.0 0.0 0.0
Assistant Principals 4.0 5.6 5.6 (1.6) (1.6)
Instructional Coaches 11.0 15.9 47.8 (4.9) (36.8)
Core teachers 330.5 350.1 504.9 (19.6) (174.4)
Specialist teachers 19.0 31.5 101.0 (12.5) (82.0)
SPED teachers 32.0 31.9 63.7 0.1 (31.7)
ELL teachers 0.0 0.6 64.4 (0.6) (64.4)
Academic extra help staff 9.1 8.7 59.8 0.4 (50.7)
Non-academic pupil support 21.1 22.3 95.2 (1.2) (74.1)
Nurses 3.0 3.0 12.7 0.0 (9.7)
Extended day/summer school staff 21.3 34.7 115.8 (13.4) (94.4)
Instructional aides 26.6 26.6 17.5 0.1 9.2
Supervisory aides 14.9 17.0 42.5 (2.1) (27.6)
SPED aides 96.4 96.5 31.9 (0.1) 64.6
Librarians 0.0 0.0 16.0 0.0 (16.0)
Library technicians 0.0 0.0 0.0 0.0 0.0
Library paraprofessionals 10.6 12.9 0.0 (2.3) 10.6
Secretaries/clerks 24.5 26.8 42.5 (2.3) (18.0)
Note. Source School district data input into the model developed by Picus and Knight (2012)
The most significant negative gap between the sample district and the EBM was found in
the allocation of core teachers. The student to teacher ratio suggested by the EBM is 15:1 in
grades K through 3; 25:1 in grades 4 through 5; and 25:1 in grades 6 through 8 is. At the time of
this study, the sample district desired an average class size of 24 in grades K through 2, of 30 in
grade 3, of 31in grades 4 through 6, and of 28.4 in grades 7 and 8. There was a deficit of 174.4
core teachers when the EBM was compared to the sample district’s allocation. When comparing
the district’s desired allocation to its current allocation, there still was a deficit of 29.6 core
ALLOCATION OF HUMAN RESOURCES 87

teachers. Due to California’s budget cuts and its lower per-pupil funding, this deficit in the
amount of core teachers is attributed to an organizational barrier caused by insufficient funds.
The next most significant negative gap was found in the staffing of Extended
day/Summer School programs. In the sample district, there were 642 students attending the
Extended School Program at six elementary sites. There were no after-school programs at its
middle school sites. There were 21.1 full time equivalent staff members working in the after
school programs. For the sample district to be equivalent to the suggested staffing of the EBM,
94.4 full-time equivalent staff members needed to be added. Summer school staff members were
not calculated into this case study because summer school is offered only to moderate-to-severe
special education students. This lack of summer school offered to general education students
may be due to a motivational barrier consisting of the district’s not valuing the summer school
program enough to offer it to general education students. Like the absence of an after-school
program in middle school, the lack of a summer school program for general education students
may be due to an organizational barrier in that the district did not receive enough funding to
support special education and general education students for summer school.
The final significant gap between the sample district’s current allocation and the
recommendations of the EBM was found in the area of specialist teachers. There was only one
music teacher at one elementary in the sample district. At one of the middle schools, electives
had been cut out altogether. The sample district employed 19 specialist teachers, 82 fewer than
what the EBM recommends. The Assistant Superintendent of Human Resources stated that the
district would love to have more specialist teachers, but with the budget cuts, there was not
enough funding to support the arts. The lack of funding, again, is an organizational barrier.
There may also be a motivational barrier found in the fact that one elementary school had the
ALLOCATION OF HUMAN RESOURCES 88

ability to hire a full-time music teacher. Other elementary school sites within the sample district
did not see enough value in a music program to staff a music teacher.
Summary Research Question #3
The previous section discussed the most significant deficits between the sample district’s
human resource allocation and the recommendations of the Evidence-Based Model. These gaps
were identified after the sample district’s data was entered into a simulation created by Picus and
Knight (2012). The Clark and Estes’ gap analysis framework was used to identify the causes for
the deficit in allocation. The following section addresses the positive gaps calculated by the
simulation in the sample district and how resources could be reallocated to align with strategies
that will increase student achievements.
Research Question #4: How Can Resources be Reallocated to Align with Strategies that
Improve Student Achievement?
This section takes a closer look at the positive gaps between the sample district’s
allocation of human resources and that recommended by the Evidence-Based Model. With
California’s low per-pupil spending compared to other states, it would not be feasible for the
sample district to reallocate its resources to mirror the recommendations of the Evidence-Based
Model. However, this section presents suggestions regarding how these positive gaps can be
reallocated to align with strategies that would improve student achievement.
In realigning resources to improve student achievement, the researcher focused on two
specific goals. The first goal was to provide students access to quality instruction that would
allow them to acquire the knowledge necessary to succeed. Teachers need quality professional
development to allow them to deliver the best instruction in core subject areas such as
mathematics, science, reading, writing, and history. The second goal is to provide “at-risk”
ALLOCATION OF HUMAN RESOURCES 89

students with additional support when they show that they have not mastered the curriculum.
To reach both these goals, the researcher suggests that more instructional coaches and academic
extra help staff be hired within the sample district.
The sample district’s allocation of Special Education instructional aides shows a positive
gap of 64.6 positions when compared to the recommendation of the EBM. Another area in
which the sample district allocated over the recommendation of the EBM is in the area of
instructional aides. The sample district has 9.2 more instructional aides than what the EBM
proposes. Combined, there is an excess of 73.8 classified positions that are allocated above the
recommendation of the EBM. If one certificated position were equivalent to three classified
positions, eliminating 73.8 instructional aide positions would allow the sample district to hire for
an additional 24.6 certificated positions. The rationale for eliminating instructional aides is that
the research does not show a link between aides and improved student achievement Odden and
Picus (2008).
Five of the 24.6 certificated positions could be reallocated to additional instructional
coaches. At the time of this study, the sample district had 11 Instructional Support Specialists
servicing its 16 sites. The sample district’s Director of Curriculum and Instruction indicated that
one of the challenges for the Instructional Support Specialists (ISS) was that they were spread
too thin. There were not enough ISS to support the number of schools and teachers. Hiring an
additional five ISS will allow each school to have one coach to support its teachers. With the
budget reduction, the sample district had decreased the amount of professional development
provided to its teachers and was trying to find different avenues to provide support for them.
One form of support was the addition of the ISS team. By increasing the number of ISS
members, the sample district would be better equipped to reach the goal of helping teachers
ALLOCATION OF HUMAN RESOURCES 90

transition to common core, become proficient in using technology, and better utilize the
instructional strategies adopted by the district. Having one ISS team member for each school site
in the district would allow the instructional coaches to provide more direct support to teachers by
providing on-site professional development. More opportunities for teachers to co-plan and co-
teach with the ISS coaches would promote more dialogue among the professionals where
feedback would be more accepted. Demonstration lessons using the adopted instructional
strategies of the district and tailored to fit the teacher’s core subject area would allow them better
understand how to deliver best first instruction. Research found that, when professional
development is entrenched into the teachers’ classrooms and they are engaged, they are more
likely to change and adopt new practices (Showers, 2002).
With the remaining 19.6 certificated positions created by eliminating instructional aides,
more academic help staff could be hired. Approximately 73% of the population in the sample
district was identified as “at-risk”. Additional certificated tutors can be assigned to each site to
support struggling students. The EBM recommends that there be one tutor to every 100
struggling students, but the funding situation in the sample district meant is was not feasible to
add the amount of tutors suggested by the EBM. Table 4.14 below shows the number of
additional academic extra help staff per school. The number of additional academic help staff
assigned to each school site is based on the population size of its “at-risk” students.

ALLOCATION OF HUMAN RESOURCES 91

Table 14
Number of Additional Academic Extra Help Staff per School
School
# Of At Risk
Students
# Of Additional Academic Extra
Help Staff
1. 586 1.7
2. 273 0.8
3. 401 1.1
4. 156 0.4
5. 398 1.1
6. 349 1
7. 699 2
8. 579 1.6
9. 450 1.3
10. 191 0.5
11. 228 0.6
12 331 1
13 372 1
14 593 1.7
15 503 1.4
16 837 2.4
Total 6946 19.6

Summary: Research Question #4
Reallocating the proposed human resources would not only bring the sample district’s
allocation closer to the research-based recommendations of the Evidence-Based Model, but it
would also maximize the district’s effectiveness in raising student achievement. It would
provide teachers with better professional development so that they become better equipped to
provide the best first instruction. The suggested reallocation would also provide additional
intervention support to struggling students. Eliminating a number of instructional aides would
allow the district to add instructional coaches to provide quality professional development to
teachers within the district. Additional academic extra help staff in the form of certificated
tutors would also provide struggling students with support from highly trained professionals
more apt to provide quality interventions.
ALLOCATION OF HUMAN RESOURCES 92

Summary
The results of the study were presented in this chapter, and an overview of the sample
district’s demographic and student achievement data was provided. In answering the four
research questions, information about how the sample district allocated its human resources was
presented. An examination of the sample district’s resource allocation revealed positive and
negative gaps between the district’s current and desired resource allocations. Gaps between the
district’s allocation and that recommended by the Evidence-Based Model were also presented.
Eliminating personnel in areas that showed positive gaps, areas where the district spent more
than the Evidence-Based Model recommends, would provide additional personnel in areas where
negative gaps were found. These negative areas are those where the district spent far less than
the EBM recommends. The purposeful tradeoffs were aligned with research-based strategies
that have been shown to improve student achievement. The next chapter presents a summary of
the study and provides recommendations and implications for future research.

ALLOCATION OF HUMAN RESOURCES 93

Chapter 5: Conclusions

As student achievement and accountability continue to be the focus of education reform,
education leaders will resume their efforts to best use their resources toward strategies that
research shows raise student achievement. This study identified the correlation between
strategies that have been identified by research as likely lead to increased student achievement
and the practices of a sample district in southern California. The study also compared the sample
district’s allocation of human resources to its desired allocation of these same resources. Using
the Evidence-Based Model (EBM) as the prototypical model for allocating human resources in
such a way as to raise student achievement, the sample district’s allocation was compared to the
recommendations of the EBM. Clark and Estes’ (2008) gap analysis framework was utilized to
identify the causes for the gaps between the sample district’s current allocations and its desired
allocation as well as between the current allocation and that suggested by the EBM. Finally, the
study also looked at how the sample district could reallocate current resources to come closer to
the recommendations of the EBM in order to maximize efforts to raise student achievement.
The Sample District
Located in southern California, the sample district is approximately 30 miles south of Los
Angeles. The district is a Kindergarten through eighth grade school district that serves 9,621
students at 17 school sites. This study focused on the 13 elementary school sites and three
middle school sites. The districts’ Child Development School was not utilized because it serves
primarily pre-school-aged children with special needs. The sample district’s student population
comes from four different cities in the surrounding area. Approximately 73% of the student
population receives free or reduced price lunch, and approximately 67% of the students are
English Learners. The majority of the district’s English Learners speak Spanish or Vietnamese.
ALLOCATION OF HUMAN RESOURCES 94

In terms of academics, the district has seen gradual growth on its Annual Performance Index
(API) and, for 2012, it achieved a score of 838. Although the district saw growth on its API, it
has not seen enough growth in its significant subgroups to meet its Annual Measurable
Objectives (AMAOs). At the time of this study, the district was in Program Improvement (PI)
and 11 out of its 17 schools were also in PI.
Limitations
The study’s limitations include the size of its sample. The findings may not be
generalizable to other school districts’ student populations due to the variation in student
demographics. The information gathered from those interviewed consists of subjective opinions
of district personnel and may not be representative of all district leaders. The period of time in
which the study was conducted is also a limitation due to its relatively short length.
Summary of Findings
Four questions relating to the correlation between the allocation of human resources and
strategies to raise student achievement were posed and answered in this study. An examination
of how a sample district allocates its resources was conducted and possible tradeoffs were
suggested to realign that allocation in order to bring it closer to that suggested by the EBM.
Research Question #1: What research-based human resource allocation strategies
improve student achievement? This study identified four key elements that research has
shown to improve student achievement. The common themes that have been vital to the success
of school reform are strong leadership, the use of assessments and database decision-making,
collaboration, and effective professional development.
Leadership. The sample district relies on its strong leadership to not only manage its
schools but also to be instructional leaders. With much of the professional development money
ALLOCATION OF HUMAN RESOURCES 95

allocated in other areas, the district relies on its administrators to provide professional
development to their teachers. The district also adopted a Professional Learning Community
(PLC) culture at its school sites where leadership teams made up of teachers and administrators
make decisions that affect the schools. This is also the area that needs more growth. Some
schools are further along in the establishment of their PLC. Their School Leadership Teams
(SLT) meet more frequently than others. More training and support is needed for those sites that
are not further along. Monthly SLT meetings should be set and agreed upon at the beginning of
the school year so that their importance is conveyed and other events can be scheduled around
them
Assessments and data-based decision-making. This study found that the sample district
uses the results of many sources of data to make its decisions. The results from the California
Standardized Test (CST), district benchmark assessments, Dibbles, Read 180, and the scores on
the Annual Measurable Achievement Objectives were analyzed. Because it is a Positive
Behavioral Intervention Support (PBIS) district, leadership also looks at attendance and
discipline data to identify areas that need improvement. More formative assessments need to be
created and, for that to occur, more training of teachers is needed on the use of the data-
collection software so that teachers are comfortable creating assessments, analyzing outcomes,
and creating an action plan based on the results. The district must also look into investing in a
system with the capacity to accumulate information from all its data sources. With enough
training, it would be more user-friendly and the teachers would be more motivated to use the
technology.
Collaboration. As a district trying to establish a Professional Learning Community,
collaboration among colleagues is a key element to its success. Unfortunately, the sample
ALLOCATION OF HUMAN RESOURCES 96

district has much growth to achieve in this area. Although scheduling was modified so that,
every Wednesday, students are released earlier to provide collaboration time for teachers, the
collective bargaining agreement between the district and the teacher association states that
teachers do not have to use that time to meet at the school site. According to the Director of
Curriculum and Instruction, many teachers do not meet at school. They take that time and leave
campus early to plan at home. When they do meet, teachers are more inclined to sort out
material for the upcoming unit. He stated that it takes strong leadership from the school sites for
meaningful collaboration to take place. An accountability system must be put in place whereby
teachers are expected to collaborate to discuss instruction, set goals, and establish measuring
tools to analyze whether the teams met their goals. Minutes from these meetings need to be
turned in to the site administrators.
Professional development. With reduced funding and added furlough days that were
formerly used for professional development, the sample district had to find different avenues to
provide professional development to its staff. Principals had to take on more of the load in
providing professional development to their staff. The district added Principal Academies to
equip their site administrators with the knowledge to provide professional development. During
the 2013-2014 school year, the district also hired teachers to be Instruction Support Specialists
(ISS). The 11 ISSs work as coaches for the teachers to help them transition to common core,
support staff members in the use of technology, and support the implementation of instructional
strategies adopted by the district. More instructional coaches are needed to support all teachers
within the district. The 11 ISSs are spread too thin among the 16 school sites.
Research Question #2: How are human resources allocated across the sample
district? The resource allocation data from the sample district was entered into the simulation
ALLOCATION OF HUMAN RESOURCES 97

model provided by Dr. Picus. The total number of certificated and classified staff members was
calculated and compared to the district’s desired allocation and the allocation suggested by the
Evidence-Based Model (EBM). Due to California having among the lowest per-pupil funding in
the nation, there were more areas where the EBM suggested more personnel than the sample
district allocated. These negative gaps were identified and addressed in the findings pertaining
to research question three.
Research Question #3: Is there a gap between current resources allocation strategies
and research-based and desired district allocations? After entering resource allocation data
from the sample district into the simulation model, the simulation calculated that there were
significant gaps between the sample district’s current human resource allocation and that
recommended by the EBM. Clark and Estes’s (2002) gap analysis framework was used to
identify possible causes for these gaps in personnel allocation. A few positive gaps, areas where
the sample district currently allocates its human resources in excess of the recommendation of
the EBM, were also identified. These positive gaps were areas where the district could reallocate
its resources and make tradeoffs that would bring it closer to the recommendations of the EBM.
The suggested tradeoffs in personnel are presented in the discussion of the findings regarding
research question four.
Research Question #4: How can resources be reallocated to align with strategies that
improve student achievement? The study revealed few areas of positive gaps between the
district’s current allocation and that recommended by the EBM. Areas where these positive gaps
occurred were in the allocation of instructional aides. The lack of research linking instructional
aides to improved student achievement provides the rationale for recommending the elimination
of these positions. Increasing student achievement was the main focus in determining which
ALLOCATION OF HUMAN RESOURCES 98

area received the reinvestment of the funding saved by eliminating a number of instructional aide
positions.
To improve student achievement, the researcher determined that improving first best
instruction and providing additional support for “at-risk” students would be the optimal use for
the funding saved by eliminating instructional aides. Adding instructional coaches or ISS
personnel to provide teachers with quality professional development would strengthen teachers’
ability to deliver first best instruction. Additionally, adding more academic support staff to each
site would increase the sites’ ability to provide interventions to struggling students. Although
these possible tradeoffs would not close the gap between the district’s current human resource
allocation and the recommendation of the EBM, they are examples of how the sample district
can reallocate its resources to affect student achievement without additional funding.
Proposition 30. On November 6
th
, 2012, California voters approved Proposition 30 by a
55% to 45% margin. Proposition 30 will raise state revenues by increasing personal income
taxes of those filing as single taxpayers earning $250,000 or more. Retroactively starting on
January 1
st
, 2012, this raise in personal income taxes for those making more that $250,000 will
be in effect for the next seven years. Proposition 30 will also increase state sales tax by ¼ cent
for the next four years. An estimated $6 billion in annual revenues will be added to the state
budget due to the passage of Proposition 30. Community colleges and K-12 schools would
receive an estimated $2.9 billion of the $6 billion. Of the estimated $2.9 billion dollars, 89% of
it will go to K-12 schools (Edsource, 2013).
With the additional funding, the sample district should look into adding additional human
resources to areas that have significant gaps between the district’s current allocations and that
recommended by the Evidence-Based Model (EBM). One of the areas that show a significant
ALLOCATION OF HUMAN RESOURCES 99

gap is in the amount of core teachers. Currently, the sample district has 330.5 full time
equivalent core teachers. This is 19.6 less than the district’s desired allocation and 174.4 less
than the recommendation of the EBM. By hiring additional core teachers, class sizes could be
reduced. Class size reduction should start in the third grade in the sample district. The average
class size for 3
rd
grade in the sample district is 30.88. Hiring additional core teachers to reduce
third grade classrooms to 24 students per classroom would make the classrooms more
manageable for the teachers. With additional funds, the sample district should also look into
additional specialist teachers in the form of computer and media teachers at the elementary level.
With the recent recession and budget cuts, specialist teachers were one of the first to be cut.
With only 101 full time equivalent specialist teachers in the sample district, there are 82 less
specialist teachers than what is recommended by the EBM. By adding specialist teachers to the
elementary sites, more collaboration time would be allotted during the school day. Grade level
teams would be able to meet with their instructional coaches to strengthen their instruction. With
the Common Core coming in the near future, students will be expected to be verse in the use of
technology. Standardized testing will also be given on computers. Students need to be able to
word process and be proficient navigating through the technology of today for them to adapt to
the technology of tomorrow.
Implication for Practice
With declining budgets and increased student achievement accountability, educational
leaders in California face the tough challenge of deciding where funding has the largest impact
on student achievement. California ranked 49
th
nationally in per-pupil spending at the time of
this study (Fensterwald, 2013). With fewer resources allocated to each student than most other
states, it is critical to effectively allocate resources. This study reports the human resource
ALLOCATION OF HUMAN RESOURCES 100

allocation for one school district in southern California. It compares the district’s current
allocation to its desired allocation. A comparison of the district’s current human resource
allocation and the recommendations of the Evidence-Based Model (EBM) was also conducted.
Gaps between the allocations were revealed and possible causes for these gaps were explained
using Clark and Estes’ (2002) gap analysis framework. Finally, suggested tradeoffs to bring the
sample district closer to the recommendations of the EBM and to align resources to support
strategies proven to raise student achievement were presented.
Developed by Odden et al. (2003), the EBM provides recommendations for the amount
of resources needed in a given school based on its enrollment numbers. The EBM suggests
resource allocations that have been proven by research to be most effective in raising student
achievement. The figures suggested by the EBM are based on a standard level of enrollment and
can be adjusted accordingly to each site. It may serve as a guide for schools wanting to compare
their current allocation of resources and to identify areas where realignment can be employed to
optimize student achievement.
Using the Clark and Estes (2002) gap analysis framework to identify causes for
shortcomings in the organization allows leaders to find solutions based on diagnostic
evaluations. Gaps among the sample district’s current allocation, its desired allocation, and the
recommendations of the EBM were identified. Determining potential causes for these gaps was
essential to finding solutions. Understanding whether the gaps were due to organizational
barriers, lack of knowledge and skill, or motivation can help leaders’ action plans to close these
gaps. A school district would be able to make the necessary changes once the gaps and their
causes have been identified.
ALLOCATION OF HUMAN RESOURCES 101

With California’s per-pupil spending, it is not feasible for school districts to reallocate
their resources to mirror the recommendations of the Evidence-Based Model. Tradeoffs that
were made through this study will bring the sample district closer to the EBM’s
recommendations and optimize student achievement. Administrators may use the results from
this study as a framework to maximize their resources and allocate them accordingly to heighten
student achievement.
Recommendations for Future Research
This study analyzed the human resource allocation of one school district in southern
California and compared it to the Evidence-Based Model to determine where reallocations could
occur to improve student achievement. It analyzed the 13 elementary schools and three middle
schools within the district. One of the recommendations for future researchers is to expand this
study and focus on a large school district. The sample school district does not include a
comprehensive high school. Conducting a study on a larger school district that includes
elementary, middle, and high schools could determine the effectiveness of the human resource
allocation patterns of a Unified School District.
Another recommendation for future study is to include interviews from site
administrators. This study only included interviews from district administrators. Interviewing
site administrators would provide a better understanding of the reasons allocations are made. It
would also provide insight regarding barriers that cause certain gaps. Understanding such causes
will allow researchers to discover more strategic solutions to close the gaps.
The final recommendation for future researchers is to conduct this study on only Title I
schools. Given per-pupil funding in California, it is not possible for a district to provide the
amount of personnel recommended by the Evidence-Based Model. Title I schools have more
ALLOCATION OF HUMAN RESOURCES 102

resources from federal dollars to provide additional personnel to better emulate the Evidence-
Based Model.
Conclusion
As accountability for high student achievement continues to be a focus, California’s
education leaders need to be more strategic in their allocation of resources due to the state’s
providing among the lowest per-pupil funding in the nation. The Evidence-Based Model
provides a framework for the allocation of human resources that has been proven by research to
increase student achievement. Districts in California can use this framework to identify areas of
excess and reallocate resources accordingly based on the recommendation of the EBM. This
study analyzed the human resource allocation on one sample district in southern California and
compared it to the EBM. Gaps between the district’s allocation and the recommendation of the
EBM were unveiled. Causes for these gaps were determined a suggestions on the reallocation of
human resources were presented that align with strategies proven to raise student achievement.
Other districts could use this study to compare their own practices and use the results to help
them make decisions regarding human resource allocation.

ALLOCATION OF HUMAN RESOURCES 103

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Williams, T., Kirst, M., Haertel, E., Perry, M., Studier, C., Brazil, N., et al. (2005). Similar
Students, Different Results: Why Do Some Schools Do Better? A large-scale survey of
California elementary schools serving low-income students. Mountain View, CA:
Edsource.

Abstract (if available)

Abstract The purpose of this study was to examine the dispersion of human capital resources within one school district in southern California and compare the use of personnel at each school to the desired allocation informed by the district’s strategies and staffing formula. The district’s resource distribution was also compared to that of the Evidence Based Model (EBM) to determine how the district spent its funding in relation to the research-based recommendations from the EBM. Gaps between the district’s allocation and the recommendation of the EBM were unveiled. Causes for these gaps were determined and suggestions on the reallocation of human resources that align with strategies proven to raise student achievement were presented. ❧ The following four questions were addressed by the study: 1. What research based human resource allocation strategies improve student achievement? 2. How are human resources allocated across Washington School District and its schools? 3. Is there a gap between current human resource allocation practices and what the research suggests is most effective? 4. How can human resources be strategically re-allocated to align with strategies that improve student achievement? ❧ A mixed methods approach with a primacy on qualitative data was used to collect data for this study. Quantitative data on the resource allocation of the sample school district was gathered. Qualitative data on the district’s instructional vision, improvement plan, and professional development plan were collected. Triangulation of the interviews, the district’s resource allocation, and its philosophy was conducted to determine the congruency among how the district is allocating their resources, how they perceive they are allocating their resources, and how they want to allocate their resources. ❧ The Evidence-Based Model provides a framework for the allocation of human resources that has been proven by research to increase student achievement. This study’s findings suggest that schools in Southern California do not have the financial resources available to allocate personnel to the recommendations of the Evidence-Based Model. Districts in California can use this framework to identify areas of excess and strategically reallocate resources so that it can more closely emulate the recommendation of the EBM and increase student achievement.

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University of Southern California Dissertations and Theses

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Asset Metadata

Creator Nguyen, Dominic (author)

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

School Rossier School of Education

Degree Doctor of Education

Degree Program Education (Leadership)

Publication Date 07/30/2013

Defense Date 05/06/2013

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

Tag allocation of human resources,OAI-PMH Harvest

Format application/pdf (imt)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Picus, Lawrence O. (committee chair), Escalante, Michael F. (committee member), Morgan, Helen F. (committee member)

Creator Email dominic_phi@yahoo.com,nguyendc@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c3-306945

Unique identifier UC11294901

Identifier etd-NguyenDomi-1886.pdf (filename),usctheses-c3-306945 (legacy record id)

Legacy Identifier etd-NguyenDomi-1886.pdf

Dmrecord 306945

Document Type Dissertation

Format application/pdf (imt)

Rights Nguyen, Dominic

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