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District allocation of human resources utilizing the evidence based model: a study of one high achieving school district in southern California

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District allocation of human resources utilizing the evidence based model: a study of one high achieving school district in southern California

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Content Running Head: DISTRICT ALLOCATION OF HUMAN RESOURCES 1
DISTRICT ALLOCATION OF HUMAN RESOURCES UTILIZING THE EVIDENCE
BASED MODEL: A STUDY OF ONE HIGH ACHIEVING SCHOOL
DISTRICT IN SOUTHERN CALIFORNIA

by

Amber Marie Lane

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

May 2013

Copyright 2013 Amber Marie Lane

DISTRICT ALLOCATION OF HUMAN RESOURCES 2
Abstract
This study applies the Gap Analysis Framework to understand the gaps that exist in
human resource allocation of one Southern California school district. Once identified,
gaps are closed with the reallocation of human resources, according to the Evidenced
Based Model, requiring the repurposing of core classroom teachers, specialists, special
education staff and instructional aides. Thus, the purpose of this study was to examine
strategies for human resource reallocation that can be done throughout individual schools
in the school district to improve student achievement in a Basic Aid district in Southern
California. Using a formative evaluation qualitative research design in the form of
document analysis, interviews, observations and human resource allocation simulations,
the study found that the district could meet organizational goals and raise student
achievement by raising class sizes by two students and reallocating special education
aides. Findings from this study indicate that school districts receiving more funding than
the California revenue limit still can reallocate resources in ways research suggests will
improve student achievement. This study builds on the adequacy research that links
human resource allocation to student achievement. Additionally, this study provides a
framework for conversations within districts as to how to allocate personnel and across
the state as to how schools should be funded to meet the needs of all students.

DISTRICT ALLOCATION OF HUMAN RESOURCES 3
Dedication
This dissertation is dedicated to my mother who taught me to always dream big, my
mother and father in law for their constant encouragement and to my husband whose love
and support has made this possible.

DISTRICT ALLOCATION OF HUMAN RESOURCES 4
Acknowledgements
I would like to acknowledge Dr. Lawrence O. Picus for engaging me in such a relevant
topic and for never giving up on me throughout this whole process. Your dedication to
your students is something that I will never forget. I would also like to thank the “OC-8”
for taking this journey with me. I have learned so much from all of you and I am not
only a better educator for knowing each of you, but a better person. Lastly, I would like
to thank my colleagues at Temecula Luiseno Elementary School who asked for daily
updates which kept me motivated when I needed it the most.
DISTRICT ALLOCATION OF HUMAN RESOURCES 5
Table of Contents
Abstract 2

Dedication 3

Acknowledgements 4

List of Tables 7

List of Figures 8

Chapter One: Overview of the Study 9
Introduction 9
Statement of the Problem 14
Purpose of the Study 15
Research Questions 15
Importance of the Study 15
Summary of the Methodology 16
Limitations 18
Delimitations 18
Assumptions 19
Definitions 19

Chapter Two: Review of the Literature 22
Introduction 22
Times of Fiscal Crisis: Doing what is Right with Limited Resources 46
Resource Allocation in Schools: Changing Theories of Action 51
Resource Reallocation: What to do When There is No Money 59
Putting it All Together: Using Gap Analysis to Allocate Resources in
Times of Fiscal Constraint 64
Conclusions 65

Chapter Three: Methodology 66
Introduction 66
Population and Sample 69
Instrumentation 76
Data Collection 77
Data Analysis 79

DISTRICT ALLOCATION OF HUMAN RESOURCES 6
Chapter Four: Findings 82
Introduction 82
Evidenced Based Model (EBM): Human Resource Allocation Strategy
that Raises Student Achievement 83
Overview of the District 86
Gap Analysis of SSSD Human Resource Allocation 94
Implement Solutions: Reallocation of Human Resources 107
Conclusion 113

Chapter Five: Summary, Conclusions, Implications 114
Introduction 114
Overview of the Study 114
Methodology 115
Limitations 115
Summary of Findings 116
Implications for Practice 120
Recommendations for Future Research 122
Conclusion 123

References 124
Appendix A: Interview Questions: Assistant Superintendent of Business Services 137
Appendix B: Interview Questions: Assistant Superintendent of Curriculum
and Instruction 138
Appendix C: Observation Checklist for SSSD Board Meetings 140

DISTRICT ALLOCATION OF HUMAN RESOURCES 7
List of Tables
Table 1: McREL Researchers Identified the 21 Key Leadership Responsibilities
that are Significantly Correlated with Higher Student Achievement 34
Table 2: Cost Structure of a Comprehensive School Reform Plan 62
Table 3: SSSD Student/Staff Information 2010-2011 71
Table 4: SSSD Student Enrollment by Ethnicity and Other Characteristics 71
Table 5: Input Criteria for EXCEL Model Gap Analysis 80
Table 6: Evidenced Based Model Staffing Structure 86
Table 7: Core Strategies for SSSD 95
Table 8: District Human Resource Allocation by Position 97
Table 9: Instructional Leadership Gaps 100
Table 10: Certificated Personnel Gaps 100
Table 11: Classified Personnel Gaps 103
Table 12: Non-Academic Pupil Support Staff Shared Throughout SSSD 106
Table 13: SSSD Desired Allocations to Raise Student Achievement 108
Table 14: Staffing Allocation with Class Size at EBM Recommended 109
Table 15: Staffing Allocation Changes when Class Size is at Current SSSD Levels 110
Table 16: Staffing Allocation Changes when Class Size is Increased by Two Students111

DISTRICT ALLOCATION OF HUMAN RESOURCES 8
List of Figures
Figure 1: The Evidence Based Model. 57
Figure 2: Aloft Elementary School API by Group. 72
Figure 3: Cuddy Elementary School API by Group. 73
Figure 4: Deck Elementary School API by Group. 73
Figure 5: Dinghy Academy of Arts and Sciences API by Group. 74
Figure 6: Overboard Elementary School API by Group. 74
Figure 7: Squall Elementary School API by Group. 75
Figure 8: Scuppers Elementary School API by Group. 75
Figure 9: Tiller Elementary School API by Group. 76
Figure 10: Academic Performance Index over the Last Five Years. 88
Figure 11: English Language Learner Proficiency on the CST-English Language Arts.89
Figure 12: English Language Learner Proficiency on the CST-Mathematics. 89
Figure 13: Students with Disabilities Proficiency on the CST- English Language Arts. 90
Figure 14: Students with Disabilities Proficiency on the CST-Mathematics. 91
Figure 15: SSSD Revenues over Last Five Years. 92
Figure 16: SSSD Expenditures over Last Five Years. 93

DISTRICT ALLOCATION OF HUMAN RESOURCES 9
Chapter One: Overview of the Study
Introduction
Educators throughout California are bracing themselves for some of the worst
cuts that education has faced in the last two decades as California’s Governor and
Legislature try to balance a state budget deficit of 9.2 billion dollars before the start of the
2012-2013 fiscal year (Taylor, 2012). The brunt of the proposed reductions will come
directly from school district budgets. In turn, these reductions will trigger districts
around the state to take drastic measures to balance their individual budgets, including
increasing class sizes even further, closing schools and laying-off thousands of teachers.
The staggering cuts are only one part of the overall picture in California, as the
whole is worsened when comparing California to other states around the country.
California ranks 43
rd
in the nation in per pupil spending and 49
th
in its overall ratio of
staff to students, and the state has about half as many school district administrators,
guidance counselors, and high school teachers per 1,000 students as do other states
(EdSource, 2011). The state also ranks last in the number of school librarians per pupil
(EdSource, 2011). This condition in education finance did not miraculously change over
the last five years, as it is the result of a system has not responded to changes in
economics or instructional practices over time. In fact, the current financial crisis has its
roots in court cases and legislative decisions of the 1970s and 1980s.
School Finance in California: The Creation of a Flawed System. Prior to
1973, K-12 schools were funded largely by local property tax revenue whereby school
boards set a budget and made all budgetary decisions at the local level. Thus, a district
with high property tax revenue would generate more per pupil spending than a low
DISTRICT ALLOCATION OF HUMAN RESOURCES 10
property tax revenue district, resulting in disparities between districts throughout the
state.
These disparities led to the landmark school finance case, Serrano v. Priest,
where the California Supreme Court ruled that the California school finance system was
unconstitutional. In their ruling, the court found that the existing system gave high-
wealth districts a distinct advantage in hiring high quality personnel, program expansion
and pupil-teacher ratios. As a result of that ruling, the California legislature was required
to equalize funding for low wealth districts to ensure disparities between districts closed
over time (Henke, 1996). Therefore, the legislature passed Senate Bill 90 to create the
revenue limit system and put a ceiling on the amount of general fund money each district
can receive (EdSource, 1983).
Shortly after Serrano, voters enacted Proposition 13, which limited property tax
rates to 1% of assessed value at time of purchase. This decision by voters, aimed at
limiting government spending and tax increases had the unintended consequence of
lowering the amount of local revenues that could be allocated to schools, forcing the
centralization of school funding to the California legislature (Henke, 1996). Proposition
13 never allowed the state to fully enact its plan to fully equalize funding among districts
over time. This new method of revenue generation also left districts vulnerable to
volatile shifts in both sales and income tax, as these became a mechanism for generating
state general fund revenues for schools (Kirst, 2007).
To stabilize school funding, voters in 1988 passed Proposition 98 to set a
minimum funding level for K-14 public school districts so that each district in the state is
equitably funded and to guarantee approximately 40% of the General Fund revenue in the
DISTRICT ALLOCATION OF HUMAN RESOURCES 11
state to K-14 education (Taylor, 2011). Proposition 98 was designed to keep pace with
growth in both K-12 student populations and personal income of California residents and
to ensure that, with the implementation of the lottery, the rest of the state’s commitment
to education funding was not reduced. Proposition 98 funding comprises approximately
71% of the funds that K-12 schools receive (EdSource, 2009). The other approximately
29% comes from local sources, federal government programs and a few state resources as
well.
Both Proposition 13 and Proposition 98 set a floor and a ceiling for the California
finance system (Kirst, 2007). Proposition 13, the ceiling, makes it impossible to raise
taxes based on increases in assessed property value and Proposition 98, the floor, bases
the current year’s funding on the funding level for the previous year or a percentage of
the state general fund budget based on the percentage set when Proposition 98 was passed
– currently approximately 40%. While legislators can choose to allocate more money to
K-14 education above the revenue limit, they usually do not because it sets the revenue
limit at a higher amount for next year, causing political implications should they have to
lower the amount of funding for the following year, which could then only be done
through a suspension of Proposition 98.
The response to both Proposition 13 and 98 left California with a Revenue Limit
funding model. Revenue limit funding is defined as the amount of general purpose
money districts receive from a combination of state taxes and local property taxes
(EdSource, 2011). This amount is adjusted annually and is funded on a per pupil basis so
that each district has its own revenue limit rather than a foundation level for all of the
districts in the state. This ensures that the state fills in funding gaps if local property
DISTRICT ALLOCATION OF HUMAN RESOURCES 12
taxes are in adequate to fund the amount. While this funding structure is the primary
source of revenue for most districts throughout the state, there are a few districts that
operate within another funding format called Basic Aid. Within this funding model,
districts generate more than their revenue limit from local property taxes and do not need
the state to add additional funds to reach the revenue limit. In fact, many of these
districts generate more than the revenue limit and are entitled to keep the extra funds.
Goal of school finance: Adequacy in allocation of resources. All of the school
finance changes in California address the concept of equity. They aim to ensure that all
California students have a basic level of funding regardless of geography. Unfortunately,
this way of thinking is not enough anymore when the stakes for students are higher than
ever and the need to compete on the global stage is at an all-time high. Educators
desperately need a new way of funding that will allow all students an adequate
educational experience that meets their unique and diverse needs. Baker and Green
(2009) argue that, for this to happen, there needs to be a more targeted distribution of
resources, rather than just the addition of more. To do this California, like many other
states have around the country, needs to rebuild its school funding system.
Many states recreated their school funding systems to address this concept of
adequacy and to allow for more resources to be funneled to the students who need them
most. In contrast, the system in California aims to do what other states have
accomplished but has failed to because of the specific and narrow purpose of most of its
categorical programs. Thus, the implementation of these programs is truly at fault and
makes the funding system vastly more complicated than it needs to be (Kirst, 2007).
DISTRICT ALLOCATION OF HUMAN RESOURCES 13
Rebuilding the California school finance system is vitally important because
California students need to be successful in an era of higher standards and accountability.
This rebuilding will be a difficult task due to the diversity of school districts and the
students they serve. During the 2010-2011 school year, the system had 6,217,002
students and 1,050 school districts. About 1,215,789 students were enrolled in one of
546 elementary school districts and another 603,188 were enrolled in one of the 82 high
school districts. In contrast, the 334 unified school districts enrolled more than 4,308,183
students. Not only are the districts diverse in number and type, they are also ethnically
diverse. During the 2010-2011 school, year 51.4% of the students in California were
Hispanic or Latino, 26.6% were White, 8.5% were Asian, 6.7% were Black or African
American, 2.6% were Filipino, 0.7% were American Indian or Alaska Native, and 0.6%
were Native Hawaiian or Pacific Islander. Of the student population, 1,052,286 are
English Language Learners and 3,465,008 qualify for Free/Reduced Lunch (Ed-Data,
2011).
Based on the levels of diversity in both district size and student population,
schools need to continue the shift toward an adequacy model of school funding so that
students get what they need in order to meet high level standards. This new model of
funding is especially needed in the time of high accountability as set forth in both state
and federal accountability systems.
State and federal accountability systems: Pressure to meet expectations.
Given the way that education is funded, California educators face an even larger
challenge in meeting hurdles set by both state and federal accountability systems. While
the budget picture worsens for California educators, accountability for student
DISTRICT ALLOCATION OF HUMAN RESOURCES 14
achievement remains at an all-time high as districts around the state focus on meeting
Annual Measureable Objectives (AMO) as set forth by the state and Adequate Yearly
Progress (AYP) as set forth by the federal government under the provisions of No Child
Left Behind (NCLB). Under the tenets of both accountability systems, students must
meet proficiency targets in Language Arts and Mathematics with the ultimate goal, under
AYP, to have all students proficient by 2014. This goal includes all sub-groups of
students, ranging from the socio-economically disadvantaged to special education
students. If states do not meet these goals for two consecutive years, they are identified
as in need of improvement and are subject to sanctions, which increase in number and
severity according to the number of years the school does not meet the targets (Kim &
Sunderman, 2005). These sanctions force all schools to look closely at how they meet
the needs of all students, including those students designated as English Language
Learner or Special Education.
Statement of the Problem
With the changes over time in school finance, imposed accountability systems,
and the current fiscal climate, there is a great need for school districts to allocate money
in ways that are purposeful and that will have a meaningful impact on student
achievement. Currently, many school districts do not employ a coordinated plan for the
allocation of personnel but, instead, base their staffing on low teacher-to-student ratios
and availability of funds earmarked for special student populations. Allocating funds in
this way leads many schools and districts to question their allocation practices in times of
fiscal stress. Unfortunately, there is a dearth of practical guides for districts looking to
reallocate their resources, which is why more research is needed in this area. The
DISTRICT ALLOCATION OF HUMAN RESOURCES 15
Evidence-Based Model developed by Odden and Picus (2008) is one tool that districts
can use as they try to reallocate resources to improve student achievement. This model
has primarily been implemented in Arkansas, Ohio, and Wyoming, and the results appear
promising, which is why California should investigate whether this approach will work
for districts throughout the state (Odden, Picus & Goetz, 2006; Picus, Odden, Aportela,
Mangan &Goetz, 2008 Odden & Picus, 2010).
Purpose of the Study
The purpose of this study was to examine strategies for human resource reallocation
that can be done at the school level to improve student achievement. The primary focus
is on human capital reallocation requiring the movement of core classroom teachers,
specialists, special education staff and instructional aides and will be generally defined in
this case study as teaching staff.
Research Questions
Four research questions guided this study:
1. What research based human resource allocation strategies improve student
achievement?
2. How are human resources allocated across the study district and its schools?
3. Is there a gap between current human resource allocation practices of the
study district and what the research suggests is most effective?
4. How can human resources be strategically reallocated to align with strategies
that improve student achievement?
Importance of the Study
Analyzing the allocation of human resources is important in the current climate of
fiscal uncertainty because districts must ensure they spend limited resources in ways that
DISTRICT ALLOCATION OF HUMAN RESOURCES 16
will have an impact on student achievement. Thus, this study gives district level
personnel a tool to make decisions that will allow them to better allocate the resources
they have. The tool will also allow them to simulate a wide range of staffing scenarios
that they might not have thought possible. Additionally, schools and districts will be able
to say that they are making decisions based on research that doubles student achievement
and account to various stakeholders for the ways in which they spend resources. In turn,
this will allow schools to better prepare students for careers in the 21
st
century. Besides
district level personnel, this study will be useful to policymakers as they set funding
priorities for a school because they will know what a prototypical school looks like and
what is required to fund it for success.
Summary of the Methodology
This study utilized a formative evaluation qualitative research design in the form
of document analysis, interviews, observations and human resource allocation
simulations to ascertain the extent to which school districts can reallocate human
resources in ways that increase student achievement. As a result, a district was selected
for the study that was in need of reallocation of resources to improve student achievement
for four particular sub-groups of students: Hispanic/Latino students, socioeconomically
disadvantaged students, English Language learners, and special education students.
The data collected were derived from the Human Resource Department of the
school district. The researcher was given a listing of the total enrollment of each school
in the district, the number of students per grade level, the number of teacher positions per
school and the number of classified employees per campus. With this data, the researcher
used an EXCEL model to run various simulations which show how school staffing can be
DISTRICT ALLOCATION OF HUMAN RESOURCES 17
changed to align with what research says are best practices and, if followed, could result
in higher student achievement.
To run the simulations, the researcher attended a one day in-service to learn how
to use the model and how to simulate different configurations of staffing depending on
class size and other factors.
In addition to the Human Resource data, the researcher derived data from School
Accountability Report Cards (SARC) prepared by the California Department of
Education. The SARC is a snapshot of each school in the district and provides a variety
of information about the school. For the purposes of this study, the researcher examined
Academic Performance Index (API) scores for the 2011 administration of the California
Standards Test (CST).
Besides document analysis, the researcher conducted interviews with the
Assistant Superintendent of Business Services and Assistant Superintendent of Education
Support Services about the mission and strategic plan of the district, what plan the district
had in place to meet the goals set forth in the plan and how staffing allocations were
made to support the plan.
Lastly, the researcher conducted observations of three school board meetings to
obtain a full picture of the school district and the decision-making process. The
observations also allowed the researcher to acquire information as to how the school
district planned to handle budget matters within the district, including the decision to
place a bond measure on the November 2012 ballot.
Once all of these data were collected, the researcher was able to complete a Gap
Analysis using the model created by Clark and Estes (2008) to ascertain the knowledge,
DISTRICT ALLOCATION OF HUMAN RESOURCES 18
motivational, and organizational gaps that exist between what research says are best
practices for human resource allocation and the practices employed by the district.
Limitations
The following limitations are present in the study:
 Due to the funding model of the school district, the findings may not be
generalized to other school districts.
 Due to student population and size of the district, the findings may not be
generalized to other school districts.
 The method of data collection was based upon structured and semi structured
interview processes, which result in the possibility that the results may be
subjective.
 Due to the nature of the Closed Session portion of school board meetings,
observation data is limited to open session items only.
Delimitations
The following delimitations are present in the study:
 The study focused on a Basic Aid district in Southern California, which has
higher per pupil funding than many districts in California and is considered
more revenue “rich.”
 The study focused on an elementary school district with eight schools. All
schools were included in the study based on the small size of the district.
 The study focused on human resource allocation for the 2011-2012 school
year only.

DISTRICT ALLOCATION OF HUMAN RESOURCES 19
Assumptions
The following assumptions are made in this study:
 That all participants were truthful with responses.
 That there will be inconsistencies between interpretation of mission and
implementation at the school level because of human error.
 The classification of school personnel may be different in the EBM than at the
school level.
 The California budget is always in a state of flux and can change depending
on ADA and legislative decisions.
Definitions
Academic Performance Index (API) is a number, used for school accountability purposes,
summarizing the performance of a group of students, a school, or a district on California's
standardized tests (EdSource, 2012c).
Adequate Yearly Progress (AYP) is a series of annual academic performance goals
established for each school, district, and the state as a whole (California Department of
Education, 2011a).
Annual Measureable Objectives (AMO) are the minimum percentages of students who
are required to meet or exceed the proficient level on the state assessments used for AYP
(California Department of Education, 2011a).
American Recovery and Reinvestment Act (ARRA) provided more than $800 billion in
federal spending and tax cuts intended to stimulate the economy because of the deep
recession in the United States brought on by global finance collapse (Mead, Vaishnav,
Porter, & Rotherham, 2010).
DISTRICT ALLOCATION OF HUMAN RESOURCES 20
Average Daily Attendance (ADA) is the total number of days of student attendance
divided by the total number of days in the regular school year (EdSource, 2012c).
Basic Aid is the minimum general-purpose aid guaranteed by the state's Constitution for
each school district in California (EdSource, 2012c).
Basic Aid School District is the historical name for a district in which local property taxes
equal or exceed the district's revenue limit (EdSource, 2012c).
California Standards Test (CST) is a test taken each spring by students in grades two –
eleven. The CST looks at how well schools and students are performing against
standards for that grade level (California Department of Education, 2012).
Categorical Program Flexibility allows school districts to use once restricted dollars,
those earmarked for special programs and purposes, for any educational purpose through
the 2014-2015 school year (Weston, 2011).
Elementary and Secondary Education Act (ESEA) is the principal federal law affecting
K-12 education created to support the education of the country's poorest children and that
remains its overarching purpose (EdSource, 2012c).
No Child Left Behind (NCLB) is the 2002 reauthorization of the Elementary and
Secondary Education Act (ESEA). It represents a significant change in the federal
government's influence in public schools and districts throughout the United States,
particularly in terms of assessment, accountability, and teacher quality (EdSource,
2012c).
Numerically Significant Sub-Group is defined as 100 or more students with valid test
scores or 50 or more students with valid test scores who make up at least 15 percent of
the total population with valid test scores (California Department of Education, 2012c).
DISTRICT ALLOCATION OF HUMAN RESOURCES 21
Professional Learning Communities (PLC) represents a group of educators in a
collaborative team who have a shared mission related to student learning and are
committed to continuous improvement (DuFour, DuFour, Eaker and Many, 2010).
Revenue Limit is the amount of general purpose money districts receive per pupil (ADA)
from a combination of state taxes and local property taxes (EdSource, 2012c).
DISTRICT ALLOCATION OF HUMAN RESOURCES 22
Chapter Two: Review of the Literature
Introduction
Accountability systems created in the last 10 years require schools to demonstrate
increases in student academic performance (Duke, 2006). According to Duke, these
pressures to perform are especially pronounced in low performing schools, but exist
across all California schools as school districts strive to produce students who can
compete in a changing job market. According to the Public Policy Institute of California
(2008), over the next 15 years, there will be a shift from manufacturing to service-related
industry jobs. While there is a projected increase of bachelor degree holding individuals,
28% in 2000 to a projected 33% in 2020, that percentage still falls short of the 39%
needed to fill service-related fields. These shortages require school districts to rise to the
occasion and prepare students who are ready to attend college, who are critical thinkers
and who are innovative. To do this, schools and school districts must have a system-wide
approach to maximize student achievement. This review of the literature will examine
what school systems must do to maximize student achievement, the impact of the current
fiscal crisis on increasing student achievement, and, lastly, how school system can
allocate resources even with these fiscal constraints.
Raising student achievement: A system-wide approach. For students to
achieve at high levels, each part of the educational system must work with the others in a
coordinated way (Togneri & Anderson, 2003). Without system-wide coordination, the
district is left with individual schools that are high performing while the district as a
whole is not. At first glance, this does not seem to be problematic, but, with changes in
accountability structures under NCLB, entire districts must show that all schools meet
DISTRICT ALLOCATION OF HUMAN RESOURCES 23
AYP targets. If they do not, they face sanctions similar to those faced by individual
schools, meaning that an entire school district or Local Education Agency (LEA) can
enter Program Improvement (California Department of Education, 2011b).
To ensure that the entire school district achieves at high levels, district leaders
must address many variables at and within the organization, including an examination of
individual school and teacher factors that aid in school success. From this examination,
trends will emerge across levels that have an impact on student performance in a positive
way. In the end, all actors are moving toward the same goal: a brighter future for
California students.
District level factors that improve student performance. In the 1980s and
1990s, the standards based reform movement caused the role of the school district’s
central office to change from one of decentralization to one focused on assessing student
performance on local, state and national standards (Honig & Colburn, 2008). The
reemergence of the central office continued into the 21
st
century with NCLB, as districts
became as responsible for student achievement as individual schools were (Leithwood,
2010). With these changes, research began to focus on the role the central office plays in
raising student achievement. Overwhelmingly, the research indicated that increasing
student achievement goes beyond the classroom and that district leadership does play a
key role in ensuring student success (Togneri & Anderson, 2003). While there are
detractors who bemoan the bureaucracy of the central office and point to individual
successful schools, evidence indicates that schools do, in fact, need the support and
organization of an outsider, whether that is a university or charter company (Togneri &
Anderson, 2003; Supovitz, 2008). Even with these detractors, the idea that districts can
DISTRICT ALLOCATION OF HUMAN RESOURCES 24
make a difference is an emergent pattern in the literature, especially in the areas of
instructional practice, data collection/analysis, professional development, and
collaboration.
Togneri and Anderson (2003) studied five high poverty districts making strides in
improving student achievement. In their research, they found that districts do, in fact,
make a difference because of the role they play in providing an instructional framework
for schools. Additionally, in a review of the literature, Leithwood (2010) found that
school districts that are exceptionally effective in closing the achievement gap do so in
large part through alignment among curriculum, instructional practice, and assessment
(Leithwood, 2010; MacIver & Farley, 2003; Togneri & Anderson, 2003). Moreover,
MacIver and Farley (2003) conducted a review of the literature about the role of the
central office in improving instruction and student achievement. Their findings also
indicate that school districts provide much needed logistical support to schools to help
them focus on high quality instruction to increase success.
Data collection and analysis was also an important function of the district office.
On the surface level, district administrators run information management systems that
allow student data to be collected, and they teach school personnel how to interpret and
use the data to make informed instructional decisions (Leithwood, 2010). On a much
larger scale, the district office is the agency responsible for allowing the “truth to be
heard” in that they share district level data with the community and set priorities for
whole school systems that are based on data and best practices related to the research
(MacIver & Farley, 2003). They also use the data collected across the whole district to
DISTRICT ALLOCATION OF HUMAN RESOURCES 25
set professional development priorities that focus on what is needed by teachers and
administrators to help current students in the system (Leithwood, 2010).
As noted above, professional development in high performing school districts is
based on data, but professional development is also job embedded for both teachers and
principals to increase the likelihood that it will transfer into schools and classrooms
(Leithwood, 2010). Furthermore, high performing school districts recognize that
professional development must be examined on a regular basis to ensure that the needs of
students are being met (Togneri & Anderson, 2003).
Lastly, the research indicates that everyone in the system must work together to
ensure student success (Leithwood, 2010; Togneri & Anderson, 2010). This is especially
important for teachers, as collaboration is essential to analyzing student needs and
planning appropriate interventions. Although this is important, high performing districts
go one step further because they understand that this type of collaboration takes work and
that teachers need to be given time in this endeavor and that the structures for
collaboration need to be constantly judged for effectiveness (Togneri & Anderson, 2010).
Ultimately, the research indicates that current structures and funding limit success
and that there are no quick fixes to the problem. In order to be successful and raise
student achievement, changes have to be made to the system itself (Leithwood, 2010;
MacIver & Farley, 2003; Togneri & Anderson, 2003).
School level factors that improve student performance. Not surprisingly,
many of the factors that propel school districts to success are the same characteristics that
make individual schools successful. Some of these strategies are outlined by Darling-
Hammond (2002) in her study of Center for Collaborative Excellence schools in New
DISTRICT ALLOCATION OF HUMAN RESOURCES 26
York City that had been restructured to put the needs of students first. In her research,
she notes 12 principles or common commitments that these schools made in order to raise
student achievement:
 School purpose
 High universal academic standards
 Interdisciplinary, multicultural curriculum, centered around powerful ideas
 Small size and personalization
 Student as worker and citizen
 Performance based assessment
 Adults and students believe in a respectful tone
 Family Involvement
 Shared decision-making between teachers and administrators
 Commitment to diversity
 Students selected these schools by choice
 Decreased teacher load and created structures for shared planning time
The principles that emerged in her research focus on all aspects of the school
community, ranging from teachers and students to family involvement, which illustrates
the idea that all aspects of the school must work together in order for students to achieve.
The work of Elmore (2003) furthers the work of Darling-Hammond in that he found
that school improvement grows out of, “consensus on norms of instructional practice,
strong internal assessments of student learning, sturdy process for monitoring
instructional practice and for providing feedback to students, teachers, and administrators
about the quality of their work” (p. 9). The one notable difference between these two
DISTRICT ALLOCATION OF HUMAN RESOURCES 27
bodies of work is that Elmore (2003) focuses more heavily on the role of the leader
within the school organization. He places a high priority on leadership within the school
and states that administrators must know good instructional practice, be able to model for
teachers, work publically on their own practice and facilitate powerful discourse about
good instruction. Beyond a strong central figure, he also contends that leadership should
be distributed throughout the organization, empowering teacher leaders at all levels.
Once again, the work of Reeves (2003) corroborates the work of Elmore and
Darling-Hammond, yet Reeves focuses more on the teachers within the school system
and what they do to encourage student success. In his research, Reeves coined the term
90/90/90 in 1995 based on observations in Milwaukee, Wisconsin, where schools had
been identified with the following characteristics: 90% or more of the students were
eligible for free or reduced lunch, 90% or more of the students were members of ethnic
minority groups, and 90% or more of the students met the district or state academic
standards in reading or another area (Reeves, 2000). From the observations he found five
characteristics that were common to all “90/90/90 Schools:”
 A focus on academic achievement
 Clear curriculum choices
 Frequent assessment of student progress and multiple opportunities for
improvement
 An emphasis on nonfiction writing
 Collaborative scoring of student work
His research is unique in the fact that he also talked about strategic assignment of
personnel. He believes in the value of every adult in the system because they allow for
DISTRICT ALLOCATION OF HUMAN RESOURCES 28
consistency in the education of students. To achieve this level of consistency and to
show the value of each adult, he also believes that, if a staff member does not have the
training to teach certain grade levels, leadership should find a job that fits the person and
his/her skill set – this does not mean s/he is a bad person. S/he is just not a good fit for the
position.
In the aforementioned literature, there is a distinct difference between instructional
practice and leadership, with researchers focusing on one or the other. The work of Duke
(2006) changes that as his synthesis of 5 turnaround schools published from 1994 – 2004
blends both ideas. From his research, he came up with 11 commonalities to turn around a
low performing school:
 Students experiencing problems with learning required content received
prompt assistance.
 Collaboration.
 Data-driven decision making
 Leadership
 Organization structure
 Staff development
 Alignment – tests are aligned with curriculum content, and curriculum content
is aligned with instruction.
 Students were assessed on a regular basis to determine their progress in
learning required content.
 High expectations
DISTRICT ALLOCATION OF HUMAN RESOURCES 29
 Parent involvement - school personnel reached out to parents to keep them
apprised of their children’s progress and to enlist them in supporting school
improvement efforts.
 Scheduling - adjustments were made in the daily schedule in order to increase
time for academic work.
The most current research by Odden (2009) in his book 10 Strategies for
Doubling Student Performance also highlight strategies that schools can use to improve
or “double” student performance based on a synthesis of literature and cases studies of
high performing schools. In his research, he found the following:
 Understanding the performance problem and challenge
 Set ambitious goals
 Change the curriculum program and create a new instructional vision
 Formative assessments and data-based decision making
 Ongoing, intensive professional development
 Using time efficiently and effectively
 Extending learning time for struggling students
 Collaborative, professional culture
 Widespread and distributed instructional leadership
 Professional and best practice
He provides a synthesis of the work that has come before him to include not only
teachers, but also leaders within the organization. He recognizes that, in order to have a
successful school both, partners, teachers and administrators, must have a shared vision
of student success.
DISTRICT ALLOCATION OF HUMAN RESOURCES 30
Overall, the research indicates that, in order for school districts and their schools
to be successful, there are many variables to consider and there is much to do by way of
improvement.
Emergent themes for system-wide instructional improvement. Based on the
review of the literature regarding the various levels within the organization we call
school, basic trends emerge regarding successful schools across all levels: the need for
strong leadership, a coherent professional development plan and a focus on data-driven
decision making.
Leadership. Leadership is defined by Northouse (2010) as a process whereby an
individual influences a group of individuals to achieve a common goal. This idea is
conceptualized in the book Good to Great by Jim Collins (2001). Based on his case
studies of companies that had surpassed their counterparts and moved from “good” to
“great,” he found that the driving force behind those changes was Level 5 Leadership
where executives build enduring greatness through a paradoxical blend of personal
humility and professional will.
In the realm of education, this could mean a principal influences his/her staff to
raise student achievement in reading or an instructional coach influences the work of a
math teacher implementing a new curriculum. In either case, the goal is to have a
positive impact on student achievement. To ensure that this happens, leaders must
develop mission/vision/goals and a leadership style that values the contribution of others.
Vision, Mission, and Goals. Hallinger and Heck (2002), in their review of the
literature on leadership and school improvement, sought to clarify the terms vision,
mission and goals because researchers use terms synonymously, but they have different
DISTRICT ALLOCATION OF HUMAN RESOURCES 31
theoretical foundations. With clarity of purpose surrounding these concepts, school
leaders can effectively operationalize vision, mission and goals to improve student
achievement. According to their work, a vision can identify a path to a new future, most
namely critical paths for change and organizational learning leading to school
improvement (Leithwood, Harris, & Hopkins, 2008) While a vision is just a starting
point, a mission is born when a group of people has a shared vision for improvement.
School leaders can then use this mission to share clear expectations for staff and students
within the organization. Lastly, goals clarify where people want to go and are specified
in measureable terms. All three concepts give power to school improvement because
they design a shared quest undertaken by the entire group.
Moving beyond the definitions, Huber and Muijs (2010) and Fullan (2010) found
that schools classified as successful possess competent and sound school leader who is
goal-oriented and decisive. They also found that these leaders had a laser-like focus on
instructional improvement and could leverage their ties with the community to realize
goals.
Transformational and Distributed Leadership. Spillane, Halverson and Diamond
(2001) provide a framework for understanding distributed leadership related to their
study of Chicago schools. In their framework, they define distributed leadership as
leadership that is grounded in the context of the school and the situations that arise.
Additionally, it takes into consideration the interaction between people and leadership,
where leadership responsibilities can be stretched over multiple leaders.
Transformational leadership, on the other hand, as defined by Northouse (2010),
is the process whereby a person engages with others and creates a connection that raises
DISTRICT ALLOCATION OF HUMAN RESOURCES 32
the level of motivation and morality in both the leader and the follower. It is concerned
with improving the performance of followers and developing followers to their fullest
potential.
According to the research, both of these leadership styles are fundamental in
building successful schools (Huber & Muijs, 2010). These styles take into account the
need to empower others and to establish conditions for teaching and learning in a
coordinated and collaborative way (Huber & Muijs, 2010; Leithwood et al., 2008).
Capacity Building through a Collaborative Culture. In successful schools,
effective leaders take the time to build capacity in their staff and they usually do this by
employing a collaborative culture. Capacity building is defined in the work of DuFour
and Marzano (2009) as the ability of leaders to provide time, structures, training,
resources and clarity of purpose so that teachers can do the work of clarifying essential
curriculum, creating common assessments, establishing consistent pacing and using
results to inform instruction. In setting the conditions for this work, leaders are building
the capacity of their staff to set their own direction and make progress toward raising
student achievement (Fullan, 2010).
A collaborative culture consists of collaborative teams working together to focus
on questions and issues that directly affect student learning (DuFour & Marzano, 2009).
To be effective, teams should meet once per week and have leaders who meet with these
teams quarterly to review their work (DuFour & Marzano, 2009). These leaders then
provide training, support and resource tools and templates to be effective. In essence,
this culture creates a synchronization of both top-down and bottom-up leadership
approaches focusing on instructional improvement (Huber & Muijs, 2010).
DISTRICT ALLOCATION OF HUMAN RESOURCES 33
Schmoker (2010) further articulates the need for a collaborative culture, arguing
that strategic planning and comprehensive reform efforts as they are done currently do
not work the way they are supposed to because they are too complex and typically are
laced with too many goals and action steps to be done properly. He goes on to say that
we must replace these complex plans with simpler plans that focus on actual teaching
lessons and units created in learning communities that promote team based short term
action and thought. He also believes that, through short term trial and error, teachers find
more effective ways to teach and that educators must work in teams to implement, assess
and adjust instruction in short-term cycles of improvement – not annually, but
continuously.
He outlines 5 benefits of improving schools in this way:
 Higher quality solutions to instructional problems
 Increased confidence among facility
 Increased ability to support one another’s strengths and accommodate
weakness
 Systematic assistance to beginning teachers
 Ability to examine an expanded pool of ideas, methods and materials
In summary, Marzano, McNulty and Waters (2005) offer the most comprehensive
listing of leadership responsibilities that lead to school improvement. Based on their
culling of the research on school leadership, they created a table of leader responsibilities
that summarize the aforementioned themes in the literature.

DISTRICT ALLOCATION OF HUMAN RESOURCES 34
Table 1
McREL Researchers Identified the 21 Key Leadership Responsibilities that are
Significantly Correlated with Higher Student Achievement
Responsibility The extent to
which the
princip a l …
Average
r
Number of
Studies
Number of
Schools
Situational Awareness Is aware of the
details and
undercurrents in
the running of the
school and uses
this information to
address current
and potential
problems
.33 5 91
Flexibility Adapts his or her
leadership
behavior to the
needs of the
current situation
and is comfortable
with descent
.28 6 277
Discipline Protects teachers
from issues and
influences that
would detract
from their
teaching time or
focus
.27 12 437
Monitoring/Evaluation Monitors the
effectiveness of
school practices
and their impact
on student
learning
.27 31 1129

DISTRICT ALLOCATION OF HUMAN RESOURCES 35
Table 1, continued

Outreach Is an advocate and
spokesperson for
the school to all
stakeholders
.27 14 478
Change Agent Is willing to and
actively
challenges the
status quo
.25 6 466
Culture Fosters shared
beliefs and a sense
of community and
cooperation
.25 15 809
Responsibility The extent to
which the
principal…
Average
r
Number of
Studies
Number of
Schools
Responsibility
Input Involves teachers
in the design and
implementation
of important
decisions and
policies
.25 16 669 Input
Knowledge or
Curriculum,
Instruction,
and
Assessment
Is knowledgeable
about current
curriculum,
instruction, and
assessment
practices
.25 10 368 Knowledge or
Curriculum,
Instruction,
and
Assessment
Order Establishes a set
of standard
operating
procedures and
routines
.25 17 456 Order
Resources Provides teachers
with materials
and professional
development
necessary for the
successful
execution of their
jobs
.25 17 571 Resources
Contingent
Rewards
Recognizes and
rewards
individual
accomplishments
.24 9 465 Contingent
Rewards

DISTRICT ALLOCATION OF HUMAN RESOURCES 36
Table 1, continued

Focus Establishes clear
goals and keeps
those goals in the
forefront of the
school's attention
.24 44 1619 Focus
Intellectual
Stimulation
Ensures that
faculty and staff
are aware of the
most current
theories and
practices
.24 4 302 Intellectual
Stimulation
Responsibility The extent to
which the
principal…
Average
r
Number of
Studies
Number of
Schools
Responsibility
Communication Establishes
strong lines of
communication
with teachers and
among students
.23 11 299 Communicati
on
Ideal Beliefs Communicates
and operates
from strong
ideals and beliefs
about schooling
.22 7 513 Ideal Beliefs
Involvement in
Curriculum,
Instruction, and
Assessment
Is directly
involved in the
design and
implementation
of curriculum,
instruction, and
assessment
practices
.20 23 826 Involvement
in Curriculum,
Instruction,
and
Assessment
Visibility Has quality
contact and
interactions with
teachers and
students
.20 13 477 Visibility
Optimizer Inspires and
leads new
challenging
innovations
.20 17 724 Optimizer

DISTRICT ALLOCATION OF HUMAN RESOURCES 37
Table 1, continued
Affirmation Recognizes and
celebrates school
accomplishments
and
acknowledges
failures
.19 6 332 Affirmation
Relationships Demonstrates an
awareness of the
personal aspects
of teachers and
staff
.18 11 505
Source: School Leadership that Works: From Research to Results (Marzano, Waters, &
McNulty, 2005)

Professional Development. Over the last two decades, the research on
professional development has sought to examine the qualities of effective professional
development and the relationship between professional development and student
achievement. While the evidence on what makes quality professional development is
quite clear, how professional development relates to student achievement is an area that is
ripe for further study.
Qualities of Effective Professional Development. The literature on professional
development, otherwise known as PD, clearly states that there are qualities that make
some PD more effective than others. Researchers agree that quality PD begins with
meaningful engagement by teachers with problems related to curriculum or instruction
(Little, 1993; Joyce & Calhoun, 1996; Smylie, 1996; Birman, Desimone, Porter, & Garet,
2000; Supovitz & Turner, 2000). They also agree that teachers must tackle these
problems as schools, departments or even grade levels (Birman et al., 2000). Lastly, they
agree that PD must be built upon itself and focus on school improvement (Birman et al.,
2000; Supovitz & Turner, 2000). After these three initial agreements, the literature
becomes divergent.
DISTRICT ALLOCATION OF HUMAN RESOURCES 38
In her work, Little (1993) discusses the need for informed dissent and opening up
of debate about instructional practice. This allows teachers of all perspectives to give
voice to their opinions provided they have information that says they are right. She also
discusses the need to take into account the experience of teachers as a valuable form of
professional development (Supovitz & Turner, 2000) and the need to ensure bureaucratic
restraint and a balance between the interests of individuals and the interests of
institutions.
While the work of Little cautions the balance between teachers and institutions,
the work of Birman et al. (2000) details more clearly the explicit steps that developers of
professional development should follow from a study of 1,000 teachers who participated
in the federal government’s Eisenhower Professional Development Program funded by
Title II. In their research, they found the following six components of effective
professional development:
 Form - professional development followed up by teacher coaching, modeling,
and observations was most effective.
 Duration - longer is better.
 Collective Participation
 Content - professional development that focused on specific content areas was
more effective than that which focused on generic teaching methodologies or
strategies.
 Active Learning
 Coherence - good professional development was shown to build on itself
DISTRICT ALLOCATION OF HUMAN RESOURCES 39
While many of the qualities are similar to what was noted above, the most
significant difference is the quality of duration. In their research, they find that
professional development should be longer in duration to allow teachers to engage with
materials in a deeper way. Their research on duration is continued in a study by Garret,
Porter, Desimone, Birman and Yoon (2001). In their research, 1,027 math and science
teachers were utilized to provide the first large-scale empirical comparison on the effect
of different characteristics of professional development on teachers’ learning. Their
findings indicate that time span and contact hours were found to have a substantial
positive influence on opportunity for active learning and coherence. Longer activities
tended to include substantially more opportunities for active learning and also tended to
promote coherence including connections to a teacher’s goals and experience, alignment
with standards, and professional communication with teachers.
Supovitz and Turner (2000) offer one additional different characteristic of
professional development: it should have a common set of standards and show teachers
how to connect their work to the standards.
Changes to current professional development practices. Besides agreeing on
qualities of effective professional development, researchers also agree that traditional
methods of professional development delivery must change in order to have a positive
impact on student achievement. Most notably, they agree that professional development
must be embedded in the work of teachers and be collaborative in nature in order to meet
the challenges of educational accountability reforms that have been pervasive over the
last decade (Little, 1993; Corcoran, 1995).
DISTRICT ALLOCATION OF HUMAN RESOURCES 40
Corcoran (1995) asserts that most districts are doing what they have always done
in regards to PD, even though standards for what students must know and be able to do
have changed dramatically. Most professional development programs lack continuity
and follow-up. Themes from his research include the concept of more teacher work time,
teachers working together and creating interdependence among teachers to solve
problems and improve practice.
Louis, Marks, and Kruse (1996) concur with the need for additional collaborative
time to create communities that focus on student learning. In their study of 8 elementary,
8 middle and 8 high schools that had made substantial progress in organizational
restructuring found that professional community contributed strongly to responsibility for
student learning. They conclude that changing school structures-providing time for
collaborative planning, shared decision making, simplifying school staffing patterns.
Spending on professional development. The value of collaboration is even
evident in recent studies that examine the expenditure on professional development by
schools. Fermanich (2002) reveals a high percentage of funds are spent on “teacher
time.” From the research, analyzing school spending on training and collaboration
increased the percentage of general funds spent on PD. Common planning time was
included as a PD cost and accounted for 27% of spending in schools.
Some researchers take a different perspective with regard to professional
development, specifically examining the relationship between spending on professional
development and increases in student achievement. The hope with this new line of
research is that educators can standardize the spending on PD across districts allowing
DISTRICT ALLOCATION OF HUMAN RESOURCES 41
policymakers to better make decisions on how to allocate funds for professional
development.
Odden, Archibald, Fermanich and Gallagher (2002) found that, generally
speaking, there is a lack of knowledge about how much districts are spending on PD
because of primarily three problems with reporting on PD expenditures: crude and
inaccurate cost estimates because accounting codes do not allow for accurate tracking of
PD expenditures, using different frameworks for capturing PD expenditures, and
collecting data only from district level while ignoring school investments. Compounding
the problem is that job-embedded PD activities are becoming more prevalent. It is more
difficult to estimate the total costs of PD. The authors attempt to provide a “cost
framework” so that there is a common language for discussing PD programs. With the
use of the proposed common cost framework, schools and districts can make better
informed decisions about PD in both program and spending.
Research done by Miles, Odden, Fermanich, and Archibald (2004) takes a
different approach in looking at professional development. In their research, they not
only wanted to define the components, purpose and organization of professional
development, they also wanted to track and describe the costs. Ultimately, the authors
wanted to create a cost framework of professional development that will allow districts
across states to get on the same page with regard to professional development. In their
study, six lessons became apparent. First, districts invest significant funds to professional
development. Second, estimates of spending should explicitly account for the cost of
contracted time for PD. Third, district spending to provide teacher time for PD is
significant, but highly variable. Fourth, most districts target PD at school-level capacity
DISTRICT ALLOCATION OF HUMAN RESOURCES 42
building, but have no formal strategies for coordinating/integrating these investments.
Fifth, districts use common delivery strategies for PD, but in very different mixes.
Lastly, districts rely on external sources of funding for almost half of PD that is provided.
Based on what we currently know about professional development, there needs to
be changes to the current practices of funding PD. As districts get on the same page as to
how PD is defined and how to calculate cost, researchers can start looking at its impact
on teacher practice and student performance, which will allow policymakers and
education leaders to organize support and make investments matter.
Data-driven decision-making within PLCs. Researchers agree that teachers need
to use data to inform their instruction and to improve student achievement. Data-driven
decision making refers to teachers and school administrators analyzing various forms of
data to help improve the success of students and schools (Marsh, McCombs & Martorell,
2009). The work of Datnow, Park, and Wohlstetter (2007) captures the work of four
school systems that were identified as leaders in data driven decision-making. These
organizations continually build a foundation for data driven decision making by having a
clear set of goals at all levels of the organization and establishing a coherent curriculum
(Hamilton et al, 2009; Wayman, Midgeley & Stringfield, 2005;). These support systems
allow educators a starting point from which to make instructional decisions and allow for
replicability and scalability between schools within the district and across districts
(Wayman, Midgeley & Stringfield, 2005). Beyond establishing goals and a clear
curriculum, these districts established a culture of data use and continuous improvement
by selecting the right data (Hamilton et al, 2009). This means that teams triangulate data,
pulling data from several sources to get a clear picture of student strengths and
DISTRICT ALLOCATION OF HUMAN RESOURCES 43
weaknesses, so teachers can analyze that data to improve instruction, which provides the
initial step for linking student achievement data with instruction (Hamilton et al., 2009;
Wayman, Midgeley & Stringfield, 2005). Lastly, they have invested in an information
management system to make data processing and analysis easier for teachers (Hamilton
et al., 2009; Wayman, Midgeley & Stringfield, 2005).
Two additional points concerning data-driven decision making come from the work
of Wayman, Midgeley and Stringfield (2005) and Hamilton et al (2009). The former
believes that there is a reciprocal relationship between data use and collaboration. Data
initiatives are more successful if teachers are allowed to work collaboratively, and the use
of data helps foster constructive collaboration. The later asserts that educators should
teach students to examine their own data and set learning goals. Both of these strategies
will allow data to be meaningful to both teachers and students.
Besides knowing the characteristics of effective data driven organizations, the
research on the topic also indicates that there are multiple benefits to using a data-based
approach in schools. In their research, Thornton and Perreault (2002) outline four
benefits of a data-based approach to school leadership:
 Document improvements in instruction
 Measure success/failure in specific programs
 Guiding curriculum development
 Promoting accountability
Even as educators use data to inform their instruction, there are things that
administrators can do to make the road easier for teachers. First, they can provide
meaning to state and local assessments by engaging teachers in meaningful projects and
DISTRICT ALLOCATION OF HUMAN RESOURCES 44
build on each success to ensure data-based decision-making becomes routine. They can
communicate openly with staff about progress toward meeting agreed upon goals and
provide a systematic approach to data analysis. Working in this way will help to
establish an aligned staff development plan. The most important thing they can do for
teachers is to provide time for teachers to analyze data in teams (Thornton and Perreault,
2002).
Knowing what attributes make for effective data use and knowing the benefits
comprise only one piece of the puzzle. Heritage and Chen (2005) give educators five
specific actions they can take in collaborative groups to use data to inform instruction.
1. Determine what you want to know: questions that guide inquiry
2. Collect data making sure to ensure that your data is valid and reliable
3. Analyze Results using multiple methods
4. Set Priorities and Goals
5. Develop Strategies
They state that the goal of data analysis infiltrating schools depends on the ability
of educators to collect and analyze data and set goals and targets based on their analysis.
Current preparation programs do not teach teachers and administrators the prerequisite
skills to use data effectively.
Over the last ten years, data driven decision making has become even easier with
the implementation of PLC’s. Louis, Marks, & Kruse (1996) define professional
community as having five elements: shared values, a focus on student learning,
collaboration, deprivatized practice, and reflective dialogue. The beginnings of PLC can
be seen in the work of Joyce and Calhoun (1996), who state that, for schools to become
DISTRICT ALLOCATION OF HUMAN RESOURCES 45
learning communities, significant organizational changes are required, namely restricting
job assignments and schedule to build time for collective inquiry into the workplace will
increase school-improvement activity. They also found that piecemeal strategies have
not been effective in school improvement. In the five case studies they conducted, they
found success because of the extensive involvement of all personnel from the outset.
Louis and Marks (1998) studied the impact of school professional community on
student performance by using survey data from 24 schools and 910 teachers. Surveys,
interviews, observational data, assessment tasks, student work and case studies were all
used as data points. Findings suggest that both professional community and social
support for achievement have a positive relationship to student performance.
The work of DuFour, DuFour, Eaker and Many (2010) in their book, Professional
Learning Communities at Work, ties all of the preliminary research on collaborative
practice and data driven decision making into a systematic process that teacher teams can
use to improve instruction and assessment. The basis of PLC is centered on four
questions that teachers use to direct their inquiry into problems of student performance:
What do we want students to learn? How will we know if they have learned it? What
will we do if students have not learned it? What will do when students have learned it?
Focusing on these essential questions forces teacher teams to have conversation about
what student learning looks like at any given grade level, the assessments practices that
are used to determine if students have mastered the curriculum and what strategies will be
employed for struggling students and those that have mastered the content. Additionally,
the conversations that abound around these questions are the first line of staff
development for teachers.
DISTRICT ALLOCATION OF HUMAN RESOURCES 46
In conclusion, school improvement requires teachers, administrators, parents and
the district office to all work together and for all systems within the organization to be
aligned: curriculum, instruction and assessment. In order to do this, educators must
remember that improvement is a developmental process that occurs in stages where we
must, “tear down old preconceptions, try out new ideas and practices working hard to
incorporate new ideas and practices” (Elmore, 2003 p. 9). We must also create a sense of
urgency in our communities in order to make change feasible (Odden, 2009). If we can
do all of these things, we are one step closer to building a school worthy of our students
and a school that is driven to excellence.
Times of Fiscal Crisis: Doing what is Right with Limited Resources
Based on the extant research, educators know what structures and strategies are
needed within an organization to improve student performance, but, unfortunately,
especially in California, there are limited resources to make these goals a reality. In late
2008, a global financial crisis plunged the US and world economies into the worst
recession since the Great Depression, leading to the sharpest declines to education
funding in recent memory and major changes to public education throughout California
(Mead, Vaishnav, Porter, & Rotherham, 2010; Shambaugh, Kitmitto, Parrish, Arellanes,
& Nakashima, 2011). In the past four years, public education has been cut by more than
$20 billion; class sizes have soared at all grade levels; more than 40,000 educators have
been laid off; art, music, vocational education and after-school programs have been
eliminated (California Teachers Association, 2012). The sheer magnitude of these cuts
illuminates the state of emergency in California’s educational system (Shambaugh, et al.,
2011).
DISTRICT ALLOCATION OF HUMAN RESOURCES 47
There have been many responses at both the federal and state level to the current
fiscal crisis in California’s public schools. Much of the response has been to fill holes in
the budget to ward off even more catastrophic changes (Mead, et al., 2010). To fill in
these holes, the federal government provided one-time-use money and the state
government has increased flexibility in funding, so decision makers at the local level can
use money to fit their individual district and school needs.
Federal response to fiscal crisis: American Recovery and Reinvestment Act.
In February 2009, the American Recovery and Reinvestment Act (ARRA) provided $100
billion in federal dollars toward education, which saved 47,000 California educator jobs
(Mead et al., 2010). This funding included $54 billion in State Fiscal Stabilization Funds
(SFSF) intended to stabilize state budgets and avert cuts to education (Mead et al., 2010).
SFSF is different than most federal allocations in that the law permits states to use the
“one time money” to fill holes in state budgets (Mead et al., 2010). This one time
spending boost was larger than the entire annual budget of the U.S. Department of
Education (Mead et al., 2010). In many cases, the funds simply helped districts tread
water as several states cut education budgets by roughly the same amount. Overall, the
funds were used to preserve existing programs, services and educator jobs (Mead et al.,
2010). To this end, Roza and Funk (2010) wrote a report on 23 state budget plans to
explore how state education spending had changed or will change with the ARRA funds.
Their analysis examines changes in education spending as a portion of the state budget in
the year State Fiscal Stabilization Funds (SFSF) was applied. They found that education
as a share of the state budget fell in 13 out of 23 states examined. These findings mirror
the work of Mead et al. (2010) in that they found that districts used ARRA funds
DISTRICT ALLOCATION OF HUMAN RESOURCES 48
primarily to maintain spending levels in the face of state and local budget cuts. They also
found that budget pressures on states and districts are proving to be even greater and
longer-lasting than initially expected and are a long term systematic problem.
States response to fiscal crisis: Myriad responses. Reschovsky (2004) explores
how state governments have in fact responded to past budgetary shortfalls, specifically
the extent to which states have protected their local governments and school districts
from funding cuts. His findings indicate that the strategy followed by many states to
balance their budgets was to reduce funding to K-12 public education. This finding is not
unique to California, but many states have offset this occurrence by raising money at the
local level through increases in property taxes. Unfortunately, this is not the case in
California, as Proposition 13 restricts the amount of additional property tax revenue that
can be allocated each year (Reschovsky, 2004; Alm & Sjoquist, 2009). Many districts
also turn to private foundations and increased voluntary contributions (Reschovsky,
2004). Continuing to make cuts to education is not going to serve the students of
California, so policymakers have also looked for additional ways to ease the tension of
cuts.
Categorical program flexibility. The main way that California responded to this
time of fiscal stress is to provide spending flexibility in their categorical programs. In
2009, the state legislature relaxed spending restrictions on more than 40 categorical
programs through 2014-2015, allowing districts to spend these funds for any educational
purposes (Weston, 2011). While this flexibility allowed school districts to fill budget
gaps, Weston (2011) proposes three ways to improve current flexibility to categorical
programs. She aims to create a more equitable and transparent source of revenue by
DISTRICT ALLOCATION OF HUMAN RESOURCES 49
consolidating funding, setting per pupil funding rates, and applying clear criteria for
flexibility. She does contend that having a system of some restricted funds is good as
well – so that funds do not support general salary increases. She also asserts that,
“allowing the state to continue direct spending on disadvantaged students and ELL while
providing districts with the flexibility to determine the best way to meet their needs”
(Weston, 2011, p. 25).
Reductions and removals. The work of Shambaugh et al. (2011) also provides
many other ways in which the state responded to the fiscal crisis. First, they allowed
districts to forgo purchasing new instructional materials. They found that over 57% of
principals interviewed delayed or cut back scheduled purchases of new textbooks
(Shambaugh et al., 2011). The state also allowed districts to decrease the required
number of school days. The most significant change in California is that the state
reduced incentives for smaller class sizes. All of these changes put students at a
disadvantage and make raising student achievement even more difficult.
Tax initiative. While the shortages in school funding fall on local districts in
many states, such is not the case in California. To help soften the blow of education cuts,
various groups, ranging from Governor Brown to community groups and the California
Teachers Association, formed a coalition in support of the Compromise Tax Initiative.
As the name implies, it is a compromise from several measures proposed for the
November 2012 ballot (California Teachers Association, 2012). According to the
coalition, the initiative is a balanced solution because it helps balance California’s state
budget without raising income taxes on those hit hardest by the recession (California
Teachers Association, 2012). All the revenue increases in this initiative are strictly
DISTRICT ALLOCATION OF HUMAN RESOURCES 50
temporary, designed to restore education funding and bring California’s budget back into
balance during these difficult times. Should this initiative fail, schools and colleges
would face more than $5 billion in additional budget cuts.
The work of Shambaugh et al. (2011) provides a succinct package of what
policymakers in California should consider in these tough economic times. In their
study, they conducted interviews with 16 different stakeholders from different levels
throughout the California school system to understand the kinds of decisions practitioners
and policymakers have been facing during those tough economic times. From their
interviews, they found four key considerations for state policymakers:
 Stabilizing and increasing education funding in the state
 Making permanent the funding flexibility allowed during the fiscal crisis
 Reforming the current budgeting process to lessen the burden on districts
 Changing state regulations on seniority to increase flexibility for districts
staffing conditions
Responses at district/local level. Based on the responses at both the federal and
state levels, school districts also must make changes and respond to budgetary shortfalls,
usually resulting in a shift of priorities in the face of declining funds. In her work, Ladd
(1997) seeks to determine how school districts typically respond to fiscal constraint. Her
findings indicate that fiscal constraints hurt students by making it necessary for schools to
have larger class sizes. In fact, 35% of school districts in California raised class size in
2010 (Shambaugh et al., 2011). Besides larger class sizes, fiscally constrained districts
spend less on central administration, have higher proportions of their total staff in
DISTRICT ALLOCATION OF HUMAN RESOURCES 51
teaching positions than non-teaching positions, and have disproportionately less support
staff.
The work of Shambaugh et al. (2011) echoes these results and finds that fiscally
constrained districts are forced to lay off teaching staff, cut salary and benefits, make
staff take furlough days and other salary reductions. They also found that there are cuts
to educational programs, most at the elementary school level, field trips, and after school
programs (Shambaugh et al., 2011). They also cut technology, maintenance/facilities,
transportation and athletics, and put off some professional development activities which
may hurt the development of some teachers in the long term (Shambaugh et al., 2011).
The only program that was untouched was Special Education due to legal entitlement of
these students to the full breadth and intensity of services prescribed in their Individual
Education Plan (Shambaugh et al., 2011).
Resource Allocation in Schools: Changing Theories of Action
The way that schools allocate resources significantly changed over time, not only
in actual dollars, but in the philosophical underpinnings of how schools should spend
money on education. Both of these changes are complex in nature and must be
completely understood if school finance systems are restructured to meet the academic
needs of students and increase student outcomes (Odden, Monk, Nakib, & Picus, 1995).
Educational dollars over time. Research done in the last decade indicates that
there has been an investment in public education, but the funds have been distributed
unfairly and used ineffectively (Odden et al., 1995). According to the work of Hanushek
and Rivkin (1997), education spending rose from $2 billion in 1890 to $187 billion in
1990. Not only that, but spending roughly quintupled from $164 per pupil in 1890 to
DISTRICT ALLOCATION OF HUMAN RESOURCES 52
$772 per pupil in 1940 and then roughly quintupled again to $4,622 per pupil in 1990
(Hanushek & Rivkin, 1997). An increasing problem is the dilemma of small amounts of
improvement in student achievement despite large increases in spending (Odden & Picus,
2008).
Instructional staff: Teachers and instructional aides. One of the largest changes
in the last 100 years in education funding has been the consistent increases to teacher
salary and the addition of instructional support staff. Teachers make more today than in
the 1960; however, they have not gained much ground compared to other occupations
since 1970 (Hanushek & Rivkin, 1997; Odden et al., 1995). In fact, the increase in
teacher salaries happened, but it was not enough to keep on par with other occupations
(Hanushek & Rivkin, 1997). In addition to the increase in teacher salary, a large portion
of real dollar increases was used to add non-core staff such as instructional aides and
other support staff (Odden et al., 1995).
For the better half of the 20
th
century, the percentage of regular classroom
teachers dropped by 33%, with an increase in the amount of elective teachers found
throughout K-12 systems (Odden et al., 1995). At the time of this study, more than 50%
of high school teachers provided instruction in non-core classes and less than 50% of the
school budget is spent on teachers in the core academic areas (Odden et al., 1995).
Increasingly, investments have been made to non-core classes as opposed to core subjects
(Odden et al., 1995). The question that remains is whether some of these resources could
be used to fund special programs or be reallocated to core subjects where student
achievement is not sufficiently high (Odden et al., 1995).
DISTRICT ALLOCATION OF HUMAN RESOURCES 53
Special education. Over the last several decades, the total number of students
identified with special education needs increased while the general population of students
declined. Between 1980 and 1990, the general population of students dropped by more
than 1.5 million students, but the population of special needs students grew by 700,000
(Hanushek & Rivkin, 1997). With an increase in special needs students came an increase
in the number of instructional staff members to support them. From 1978 to 1990, the
special education teacher population grew more than 50% (Hanushek & Rivkin, 1997).
In fact, more teaching staff was used to expand special education during the 1980s,
disproportionate to other increases (Odden et al., 1995). Besides the increased resources
to special education, current research on school finance questions the way special
education is funded. Current revenues in the public education system already targeted to
special education are generally sufficient to support extra services; however, they usually
come from local dollar when it should be replaced by state or federal revenues (Odden et
al., 1995).
A shift from equity to adequacy. Long focused on fiscal equity, school finance
is now shifting toward fiscal adequacy. This shift represents a fundamental change over
time (Baker, 2005). School finance today encompasses not only fiscal inputs, but also
their connection to educational programs, teacher compensation and student achievement
(Baker, 2005). As defined by Clune (1994), equity means equal and implies that one
district or school receives the same amount as another usually in the same state or district.
Adequacy, on the other hand, means adequate for some purpose, and that purpose is,
typically, student achievement (Clune, 1994). To achieve a given level of adequacy,
adequacy studies aim to determine objectively the amount of funding needed to provide
DISTRICT ALLOCATION OF HUMAN RESOURCES 54
all students with a meaningful opportunity for an adequate education (Rebell, 2006).
Prior to 1990, there were only a handful of adequacy studies, but, starting in 1990,
adequacy cost studies have been conducted in more than 30 states. While the purpose of
the studies vary from school funding lawsuits to requests from lobbying groups, they
have a potent impact as an increasing number of legislatures have directly relied on cost
studies in formulating their education funding policies (Rebell, 2006). For example, in
1989, the Kentucky Supreme Court’s decision in Rose v. Council for Better Education
was the first to focus on adequacy, as it deemed the entire Kentucky school system
unconstitutional, leading to the Kentucky Education Reform Act to create an adequacy
based school funding model (Picus, 2004).
There will probably never be a single standard that applies across all states as the
absolute cost of an adequate education. “The overall level or absolute standard of
adequacy of any state’s public educational system will continue to be derived from the
political will of legislatures under the watchful eye of courts in the sometimes tenuous
context of fluctuating state economies” (Baker, 2005, p. 260). Most notably, there are
those lobbying for cost increases for students with special educational needs because
those students need different levels of resource intensity, more teacher contact time, and
may also need greater or different levels of resource quality, and instructors with special
training/background (Baker, 2005).
Even with no definitive answer as to which approach is best for students,
researchers agree that, to better meet the needs of students, continued research and
understanding is needed regarding the four different approaches to achieving educational
DISTRICT ALLOCATION OF HUMAN RESOURCES 55
adequacy: the successful school district approach, cost function approach, professional
judgment approach, and the evidence-based or expert judgment.
Successful school district a vpproach. This approach uses average expenditures
from successful school districts as a fair estimate of the actual cost of an adequate
education and establishes a direct link between costs and desired outcomes, but it is
dependent on availability of accurate data from the school district (Rebell, 2006). As of
the date of this study, it has been implemented in Illinois, Maryland, Mississippi, and
Ohio (Odden, 2003; Rebell, 2006).
Cost function approach. The cost function approach uses statistical modeling to
determine what certain levels of achievement would cost. The model generates how
much a particular school district would spend relative to the average district to produce a
set performance target, given characteristics of the school district and student body
(Rebell, 2006). Currently, Texas is the only state to use this approach (Gronberg, Jansen,
& Taylor, 2011) namely due to the fact that explaining the model outside of academic
circles is difficult and the reliance on available data limits accuracy (Rebell, 2006).
Recent research also suggests that district inefficiency is difficult to measure with great
precision and accuracy, leading to distortions in cost function analysis (Baker, 2005).
Professional Judgment Approach. The professional judgment approach uses a
panel of educators to design an educational program that would deliver an adequate
education and to identify specific resources needed for success (Rebell, 2006). After the
base prototype school is created, panel members are asked to consider whether extra
resources should be required for certain groups (Rebell, 2006). This model takes
advantage of educators’ familiarity with the learning needs of the area, promotes dialogue
DISTRICT ALLOCATION OF HUMAN RESOURCES 56
and consensus. One disadvantage is that it lacks specificity and statistically oriented
methodology (Rebell, 2006). The approach has been used in Kansas, Maryland, Oregon
and Wyoming (Odden, 2003).
Expert Judgment/Evidence Based Approach. This approach is a variation on the
professional judgment approach, as it derives resource needs from the literature on
“proven effective” school reform models instead of expert judgment (Rebell, 2006). This
approach allows expert researchers to make choices depending on educational delivery
strategies that they believe to be supported by research or proven best practices. One
advantage is its simplicity, transparency and comprehensive inclusion of a full range of
needs and outputs, while a disadvantage is that the validity is undermined if the research
base is inconclusive, limited and applicability in the particular context has not been tested
(Rebell, 2006). This approach was used as the basis for the 1998 final state Supreme
Court decree in the 25 year old school finance litigation in New Jersey (Odden, 2003). A
variation of the model has been proposed in Wisconsin, and this approach was the basis
for a recent recommendation to the Kentucky State Board of Education (Odden, 2003).
Currently, Odden and Picus are the prime researchers using this approach and
have conducted research in various states across the country using their Evidence Based
Model, which will allow schools to deploy just about every strategy research has shown
to have a statistically significant impact on student learning (Odden, 2003). Figure 2.1
presents an overview of the Evidence Based Model.

DISTRICT ALLOCATION OF HUMAN RESOURCES 57

Figure 1. The Evidence Based Model. Source: PowerPoint by Dr. Lawrence O. Picus
(2011)
In their work using the Evidence Based Model, Odden, Picus, Fermanich, and
Goetz (2004) conducted an adequacy study for the Arizona Department of Education that
outlined a clear strategy for spending all money more effectively – both the money
currently in the system and any new money that might be allocated. Their study provided
a blueprint of how to double or even triple student performance throughout the state. In
their report, they outline a new school vision for the state encompassing all of the
components of the evidence based model. In the end, they recommend a phase-in
approach for the new model starting with full day kindergarten, moving on to
instructional coaches/professional development, class size over 5 years, and, lastly,
technology.
Continuing their work, Lawrence O. Picus and Associates (2006) conducted a
study of 107 schools in Arkansas, where the legislature had increased school resources
Instructional
Materials
Pupil Support:
Parent/Community
Outreach/
Involvement
Gifted
Tutors and pupil support:
1 per 100 at risk
Elem
20%
Middle
20%
High School 33%
The Evidence Based Model:
A Research Driven Approach to Linking Resources to Student Performance
K-3: 15 to 1
4-12: 25 to 1
State and CESAs
District Admin
Site-based Leadership
Teacher
Compensation
ELL
1 per
100
Technology
DISTRICT ALLOCATION OF HUMAN RESOURCES 58
according to the evidence based model. In their research, they found that allocations at
the school level differed from the evidence based model. They found that class sizes
were higher than the evidence based model suggested and that funds were used for higher
salaries and extra help resources for teachers rather than for helping students.
Picus, Odden, Aportela, Mangan, & Goetz (2008) had similar results when they
conducted a study of 334 of the 362 schools in Wyoming, regarding the allocation and
use of school level resources following an increase in education funding. They analyzed
how Wyoming used the funds they received during the first year the state implemented
this funding model. They recalibrated the funding model developed on the finding from
evidence based adequacy studies. They found that, in most cases, districts and schools
employed staff resources in a pattern that varied considerably from the funding model.
Overall, there were significantly fewer certified teachers who provide tutoring services in
sample schools. Many schools chose to use instructional assistants to fill this role.
Research suggests that, before this is a good idea, they have extensive professional
development to be effective in improving student learning. They concluded that
Wyoming may be relying on a different theory on how to improve student performance
than the one embedded in the adequacy model used to develop the funding system.
The most vocal critic of these approaches is Eric Hanushek of Stanford
University. He calls these studies “alchemy” and not real science because they do not
answer, “what level of funding would be required to achieve a given level of student
performance?” (Costrell, Hanushek & Loeb, 2008; Hanushek, 2007; Rebell, 2006) He
does not provide any alternative scientific methodology to accomplish his task and
DISTRICT ALLOCATION OF HUMAN RESOURCES 59
ignores the most critical policy issue at stake – that they provide a rational and more
equitable approach to decision-making even if they are flawed (Rebell, 2006).
No matter what approach is used, the likely outcome will be increased spending
for education and increased accountability for student performance. Policymakers need
to run multiple studies using all adequacy models before making a decision about which
is best for their state (Picus, 2004).
Resource Reallocation: What to do When There is No Money
Thus far, the research has suggested that educators know how to raise student
performance, but there are constraints to that ability based on the current fiscal climate
and how resources have been allocated over time. Over the past ten years, researchers
tried to give schools answers about how they can work with the resources currently in
their systems to better meet the needs of students. This research operates under the
assumption that no new money will make its way to schools and that schools systems can
be more strategic about how they allocate funds.
Miles (1995) conducted a case study of the Boston Public School system. From
her research, she found that using a set of four strategies could potentially free up 42% of
Boston’s teaching resources:
 Reduce the use of pull-out programs
 Redesign provision of teacher-planning and development time
 Modify formula-driven student assignment to create more flexibility
 Restructure daily schedule in secondary schools
Miles and Darling-Hammond (1997) conducted a qualitative study that provides a
framework for resource allocation based on case studies of 5 (3 elementary, 2 high
DISTRICT ALLOCATION OF HUMAN RESOURCES 60
school) high-performing schools. Based on the findings of the study, the authors assert 6
overarching resource reallocation principles, developing further the findings of Miles
(1995):
 Reduction of specialized programs to provide more individual time for all in
heterogeneous groups.
 More flexible student groupings
 Structures that create more personalized environments
 Longer and varied blocks of instructional time
 More common planning time for staff
 Creative definition of staff roles and work schedules
Based on both of these foundational studies, patterns begin to emerge about how
to reallocate resources within a school system, most notable the flexibility and integration
needed across the school system to create smaller class sizes for students and increased
collaboration time for teachers. Additionally, schools must reduce the use of pull-out
programs and integrate these students with their mainstream peers, freeing resources and
putting them back into the system to support all students creating cross functional teams
(Miles, 1998).
New themes are seen in the work of Miles (1998) who focuses on the “missing
piece,” which she defines as schools having limited ability to change their use of
resources to meet higher standards-making school control or resources an important
“missing piece” in creating meaningful accountability. In this brief, she describes the
kinds of changes schools find they want to make in the use and organization of resources,
the typical barriers they confront and how districts are responding to give schools the
DISTRICT ALLOCATION OF HUMAN RESOURCES 61
control they need. Her basic finding is that schools need to have control over their
resources in both personnel and money. Unfortunately, schools face barriers to doing so,
ranging from inaccurate projections of the number of students who will enroll to
contractually defined transfer rules. To help schools fill in the missing piece, she
suggests:
 District managers learn how to meet individual school needs and fulfill
organizational requirements.
 Decentralizing district services and allowing schools choice about their
service providers.
 Looking closely at the teacher contract rules and regulations surrounding
teacher evaluation and hiring.
 Developing systems for matching teachers to open positions based on
qualifications, interests, and school design/philosophy.
 Use of time and length of school day, structure of the teacher work day and
use of teachers from special programs to create smaller groups for academic
subjects.
 Providing support/training for schools to use their resources wisely to support
student learning. In addition, they will need to ensure that schools follow
legal requirements.
The work of Odden (2000) takes a different perspective from that of Miles as his work
details the cost structure of a Comprehensive School Reform Plan based on an
elementary school of 500 students needing to be prorated up or down for schools of
differing size. To build his CSR, model he takes pieces from many successful reform
DISTRICT ALLOCATION OF HUMAN RESOURCES 62
models and identifies a set of elements that should be included in all comprehensive
school designs (Table 2).
Table 2
Cost Structure of a Comprehensive School Reform Plan
Elements of a Comprehensive
Design
Number of Positions Cost
Principal 1 $70,000
Instructional Facilitators 1-2 $50,000-$100,000
Classroom Teachers 20 $1,000,000
Regular Education Specialists 4 $200,00
Strategy for Struggling Students 1-4 depending on poverty level $50,000 for 0%-25% poverty:
$200,000 for 75% - 100%
poverty
Pupil Support/Family Outreach 1-4 $50,000 - $200,000
Technology $125,000
School Provided Professional
Development and Training
$60,000
Base Total 28 $1,605,000
Additional Tutors for all-
poverty schools
3 $150,000
Additional Facilitator 1 $50,000
Family Health Team 3 $150,000
Total with Additional Staff 35 $1,955,000
Source: The Costs of Sustaining Educational Change through Comprehensive School
Reform (Odden, 2005)
Odden (2000) then goes on to discuss how a school would reallocate existing
resources to build this model. First, he suggests changing existing assistant principal
positions into instructional facilitators. Then, he suggests reallocating current categorical
dollars to fund technology and professional development. He urges schools to analyze
DISTRICT ALLOCATION OF HUMAN RESOURCES 63
each element in the table to determine how that element addresses its overall needs and
cautions, that “as districts and schools move forward with comprehensive school reform
strategies they need to ask many, many questions before they select a specific strategy,
and they must ensure above all that the design they select is both affordable and
appropriate to their local needs” (Odden, 2000, p. 438).
Building on the cost structure work of Odden (2000), Odden and Picus (2010)
worked with 4 diverse districts in Ohio to utilize the Evidence Based Model and Strategic
Budgeting Tool to make trade-offs regarding how to best reallocate resources in each
district to maximize student achievement. By definition, the Strategic Budgeting Tool is
an Excel spreadsheet that allows schools districts to input current allocations and
compare them to recommendations provided by the Evidence Based Model. For
example, in one district, Olentangy, a large suburban district, they discovered that, if
Olentangy increased class size in Advance Placement classes to 25 from 15, the school
district would save 13 staffing positions that could be used for other endeavors.
Moreover, if the middle and high schools were to increase class size by 1 student, they
would reallocate 28 positions.
While working with the district, the authors also discuss prioritization of
resources when a district cannot fully fund the EBM. In their perspective, they would
fully fund the full range of professional development before funding other strategies in
the model. Their approach to prioritization has been to provide each state with an
analysis of effect sizes research has identified for every strategy, which allows them to
choose the most cost effective strategies first while assuming the state is unable to fund
all the models resource recommendations immediately.
DISTRICT ALLOCATION OF HUMAN RESOURCES 64
As the fiscal climate across the country has gotten worse, researchers are very
specific about what schools should do to prioritize their spending to maximize student
achievement. Odden and Picus (2011) propose five interrelated strategies for schools to
capitalize on the resources they have in efforts to maximize student achievement. First,
they argue that schools must resist the cost pressures on schools, primarily the need to
reduce classes, hire more elective teachers and give automatic pay increases (Miles,
2011). Second, they contend that schools must develop a more powerful school vision
based on data and adopt new curriculum and textbook materials to put that vision into
place. Third, they say that schools must identify necessary resources to meet the new
school vision, keeping in mind that there are other strategies to support the new vision
besides smaller classes, including professional development and pupil support. Fourth,
schools need to reallocate resources to meet the new vision. If schools are facing budget
shortfalls, the authors suggest being flexible about class size and to provide all of the
resources to help teachers and students (Miles, 2011). Lastly, school districts need to
rethink teacher compensation because they provide weak incentives for the core goal of
the education system- improved teaching and learning (Miles, 2011).
Putting it All Together: Using Gap Analysis to Allocate Resources in Times of Fiscal
Constraint
The Gap Analysis model created by Clark and Estes (2008) is the conceptual
framework that will be used in this study to analyze school district data. In their work,
Clark and Estes (2008) outline seven steps by which organizations can improve
performance and move toward meeting their goals. First, organizations should identify
key business goals. From there, organizations should determine the performance gap,
DISTRICT ALLOCATION OF HUMAN RESOURCES 65
which is a gap between their desired goal and actual performance. Once gaps have been
identified, organizations must analyze gaps to determine causes, which fall into three
main categories: knowledge, motivation and organization. Clark and Estes (2008) define
knowledge and skills gaps as not knowing how to achieve performance goals and
motivation gaps as gaps in the internal, psychological process of going and getting the
job done. They go onto specify that gaps in motivation can come from one of three
motivational indexes: active choice, persistence, or mental effort (Mayer, 2008). Active
choice is defined as occurring when people choose or fail to choose to actively pursue a
work goal. Persistence is defined as persevering through distractions that may derail
individuals from their goals. Mental effort is defined as the amount of effort to invest in
achieving a goal. Clark and Estes (2008) define organizational gaps as gaps in the
efficient and effective organization work processes and material resources. Once all of
the causes for the gaps have been determined, the organization must implement solutions
based on the information and then, lastly, evaluate the results and revise goals.
Conclusions
Given what we know about how schools improve, the current fiscal health of the
nation and how schools should be funded, the wisest choice would be to employ a
resource allocation strategy that embeds research proven strategies to raise student
achievement, that is responsive to times of fiscal constraint, and that gives school systems
the flexibility they need to paint outside the lines. That choice would be the EBM
developed by Odden and Picus (2008), especially because preliminary data shows that it
appears to be working in states that have fully fund the model. The test will be to see
whether California can do it as well.
DISTRICT ALLOCATION OF HUMAN RESOURCES 66
Chapter Three: Methodology
Introduction
Education is facing a perfect storm: accountability increases over time coupled
with the declining fiscal health of schools in California over the last four years
(EdSource, 2010). Both of these events caused schools and school districts to revisit their
financial planning as well as how they meet the academic needs of diverse student
bodies. With school district personnel being the biggest expenditure for a school district,
with the ways in which human resources are allocated is a strategic place to begin
(EdSource, 2012a). Deciding how to allocate these resources can prove difficult, which
is why all parts of the school district must work together to make changes for students.
These changes include changes to instructional practice, teacher collaboration,
professional development, leadership and data-driven decision making.
The conceptual framework of school systems working together to provide an
adequate education for students has its roots in both structuralism and social capital
theory. Considered the “father of structuralism” Claude Levi Strauss believed that
underlying patterns of human thought organize our worldview and that the elements of
culture are not explanatory in and of themselves, but, rather, form part of a meaningful
system (Briggs & Mayer, 2009). In education, this means understanding how all parts of
the system are interconnected and how they must work together to create a whole. This
whole is created through the exchanges made between participants in the educational
system, otherwise known as social capital. The first contemporary analysis of social
capital was produced by Pierre Bourdieu, who defines social capital as the aggregate
resources of all members of the group. He adds that social capital is affirmed and
DISTRICT ALLOCATION OF HUMAN RESOURCES 67
reaffirmed through a continuous cycle within group context (Bourdieu, 1986). In
education, this context is provided through exchanges between teachers and
administrators, schools and districts offices, and, lastly, between the school district and
the community it serves. Both of these ideologies combined for the underpinning of how
human resources are allocated within a school and across a school district.
Basis of the study. The intention of this study was to examine strategies for
human resource allocation that can be implemented at the school level to improve student
achievement. The current focus is on human capital reallocation requiring the movement
of core classroom teachers, specialists, special education staff and instructional aides
within individual schools and across the school system. This study aimed to answer four
research questions:
1. What research-based human resource allocation strategies improve student
achievement?
2. How are human resources allocated across the study district and its schools?
3. Is there a gap between current human resource allocation practices of the
study district and what the research suggests is most effective?
4. How can human resources be strategically reallocated to align with strategies
that improve student achievement?
At the time of this study, Seven Seas School District (a pseudonym) was
undergoing strategic planning and one component of this process is determining how to
utilize the personnel currently in the system, which is why assessing the current state of
their human resource allocation, along with determining knowledge, motivation and
DISTRICT ALLOCATION OF HUMAN RESOURCES 68
organizational gaps and how to close them, will provide information to district level
administrators.
To better understand the allocations made by SSSD, the Evidence Based Model
developed by Odden and Picus (2008) is used to compare current allocations at both the
school and aggregate district level to the allocations recommended under the Evidence
Based Model. From this comparison, staff allocation gaps emerged and the researcher
examined not only the causes for the gaps, but how gaps can be closed by reallocating
human resources that are already in the system without having to acquire new resources.
This study employed qualitative formative evaluation methods which “serve the
purpose of improving a specific program, policy, group of staff, or product” (Patton,
2002, p. 220). The results of this formative evaluation will provide both the Assistant
Superintendent of Business Services and the Assistant Superintendent of Education
Support Services answers as to how they can allocate resources in new ways that will
maximize their efforts to raise student achievement. Findings indicating that the school
district is effective in allocating their resources can lead to further work to ascertain
which specific allocations make it successful. Conversely, finding that the allocations are
ineffective may lead to further formative research to ascertain which allocations are not
working and what changes need to be made within the district. In addition to judging the
effectiveness of allocation strategies, the findings of the study may allow district level
administrators, including the School Board, to make decisions regarding the allocation of
human resources for the 2013-2014 school year.

DISTRICT ALLOCATION OF HUMAN RESOURCES 69
Population and Sample
School districts in California fall into two main categories, Basic Aid or Revenue
Limit, depending on how the school district is funded. Basic Aid districts are
characterized as “excess revenue” districts because they generate more per pupil dollars
from local property tax than other school districts (EdSource, 2012b). While these
districts, as a whole, may have more revenue, not all Basic Aid districts have the same
amount in excess revenue. SSSD has $7,580.57 per student compared to the state
revenue limit of $4,983.07 per student, which equals a difference of $2,597.50
(Investigative Newsource, 2010). This excess is small in comparison to its neighboring
district, which has an excess of $5080.60 per student. Revenue Limit districts,
alternatively, receive a combination of funding from local property tax and state taxes to
generate enough money to meet the revenue limit or base amount of funding for schools
in California (EdSource, 2012b). For the purpose of this study, the researcher chose to
focus on Basic Aid districts, as they are more revenue rich in these uncertain economic
times and can allocate their resources in ways that a revenue limit district may be unable
to, including allocation of resources to strategically meet the needs of specific student
groups. Beyond a Basic Aid district, the researcher wanted districts that were high
performing as defined by meeting or exceeding the Annual Measurable Objectives
(AMO) set forth by the state of California. In choosing to study high achieving districts,
the researcher was able to focus on specific sub groups that can be overlooked in
otherwise high performing schools. The researcher also chose districts located in
Southern California to make them easily accessible for interviews and observations.
DISTRICT ALLOCATION OF HUMAN RESOURCES 70
Lastly, the researcher wanted to focus on the district as a whole entity, so a small to
medium district was ideal.
Selecting the sample. Once the criteria were defined, the researcher used the
California Department of Education website to identify several potential districts to
study. Each of these districts provided an extreme or deviant sample because, as defined
by Patton (2002), they are unique or unusual in some special way and would provide an
evidence-rich context in which to study. In consultation with her dissertation chair, the
researcher chose SSSD as it met all of the criteria listed above.
Characteristics of sample. SSSD is a medium-sized elementary school district
comprised of 4,363 students, in eight schools, ranging in grades kindergarten through
sixth grade. Student sub groups include White (61.8%), Asian (27.3%), Hispanic (6.3%),
Students with Disabilities (10.4%), and English Language Learners (7.9%). It is one out
of almost 1,000 California school districts (EdSource, 2012b), more than half of which
are elementary districts K-8 (EdSource, 2012b), and it is one out of 124 Basic Aid School
Districts in California for the 2011-2012 school year (California Department of
Education, 2012). The following tables and figures provide an overview of the district
and its academic performance, disaggregated by ethnicity. As these data reveal, each
school is high performing, but has room for improvement in meeting the academic needs
of particular sub-groups of students, as the following tables and figures illustrate.

DISTRICT ALLOCATION OF HUMAN RESOURCES 71
Table 3
SSSD Student/Staff Information 2010-2011
Aloft Cuddy Deck Dinghy Overboard Squall Scuppers Tiller
Total Student
Enrollment
443 478 431 312 744 762 472 716
Grade Levels
Served
K-6 K-6 K-6 K-6 K-6 K-6 K-6 K-6
Teachers on
Staff
21 24 23 16 38 34 24 38
Title I
Funding
None None None None None None None None
API Score 953 931 958 920 977 979 954 947
Source: 2010-2011 School Accountability Report Card
Table 4
SSSD Student Enrollment by Ethnicity and Other Characteristics
Aloft Cuddy Deck Dinghy Overboard Squall Scuppers Tiller
Total Student
Enrollment
443 478 431 312 744 762 472 716
Black/African
American
0% 1% 3% 1% 1% 0% 1% 1%
American
Indian
0% 0% 0% 1% 0% 0% 0% 0%
Asian 23% 24% 13% 15% 38% 24% 32% 36%
Filipino 1% 1% 1% 1% 1% 1% 2% 1%
Hispanic/
Latino
4% 9% 6% 11% 3% 4% 9% 8%
Pacific
Islander
0% 0% 0% 0% 0% 0% 0% 0%

DISTRICT ALLOCATION OF HUMAN RESOURCES 72
Table 4, continued
White (Not
Hispanic)
68
%
63% 73% 70% 56% 69% 53% 51%
Two or more
races
2% 2% 5% 2% 1% 2% 3% 3%
Socioeconomically
disadvantaged
1% 7% 4% 12% 2% 0% 12% 3%
English Learners 6% 18% 7% 14% 13% 10% 21% 20%
Students with
disabilities
12
%
11% 12% 7% 8% 11% 5% 10%
Source: 2010-2011 School Accountability Report Card

Figure 2. Aloft Elementary School API by Group. Source: 2010-2011 School
Accountability Report Card

200 300 400 500 600 700 800 900 1000
Learning Disabled
English Learners
White/Other
Hispanic/Latino
Asian American
All Students in this School
Aloft API by Group
DISTRICT ALLOCATION OF HUMAN RESOURCES 73

Figure 3. Cuddy Elementary School API by Group. Source: 2010-2011 School
Accountability Report Card

Figure 4. Deck Elementary School API by Group. Source: 2010-2011 School
Accountability Report Card

200 300 400 500 600 700 800 900 1000
Learning Disabled
English Learners
Low Income
White/Other
Hispanic/Latino
Asian American
All Students in this School
CuddyAPI by Group
200 300 400 500 600 700 800 900 1000
Learning Disable
English Learners
Low Income
Multiple Ethnicities
White/Other
Hispanic/Latino
Asian American
All Students in this School
DeckAPI by Group
DISTRICT ALLOCATION OF HUMAN RESOURCES 74

Figure 5. Dinghy Academy of Arts and Sciences API by Group. Source: 2010-2011
School Accountability Report Card

Figure 6. Overboard Elementary School API by Group. Source: 2010-2011 School
Accountability Report Card

200 300 400 500 600 700 800 900 1000
Learning Disabled
English Learners
Low Income
White/Other
Hispanic/Latino
Asian American
All Students in this School
DinghyAPI by Student Group
200 300 400 500 600 700 800 900 1000
Learning Disabled
English Learners
White/Other
Hispanic/Latino
Asian American
All Students at this School
Overboard API by Student Group
DISTRICT ALLOCATION OF HUMAN RESOURCES 75

Figure 7. Squall Elementary School API by Group. Source: 2010-2011 School
Accountability Report Card

Figure 8. Scuppers Elementary School API by Group. Source: 2010-2011 School
Accountability Report Card

200 300 400 500 600 700 800 900 1000
Learning Disabled
English Learners
White/Other
Hispanic/Latino
Asian American
All Students in this School
Squall API by Student Group
200 300 400 500 600 700 800 900 1000
Learning Disabled
English Learners
Low Income
White/Other
Hispanic/Latino
Asian American
All Students in this School
Scuppers Ridge API by Student Group
DISTRICT ALLOCATION OF HUMAN RESOURCES 76

Figure 9. Tiller Elementary School API by Group. Source: 2010-2011 School
Accountability Report Card
Instrumentation
This study employed two instruments to collect data about SSSD. The first
instrument, interview questions, was designed to collect information about the nature of
the organization as a whole and specific resource allocation practices. These interviews
helped the researcher to understand the context by which the gaps in SSSD occurred and
will provide insight as to how the school district would like to reallocate resources to
meet desired goals. Additionally, the interviews allowed the researcher to ascertain the
level to which there is congruity in vision between individuals of the same decision
making power in the organization as they strive to raise student achievement. The
interview questions and protocol were adapted from Odden, Picus, Archibald, and Smith
(2009) and Morgan (2009) and are included in Appendices A and B. The first interview
to take place was with the Assistant Superintendent of Business Services, and the second
interview was with the Assistant Superintendent of Curriculum and Instruction.
The second instrument used in this study was an observation protocol used during
the observation of two separate SSSD school board meetings. These observations
200 300 400 500 600 700 800 900 1000
Learning Disabled
English Learners
Low Income
White/Other
Hispanic/Latino
Asian American
All Students in this Group
Tiller API by Student Group
DISTRICT ALLOCATION OF HUMAN RESOURCES 77
allowed the researcher to see the entirety of the school district decision-making body, as
the school board sets priorities for the Superintendent and her cabinet. The observation
protocol is included in Appendix C.
Data Collection
The Assistant Superintendent of Instructional Services for SSSD was contacted by
the researcher to arrange for data to be collected in the district. Once the Assistant
Superintendent had the permission of the Superintendent, the researcher was authorized
to gather data about his district. The Assistant Superintendent continues to be the
primary contact at the district level, arranging for meetings with the Assistant
Superintendent of Business Services. The researcher and the district contact made
arrangements for the research to, during the summer and fall of 2012, conduct interviews
with district personnel, observe the school board and collect documents. The district
contact was provided the interview questions and the protocols for data collection prior to
conducting the interviews.
Data collection training. The participants in the thematic dissertation group, of
which this researcher was a member, attended a one-day training on the EXCEL model
that was used to collect data and run human resource allocation simulations. The training
was conducted by Picus and his PhD student Knight, the creators of the EXCEL model,
which is based on the work conducted by Odden and Picus (2010).
Administration of instruments. Three different data sources were used in this
study to gain qualitative data triangulation which will “strengthen the study by combining
methods” (Patton, 2002 p. 247). These data include district documents, interviews with
DISTRICT ALLOCATION OF HUMAN RESOURCES 78
district personnel and school board observations. Primary data was collected through a
variety of documents provided by the school district:
 2012-2013 SSSD Budget
 School Level Allocations of faculty/staff and categorical program dollars
 Certificated Staff Allocation Formula
 SSSD Strategic Plan
 SSSD School Board Minutes
These data were entered used to determine how resources are allocated
throughout SSSD and what human resource allocation gaps, if any, exist within the
district.
The second data source, interviews with district personnel, was accessed in late
summer and fall of 2012 as arranged through the district contact. To ensure a positive
experience for each interviewee, the interviews were scheduled to run no longer than one
and one half hours. During the interview, the researcher took copious notes according to
the interview protocol and recorded the interview, which was reviewed later with
participant permission. Immediately following the interview, the researcher transcribed
notes and reviewed the audio recording to ensure accuracy of notes.
The last data source, school board observations was conducted in late summer and
fall of 2012. To choose which three board meetings to attend, the researcher culled
through the consent calendar for each meeting beginning in June 2012 to see when/if the
board was discussing budgetary items or human resource issues. The observations lasted
the entirety of the school board meeting. To assist with the length of the meeting, the
researcher took pictures to describe the visual setting of the meeting and to be used as
DISTRICT ALLOCATION OF HUMAN RESOURCES 79
memory aides during the review of field notes. These observations allowed the
researcher to find out if goal alignment existed within the system as well as to determine
allocation priorities based on board discussions.
Data Analysis
To diagnose the causes of human resource allocation gaps and find implementable
solutions, this study utilized the Gap Analysis Model developed by Clark and Estes
(2008). In their model, Clark and Estes begin the analysis with a problem that is
occurring within one part or the whole organization. To determine which problem to
analyze, leaders within the organization determine goals and methods to measure those
goals. Organizations can choose to use standards within their field to measure or can
measure themselves against benchmarked standards set by other organizations. Once a
gap, a difference between measured goals and the benchmark, has been determined, the
organization can move to ascertaining the causes for the gap, which can be related to
knowledge, motivation, or to the organization. Once the causes for the gap are identified,
members within the organization work to find solutions for the problem and put them into
an integrated implementation plan.
From preliminary conversations with the school district at the time of this study,
the researcher learned that SSSD was undergoing strategic planning to evaluate their
goals for student achievement, resource allocations and expenditures over the last several
years. From this perspective, district leaders sought to ensure that what they were doing
was effective in meeting the needs of their students. For the purpose of this study, the
focus is specifically on the district’s ability to allocate human resources in ways that will
raise student achievement, especially for their English Language Learner and Special
DISTRICT ALLOCATION OF HUMAN RESOURCES 80
Education populations. To measure whether a gap exists, the researcher compared
current human resource allocations in all categories to those proposed by the Evidence
Based Model, paying special attention to the allocations for struggling students. To
identify gaps, data collected from the personnel allocations information and district
budget were entered into the EXCEL model. The data that entered for gap measurement
are in included in Table 5.
Table 5
Input Criteria for EXCEL Model Gap Analysis
Input Criteria for EXCEL Model Gap Analysis
Enrollment by grade level for each school in the district
Percentage of student population who are English Language Learners, Special Education, and
Free and Reduced Lunch
Current class size by grade level
Number of students per instructional aide
Percentage of Specialist Teachers
Number of Instructional Coaches
Number of Tutors
Number of English Language Learner Teachers
Extended Day Teachers
Number of Instructional Aides
Number of Librarians/Nurse/Guidance Counselors/Administrators
Enrollment by grade level for each school in the district
Source: Evidence-Based Model Gap Analysis Spreadsheet
Once the model ascertained which gaps existed in the organization, the researcher
moved into identifying the causes of the gaps through the interview process. Lastly, the
DISTRICT ALLOCATION OF HUMAN RESOURCES 81
researcher used the model to simulate options that will manage the gaps by finding
research based approaches to allocate the available resources to improve student
achievement and meet district goals. For example, the model can take a component like
class size and compare current allocation to what is recommended under the EBM. From
there, the researcher was able reallocate class size numbers, either raising or lowering
them, to determine whether that shift freed personnel resources to allocate to a different
function like instructional coach or tutor. Beyond within-school allocation, the model
allowed the researcher to look at between-school allocations, since school level data was
entered for each site within SSSD. Using this data, the researcher was able to determine
if reallocation across schools is needed to better meet district goals or provisions within
the EBM.
Based on the review of the literature and basic district data, some preliminary
themes emerged. Most salient are the power relationships that exist within the district,
which refers to which people have the ability to make decisions about human resource
allocations and whether that power is centralized or decentralized, as each plays a large
role in student achievement. Besides power, another theme, the idea of convenience,
may play a central role at the district level, especially if resources were allocated in ways
that are convenient rather than in ways that increase student achievement.

DISTRICT ALLOCATION OF HUMAN RESOURCES 82
Chapter Four: Findings
Introduction
As the budgets of local school districts fluctuate throughout the state of
California, school districts are forced to examine their programs and staffing allocations
at every level of the organization. To this end, many districts find it necessary to be
creative with staffing allocations to meet the needs of an ever-changing student
population. The need for this creativity includes all types of school districts, including
Basic Aid districts.
Basic Aid school districts suffer from declining revenue, just like their revenue
limit counterparts due to the fact that they are funded solely on local property tax
revenue, so, when property values fall, the funding for these districts also falls (Batten
2012). They also face pressures with increasing enrollment since they are not funded
per-pupil like revenue limit districts. As a result, when enrollments increase, their
revenue does not increase to meet the needs of an expanded student population, as it does
for districts funded on a per pupil basis. Additionally, Basic Aid districts also have to
contend with an additional loss of revenue known as “fair share” which can be defined as
a cut to basic aid non-flexible state categorical funds (Batten, 2012). Losing these
additional dollars leads to complications for Basic Aid districts
Given the context for Basic Aid districts, this chapter focuses on how Seven Seas
School District (SSSD), a Basic Aid district, can use the Evidenced Based Model (EBM)
to realign human resources to serve special populations and improve student
achievement. Specifically, this chapter describes the EBM, a human resource adequacy
model which helps schools and districts raise student achievement. It then discusses the
DISTRICT ALLOCATION OF HUMAN RESOURCES 83
study district, SSSD. Then, both the EBM and the Gap Analysis Model developed by
Clark and Estes (2008) are used to determine personnel gaps and the causes for these
gaps. Lastly, recommendations are made regarding how to reallocate current resources
within the system to meet the requirements of the EBM and the desires of SSSD. In
summary, the following research questions are answered throughout the chapter:
1. What research-based human resource allocation strategies improve student
achievement?
2. How are human resources allocated across the study district and its schools?
3. Is there a gap between current human resource allocation practices of the
study district and what the research suggests is most effective?
4. How can human resources be strategically allocated to align with strategies
that improve student achievement?
Evidenced Based Model (EBM): Human Resource Allocation Strategy that Raises
Student Achievement
The EBM, developed by Odden and Picus (2008), serves as an adequacy model
allowing schools to comprehensively allocate human resources to raise student
achievement by employing all research-based strategies that raise student achievement.
At its core, the model draws upon class size research, particularly the Tennessee STAR
(Mosteller, 1995) study to assign 15 students to a classroom for grades PK through 3 and
25 students to classroom for grades 4 through 12, which falls within the study-determined
optimal class size range of 13 to 17 in grades K through 3 and 22 to 25 for grades 4
through 6. Once the number of core teachers is established, the model can be broken
DISTRICT ALLOCATION OF HUMAN RESOURCES 84
down into staffing amongst three categories: instructional leadership, certificated staff
and classified staff.
The model calls for at least one principal and one instructional coach at each
school site to guide the instructional program and monitor teacher progress. It also calls
for additional support, in the form of assistant principals, for schools with more than 450
students. All of these instructional leadership positions facilitate the mission and vision
of the school, deliver job-embedded professional development and guide teachers in their
data-based decision-making helping to create collaborative school systems that meet the
needs of individual students.
The bases of the certificated staff are the core teachers who teach students for the
largest portion of instructional minutes each school day. They are not alone in their
endeavors, as the EBM also calls for specialist teachers who teach elective classes,
special population teachers and extended-day/summer school staff. According to the
model, a school should allocate 20% of its teaching faculty at the elementary levels and
middle school and 33% at the high school level to teaching elective classes ranging from
physical education to art. The model also calls for teachers to teach small groups of
Special Education Students and English Language Learners either in a collaborative
approach with the core teacher or using a pull-out program. The model also gives extra
certificated teacher assistance to students before/after school and during the summer so
that students do not fall behind in their academics.
Besides certificated staff, the model calls for classified staff who assist teachers in
meeting the needs of students or who help with the day-to-day operations of the school.
Extra support staff, aides, and tutors help teachers create smaller groups for support
DISTRICT ALLOCATION OF HUMAN RESOURCES 85
across content areas based on data collected both formally and informally. Furthermore,
nurses ensure that students are healthy and attentive during classroom instruction. Lastly,
site secretaries help keep the school’s front office running smoothly by assisting parents,
teachers and administrators.
Beyond staffing, the EBM calls for 10 additional days per school year for
teacher staff development and time within the school day for collaboration, using PLC or
another model for teacher collaboration. It also calls for minimum funding for Gifted and
Talented Education, instructional technology, instructional materials and assessment,
professional development and student activities. While these factors are important, they
are not the basis for the study, as the study focuses solely on the human resource
allocation portion of the EBM.
The table below presents the minimum level of resources in every category of
staff, ranging from administration to certificated and classified staff, who serve to help a
school function. Table 6 provides an overview of the ways in which the EBM allocates
human resources at the elementary school level.

DISTRICT ALLOCATION OF HUMAN RESOURCES 86
Table 6
Evidenced Based Model Staffing Structure
Staffing (Certificated and Classified) Number per Elementary School
Core Teachers 1.0 FTE per 15 P-3
rd
grade students
1.0 FTE per 25 4
th
-6
th
grade students
Specialist Teacher Total Core Teachers multiplied by 20%
Instructional Coaches 1.0 FTE per 200 students
Tutors 1.0 FTE per 100 students classified as “at
risk”
English Language Learner Teacher 1.0 FTE per 100 English Language Learners
Extended Day Staff 0.833 FTE per 100 students classified as “at
risk”
Summer School Staff 0.833 FTE per 100 students classified as “at
risk”
Special Education Staff 1.0 FTE per 150 students
Librarian 1.0 FTE per school
Non-Academic Pupil Support 1.0 FTE per 450 students
1.0 FTE per 100 students classified as “at
risk”
Nurses 1.0 FTE per 750 students
Special Education Aides 1.0 FTE per 300 students
Instructional Aides 1.0 FTE per 15 pre-kindergarten students
Non-instructional aides 2.0 FTE per school
Principal 1.0 FTE per school
Assistant Principal 1.0 FTE for elementary schools with
enrollments higher than 450 students
Secretary 2.0 FTE per school
Source: Odden and Picus (2008)
In creating the model in this manner, Odden and Picus (2008) ensured that
students’ needs are met regardless of learning challenge and teachers have the time and
the support of one another and of their leadership time to create quality instructional
opportunities for students and .
Overview of the District
At the time of this study, SSSD was a medium-sized elementary school district,
comprised of 4,363 students in eight schools whose grade levels ranged from
kindergarten through sixth grade, located in Southern California. The student body was
primarily composed of White and Asian students, 10.4% of the student population was
DISTRICT ALLOCATION OF HUMAN RESOURCES 87
categorized as Students with Disabilities, 7.9% as English Language Learners, and 4.4%
received free or reduced-price lunch. SSSD was one out of 124 Basic Aid School
Districts in California for the 2011-2012 school year (California Department of
Education, 2012) and was bordered by two other Basic Aid Districts in its region
(Investigative Newsource, 2010).
SSSD academic performance over time. In the previous five school years,
SSSD maintained high levels of academic progress as measured by the Academic
Performance Index (API) for the state of California. The API measures performance on
the California Standards Test, and scores range from A 200 to a high of 1000. The test
measures the ability of schools to raise the academic achievement of statistically
significant student populations, including Students with Disabilities and English
Language Learners. Starting with the 2007-2008 school year, SSSD had an API of 944.
The largest increase in achievement occurred between that school year and the next,
2008-2009, as the overall API by grew by 15 points to 959. As evidenced in Figure 4.1,
from 2008-2009 forward SSSD hovered around the same API, with increases or
decreases of approximately 5 points.

DISTRICT ALLOCATION OF HUMAN RESOURCES 88

Figure 10. Academic Performance Index over the Last Five Years. Source: 2010-2011
School Accountability Report Card
While the district maintained high academic performance over five years, two
special populations of students did not experience consistent levels of academic
achievement as their counterparts: English Language Learners and Students with
Disabilities.
English language learner performance over time. English Language Learners
throughout the district performed inconsistently in language arts and mathematics over
the previous five years with the biggest decline in achievement between the 2009-2010
and the 2010-2011 school years for all schools except Tiller. These results are
summarized in Figures 4.2 and 4.3. With inconsistencies such as these, SSSD would
benefit from an examination of its use of resources in meeting the needs of this
population of students.

900
920
940
960
980
1000
2007-2008 2008-2009 2009-2010 2010-2011 2011-2012
Axis Title
Academic Performance Index (API)
District Wide API
DISTRICT ALLOCATION OF HUMAN RESOURCES 89

Figure 11. English Language Learner Proficiency on the CST-English Language Arts.
Source: 2010-2011 School Accountability Report Card

Figure 12. English Language Learner Proficiency on the CST-Mathematics. Source:
2010-2011 School Accountability Report Card
Special education student performance over time. The performance of
students with disabilities is much more consistent than the performance of English
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
2007-2008 2008-2009 2009-2010 2010-2011
Percentage Proficient
School Year
English Language Learner Proficiency
in CST English Language Arts
Aloft
Cuddy
Deck
Dinghy
Overboard
Squall
Scuppers
Tiller
0
0.2
0.4
0.6
0.8
1
2007-2008 2008-2009 2009-2010 2010-2011
Percentage Proficient
School Year
English Language Learner Proficiency
in CST Mathematics
Aloft
Cuddy
Deck
Dinghy
Overboard
Squall
Scuppers
Tiller
DISTRICT ALLOCATION OF HUMAN RESOURCES 90
Language Learners. As seen in Figures 4.4 and 4.5, 60% or more of students with
disabilities across the district scored proficient or advanced in English Language Arts and
Mathematics over the last four years. While this number fluctuated slightly, the only
exceptions were Dinghy and Overboard, as they saw a 20% drop in proficiency from the
2009-2010 to the 2010-2011 school year.

Figure 13. Students with Disabilities Proficiency on the CST- English Language Arts.
Source: 2010-2011 School Accountability Report Card
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
90.00%
2007-2008 2008-2009 2009-2010 2010-2011
Percentage Proficient
School Year
Student with Disabilities Proficiency
in CST English Language Arts
Aloft
Cuddy
Deck
Dinghy
Overboard
Squall
Scuppers
Tiller
DISTRICT ALLOCATION OF HUMAN RESOURCES 91

Figure 14. Students with Disabilities Proficiency on the CST-Mathematics. Source:
2010-2011 School Accountability Report Card
While the overall academic health of SSSD cannot be disputed based on the
district API of 961, there are inconsistencies within special populations that could
possibly be addressed with a reallocation of staff within or across schools.
Fiscal Fluctuations over Time. Besides academic inconsistencies, there
have been financial fluctuations within the budget of SSSD Predominantly, there was an
overall decline in school funding over the five years prior to this study. In the previous
five years, SSSD experienced a modest decline in revenue per student compared to most
districts throughout the state. The district’s revenue decreased $233 per student,
beginning in the 2007-2008 school year, to reach a low of $9,303 per student at the end
of 2011-2012 school year (Batten 2012b), which is summarized in Figure 4.6. The
majority of the decline in revenue between the 2010-2011 and 2011- 2012 school year
was attributed to the Basic Aid Reduction, or “Fair Share,” which required a reduction in
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
90.00%
2007-2008 2008-2009 2009-2010 2010-2011
Percentage Proficient
School Year
Students with Disabilities Proficiency
in CST Mathematics
Aloft
Cuddy
Deck
Dinghy
Overboard
Squall
Scuppers
Tiller
DISTRICT ALLOCATION OF HUMAN RESOURCES 92
basic aid categorical dollars (Batten 2012b). For SSSD, this translated into a $2.5 million
decrease in revenue (Batten 2012b). This was coupled with rising expenditures over the
same five year period. Expenditures per student rose from $9,057 in the 2007-2008
school year to $9,846 in the 2011-2012 school year. According to the Assistant
Superintendent of Business Services, this increase of $789 per student came directly from
increases in teacher salary and in other operating expenses (Batten 2012). Figures 4.6 and
4.7 present these numbers.

Figure 15. SSSD Revenues over Last Five Years. Source: SSSD Unaudited Actuals
2011-2012
DISTRICT ALLOCATION OF HUMAN RESOURCES 93

Figure 16. SSSD Expenditures over Last Five Years. Source: SSSD Unaudited Actuals
2011-2012
With rising expenditures and decreasing revenues, SSSD placed Proposition CC
on the November 2012 ballot, but it was rejected by voters. Proposition CC was a
General Obligation Bond proposition that would have increased the property tax for
every property, commercial or retail, by approximately $65 per property, raising a total of
approximately $78.5 million for the district over the next 20 years. These monies would
have been used to modernize and repair facilities, improve instructional technology and
increase efficiency of all SSSD schools (Batten, 2012a). At the time of this study, SSSD
was researching alternative ways to address district needs.
These fluctuations in revenue, coupled with inconsistencies in achievement for
their statistically significant special populations, caused SSSD to examine personnel
DISTRICT ALLOCATION OF HUMAN RESOURCES 94
allocations more closely to find ways to meet the needs of students without having to hire
more staff.
Gap Analysis of SSSD Human Resource Allocation
Over the years, SSSD experienced declining revenue, making it difficult to staff
schools with the support staff that students need to be successful. As a result, increases in
student achievement were not uniform and, in some schools, performance declined.
Given these fluctuations, the Gap Analysis Model developed by Clark and Estes (2008),
in conjunction with the EBM, can be used to analyze the problem and make
recommendations. The Gap Analysis Model is a conceptual framework that outlines
seven steps by which organizations can improve performance and move toward meeting
goals. First, organizations should identify key business goals. From there, organizations
should determine the performance gap, which is a gap between their desired goal and
actual performance. Once gaps are identified, organizations must analyze gaps to
determine causes, which fall into three main categories: knowledge, motivation and
organization. Once all of the causes for the gaps have been determined, the organization
must implement solutions based on the information and then, lastly, evaluate the results
and revise goals.
Identification of key business goals. The SSSD Strategic Plan outlines the
seven goals, or Core Strategies, of the organization for the next five years and is
summarized in Table 7.

DISTRICT ALLOCATION OF HUMAN RESOURCES 95
Table 7
Core Strategies for SSSD
Overarching Category Unique Goals
Educational Program We will implement and assess a
comprehensive educational program based on
21
st
Century skills to educate the whole child.
Technology Every student will actively use technology to
develop 21
st
Century skills within a safe and
secure digital environment.
Professional Development The professional development program,
which includes time for planning,
collaboration and in-services, will support
ALL district employees to provide a
nurturing, inspiring, and rigorous educational
program.
Funding We will actively pursue funding to maintain a
stable level of resources necessary to fulfill
our mission.
Facility Optimization We will develop a plan to maximize
functional use of facilities.
Communication We will facilitate communication with
stakeholders at every level consistent with our
core values to promote our mission and to
achieve our mission.
External Relations We will establish partnerships with corporate
entities and community members.
Source: SSSD Strategic Plan (SSSD, 2011)
Each goal in the Strategic Plan is directly linked to raising student achievement,
according to Superintendent Mooring. In her words:
the district wants all children to be proficient and that [is what] we consider to be
the floor not the ceiling for children as far as what proficient is for them in their
independent abilities, but the ceiling is providing the rigor for every child. That is
the goal for every child in the district, a continuous message that is reflected
throughout our strategic plan. (H. Mooring, personal communication, July 10,
2012)
DISTRICT ALLOCATION OF HUMAN RESOURCES 96
Under the human resource allocation at the time of this study, these goals were not met
for all students and staff within SSSD. Thus, leadership’s primary desires were to better
align their staffing to meet the goals listed above, which include adding more assistant
principals so that professional development extends throughout all levels of the
organization, to add more instructional coaches and teacher librarians to assist in bringing
technology and a curriculum based on 21
st
Century Skills to SSSD, and to provide
support for special populations of students so they could meet the rigorous challenges
ahead.
Determining performance gaps. Once key business goals have been
determined, Clark and Estes recommend determining performance gaps within the
organization. For the purpose of this study, the performance gaps are related to how the
district allocates their human resources to meet their key business goals. The first step in
that process is to examine how SSSD currently allocates their human resources.
Human resource allocation across SSSD. At the time of this study, human
resources are allocated throughout SSSD according to the staffing ratio of 20:1 in grades
K through 3 and 27:1 in grades 4 through 6. In addition, special education staff was
allocated based on student Individualized Education Program (IEP). Table 8 provides an
overview of how human resources were currently allocated across SSSD.

DISTRICT ALLOCATION OF HUMAN RESOURCES 97
Table 8
District Human Resource Allocation by Position
Title Current Allocation
Principals 8.0
Assistant principals 0.0
Instructional coaches 1.0
Core teachers 200.0
Specialist teachers 44.0
SPED teachers 18.0
ELL teachers 0.0
Academic extra help staff 0.0
Non-academic pupil support 26.0
Nurses 11.0
Extended day / summer school
staff 0.0
Instructional aides 0.0
Supervisory aides 0.0
SPED aides 66.0
Librarians 0.0
Library technicians 8.0
Library paraprofessionals 0.0
Secretaries / clerks 16.0
Source: Odden, A.R. and Picus, L.O., (forthcoming). School Finance: A Policy
Perspective, 5
th
edition.
School site administration was sparse at every school site throughout SSSD at the
time of this study. There was one school site principal who made instructional decisions
for each school based on student and teacher need. There were no assistant principals on
any campus in the district, as they were eliminated due to lack of fiscal resources across
the district. To help with instruction, SSSD did have one district level Teacher on
Special Assignment (TOSA) who worked in the office of Instructional Support Services
helping teachers throughout the district with various curriculum programs.
The certificated staff of SSSD ranged from core classroom teachers to specialists
and Special Education teachers. A core classroom teacher is defined as any teacher who
DISTRICT ALLOCATION OF HUMAN RESOURCES 98
works with a designated class for the entire school day, whereas a specialist teacher
works with students for part of the school day in areas such as science, art, music,
physical education and computer technology. The Special Education staff was comprised
of 10 Resource Program (RSP) teachers who pulled students out of their regular
education class into small groups for differentiated instruction and eight Special Day
Class (SDC) teachers who each taught a small group of students in a self-contained
classroom. There were no certificated personnel for extended-day or summer school
programs for struggling students due to the high API of the school district.
Classified employees support instruction that happens daily on campus. Non-
academic support at the district consisted of six school psychologists, twelve speech and
language pathologists, two adaptive physical education teachers, four occupational
therapists, one physical therapist and one autism specialist, all shared throughout the
district. At the time of this study, SSSD did not employ any instructional aides. However
it did employ 66 FTE special education aides (96 aides, who work a 70% contract, or 30
hours per week) who work with students in the special education program either in the
Special Day class or the Resource Program. SSSD also did not staff a certificated
librarian at each school site. Instead, it staffed a classified library technician whose job
responsibility was to check books in and out for students and teachers. Lastly, each
school was staffed with front office classified personnel: one school administrative
assistant and one school office assistant, one school health clerk and .38 FTE of a nurse.
For the purpose of analysis, health clerks were classified as nurses based on the job duties
they performed at each school site.
DISTRICT ALLOCATION OF HUMAN RESOURCES 99
Human resource allocation gaps across SSSD. The Evidence Based Model
(EBM) developed by Odden and Picus (2008) provides the framework with which to
examine school district human resource allocation practices and determine performance
gaps. To make the model more viable for school districts, Odden and Picus created the
Evidence Based Simulation, an EXCEL spreadsheet which allows school districts to
determine gaps between their allocations and what the EBM recommends and/or their
desired allocations, if different from those in the EBM. There are many allocation gaps
between what the EBM recommends and allocations within SSSD. For the purposes of
analysis, only deficit gaps are discussed in Tables 4.4 to 4.6. Positive gaps are discussed
in the reallocation, section as those are potential opportunities to reallocate resources to
better meet the needs of students throughout SSSD.
Instructional leadership gaps. The first gaps, summarized in Table 9, that occur
fall within the instructional leadership of the schools, in terms of both Assistant
Principals and Instructional Coaches. According to the EBM, SSSD would receive 2.1
assistant principals, based on the enrollment of five of the eight schools, with was more
than 450 students. The district would then divide the services of those two assistant
principals among the five schools, with the majority of assistance going to Overboard and
Squall due to their respective enrollments of 764 and 743. While the gap in numbers of
assistant principals was modest, the gap in numbers of instructional coaches is
significant, as the EBM calls for 20.9 more than the current allocation of one.

DISTRICT ALLOCATION OF HUMAN RESOURCES 100
Table 9
Instructional Leadership Gaps

Position Counts Gap
Title Current EBM Current - EBM
Assistant principals 0 2.1 -2.1
Instructional coaches 1 21.9 -20.9
Source: Odden, A.R. and Picus, L.O., (forthcoming). School Finance: A Policy
Perspective, 5
th
edition.
Certificated personnel gaps. Along with gaps in the numbers regarding
instructional leadership gaps, there were gaps in the numbers of certificated personnel,
who deliver daily instruction to students whether as the student’s primary teacher or in
specialist positions summarized. Table 10 presents the data on these numbers.
Table 10
Certificated Personnel Gaps

Position Counts Gap
Title Current EBM Current - EBM
Core teachers 200 241.7 -41.7
Specialist teachers 44 48.3 -4.3
SPED teachers 18 29.2 -11.2
ELL teachers 0 3.7 -3.7
Academic extra help staff 0 7.7 -7.7
Extended day / summer school
staff 0 3.2 -3.2
Source: Odden, A.R. and Picus, L.O., (forthcoming). School Finance: A Policy
Perspective, 5
th
edition.
The gap in number of core teachers is the largest among the numbers of
certificated personnel, due to the fact that the EBM staffs primary classrooms (PK-3)
with a student-teacher ratio of 15:1 and upper grade classrooms (4-6) with a ratio of 25:1.
DISTRICT ALLOCATION OF HUMAN RESOURCES 101
Using this ratio, SSSD would need to hire 42 more core teachers to accommodate these
class sizes. As for specialist teachers, SSSD’s allocation as compared to the EBM yields
a gap of 4.3 specialist teachers. This gap was calculated by taking 20% of the core
teacher count, which would give each school between 4 and 8 specialist teachers. Aloft,
Dinghy, Squall and Tiller would each receive one more specialist teacher to reach the
20% threshold for specialist teachers. Having a low gap in the specialist teacher category
is due in large part to the SSSD Foundation’s raising over $2 million annually (Del Mar
Schools Foundation, 2012) to pay for specialist teachers throughout the district.
While there are core teachers and specialist teachers who service both the general
and special education population, special education and English Language Learner (ELL)
teachers serve two small, yet significant populations. The gap in Special Education
teacher numbers is 11.2. The EBM allocates one special education teacher for every 150
students. These positions could either create more RSP programs or place teachers in
collaborative models where two teachers teach a heterogeneous class comprised of
general and special education students. At the time of this study, SSSD did not staff any
English Language Learner (ELL) teachers to work with students who speak a primary
language other than English. SSSD cited the its high API score as the reason for not
hiring these teachers. Under the EBM, the district should allocate 3.7 FTE teachers to
work with these students in small groups to support their learning of English.
The last branch of certificated staff provides support to students one-on-one or in
small groups. There was a gap of 7.7 FTE in the academic support staff category.
Academic support staff is defined as anyone who works with struggling students one-on-
one or in small groups (Odden & Picus, 2008). These can include tutors, intervention
DISTRICT ALLOCATION OF HUMAN RESOURCES 102
specialists, and reading teachers. Another group, extended-day/summer school staff,
works with students outside of the regular school day or year to provide intervention and
support. At the time of this study, due to the high overall API, SSSD did not employ
extended-day or summer school staff to assist struggling students, thus creating a gap of
3.2 FTE between their current allocation and that in the EBM.
Classified personal gaps. Lastly, there were gaps between EBM recommendations for
classified personnel and the district’s allocations, summarized in Table 11. The first gap
that occur was found in the number of instructional aides where the EBM provides one
instructional aide for every 15 Pre-Kindergarten students (Odden & Picus, 2009), leaving
a gap of 3.3 FTE instructional aides. At the time of this study, SSSD did not employ
supervisory aides, as these positions were filled by a combination of parent volunteers
and support staff, neither of whom was equivalent to one FTE per school, causing a gap
of 19.5 FTE aides. Along with aides, there was an 8.0 FTE gap in the number of
librarians, although this was, theoretically, cancelled out by the 8.0 FTE library
technicians employed by SSSD. Lastly, SSSD had two secretarial/clerk positions at each
school. The EBM recommends two per prototypical elementary school, a site with 450
students. Accordingly, the EBM allocates more clerical assistance to those schools with
over 450 students: Cuddy, Overboard, Squall, Scuppers and Tiller. These sites would
then share the extra resources.

DISTRICT ALLOCATION OF HUMAN RESOURCES 103
Table 11
Classified Personnel Gaps

Position Counts Gap
Title Current EBM Current - EBM
Instructional aides 0 3.3 -3.3
Supervisory aides 0 19.5 -19.5
SPED aides 66 14.6 -51.4
Librarians 0 8 -8
Library technicians 8 0 8
Secretaries / clerks 16 19.5 -3.5
Source: Odden, A.R. and Picus, L.O., (forthcoming). School Finance: A Policy
Perspective, 5
th
edition.
Causes of gaps: Knowledge and skills, motivation, and organization. Since
gaps were identified with the Strategic Budgeting Tool, the next step is to identify causes
of the gaps. The causes fall into three categories: knowledge, motivation, and
organization. Clark and Estes (2008) define knowledge and skills gaps as not knowing
how to achieve performance goals and motivation gaps as gaps in the internal,
psychological process of getting the job done. They specify that gaps in motivation can
come from one of three motivational indexes: active choice, persistence, or mental effort
(Mayer, 2008). Active choice occurs when people choose or fail to choose to actively
pursue a work goal. Persistence is defined as persisting through distractions that can
derail a person from his/her goals. Mental effort is defined as the amount of effort
needed to invest in achieving a goal. Clark and Estes (2008) define organizational gaps
as gaps in the efficient and effective organization work processes and material resources.
DISTRICT ALLOCATION OF HUMAN RESOURCES 104
Knowledge and skills gaps. The largest positive gap for SSSD was found in the
number of Special Education aides. The district employed 94 special education aides
working 70% FTE, or 30 contract hours, for 66 FTE total. The EBM staffs this position
at 1 FTE for every 300 students, which would equal 14.6 FTE for the entire SSSD,
creating a gap of 51.4 FTE positions that could be reallocated to meet other areas of the
Strategic Plan.
This gap was primarily caused by the ways in which Special Education aides were
staffed. According to the Director of Human Resources, these aides were staffed by what
is written into a student’s IEP, and not based on a ratio of Special Education students or
other staff allocation formula. While a case can be made that this group of students is
entitled to accommodations based on their IEP, there is a need for change at the district
level on how IEP’s are written and how aides are staffed for this population, especially
given that SSSD has many goals to achieve under their strategic plan.
Motivational gaps. Based on interviews with district administration, motivational
gaps were not readily apparent. According to the interview with the Superintendent, the
district strove to implement research-based practices to raise student achievement. At the
time of this study, the district was undergoing simultaneous improvement projects in
language arts and mathematics. In mathematics, teacher leaders were piloting
Cognitively Guided Instruction to enhance the conceptual teaching of mathematics. They
would then teach these skills to other teachers throughout SSSD. For language arts,
teachers were working together to unpack the Common Core State Standards in Written
and Oral Language. Once unpacked, teacher teams would create lessons and assessments
to be used district wide. In addition to district wide staff development, teachers met
DISTRICT ALLOCATION OF HUMAN RESOURCES 105
weekly in two-hour Professional Learning Communities with the focus on improving
teaching and learning.
Teacher groups were not the only ones to meet regularly, as district officials met
at least three times per year to supervise the educational program at each of the eight
SSSD schools. In these three meetings, the Superintendent and Assistant Superintendent
of Instructional Services conducted walkthroughs of the school, completed lesson
analysis conversations about what they saw, and helped in the development of goals for
the school specific to their needs as a school. According to Superintendent Mooring, they
offered integral support to the principals in shaping improvement, as they were the direct
link and saw the overall picture in connection with the district (personal communication,
July 10, 2012).
Organizational gaps. While the district was high performing, it did have special
populations that require support different from that of their peers. SSSD, at the time of
this study, did not have a system in place to help support struggling students, either after
school or summer school. Summer school was offered for Special Education students,
but not for English Language Learners. While the EBM calls for 3.7 teachers for these
students, there were none on staff at any SSSD school. The same could not be said for
the Special Education students who had RSP and SDC teachers and aides at most
campuses.
The district could also consider a reexamination of their non-academic pupil
support staff. At the time of this study, according to the EBM, the district was
overstaffed by 14.3 FTE. Table 12 identifies the quantities of non-academic pupil
support staff. While reductions in every area were not feasible, there may be places for
DISTRICT ALLOCATION OF HUMAN RESOURCES 106
the district to reallocate the services of one person to another duty related to the district’s
Strategic Plan.
Table 12
Non-Academic Pupil Support Staff Shared Throughout SSSD
Non-Academic Pupil Support Staff Quantity
Psychologists 6
Autism Specialist 1
Adaptive PE 2
Occupational Therapist 4
Physical Therapist 1
Speech and Language Pathologist 12
Total 26
Source: Odden, A.R. and Picus, L.O., (forthcoming). School Finance: A Policy
Perspective, 5
th
edition.
Another organizational gap present within SSSD is found in the way in which it
allocated non-core teacher/specialist resources. At the time of this study, the district
allocated these resources by school, rather than by student, causing inequities between
large schools and small schools. Under its system, no school in SSSD had an assistant
principal. While this worked for Dinghy’s327 students, Overboard’s 764 students could
benefit from the extra help. This practice may make less work for the Human Resource
Department, as it does not take into account the special challenges that each school faces.
The fiscal crisis in California is the most significant organizational gap faced by
SSSD. As of November 1
st
, 2012, SSSD changed their district policy, stopping the use
of discretionary funds district wide (H. Mooring, personal communication, July 10,
2012). This stoppage was only the latest in cuts the district put into place to address the
shrinking budget. In the last year, leadership had conducted an analysis of each
department budget to cut out extras, including travel and conferences, at all levels, and
DISTRICT ALLOCATION OF HUMAN RESOURCES 107
they were not spending money on upgrades of equipment and placed stricter control
over expenditures, saving the district $100,000.
Implement Solutions: Reallocation of Human Resources
At this point, the district has to make trade-offs in its human resource allocation
based not only on what the EBM and research suggest, but with what leadership believes
will raise student achievement. To this end, the Superintendent stated a desire to
implement a number of staffing changes to meet goals under the new Strategic Plan.
First, she would like to have one assistant principal at each school site so that principals
can have a school site PLC of their own, increasing collaboration at the administrative
level to help teachers. She stated she would also like to see two instructional coaches at
each school site, one in language arts and one in mathematics, to assist teachers with
lesson creation and implementation of both district wide curriculum projects. Lastly, she
would like to see one full time credentialed librarian at each school site who could not
only assist teachers with curriculum and instruction, but who could be the lead for
teaching 21
st
Century technology skills to students in grades K through 6. These desired
allocations are summarized in Table 13 with the district’s resource allocation for
comparison purposes. To achieve these goals, the EBM can be used to simulate options
available to SSSD.

DISTRICT ALLOCATION OF HUMAN RESOURCES 108
Table 13
SSSD Desired Allocations to Raise Student Achievement
Position Counts
Title Current Desired
Principals 8.0 8.0
Assistant principals 0.0 8.3
Instructional coaches 1.0 15.9
Core teachers 200.0 194.6
Specialist teachers 44.0 38.9
SPED teachers 18.0 29.2
ELL teachers 0.0 3.7
Nurses 11.0 5.8
SPED aides 66.0 14.6
Librarians 0.0 8.0
Library technicians 8.0 0.0
Source: Odden, A.R. and Picus, L.O., (forthcoming). School Finance: A Policy
Perspective, 5
th
edition.
Recommendation one: raise class size. According to research on class size,
there is only one experimental research study that found a positive link between class size
and student achievement. The Tennessee STAR study found that the optimal class size
for grades K through 3 ranges from 13 to 17 and from 22 to 25 for grades 4 through 6
(Mosteller, 1995). This research is the basis for the EBM, but with the lack of
substantiated research supporting lower class sizes, altering class size may be one of the
easiest ways to achieve the goals of SSSD. For the purpose of comparison, Table 14
illustrates the position counts and gaps between current and desired and between current
and EBM allocation with class size set at the EBM recommended class sizes for grades
PK through 6. As the table illustrates, in all positions, except Special Education aides
and Library Technicians, there is a shortage of personnel. Therefore, the current staffing
of SSSD cannot support what the EBM recommends for class size.
DISTRICT ALLOCATION OF HUMAN RESOURCES 109
Table 14
Staffing Allocation with Class Size at EBM Recommended

Position Counts Gaps
Title of Position Current

Desired EBM
Current -
Desired
Current -
EBM
Principals 8.0
8.0
8.0 0.0
0.0
Assistant
principals 0.0

8.3 2.1 -8.3

-2.1
Instructional
coaches 1.0

15.9 21.9 -14.9

-20.9
Core teachers 200.0
241.7
241.7 -41.7
-41.7
Specialist teachers 44.0
48.3
48.3 -4.3
-4.3
SPED teachers 18.0
29.2
29.2 -11.2
-11.2
ELL teachers 0.0
3.7
3.7 -3.7
-3.7
SPED aides 66.0
14.6
14.6 51.4
51.4
Librarians 0.0
8.0
8.0 -8.0
-8.0
Library technicians 8.0
0
0.00 8.0
8.0
Source: Odden, A.R. and Picus, L.O., (forthcoming). School Finance: A Policy
Perspective, 5
th
edition.
Since SSSD cannot support the EBM recommended class size, a more realistic
option for the district would be to compare their desired allocation to their current
allocation. This would mean changing the class size from the EBM recommended 15 in
grades PK through 3 to 20, and from 25 in grades 4 through 6 to 27. These changes are
summarized in Table 15. From these small changes, a positive gap of 5.4 core teachers
and 5.1 specialist teachers is created, illustrating that, even in the district’s staffing
allocation at the time of this study, there were 10.5 positions that could potentially be
reallocated to achieve one of the stated goals. The easiest conversion would be to change
teachers, either specialist or core, into instructional coaches, allowing at least one per site,
rather than one for the entire district. While it may seem easier to convert these to
teacher librarians because that would cover the gap almost perfectly, the teacher librarian
requires a California approved teaching credential and a supplemental Teacher in Library
DISTRICT ALLOCATION OF HUMAN RESOURCES 110
Sciences service credential (California Commission on Teacher Credentialing, 2012).
Therefore, this recommendation would be slightly less feasible than selecting qualified
instructional coaches from an existing teacher staff.
Table 15
Staffing Allocation Changes when Class Size is at Current SSSD Levels

Position Counts Gap
Title Current Desired
Current -
Desired
Principals 8.0 8.0 0.0
Assistant principals 0.0 8.3 -8.3
Instructional coaches 1.0 15.9 -14.9
Core teachers 200.0 194.6 5.4
Specialist teachers 44.0 38.9 5.1
SPED teachers 18.0 29.2 -11.2
ELL teachers 0.0 3.7 -3.7
SPED aides 66.0 14.6 51.4
Librarians 0.0 8.0 -8.0
Library technicians 8.0 0.0 8.0
Source: Odden, A.R. and Picus, L.O., (forthcoming). School Finance: A Policy
Perspective, 5
th
edition.
Another consideration would be raising the class size from 20 in grades PK
through 3 and 27 in grades 4 through 6 to 22 and 29, respectively. This modest change
would allow for even more flexibility in staffing, as seen in Table 16. First, raising class
sizes to these levels would generate a surplus of 21.6 core teachers and 8.3 specialist
teachers for a combined total of 29.9 positions. These extra 29 positions would provide
SSSD the correct number of instructional coaches and assistant principals for the district.
While generating certificated teacher librarians is more difficult, finding teachers already
in the district with administrative services credentials could potentially be easier,
especially since many teachers obtain their Master’s Degrees in administrative services.
While the shift in teachers to instructional coaches or TOSA does not generate a rise in
DISTRICT ALLOCATION OF HUMAN RESOURCES 111
pay, the possibility does exist that the potential shift in teacher to administrator would
cost the district money. This, in fact, is true, as the average teacher salary is $73,000 and
the starting assistant principal salary is $84,246.
Table 16
Staffing Allocation Changes when Class Size is Increased by Two Students

Position Counts Gap
Title Current Desired
Current -
Desired
Principals 8.0 8.0 0.0
Assistant principals 0.0 8.3 -8.3
Instructional coaches 1.0 15.9 -14.9
Core teachers 200.0 178.4 21.6
Specialist teachers 44.0 35.7 8.3
SPED teachers 18.0 29.2 -11.2
ELL teachers 0.0 3.7 -3.7
SPED aides 66.0 14.6 51.4
Librarians 0.0 8.0 -8.0
Library technicians 8.0 0.0 8.0
Source: Odden, A.R. and Picus, L.O., (forthcoming). School Finance: A Policy
Perspective, 5
th
edition.

Recommendation two: Reallocate special education aides. At the time of this
study, SSSD employed 66 FTE special education aides, classified as Aide I or Aide II
depending on which population of special education student they serve. Aide I’s serve
students classified as mild to moderate and Aide II’s serve those considered moderate to
severe students. The discrepancy between their current allocation and the EBM’s
recommendations suggests the district could reallocate up to 51.4 FTE aides, indicated in
Table 16. Reallocating this many aides is not feasible due to having both SDC and
Resource Programs at many schools that require aides for students of varying disability
levels. Keeping that in mind, it would be feasible to reallocate some of the aides,
somewhere in the range of 8, and create 4 ELL teachers to serve schools with high ELL
DISTRICT ALLOCATION OF HUMAN RESOURCES 112
populations throughout the district. This figure was calculated based on the fact that the
lowest possible aide salary is a 10 month contract for $27,652.54, according to the SSSD
classified salary schedule and the lowest teacher salary is $41,848, according to the SSSD
certificated salary schedule. Using these figures, the salary of two aides is the
approximate salary of one certificated teacher. Obviously, SSSD should not fire aides in
order to make these reallocations happen, but this is something that could be slowly
phased in due to attrition of aides throughout the school district. When three aides, or the
equivalent salary therein, retire or move on in their career, the district could hire an ELL
teacher, as it currently does not employee any. The two schools that should get first
priority are Tiller, which the greatest number of ELL students, and then Cuddy, which
has the second highest amount. The reallocation of aide positions, coupled with the
changes to class size, would reconcile most of the deficiencies in staffing between what
SSSD desires and their allocations at the time of this study, leaving only the deficit 11.2
FTE Special Education Teachers and the 8.0 FTE Librarians, neither of which is a
priority for SSSD.
While conducting simulations in a spreadsheet may not match the exact
conditions that exist at each school site, it is reasonable to assume that these adjustments
highlight options that SSSD can look over to decide which will best serve its needs and
those that are research-based about how schools can be staffed to maximize student
achievement. These simulations also do not factor in fiscal conditions for the school
district due to changes in the property tax value and “fair share” contributions.

DISTRICT ALLOCATION OF HUMAN RESOURCES 113
Conclusion
At the time of this study, SSSD utilized many research-based strategies to meet
the needs of its diverse student population, ranging from a strong professional
development program to the collaborative use of data to guide instruction. As a result of
this work, the district attained success on standardized tests for most of their students,
with the exception of English Language Learners and Students with Disabilities. The
inconsistent achievement of these two populations raises important questions about how
resources can be maximized to meet their needs. The simulations of the EBM can to be
used to reallocate existing resources to help these students. From this analysis, there are
several possible ways to reallocate resources to meet not only the district’s goals as
outlined in their Strategic Plan, but also the individual needs of underrepresented
students. By paying attention to these special populations, SSSD ensures success for all
of its students
DISTRICT ALLOCATION OF HUMAN RESOURCES 114
Chapter Five: Summary, Conclusions, Implications
Introduction
Over the course of the year prior to this study, California survived threatened
budget cuts because of the passage of Proposition 30, an initiative on the November 2012
ballot, which is slated to raise approximately 2.9 billion dollars for K-12 education for the
2012-2013 school year (EdSource, 2012d). While this initiative helped California
schools, school districts throughout the state will continue to examine ways in which they
can better utilize resources within their system, including the allocation of personnel, the
single biggest resource in any school district.
Overview of the Study
This study examined strategies for human resource reallocation that can be
implemented at both the school and district level to improve student achievement. The
primary focus was on human capital reallocation requiring the movement of teaching
staff within and between schools in SSSD. Analyzing the allocation of human resources
is important in climates of fiscal uncertainty because districts must ensure they spend
limited resources in ways that will have an impact on student achievement. Thus, this
study gives district level personnel a tool to make decisions that will allow them to better
allocate the resources they have. The tool also allows them to simulate a wide range of
staffing scenarios that they might not have thought possible. Additionally, schools and
districts will be able to say they make decisions based on research that can lead to
dramatic improvements in student achievement and account to various stakeholders for
the ways in which they spend resources.

DISTRICT ALLOCATION OF HUMAN RESOURCES 115
Methodology
This study utilized a formative evaluation qualitative research design in the form
of document analysis, interviews, observations and human resource allocation
simulations to ascertain the extent to which school districts can reallocate human
resources in ways that increase student achievement. Once data were collected, the
researcher completed a Gap Analysis using the model created by Clark and Estes (2008)
to ascertain the knowledge, motivational, and organizational gaps that exist between what
research says are best practices for human resource allocation and the practices employed
by the district.
Sample and population. For this study, a purposeful sample was chosen from
Southern California Basic Aid school districts to study resource allocation in a unique
context. SSSD, a medium-sized elementary school district, provided such a context
because its leadership can potentially allocate resources in more flexible and creative
ways than revenue limit districts throughout the state. Additionally, the district had
student sub-groups, including Students with Disabilities (10.4%), and English Language
Learners (7.9%), who might benefit from additional personnel resources to improve their
performance.
Limitations
The following limitations are present in the study:
 Due to the funding model of the school district, the findings may not be
generalized to other school districts.
 Due to student population and size of the district, the findings may not be
generalized to other school districts.
DISTRICT ALLOCATION OF HUMAN RESOURCES 116
 Due to the structure of the Evidence Based Model, custodial and janitorial
staff were excluded from reallocations, so there could have, potentially, been
more ways to reallocate resources to raise student achievement
 The method of data collection was based upon a structured and semi-
structured interview processes, which result in the possibility that the results
may be subjective.
 Due to the nature of the Closed Session portion of school board meetings,
observation data is limited to open session items only.
Summary of Findings
This study examined how the Evidenced Based Model (EBM), a strategy for
human resource allocation could be used to improve student achievement within SSSD.
Ultimately, the study simulated options for SSSD human resource reallocation to meet
district priorities and to raise achievement for their English Language Learners and
Students with Disabilities. Thus, this section provides a summary of the study findings as
they pertain to each of the four research questions.
Research question one: What research-based human resource allocation
strategies improve student achievement? The EBM, developed by Odden and Picus
(2008), serves as an adequacy model allowing schools to comprehensively allocate
human resources to raise student achievement. At the base of the model is certificated
staff: core teachers, specialist teachers, a school site principal, an instructional coach,
special population teachers and extended-day/summer school staff. The model also
gives extra certificated teacher assistance to students before/after school and during the
summer so that students do not fall behind in their academics.
DISTRICT ALLOCATION OF HUMAN RESOURCES 117
Besides certificated staff, the model calls for classified staff who assist teachers in
meeting the needs of students or who help with the day-to-day operations of the school.
Extra support staff, aides and tutors, helps teachers create smaller groups for support
across content areas, and nurses ensure that students are healthy and attentive during
classroom instruction. Lastly, site secretaries help keep the front office of the school
running smoothly by assisting parents, teachers and administrators.
Beyond staffing, the EBM calls for 10 additional days per school year for teacher
staff development and time within the school day for collaboration. It also calls for
minimum funding for Gifted and Talented Education, instructional technology,
instructional materials and assessment, professional development and student activities.
Research question two: How are human resources allocated across the study
district and its schools? Human resources are allocated throughout SSSD to serve the
district’s 4,379 students. At the time of this study, there was one school site principal and
no assistant principals on each campus in the district. SSSD did also have one district
level Teacher on Special Assignment (TOSA) helping teachers with various curriculum
programs.
The certificated staff of SSSD ranged from core classroom teachers to specialists
and Special Education teachers. There were 200 core classroom teachers, 44 specialist
teachers, ten Resource Program (RSP), and eight Special Day Class (SDC) teachers
serving all eight district elementary schools. Currently, there were no certificated
personnel for extended day or summer school programs for struggling students due to the
high API of the school district.
DISTRICT ALLOCATION OF HUMAN RESOURCES 118
Classified employees are composed of both academic and non-academic support.
Academic support consisted primarily of the 66 FTE special education aides, as SSSD
did not employ instructional aides. SSSD also did not staff a certificated librarian at each
school site, but it employed classified library technicians whose job responsibility was to
check books in and out for students and teachers. Non-academic support was comprised
of six school psychologists, twelve speech and language pathologists, two adaptive
physical education teachers, four occupational therapists, one physical therapist and one
autism specialist shared throughout the district. Lastly, each school was staffed with
front office classified personnel: one school administrative assistant, one school office
assistant, one school health clerk and .38 FTE of a nurse.
Research question three: Is there a gap between current human resource
allocation practices of the study district and what the research suggests is most
effective? There were many allocation gaps between what the EBM recommends and
the allocations within SSSD. These gaps occurred for a variety of reasons, but most
occur because the Evidenced Based Model (EBM) staffs schools with more personnel
than are allocated under district conditions. At the time of this study, SSSD allocated
staff based on class sizes of 20 students in grades K through 3 and 27 in grades 4 through
6, while the EBM recommends, respectively, 15 and 25. While the difference is only two
students per class in the upper grades, the five student difference in the primary grades
allows for gaps in personnel allocations across the board from core/specialist teachers to
support staff. They only staffing allocation where SSSD had a surplus was in the number
of Special Education aides. Additionally, the EBM sets school sizes at a prototypical
level: 450 students in an elementary school. Five of the eight schools in SSSD are larger
DISTRICT ALLOCATION OF HUMAN RESOURCES 119
than 450 students, thus, according to the EBM, they would be allocated additional
personnel. SSSD allocated many resources per school, so either all schools received the
resource or no schools did.
Beyond gaps created by the EBM, many gaps were created due to lack of a
perceived need. SSSD was a high-performing district with an Academic Performance
Index Score (API) of 961, causing it to not employ English Language Learner teachers,
academic extra help staff, instructional aides or extended-day teachers to assist small
groups of students, particularly their English Language Learners. SSSD leadership also
felt they did not need supervisory aides because parent/community volunteers filled most
of these positions.
Lastly, personnel gaps were caused by the reduction of staff due to the fiscal crisis
in California or the cost of hiring. SSSD cut all assistant principals to save on
administrative costs. It also employed health clerks instead of nurses and library
technicians instead of credentialed librarians at each of the schools to save money.
Research question four: How can human resources be strategically allocated
to align with strategies that raise student performance? Resources can be
strategically reallocated in two ways: raising class sizes and reallocating special
education aides. SSSD could not meet the resource allocations set forth under the
Evidence Based Model (EBM) because class sizes under the EBM were lower than
district practice, and the district did not have enough personnel to meet demand. While
maintaining allocations is an option, student achievement data shows the district was not
meeting the needs of special. This left SSSD with the option of raising class sizes by two
students to enable the district to meet the desired allocation of an assistant principal and
DISTRICT ALLOCATION OF HUMAN RESOURCES 120
instructional coach for language arts and mathematics at each site. While raising class
sizes moves away from the EBM recommendations for class size, it frees up core
teachers who can move SSSD closer to the recommendation of 21.9 FTE instructional
coaches. Focusing on personnel allocation in this way simultaneously meets district
priorities as well as the prioritization that Odden, Picus, Fermanich, and Goetz (2004)
recommend when schools phase in the EBM. These changes, coupled with the
reallocation of at least eight of the 66 FTE special education aides, would create four
English Language Learner teachers. Thus, SSSD could meet district priorities under the
strategic plan and help raise achievement for one of their special populations.
Implications for Practice
This study examined one elementary district and how it can reallocate resources
to maximize student achievement during times of fiscal stress. As evidenced in recent
years, the fiscal crisis in California caused continued times of uncertainty necessitating
careful consideration of monetary and personnel allocations.
Allocation to support student achievement. This study will allow SSSD and
districts like it to have a practical tool to allocate resources based on the most current
research in leadership, curriculum and instruction. By following the EBM and the
recommendations of this study, SSSD will ensure it meets the needs of all student sub-
groups and continues to provide avenues for students to be “proficient in their
independent abilities” (H. Mooring, personal communication, July 10, 2012).
Additionally, this tool will allow SSSD to allocate resources to “provide rigor for every
child” (H. Mooring, personal communication, July 10, 2012), whether in small group
settings, through extra support staff, or through teacher professional development.
DISTRICT ALLOCATION OF HUMAN RESOURCES 121
Increase human resource department efficiency. This study will allow the
SSSD Human Resources Department (HRD) to begin conversations with departments
throughout the district about the way they utilize personnel. For example, the Evidence
Based Model could be used to start a conversation with Pupil Services about the 66 FTE
Special Education aides on staff and whether the district needs that many aides to meet
the needs of its students. In having that conversation, some of those aides could,
potentially, be reallocated to better meet district priorities. Additionally, the SSSD
Human Resources Office can strategically fill vacancies from within the system by
simulating options with current personnel. While this model does not take skill level,
personality and other factors into account, it does show where resources are and gives the
district options. Lastly, the HRD can use this model as a way to validate resource
allocation practices, ensuring stakeholders at all levels they are use resources in ways that
research states are in the best interest of students.
Policymaking in California. Beyond the district level, this study highlights the
need to reform school finance in California. To begin with, this study shows that, even in
a successful district with a wealth of resources, there is work to be done to meet the needs
of all students. Furthermore, if a district like SSSD needs to reallocate resources to meet
the needs of struggling students, the implications for lower performing districts are even
more salient, which should result in a sense of urgency related to school finance and
resource allocation across the state. Additionally, this study should confirm the need to
fund schools so that they can implement what research says is good for students. If a
district with almost double the resources of an average district cannot fund the EBM, then
DISTRICT ALLOCATION OF HUMAN RESOURCES 122
there should be work done at the state level to overhaul the funding system in California
to provide schools the resources they need to double student achievement.
Recommendations for Future Research
This study extends the research on district and elementary school-level human
resource allocation, and recommends allocation and effective strategies to improve
student achievement. The focus of this study was to analyze eight schools within one
medium-sized elementary district. Based on the findings of this study, the following
recommendations for future research are made:
 SSSD should complete the Gap Analysis started in this study by implementing
and measuring whether the staffing reallocations were effective in raising
student achievement for the district as a whole and for both English Language
Learners and Students with Disabilities.
 Knowing that this study was conducted during a time of fiscal stress in
California, further research could be conducted when the district is in a period
of fiscal growth. At the time of this study, all levels of school administration
had reconsidered how they spent their resources, including the allocation of
personnel. Conversely, during times of fiscal abundance, district personnel
may not consider how every dollar is spent and whether or not the funds help
raise student achievement.
 Since this study focused on a single Basic Aid, elementary district, further
research should be conducted on surrounding Basic Aid, elementary districts
in close proximity to SSSD. By benchmarking another district, SSSD could
DISTRICT ALLOCATION OF HUMAN RESOURCES 123
ascertain alternative allocation strategies to continually raise student
achievement.
Conclusion
The climate of fiscal uncertainty in California provided policymakers with new
challenges in education, ranging from the implementation of the Common Core
Standards to expanding technology in the classroom. The Evidence-Based Model (EBM)
provides a research-based framework of resource allocation that can be used to solve
school district problems without adding more money to school budgets. Furthermore, the
EBM can be used when California is able to adequately fund schools, allowing
policymakers and district level officials to align resources with what research says
students and teachers need to be successful.

DISTRICT ALLOCATION OF HUMAN RESOURCES 124
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Appendix A
Interview Questions: Assistant Superintendent of Business Services
Interview Protocol: The researcher will interview the Assistant Superintendent of
Business Services about the human resource allocation methods used at SSSD. The
information provided in this interview will be utilized to complete a dissertation as part of
the doctoral program.
Name of Assistant Superintendent:
Contact Phone Number/E-Mail:
1. How long have you been in this position?
2. What was your previous position?
3. In the current fiscal climate, what measures has your district implemented to
address budget issues?
4. Will your district be able to maintain a balanced budget for the next three years?
5. What is your budget reserve projected to be in three years?
6. What is the district plan for addressing continued declining resources?
7. What roles does staff play in determining proposed program cuts?
8. How much control do school sites have in determining the use of their non-
restricted funds?
9. What do you see as the greatest challenge for districts given the current fiscal
outlook?
10. How much does each school receive for general fund allocation?
11. How much does each school receive for categorical fund allocation?
12. What is the class size for each grade level?
13. Is there anything else you would like to address?
DISTRICT ALLOCATION OF HUMAN RESOURCES 138
Appendix B
Interview Questions: Assistant Superintendent of Curriculum and Instruction
Interview Protocol: The researcher will interview the Assistant Superintendent of
Curriculum and Instruction about the human resource allocation methods used at SSSD.
The information provided in this interview will be utilized to complete a dissertation as
part of the doctoral program.
Name of Assistant Superintendent:
Contact Phone Number/E-Mail:
1. How long have you been in this position?
2. What was your previous position?
3. What are the goals for student achievement in this district?
4. What is the district plan for raising student achievement?
5. What role does the district play in the selection of curriculum for school site?
6. Has your district identified key standards from the state adopted standards?
7. Has your district defined what good instruction is for your students?
a. What is it?
b. How was it developed?
c. To what degree have the schools implemented it?
d. How is this measured?
e. Do you believe it has made a difference?
f. What is your role in developing school improvement goals?
8. How is student assessment data used in your district?
9. How is professional development provided to staff?
10. Does the district offer full-day kindergarten? If so, for how long has it been
implemented?
DISTRICT ALLOCATION OF HUMAN RESOURCES 139
11. Does the district offer extended day services for struggling students?
a. How many sites?
b. What do the services look like?
12. Does the district offer summer school?
a. What is the purpose of summer school?
13. Do you do any sort of monitoring at the school level of curriculum
implementation? If so, please explain.
14. How does the current budget crisis impact curriculum and instruction in your
district?
15. How are decisions made on allocating resources to programs/strategies/materials
for the school sites?
16. What implementation do you see has had the greatest impact on student
achievement?
17. Is there anything else you would like to address?

DISTRICT ALLOCATION OF HUMAN RESOURCES 140
Appendix C
Observation Checklist for SSSD Board Meetings
Date of Observation: Time of Observation: End of Observation:

General Information about School Board Meeting
Description of facility where board meetings are held

School Board Members Present:

Description of Room Arrangement

Number of Audience Members Present:

Description of Audience Members

School Board Meeting Observation
Number of People Who Speak During Public Comment

Topics of Discussion during Public Comment

Do parents/community members speak about special populations?

Number of budgetary topics

Budgetary Topics Covered

Length of time devoted to budgetary topics

Interactions between board members

Interactions between board members and community

Interactions between board members and Superintendent

How are decisions made with regard to human resource allocation?
Is there discussion of strategies for human resource allocation?

Abstract (if available)

Abstract This study applies the Gap Analysis Framework to understand the gaps that exist in human resource allocation of one Southern California school district. Once identified, gaps are closed with the reallocation of human resources, according to the Evidenced Based Model, requiring the repurposing of core classroom teachers, specialists, special education staff and instructional aides. Thus, the purpose of this study was to examine strategies for human resource reallocation that can be done throughout individual schools in the school district to improve student achievement in a Basic Aid district in Southern California. Using a formative evaluation qualitative research design in the form of document analysis, interviews, observations and human resource allocation simulations, the study found that the district could meet organizational goals and raise student achievement by raising class sizes by two students and reallocating special education aides. Findings from this study indicate that school districts receiving more funding than the California revenue limit still can reallocate resources in ways research suggests will improve student achievement. This study builds on the adequacy research that links human resource allocation to student achievement. Additionally, this study provides a framework for conversations within districts as to how to allocate personnel and across the state as to how schools should be funded to meet the needs of all students.

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Asset Metadata

Creator Lane, Amber Marie (author)

Core Title District allocation of human resources utilizing the evidence based model: a study of one high achieving school district in southern California

School Rossier School of Education

Degree Doctor of Education

Degree Program Education (Leadership)

Publication Date 03/29/2013

Defense Date 02/11/2013

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

Tag basic aid,EBM,evidence based model,gap analysis,human resources,OAI-PMH Harvest,repurposing,resource allocation,school finance

Language English

Contributor Electronically uploaded by the author (provenance)

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

Creator Email amberlane.722@gmail.com,ambermsm@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c3-229059

Unique identifier UC11293608

Identifier usctheses-c3-229059 (legacy record id)

Legacy Identifier etd-LaneAmberM-1497.pdf

Dmrecord 229059

Document Type Dissertation

Rights Lane, Amber Marie

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