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Adequacy in education: an evidence-based approach to resource allocation in alternative learning environments

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Adequacy in education: an evidence-based approach to resource allocation in alternative learning environments

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Content ADEQUACY IN EDUCATION: AN EVIDENCE-BASED APPROACH TO
RESOURCE ALLOCATION IN ALTERNATIVE LEARNING ENVIRONMENTS

by

Kyle Y. Shodai

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

August 2012

Copyright 2012 Kyle Y. Shodai

ii
DEDICATION
I dedicate this to my grandmother, Helen Kahaleiwi Won, whose life is an
inspiration to me.

iii
ACKNOWLEDGEMENTS
This project would not have been possible without God and the support of my
committee members, my family and friends, and educational leaders and administrators.
First, I would like to express my deepest gratitude to my advisor, Dr. Lawrence
Picus, for his patience, encouragement, and guidance each step of the journey. I would
also like to thank Dr. Melora Sundt and Dr. Dominic Brewer for their feedback and
probing questions that helped to challenge and clarify my thinking. Special thanks to Dr.
Linda Fischer, who provided feedback and helped me to revise drafts of the dissertation.
I would like to express my immense gratitude to my parents, my brother, and my
sister-in-law. They never stopped cheering for me with their words of encouragement
and prayers. I would also like to thank Pastor Alfredo Canencia and the men of my small
group—Alt Kagesa, John Lam, Steve Ching, Edwin Chung, Steven Fong—for speaking
words of faith and hope into my life and celebrating with me when I crossed the finish.
I would like to acknowledge my colleagues Alika Souza, Leigh-Taina Aweau,
and Joni Wong, whose support and understanding made work a fun place I looked
forward to each day. I would also like to thank my friends who kept me sane and
laughing along the way—Cleve Hamasaki, Marc Inouye, Keola Tom, Aaron George,
Chris Masutani, Steve Kao, Ian Katsuda, Kahoko Taki, Louise Bninski, Jolin Kidder,
Mike Zane, and Greg Taguchi.
Finally, yet equally important, I would like to thank the educational leaders and
administrators who supported the project and helped in various ways—Leslie Okoji,

iv
Daniel Hamada, Randiann Porras-Tang, Michael Tokioka, Dr. Nathan Murata, Lynn
Meguro-Reich, Russell Yamauchi, and Richard Nakatsu.

v
TABLE OF CONTENTS
Dedication ii
Acknowledgements iii
List of Tables viii
List of Figures x

Abstract xi

Chapter One: Overview of the Study 1
Background of the Problem 4
Statement of the Problem 16
Purpose of the Study 19
Research Questions 20
Importance of the Study 20
Methodology 22
Limitations 23
Delimitations 23
Assumptions 24
Definition of Terms 25
Organization of the Study 27

Chapter Two: Literature Review 29
Definitions of Alternative Learning Environments and Programs 29
Brief History of Alternative Education 30
Alternative Education Policy and Legislation 33
Definition of Alternative Education 33
Administration and Operation of Alternative Learning 34
Environments
Locations and Grade Levels of Alternative Learning 36
Environments
Types of Alternative Learning Environments 37
Student Selection Process for Alternative Learning Environments 38
Funding and Personnel for Alternative Learning Environments 39
Policy and Legislation for Funding 39
Demand for Alternative Education 40
Teacher Requirements and Qualifications 40
Evaluation of Alternative Learning Environments 41
Student Performance Data 42
Validity of Findings 43
How Alternative Learning Environments Work in Hawaii 43

vi
Theoretical Frameworks 44
School Improvement Strategies 44
Evidence-Based Model 52
Conclusion to Literature Review 63

Chapter Three: Research Methodology 64
Research Design 65
Population 67
Sample 68
Instrumentation 70
Data Collection 74
Data Analysis 76
Conclusion to Research Methodology 81

Chapter Four: Findings 82
Overview of School Sites and Participants 84
Frameworks for Data Analysis 85
10 Strategies for Doubling Student Performance 85
Evidence-Based Model 87
Results Research Question 1 88
Summary for Research Question 1 93
Results Research Question 2 94
Summary for Research Question 2 98
Themes Research Question 3 99
Summary for Research Question 3 104
Results Research Question 4 104
Summary for Research Question 4 106
Summary of Findings 107
Research Question 1 107
Research Question 2 109
Research Question 3 120
Research Question 4 121

Chapter Five: Discussion 122
Overview of the Study: Conclusions 123
Summary of Findings 124
Limitations 126
Implications 128
Implications for Practice 129
Implications for Research 131
Implications for Policy and Funding 132
Conclusion to the Study 133

References 135

vii
Appendices
Appendix A: IRB Determination of NOT Human Subjects Research 142
Appendix B: Hawaii Department of Education Approval 144
to Conduct Research
Appendix C: Agreement to Participate in Research 146
Appendix D: Document Request List 148
Appendix E: Data Collection Protocol 151
Appendix F: Data Collection Codebook 163
Appendix G: Open-Ended Data Collection Protocol 174
Appendix H: Case Study: Regular High School 176
Appendix I: Case Study; Alternative Learning Environment 214
(ALE) School

viii
LIST OF TABLES
Table 1 State of Hawaii Department of Education Operating Budget 1
Table 2 Adequate Resources for Prototypical High Schools 60
Table 3 Adequate Resources for Alternative High Schools (1+1:7 Model) 62
Table 4 Comparison of High School and Alternative Program 93
Characteristics with Evidence Based (EB) Model
Prototypical High School (SY 2010–2011)

Table 5 Resource-Level Comparison of ALE School and Leadership 97
Academy with Evidence-Based (EB) 1 Plus 1:7 Model
Alternative School (SY 2010–2011)

Table 6 Student Enrollment for Extra Help Strategies (SY 2010–2011) 101
Table 7 Comparison of Student Performance at High School and 106
Alternative Program Sites (SY 2010–2011)

Table 8 Resource-Level Comparison of Learning Environments with 113
Evidence-Based (EB) Model Prototypical High School
(SY 2010–2011)

Table 9 Comparison of Student Performance at Regular High School 187
and Academy (SY 2010–2011)

Table 10 Comparison of School Characteristics of Regular High School 196
with Evidence-Based (EB) Model Prototypical
High School (SY 2010–2011)

Table 11 Comparison of Personnel Resources of Regular High School 200
with Evidence-Based (EB) Model Prototypical High
School (SY 2010–2011)

Table 12 Comparison of Characteristics of the Leadership Academy 203
with Evidence-Based (EB) Model Prototypical High
School (2010–2011)

Table 13 Comparison of Personnel Resources for the Leadership 206
Academy with Evidence-Based (EB) Model
Prototypical High School (SY 2010–2011)

ix
Table 14 Comparison of Personnel Resources for the Leadership 208
Academy with Evidence-Based (EB) 1 Plus 1:7 Model
Alternative High School (SY 2010–2011)

Table 15 Student Performance at ALE School (SY 2010–2011) 222

Table 16 Comparison of Characteristics of ALE School with Evidence- 224
Based (EB) Model Prototypical High School
(SY 2010–2011)

Table 17 Comparison of Personnel Resources for the ALE School with 227
Evidence-Based (EB) Model Prototypical High School
(SY 2010–2011)

Table 18 Comparison of Personnel Resources for the ALE School with 229
Evidence-Based (EB) 1 Plus 1:7 Model Alternative High
School (SY 2010–2011)

x
LIST OF FIGURES
Figure 1 Ethnic Breakdown of School Population at Regular High School 177
Figure 2 AYP Cell Count Results for Regular High School (School 178
Years 2007–2011)

Figure 3 Reading AYP for Regular High School 180
(School Years 2007–2011)

Figure 4 Math AYP for Regular High School (School Years 2007–2011) 181

xi
ABSTRACT
The problem of students dropping out of school continues today in schools and
districts across the nation, particularly for students whose needs are not being met in
regular school settings. Therefore, the development of standards-based systems in
alternative learning environments requires funding and resources that match or exceed
those of traditional schools. It is no longer sufficient to merely focus on equitable inputs,
as is the case with the implementation of the weighted student formula. Rather, we must
begin analyzing how resources are used so that we may provide educational
programming that produces adequate outputs for all students.
The purpose of the study was to compare the combined impacts of the weighted
student formula and the state’s recent budget reductions on adequacy levels, student
characteristics, student performance, and instructional programming in public schools.
The study compared two high school sites, including a district-administered alternative
learning environment (ALE) and a regular high school, both of which served struggling
students in grades 9–12 who were at risk of school failure and of potentially dropping out
of school. The study was designed as a mixed-method case study that examined data,
from interviews, district records, and school documents, using adequacy frameworks
including the Evidence-Based Model (Odden & Picus, 2008) and the 10 Strategies
Framework for Doubling Student Performance (Odden, 2009). Although the study was
limited by the scope and sample size of the study, findings showed that personnel
resource levels largely remained the same for at-risk programs between school years
2010–2011 and 2011–2012. However, staffing levels were consistently less than the

xii
adequacy levels recommended by the Evidence-Based Model. Despite inadequate
resources, schools continued to implement instructional programming that reinforced the
development of the basic skills students needed to achieve standards and graduate with a
diploma. The implementation of programming at the sites also promoted adult learning
and built leadership capacity through professional collaboration and analysis of student
performance data. Although graduation and dropout rates were not considered proxies
for student learning, they provided evidence that schools were fulfilling the purpose for
which they were developed—to help students persist toward graduation.
The study concluded that educational leaders were doing everything within their
power to stabilize resources for struggling students, amid shrinking budgets and funding
reallocations of the weighted student formula, by redirecting resources to programs for
at-risk students and lobbying for staff positions at the legislature. Furthermore, the fact
that these programs produced positive results in spite of inadequate resources was a
testament to the commitment and hard work of teachers and staff at each site. Notably,
positive gains cannot be expected by merely reallocating inadequate funding. Therefore,
findings from the study are important for multiple stakeholders to promote ongoing
evaluation using adequacy frameworks to ensure that schools and districts receive the
adequate funding and resources necessary to help all students meet rigorous academic
standards.

1
CHAPTER ONE:
OVERVIEW OF THE STUDY
The Department of Education (DOE) in Hawaii is facing tough economic
challenges. In the past four years, the DOE has endured a significant decrease ($132
million) in its annual general-fund operating budget. Table 1, below, identifies the
DOE’s annual budget appropriation in dollars and illustrates the downward trend in the
department’s total executive operating budget for the following fiscal years (State of
Hawaii Department of Education Financial Reports, 2012):
Table 1
State of Hawaii Department of Education Operating Budget
Fiscal Year Total Executive Operating Budget
(dollars in billions)
2007–2008 $2.54
2008–2009 $2.59
2009–2010 $2.43
2010–2011 $2.46
2011–2012 $1.8
2012–2013 $1.79

At the same time, the DOE is currently cutting Weighted Student Formula (WSF)
funding appropriations to schools by $7.78 million.

2
The WSF was first implemented in Hawaii, in school year 2006–2007 and at the
time this study was conducted was used to allocate funding to Hawaii’s 286 public
schools. School districts implement weighted-pupil programs to distribute funds to
schools to ensure additional funding for students with greater educational needs
(Fordham Institute, 2006). As an approach that emerged out of school finance reform of
the late 1960s (Ryan, 2009), pupil-weighted programs are implemented in about 20 states
(Odden & Picus, 2008). According to Odden and Picus (2008), the extra funds that
schools receive can be used to used to provide extra services and support to students who
might come from low-income families, have special needs, or are English language
learners. The dollar amount attached to a particular student follows the student to the
school he or she attends and provides extra resources to address the additional needs of
that student (Odden & Picus, 2008). Although the budget reduction will impact
individual schools differently according to school size and student demographic
characteristics, the funding reduction translates into a $28,000 average decrease for each
of the state’s 286 public schools. Hawaii spent $11,800 and $12,399 per pupil in 2008
and 2009, respectively (U.S. Census Bureau, 2010 & 2011).
During the summer of 2011, the department proposed a budget plan to tackle a
$32 million deficit through the next two fiscal years (2011–2013). In a unanimous vote
on Tuesday, June 7, 2011, the Board of Education approved the DOE’s projected budget.
A recommendation for reducing the budget was to move some categorical programs, such
as Alternative Learning Centers (ALCs), into the WSF and eliminate the general fund
appropriations for these programs. The ALC is a type of alternative learning

3
environment (ALE) for severely at-risk students whose needs the regular school or
traditional education system cannot meet and who are therefore at risk of academic
failure and dropping out of school. In this way, the ALE is an overarching concept that
encompasses various models, types, and forms of alternative education separate from
traditional school settings that do not focus primarily on vocational, special, or alternative
education. In Hawaii, ALCs are different from learning centers, which are developed
using the “school within a school” model and include programs that focus on areas such
as performing arts, business, health, and international studies. Approximately $3 million
for alternative learning programs will be transferred to the WSF in 2011. When this
funding is transferred, schools will no longer receive funds to operate ALCs, leaving
principals to decide how—or even if—to continue such programs with their general
budgets.
Students continue to fail and drop out of school as public schools are expected to
do more with less. During the school years from 2000–2001 to 2004–2005, the dropout
rate in Hawaii’s public schools was approximately 14.7% (Programs and Services,
2007). This number translates into about 1,470 students from five graduating classes
who did not graduate from their respective high schools. More recently, in the 2009–
2010 school year, the dropout rate was 16.6% according to the Superintendent’s Report,
which revealed a slight increase (State of Hawaii, 2011).
Dropping out of school has negative implications for individual students and for
society as a whole. According to Aron (2006), the earning power of high school dropouts

4
has fallen over the last several decades. The Gates Foundation estimates that each high
school dropout earns about $9,245 less in annual salary than a high school graduate—
which equals almost half a million dollars less over a lifetime (Programs and Services,
2007). Furthermore, today’s 21
st
-century global economy increasingly requires students
to attain some form of postsecondary education and training beyond a high school
diploma (Aron, 2006). Dropouts are also more prone to unemployment (Pennington,
2003; Snyder, Dillow, & Hoffman, 2007; U.S. Department of Labor 2003) and consume
more public health, welfare, and prison resources (Coalition for Juvenile Justice, 2001;
McKinsey & Company, 2009; Moretti, 2007).
Background of the Problem
Traditional education does not work for all students, as illustrated in current
dropout rates. Therefore, alternative education is necessary for some students to succeed.
The DOE in Hawaii provides alternative education to students at risk of academic failure
and to potential dropouts who experience difficulty succeeding in traditional learning
environments and therefore require additional services and support to address their needs.
During school year 2006–2007, 62 secondary schools in Hawaii provided alternative
education, compared to 81 schools in 2005–2006, which was the year before the WSF
was implemented (Yamauchi, 2008).
In 1971, the Hawaii state legislature established the Comprehensive School
Alienation Program (CSAP) to address the problem of increasing numbers of students in
secondary school who were not succeeding in the regular school environment and were
dropping out of school (DataWise Hawaii, 2003). At one point, CSAP was the largest of

5
14 alternative programs and schools in Hawaii (DataWise Hawaii, 2003). Funding
became the distinguishing factor between CSAP and the other programs. The DOE
supported CSAP with general funds, and the other 13 programs were legislatively funded
and established by different organizations in individual schools or districts. In school
year 2000–2001, the Comprehensive School Alienation Program in Hawaii was
implemented in 77 secondary schools statewide (37 intermediate/middle schools and 40
high schools) (DataWise Hawaii, 2003). During the 2006–2007 school year, 62
secondary schools in Hawaii provided alternative education, compared to 81 schools in
2005–2006, which was the year before the Weighted Student Formula was implemented
(Yamauchi, 2008).
In 1997, the administration of the 13 programs was placed under CSAP. In
school year 2001–2002, all 14 programs were administratively placed under the Student
Support Branch of the Student Support Services Group, which has been reorganized into
the Comprehensive Student Support Services Section (CSSSS), a branch of the Hawaii
State Department of Education that manages the implementation of preventive and
developmental services and supports for all students. Although it ended in school year
2006–2007 with the implementation of WSF, CSAP was an important part of the
Comprehensive Student Support System (CSSS) in providing academic and personal
development through instructional and counseling services (DataWise Hawaii, 2003).
CSSS is a framework, for the continuum of programs and services, which supports the
academic, social, emotional, and physical environments of schools (DataWise Hawaii,
2003). The aim of CSSS is to bring together support, family and community

6
involvement, and human and financial resources from public and private agencies on
behalf of helping students succeed in school (Programs and Services, 2007).
Legislative policy for alternative education was passed on November 3, 2005,
when the Board of Education approved Policy 2131, also known as Programs and
Services for Secondary Alienated/At-Risk Students. The primary purpose of the policy is
to define the DOE’s responsibility for ensuring early identification and intervention for
students who are at risk of academic failure and potential dropout. The policy contains
several elements worth noting. First, Policy 2131 acknowledges that there are secondary
students who have difficulty succeeding in traditional learning environments because of
academic, social, emotional, or behavioral difficulties. Second, a major focus of the
policy is the creation of effective and supportive learning environments to help these
students develop the necessary competencies to achieve state standards and graduate
from high school. Third, to meet the needs of the target population, the policy identifies
services and support, including Alternative Learning Centers (ALC), Special Motivation
Classes (SMC), smaller academic houses, tutorial services, work-based learning
experiences, and other models that meet the needs of the target population.
The assessment process to identify students for alternative schools and programs
in Hawaii typically occurs at the school level and is largely based on recommendations
from a committee of teachers, administrators, and counselors (DataWise Hawaii, 2003).
A non-Department of Education agency such as Family Court can initiate a referral,
which is received and processed by a school counselor or administrator (DataWise
Hawaii, 2003). Whereas the screening committee plays an integral part in deciding the

7
eligibility of students for attending alternative schools and programs, the final
determination of students’ status ultimately rests with the school principal. The referral
process is documented by the screening committee on Form 1 (School Screening
Committee Eligibility and Placement List), which includes the following data: (1) school
name, student name, ID, and grade; (2) eligibility criteria (academic, attendance, and
behavior); (3) program needs (academic, social/emotional, and physical/medical); and (4)
service status (yes/no) (p. 29). The information is used to count the number of eligible
students and for determining resource allocations (DataWise Hawaii, 2003).
Although the CSAP no longer exists, the enrollment criteria developed by the
DOE for the program are still used by site-level screening teams to identify students for
alternative education. The following criteria are used to identify students who are at risk
of academic failure and temporary or permanent withdrawal from school (DataWise
Hawaii, 2003; Programs and Services, 2007):
• ten or more unauthorized absences
• two or more courses failed
• one or more grade levels behind
• three or more disciplinary referrals
• adjudicated and involved in the juvenile justice system
• pregnant or parenting
Students who meet two or more criteria are identified as at risk, and those who meet four
or more criteria are considered severely at risk.

8
SMCs serve students at risk who meet two or more of the criteria for alternative
education (DataWise Hawaii, 2003; Programs and Services, 2007). Some students may
have the academic ability to succeed but lack the motivation to perform. These students
need the special motivation services. SMCs are an on-campus option. The overarching
goal of SMCs is to integrate students into the regular school program in service of
helping them fulfill the requirements for graduation (DataWise Hawaii, 2003). SMCs
focus on social and personal development as well as on academic skills (DataWise
Hawaii, 2003). SMCs also provide students with some participation in the regular school
program while serving as a temporary setting for students transferring from off-campus
alternative placements (DataWise Hawaii, 2003). The instruction in SMCs is
individualized and activity oriented.
ALCs serve students who are severely at risk of school failure, as identified by
four or more criteria (DataWise Hawaii, 2003; Programs and Services, 2007). Students
who are identified as severely at risk can interfere with the learning process and
negatively affect the school climate by being physically aggressive, violent, and verbally
hostile (DataWise Hawaii, 2003). Therefore, ALCs become an option for students once
all available resources on the regular campus have been exhausted (DataWise Hawaii,
2003). ALCs may be located either on campus or off campus. They typically have their
own staff, rules, curriculum, and schedules, which are adjusted to meet the needs and
learning styles of the students (DataWise Hawaii, 2003). The goal of ALCs is to provide
a complete educational program that allows students to fulfill graduation requirements
through the ALC (DataWise Hawaii, 2003). When appropriate, students are integrated

9
into regular school programming for campus-wide functions such as assemblies, clubs,
and student activities (DataWise Hawaii, 2003). Students can be transferred from ALCs
to SMCs or regular classes when they display a readiness for increased integration
(DataWise Hawaii, 2003). The implementation of ALCs is not standardized across the
state. Some ALCs are implemented at individual schools, whereas others are
administered at the district level and serve students from high schools within the district
or complex area.
In Hawaii, school districts are organized into complex areas, smaller
administrative units that replaced larger district organizational structures in January 2002.
Each one of the 15 complex areas is headed by a complex area superintendent (CAS).
Complex areas consist of two to three complexes, which include the high school and the
intermediate/middle and elementary schools whose students feed into it. Complex areas
were created to focus the scope of responsibilities for district-level administrators. The
organizational design aims to improve supervision and accountability practices and to
position decision making and resource management closer to the school level to better
address the needs of students within a continuum of support that is implemented from
kindergarten to graduation.
To exit or mainstream a student from an alternative program, the School
Screening Committee/Student Support Team is convened, along with the student and
parents/guardians, to decide the student’s placement based on data. Students typically do
not remain in alternative programs for longer than a school year, with the exception of
students who are severely at risk of academic failure. Criteria for successful exit to a

10
regular school program include positive behavioral and/or academic gains as
demonstrated by a reduction in attendance, tardy, and behavioral problems and by
satisfactory achievement in reading, math, performance assessments, and post-tests.
Students can also exit the program voluntarily or as a result of a serious infraction of the
student agreement.
The DOE also provides guidelines for allocating resources to alternative learning
environments, for instance full-time equivalents (FTE’s) to staff programs, and for
teacher-pupil ratios to serve students at risk. FTE is a classification of an employee’s
full-time status as a worker. The department recommends staffing for ALCs to include
one full-time teacher (100% FTE) for every 12 severely at-risk students. In addition to
the full-time teacher, the state recommends one Part-Time Teacher (PTT) who works up
to seventeen hours per week for every four additional severely at-risk students. Part-time
teachers (PTTs) or casual hires are considered noncertificated staff who provide
instructional support and are paid hourly at an average cost of $17,500 per year.
Furthermore, one full-time Educational Assistant (EA) (100% FTE) is suggested for
every eight additional severely at-risk students (DataWise Hawaii, 2003). The
Department of Education recommends one full-time outreach counselor (100% FTE) to
support at-risk students on the regular school campus or in ALCs.
Alternative schools and programs are generally characterized by commitment to
maintain small class sizes that emphasize one-on-one interaction between teachers and
students (Arnove & Strout, 1980; Barr, 1981; Bryk & Thum, 1989; Natriello, McDill, &
Pallas, 1990; Tobin & Sprague, 1999; Young, 1990). To provide this personalized

11
attention and support for at-risk students, Barr (2001) has recommended a teacher-pupil
ratio of 15:1. When dividing the total number of students serviced by the total number of
staff for alternative schools and programs in Hawaii, the teacher-pupil ratio in alternative
education is twice as high as the recommendation suggests, with approximately 30
students assigned to each teacher (DataWise Hawaii, 2003).
Several evaluations have been conducted on alternative learning environments in
Hawaii. In 1984, the Department of Education Planning and Evaluation Services Branch
did an evaluation of CSAP, and in 1996 the state auditor completed an audit of ALCs.
Follow-up visitations and reviews occurred in 1998 in response to recommendations from
the audit. During school years 1999–2000 and 2001–2002, statewide professional
development was implemented for alternative programs. Additionally, plans for an
online data collection system were developed in school year 1999–2000. The data
system was designed to allocate resources, to evaluate the effectiveness of the system,
and to facilitate the student identification and exiting process for alternative schools and
programs.
The Department of Education in Hawaii conducted an evaluation of its budgeted
programs in school year 2001–2002, which included the 14 alternative schools and
programs, the largest of which was the CSAP. The purpose was to, “(1) determine the
extent of congruence of the Department’s programmatic activity and resource use with
the central goal of improving student achievement of state content standards and (2)
improve the targeting of resources and program effectiveness” (DataWise Hawaii, 2003,
p. i). The fourteen alternative schools and programs, along with 145 programs statewide

12
did not receive the “continue as is” recommendation from the program review panel,
therefore requiring “follow-up” actions and “strategic reviews” of the programs. The
alternative programs did not meet the criteria of the review because they did not serve the
targeted group of students identified as at risk.
During the school years from 1998–1999 to 2000–2001, the enrollment of
secondary students in grades 6–12 averaged 81,304 students. An average of 17,512 of
those secondary students was identified as at risk of school failure or becoming dropouts
and therefore eligible for alternative education (DataWise Hawaii, 2003). Of those
identified as at risk during those three school years, approximately 5,683 to 6,461, or 33
to 36%, were served (DataWise Hawaii, 2003). More recently, during the 2005–2006
school year, when WSF was piloted, approximately 16,663 students were identified as at
risk/alienated, and about 3,099 students, or 18%, were directly served by the CSAP
implemented by the secondary schools (Yamauchi, 2008). This finding is consistent with
similar trends nationwide. During the 2007–2008 school year, 33% of the districts
surveyed nationwide reported that they were unable to enroll new students in alternative
schools and programs due to limitations in staffing or space (NCES, 2010).
As a result of not adequately serving at-risk students, follow-up actions were
implemented by the DOE in Hawaii, during the same school year, 2001–02, involving
strategic reviews of the programs in two areas: needs assessment and program evaluation.
The DOE strategic reviews involved the collection of quantitative and qualitative data
through an interview of the program manager, interviews and surveys of program staff at
alternative learning sites, a review of program documents, observations from site

13
visitations, and meta-analyses of program data and data of student demographics and
performance to evaluate the effectiveness of alternative schools and programs statewide.
The state strategic reviews included the following indicators and goals for student
performance to determine congruence between resource allocation and learning
outcomes:
• Attendance rate. At least 70% of the program students will maintain a
program attendance rate of 70% or more.
• Dropout rate. Less than 10% of students will drop out of school.
• Graduation rate. At least 75% of the program seniors (12
th
-graders) will
graduate by the end of the school year.
• Number of students mainstreamed to the regular education program. At least
10% of the program students will be recommended for mainstreaming or
mainstreamed by the end of the school year.
• Number of courses passed. At least 50% of the program students will pass all
of their required alternative education courses.
• Pre- and post-tests of academic achievement. At least 70% of the program
students show improvement in a pre-post assessment.
The Report on the Strategic Review of Fourteen Student Alienation Programs
(2003) presented the findings on the alternative programs. With regard to alternative
programs as a whole, the evaluation found that students were served by a total of 103
alternative learning sites: 70 SMCs, 20 on-campus ALCs, and 13 off-campus ALCs
during school year 2000–2001. The numbers of CSAP staff remained at the same level

14
for the three years from school year 1998–1999 to 2000–2001. The teacher-pupil ratios
during those three years were 33:1, 28:1, and 34:1, respectively. These figures were
calculated by dividing the total numbers of students serviced by the total number of staff
during those three years.
With regard to the students served in alternative learning environments, the
evaluation found that absenteeism and failure in academic courses were the two most
prevalent indicators for identification for alternative learning environments (DataWise
Hawaii, 2003). The top three grades levels for absenteeism, academic failure, and grade
levels behind were grades 9, 10, and 11. The top three grades for disciplinary referrals
were grades 7, 8, and 9. More male students than female students and more grade 9
students than other grades were identified as at risk. During the three years from school
year 1998–1999 to 2000–2001, ESLL, SPED, and Free Lunch student populations
increased in the general population and in the population of students at risk. About 9% of
the at-risk student population was also identified as ESLL, about 21% SPED, and about
24% on the free and reduced price lunch program. During the three years from school
year 1998–1999 to 2000–2001, the top seven ethnic groups represented in the at-risk
population remained consistent: Part Hawaiian, Filipino, Other, Caucasian, Japanese,
Samoan, and Hawaiian.
In all three years of the review from school years 1998–1999 to 2000–2001, the
evaluation revealed that the alternative program was successful in preventing students
from dropping out, helping students pass required courses, and exiting students back into
the regular classroom setting (DataWise Hawaii, 2003). From school year 1999–2000 to

15
2000–2001, an average of 94% of alternative students remained in school for the year,
72% passed all required courses, and 41% was mainstreamed by the end of the school
year (DataWise Hawaii, 2003). However, about twice as many CSAP students scored
below average on standardized tests (Stanford Achievement Test-Reading and Math)
compared to their counterparts in the regular educational program. The evaluation
concluded that CSAP helped students complete school, gain life skills, and improve
behavior but that, based on scores from standardized tests, academic performance
remained an area in need of considerable improvement. Additionally, the evaluation
identified serious technical problems with the data collection and management system,
particularly involving incompatible documentation formats that limited the aggregation
and disaggregation of data.
Therefore, recommendations primarily focused on improvements in (a)
assessment, data management, and program evaluation through advanced technology; (b)
smaller learning environments with teacher-to-pupil ratios of 1:15; and (c) pre- and post-
assessment measures of student competencies that are aligned to an established standard
(criterion-referenced) for students at risk that can be used to inform instruction. Student
outcomes cannot depend solely on the standardized test because it is not given to all
students and is not a criterion-referenced test. Instead, what was recommended was an
assessment that shows student progress before and after the program and that will
diagnose areas of student academic needs to inform instruction.

16
Statement of the Problem
As mentioned above, the DOE has developed a set of enrollment criteria for the
CSAP program, and site-level screening teams continue to use them to identify students
who are at risk of academic failure and temporary or permanent withdrawal from school.
The department also provides guidelines recommending that SMCs serve at-risk students
who meet two or more criteria, and that ALCs serve severely at-risk students who meet
four or more criteria. In Fall 2011, the DOE planned to develop and implement an early
warning system to improve timely identification and intervention for students who need
additional services and support.
However, what remains unknown is whether consistency exists in the way site-
level screening teams identify and select students for alternative programs. Would a
student enrolled in an ALC in a particular school district be selected for the same
placement in another district? Would he or she be enrolled in an SMC instead? For
instance, a student who is enrolled in an alternative learning center located in an affluent
community might be denied in a different school district when considered alongside other
students who come from disadvantaged families, for example. Inconsistent
implementation of enrollment criteria can create discrepancies in who receives alternative
education, however alternative programs cannot achieve expected outcomes if they are
not operating according to design. Therefore, information on how consistently site-level
screening teams identify and select students for alternative education can help to
implement the enrollment criteria across different alternative learning centers.

17
The lack of reliable funding sources threatens the very existence of alternative
learning environments. Although Hawaii policy and legislation outline the goals for
alternative education and several models for delivering services and support for students
at risk, Policy 2131 lacks language about the funding sources for alternative education
(Lehr, Chee, & Ysseldyke, 2009). As mentioned in the introduction, secondary school
principals must figure out on their own how to implement the policy without financial
support from the DOE. At the same time, Hawaii is not unique. Lehr et al. (2009) found
that state-level funding was most often referred to for alternative education, but a
consistent funding mechanism across states was not clearly specified. Although 34 states
had legislation that included language identifying sources of funding for alternative
schools, 40% of states with formal legislation for alternative education did not address
the issue of funding (Lehr et al., 2009). In the national study conducted by Lehr et al.
(2009), data were collected via (a) a comprehensive web-based search of state-level
alternative education legislation and policy from 48 states and (b) a survey administered
to key contacts at 50 state departments of education, including the District of Columbia,
who were most knowledgeable about alternative schools and programs.
As a result, the needs of students at risk of academic failure and dropping out are
not being met. Findings from the evaluation of CSAP in school year 2001–2002
indicated that the demand for alternative education in Hawaii clearly exceeded the
number of slots available to students. Amid today’s economic uncertainties, what remain
unknown are the levels of resource allocations, particularly in the area of personnel
(FTEs) necessary to staff alternative learning environments. Determining current

18
personnel allocations for alternative learning centers and the impact they have on student
enrollment and teacher-pupil ratios plays an important part in identifying the resources
needed to adequately sustain alternative programs.
Ultimately, the goal is to ensure that resources are equitably and adequately
allocated to meet the needs of students who are not succeeding in traditional learning
environments. Development of a standards-based alternative education system will
require a funding system that allocates resources to alternative schools and programs at
levels that that match or exceed traditional schools (NCES, 1990). Redistributing
inadequate funds and resources will not meet the needs of students who need them most
(Rubenstein, Schwartz, & Stiefel, 2006).
The evaluation of the 14 alternative schools and programs examined student
achievement as well as the systems used to collect data on student outcomes. The
evaluation identified serious technical problems with the data collection and management
system, particularly involving incompatible documentation formats that limited the
aggregation and disaggregation of data. In response to the findings from the evaluation,
significant improvements were made to the system, making it more user friendly for data
entry at the site level. Nevertheless, data collection remains problematic, with the lack of
accountability to input data at alternative program sites. The lack of consistent data
collection and system limitations, therefore, make it difficult to determine how well at-
risk students are achieving state standards. Information about what data alternative
learning centers collect to measure student achievement can help increase accountability
of alternative programs to improve student achievement.

19
Purpose of the Study
The purpose of the study was to compare the impact of the weighted student
formula’s resource reallocations and the state’s recent budget reductions on alternative
learning environments (ALEs) and regular high schools using the Evidence-Based Model
(Odden & Picus, 2008) and the 10 Strategies Framework for Doubling Student
Performance (Odden, 2009). In the study, the Evidence-Based Model was used as an
adequacy framework that links spending to student performance. This link is notable
because a basic problem within the field of school finance involves granting schools
enough resources to provide all students with an education that is equitable and adequate
(Odden & Picus, 2008). Merely focusing on equitable inputs is no longer sufficient, as in
the implementation of the weighted student formula; it is necessary to analyze how
resources are used to provide educational programming that helps all students achieve
state standards. In this way, the EB Model and 10 Strategies Framework shift the focus
beyond studying whether schools are allocated enough funding toward producing
adequate output for all students. As Clune (1995) conceptualized, adequacy for particular
groups such as low-income students can likewise benefit all students.
Specifically, the study examined an ALC that served students who were severely
at risk of academic failure and had needs that could not be met by the regular school
environment. The comparison included a non-ALE, or traditional high school
environment, that served students who were severely at-risk and therefore eligible for an
alternative education but not enrolled in an ALC per se. To describe how the state’s
budget reductions impacted struggling students, the study analyzed student

20
characteristics, resource allocations, instructional programming, and student performance
at separate school sites.
Research Questions
Achieving the purpose of the study required undertaking examination along
multiple fronts. Therefore, the study focused on the following research questions:
• How do the characteristics of at-risk students in alternative learning environments
(ALEs) compare to those enrolled at regular high schools?
• How do resource adequacy levels at ALEs compare with regular high schools, in
relation to the Evidence-Based Model, and change as a result of resource
reallocations of the weighted student formula?
• What factors influence educational leaders’ decisions to allocate resources to
support struggling students?
• How effective are ALEs and regular high schools at helping struggling students
achieve the state’s performance goals?
Importance of the Study
The study is valuable for educational practitioners, policymakers, funders, and
researchers. Each shareholder group plays an important role in promoting adequacy in
public education. In Hawaii, the collective focus of each group is particularly critical for
sustaining focus on systemic priorities such as the implementation of Policy 2131.
Findings from the study regarding the alignment of resource allocations to the Evidence-
Based Model can anchor conversations among different role groups to ensure that all
students who are eligible for additional support in fact receive the extra help they need to

21
meets the rigorous academic standards of the regular curriculum and graduate from high
school.
Education practitioners, specifically leaders who make resource decisions, can
reflect upon findings from the study to facilitate decisions about how to allocate limited
resources in their schools and districts. For instance, information about the factors that
influence resource allocation might provide leaders in public education with data to
clarify their rationale to ensure adequate resources to support struggling students.
Policymakers and funders can also use the findings as a basis to advocate for alternative
education and to ensure that adequate resources are available to implement Policy 2131
as designed. The study’s data on changes in resource allocation as a result of the budget
cuts may provide policymakers and funders with a sense of the resources necessary to
increasing the academic achievement of at-risk students and to establishing reliable
sources of funding to support them.
The study is also important for education researchers who contribute to the
literature on site-based management of alternative learning environments. The role of
researchers within this context is to provide other shareholders with the current
knowledge to make the most informed decisions to increase adequacy in education. To
this end, researchers can build upon findings from the study to conduct further research
that uses experimental designs to examine resource patterns. For example, the study
might contribute knowledge regarding the impact of weighted pupil funding programs,
which can be generalized to larger populations of alternative learning environments and,

22
more specifically examine the validity of adequacy models such as the Evidence-Based
Model to allocate resources at the site level.
Methodology
The study was designed as a mixed-method case study and validated findings
through methodological triangulation. The following approaches build on the strengths
of multiple designs and minimize the limitations of using any one approach in isolation:
naturalistic inquiry, quantitative and qualitative data, and statistical and content analysis.
The study is considered a naturalistic inquiry because it aims to compare learning
environments as they existed at the time of the study within the public school system in
Hawaii rather than attempting to manipulate or control variables. Furthermore, the study
involved a combination of quantitative and qualitative data collected through documents,
websites, and oral interviews. Statistical software was used to analyze quantitative data,
and content analysis was conducted based upon grounded theory.
The unit of analysis in the study was the learning environments in which students
were enrolled. The learning environments examined in the study were selected using a
method of purposeful criterion-referenced sampling. The study compared two high
school sites on the island of Oahu including a district-administered alternative learning
environment (ALE) and a non-ALE or regular high school setting, both of which received
public funding from the state and served struggling students in grades 9–12 who were at
risk of school failure and potentially dropping out of school.

23
Limitations
The study had several limitations associated with external and internal validity
and the reliability of data collection methods. First, a limitation of the study was the
small sample size and that the study did not attempt to control variables through random
sampling or by assigning some schools and districts to implement alternative learning
centers while others did not. Therefore, findings cannot be generalized from the sample
to the larger population of alternative learning centers across the state let alone to
alternative learning environments outside of Hawaii. A second limitation is the potential
for interview data to be distorted by personal biases, the mood of the respondent, politics,
rapport with the interviewee, and potential for inconsistent implementation of the
interview protocol. Third, the study did not examine the dollar-per-pupil amount of
funding allocated to sites through the weighted student formula; therefore, conclusions
cannot be drawn from findings about the equity of funding levels at sites. Fourth,
documents and records can be difficult to access and might be incomplete or inaccurate.
Finally, the limitation of using qualitative data analysis in the study is that the
researcher/analyst can impose his or her personal constructs on the data rather than
allowing patterns and themes to emerge naturally.
Delimitations
Despite the limitations described above, the study examined alternative learning
centers in Hawaii by gathering and analyzing data from interviews, documents, and
records. Although no attempt was made to control variables, the study applied criterion-
referenced, purposeful sampling to align the sample of alternative learning centers in the

24
study to the larger population of alternative learning environments nationwide and in
Hawaii. To address limitations associated with validity, the study also incorporated
methodological triangulation to build upon the strengths of multiple design approaches
and minimize the limitations of using any one approach in isolation. The difficulty of
gaining access to documents and records cannot be controlled, nor can the possibility that
some data may be incomplete or inaccurate. Therefore, the study included interviews to
supplement the data that was accessible. Additionally, the study could not control for
factors that distort interview responses nor the potential for variance in the questions that
the interviewer asks, but triangulation of interview approaches can help to outline
important issues in advance while providing the interviewer with flexibility and structure
where necessary to collect the data to address the research questions of the study.
Researcher bias cannot be fully removed from data analysis; therefore, the study
addressed this limitation with careful distinction and documentation of researcher
impressions and reflections noted during data collection. Finally, although graduation,
dropout, and attendance rates are not proxies for learning, they were used as indicators to
examine student performance.
Assumptions
The following assumptions were made as part of conducting the study:
• Students failing academically and dropping out of school is an issue worthy of
examination.
• Given enough time, most students can achieve high standards.

25
• Education leaders’ decisions to allocate resources to alternative learning
environments are influenced by their perceptions of the value and
effectiveness of current strategies to help struggling students.
• Site-level screening teams use a set of criteria to identify and select high
school students for alternative learning centers.
• High school students are selected for alternative learning centers on the basis
of decisions by a site-level screening team.
• Enrollment criteria are critical to the implementation of alternative programs
• Interviewees will provide accurate information.
• Alternative learning centers receive personnel positions through the state.
• The personnel hired for alternative learning centers are highly qualified and
meet the requirements set forth by the Department of Education.
Definition of Terms
Alternative Education: a broad category of educational approaches designed to serve
students at risk of academic failure and potential dropouts whose needs cannot be met by
the regular school or traditional education system
Alternative Learning Center (ALC): a model of alternative education for severely at-risk
students who are identified by four or more enrollment criteria and have a history of
negatively affecting the learning process and school climate
Alternative Learning Environment (ALE): overarching concept that encompasses various
models, types, and forms of alternative education

26
Alternative program: classification of alternative learning environments usually
implemented on the campus of regular school
Alternative school: classification of alternative learning environments typically located at
separate sites from regular schools that serve the larger student population
At-risk student: students who meet two or more criteria of academic failure or temporary
or permanent withdrawal from school
Charter School: publicly funded elementary and secondary schools governed by separate
rules and regulations from regular public schools in exchange for accountability for
student performance
Comprehensive School Alienation Program (CSAP): program established in Hawaii to
address increasing numbers of students dropping out of traditional school settings
Comprehensive Student Support Services Section (CSSSS): a branch of the Hawaii State
Department of Education that manages the implementation of the Comprehensive Student
Support System to address students’ needs through preventive and developmental
services and support
Comprehensive Student Support System (CSSS): a framework for the continuum of
instructional and counseling programs and services that support the academic, social,
emotional, and physical learning environments that help students succeed in school
Full-Time Equivalent (FTE): classification of an employee’s full-time status as a worker
Learning Centers: a model of learning developed in Hawaii from the “school within a
school” concept that includes areas such as performing arts, business, health, and
international studies

27
Magnet Schools: public elementary, middle, and high schools that provide courses and
curricula in various areas of specialization and focus
Severely at-risk student: students who meet four or more criteria of academic failure or
temporary or permanent withdrawal from school
Special Motivation Class (SMC): a model of alternative education for at-risk students
who meet two or more enrollment criteria and have the academic ability to succeed but
lack the motivation to perform
Regular/traditional school: a public elementary or secondary school that does not focus
primarily on vocational, special, or alternative education
Weighted Student Formula (WSF): a system-wide funding strategy in Hawaii that
considers student characteristics to allocate additional funding to schools for extra
services and support to students who come from low-income families, have special needs,
and are English language learners
Organization of the Study
Chapter One of the study presented an overview of the study, the background of
the problem, the statement of the problem, the purpose of the study, the questions to be
answered, the importance of the study, a brief description of the methodology,
limitations, delimitations, assumptions, and the definitions of terms. Chapter Two is a
review of the relevant literature; it includes the following topics: National Information on
Defining Alternative Learning Environments and Programs, National Information on
Funding for Alternative Learning Environments, National Information on the Evaluation
of Alternative Learning Environments, and How Alternative Learning Environments

28
Work in Hawaii. Chapter Three presents the methodology used in the study, including
research design, population and sampling procedure, and the instruments and their
selection or development, along with information on validity and reliability. Each of
these sections concludes with a rationale, including strengths and limitations of the
design elements. The chapter goes on to describe the procedures for data collection and
the plan for data analysis. Chapter Four presents the results of the study. Chapter Five
discusses and analyzes the results, culminating with a conclusion and recommendations.

29
CHAPTER TWO:
LITERATURE REVIEW
This chapter aims to provide a review of current research conducted on alternative
learning environments nationwide and then examines the alternative education landscape
in Hawaii. The first section will discuss alternative education as a solution to the national
problem of student dropout from public schools. This section will explain how
alternative education began in the United States, who is served, how students are
selected, and how alternative learning environments operate in terms of administration
and location. The second section examines policy- and funding-related issues, and how
the lack of reliable funding sources impacts alternative learning environments. The third
section discusses the indicators used to measure student performance in alternative
learning environments and the evaluation issues that emerge from a lack of student
outcome data and lack of experimental designs that can be generalized to larger
populations. The fourth section focuses on issues specific to alternative education in
Hawaii, namely those related to program implementation, funding, and evaluation of
alternative learning environments. The final section introduces the theoretical
frameworks used in the study.
Definitions of Alternative Learning Environments and Programs
This section begins with a brief history of alternative education in the United
States with regard to federal policy and discusses how the past has shaped today’s
educational landscape. Furthermore, this section examines the definition of alternative
education, the administration and operation of alternative learning environments as well

30
as the diversity in location and grade levels served nationally. The section ends with a
discussion of various types of alternative learning environments and the process for
selecting students for alternative education.
Brief History of Alternative Education
Alternative education emerged in the United States in the late 1950s and early
1960s, at a time when the civil rights movement was gaining increased attention across
the nation (Lange & Sletten, 2002). During this period of heightened public engagement
in social issues, disaffected middle- and upper-middle class youth became the
predominant voices behind growing concerns about the quality of traditional schooling
(Duke & Muzio, 1978). The alternative education movement gained momentum as
public awareness grew about discrimination in regular public school systems toward
students from minority and low-income backgrounds (Lange & Sletten, 2002).
In the mid-1960s, public education was the focus of significant political attention.
Under President Lyndon Johnson’s nationwide campaign against poverty, public
education systems were tasked to lead the charge of fulfilling the nation’s promise of
equality through high-quality education for all children especially those from minority
and disadvantaged backgrounds (Lange & Sletten, 2002). Congress established the
Elementary and Secondary Education Act of 1965, which provided unprecedented
amounts of funding to public schools in the form of Title I programs, such as Head Start,
to offset the disadvantages endured by low-income families (Raywid, 1981).
Corporations and well-known foundations such as Ford, Carnegie, and Rockefeller also
directed funding toward alternative education (Raywid, 1981).

31
During this time, alternative schools and programs emerged both outside and
within public education systems. Regardless of where they were located or how they
were administered, alternatives sought to distinguish themselves from the traditional
school environment (Lange & Sletten, 2002). Two broad categories classified alternative
schools and programs that were established outside of public education. The first were
Freedom Schools, which were based within communities, in various locations from
churches to storefronts. The main focus of Freedom Schools was to educate students
from minority backgrounds who were marginalized by regular public schools (Lange &
Sletten, 2002). Second was the Free School Movement, which fostered one’s individual
freedom to explore curiosities for the pure enjoyment of learning rather than to conform
to formal instructional approaches. Alternatives were also established within public
school systems. For instance, Open Schools, developed by public school educators,
aimed to promote school choice by offering student-centered instruction in a
noncompetitive environment that allowed students to be self-directed and work at their
own pace (Lange & Sletten, 2002).
The 1970s were marked by a fresh sense of innovative and progressive
educational practices introduced by alternative schools and programs (Young, 1990);
however, many of them were not sustainable over time (Raywid, 1981). Evaluations of
student learning during this period revealed mediocre results with increasing numbers of
students performing below average on academic tests (Young, 1990). In response to
these poor academic results, alternative schools and programs of the 1980s witnessed a
shift toward teaching the fundamentals through such models as Continuation Schools for

32
failing students and Fundamental Schools that emphasized teaching the basic skills
(Young, 1990).
A number of events laid the foundation for some of the trends that currently exist
in the educational landscape, namely those related to legislation and funding for
alternative education as well as to the varying types and purposes of alternative learning
environments. For example, the establishment of the Elementary and Secondary
Education Act of 1965 by Congress set the precedence for current state-level legislation
and funding for alternative education and for Title I funding, which still exists today and
remains a significant source of funding for schools with high percentages of students
receiving free-and-reduced-priced lunch. Furthermore, well-known foundations continue
to support alternative education, as illustrated in 2002 when the Bill and Melinda Gates
Foundation launched the Alternative High School Initiative, with combined support from
the Charles Stewart Mott Foundation, the Kellogg Foundation, and the Walter S. Johnson
Foundation, to scale up successful models of alternative education (Aron, 2006).
The alternative schools and programs of the 1960s and 70s gave way to diversity
in purpose and to the types of alternative learning environments that exist today. For
example, Open Schools influenced public alternatives such as (a) schools without walls,
which encourage community-based learning, (b) learning centers that involve additional
resources to implement engaging and relevant curriculum, (c) multicultural schools that
anchor learning in culture and ethnicity, and (d) magnet schools developed around
themes that promote racial and cultural diversity (Young, 1990). In this way, the early
models of alternative education introduced concepts such as school choice and innovation

33
involving community involvement, student-centered, inquiry-based approaches, and
culturally relevant and thematic approaches, all of which presented drastic shifts from the
highly structured instructional approaches of traditional education.
Alternative Education Policy and Legislation
In recent years, state-level legislation and policies on alternative schools have
emerged to serve students at risk of school failure within the traditional education system
(Iowa Association of Alternative Education, 2002; Lehr et al., 2009; Morley, 1991; State
of Wisconsin, 2001). A total of 48 states have legislation on alternative education (Lehr
et al., 2009). Thirty-four states have legislation that included language on the definition
of alternative schools including purpose, location, students served, or desired outcomes
(Lehr et al., 2009).
Definition of Alternative Education
Alternative education is designed to serve students at risk of academic failure and
potential dropouts whose needs cannot be met by the regular school or traditional
education system (Lehr et al., 2009). The U.S. Department of Education (2002) has
defined alternative education as:
A public elementary or secondary school that addresses needs of students
that typically cannot be met in a regular school, provides nontraditional
education, serves as an adjunct to a regular school, or falls outside the
categories of regular, special education or vocational education (p. 55).

Alternative schools and programs are designed to meet student needs that are not met in
regular schools (NCES, 2010).
Within the context of alternative education, the term alternative school is
distinguished from alternative program. Alternative schools are typically located at

34
separate sites from regular schools that serve the larger student population (NCES, 2010).
Alternative schools and programs can be located in community centers, juvenile justice
centers, store-front neighborhood organizations, public housing facilities, homeless
shelters, medical or mental health facilities, community colleges or other postsecondary
campuses (Aron & Zweig, 2003). In contrast, alternative programs are usually
implemented on the campus of regular school (NCES, 2010). Alternative programs can
be located in regular schools during school hours and nonschool hours (Aron & Zweig,
2003).
Administration and Operation of Alternative Learning Environments
Alternative education calls for policies and administrative procedures that are
adapted to meet student needs, thereby representing a departure from the traditional K–12
school environment (Aron & Zweig, 2003). To examine how alternative schools across
the nation operate, Lehr and Lange (2003) conducted a national study involving
interviews of state directors of special education and designees. They found that most
alternative schools, over 60%, were governed at the local level, with schools and districts
developing their own procedures and practices (Lehr & Lange, 2003). Less than 20% of
respondents mentioned alternative schools governed by community-based organizations
or private companies (Lehr & Lange, 2003).
NCES (2010) conducted a study that involved mailing an initial district survey to
1,806 public school districts about alternative schools and programs during school year
2007–2008 and a brief follow-up survey. Forty percent of districts reported having at
least one district-administered alternative school or program during school year 2007–

35
2008 (NCES, 2010). The study found that, in the United States, 10,300 district-
administered alternative schools and programs served at-risk students (NCES, 2010).
Thirty-five percent of districts with alternative schools and programs had at least one
alternative school or program administered solely by another entity. Twelve percent of
districts with alternative schools and programs had alternative schools and programs
administered by both the district and another entity (NCES, 2010). Of the 35% of
districts that reported using alternative schools or programs administered by an entity
other than the district during school year 2007–2008, 81% had alternative schools and
programs that were administered by a public entity (e.g., regional program, consortium,
cooperative, or another school district). Twenty-six percent of districts had alternative
schools and programs that were administered by a private entity contracted by the district.
Eight percent of districts had alternative schools and programs that were administered by
a two- or four-year postsecondary institution in partnership with or contracted by the
district.
The NCES study found that a total of 645,500 students were enrolled in
alternative schools and programs. Most students were enrolled in alternative schools and
programs administered solely by the district rather than alternative schools and programs
administered solely by another entity. Moreover, 558,300 students were enrolled in
alternative schools and programs administered solely by the district, and 87,200 students
were enrolled in alternative schools and programs administered solely by another entity
(NCES, 2010).

36
Location and Grade Levels of Alternative Learning Environments
Alternative schools and programs are set up by states, school districts, and other
entities to serve students who are not succeeding in a traditional public school
environment (Aron, 2006). Thirty-seven percent of district-administered alternative
schools and programs are housed within a regular school, and 63% is housed within
separate facilities (NCES, 2010). Four percent of district-administered alternative
schools and programs are located in juvenile detention centers. Three percent of district-
administered alternative schools and programs are operated as charter schools. (Charter
schools are generally located in a separate facility, although charter schools are
characterized as such by their type of administrative structure rather than by location, per
se.) Seventeen percent of district-administered alternative schools and programs used
distance education as a mode of instructional delivery. Distance education is unique in
that it can occur at school, at home, or other locations that accommodate student needs.
Alternative learning environments serve students in all grade levels. Most district-
administered alternative schools and programs focus on the secondary level, particularly
serving grades 9–12 (NCES, 2010). Six to 18% of district-administered alternative
schools and programs were elementary level, serving grades K–5 (NCES, 2010). Forty-
one to 63% of district-administered alternative schools and programs were middle level,
serving grades 6–8 (NCES, 2010). Eighty-eight to 96% of district-administered
alternative schools and programs were high school level, serving grades 9–12 (NCES,
2010).

37
Types of Alternative Learning Environments
In its broadest sense, alternative education encompasses a wide array of services
for vulnerable youth who are no longer in the traditional K–12 school system, including
home schooling, GED preparation, gifted and talented programs, and charter schools
(Aron, 2006). Raywid (1994) has described three types of alternative learning programs,
each of which has distinct purposes and physical characteristics that inform its
instructional focus and enrollment process. Alternative learning environments will
oftentimes reflect a combination of different types of programs rather than one
exclusively, and each type will reflect varying degrees of deviation from traditional
organizational and administrative practices.
Type I programs, according to Raywid (1994), are considered “Popular
Innovations.” The purpose of Type I programs is to improve the learning environment
for students. These programs are often located in separate facilities and sites from the
traditional school. Type I programs might resemble magnet schools in some places and
are designed around programmatic themes that make school challenging and fulfilling for
students and adults. Students typically choose to attend Type I alternative programs.
Type II programs are referred to as “Last-Chance Programs” (Raywid, 1994).
Unlike the procedure for Type I programs, students are placed into Type II programs and
are required to attend. In other words, students are not given a choice to attend Type II
programs. Some educators refer to them as “soft jails” for the chronically disruptive.
Students are sent to the school or program for specified periods of time and/or until
behavior requirements are met (DataWise Hawaii, 2003). The classroom climate is

38
highly structured and regulated with systems of rewards and consequences (DataWise
Hawaii, 2003). Type II programs are designed to focus on behavior modification with
less emphasis on academics. Academic work can come from the same classes from
which students were initially removed, therefore limiting instruction to rote drill.
Common forms of Type II programs include in-school suspension programs and cool-
out-rooms, usually located on the regular school campus (Raywid, 1994).
Type III programs are characterized as “Remedial Focus” for students presumed
to need remediation or rehabilitation (Raywid, 1994). Although Type III programs
provide academic remediation, the purpose and focus is therapeutic and intended to
provide social and emotional rehabilitation. The goal is to provide students with
treatment so that they can return to the general education setting. Students are typically
referred to Type III programs. Interactions in these settings are student centered and
therapy oriented. These programs can be located on the main campus or at a separate
facility. In some cases, instructional modifications take place through a home school
arrangement.
Student Selection Process for Alternative Learning Environments
According to Lehr et al. (2009), 42 states had legislation that included language
on the criteria to determine the eligibility of students for alternative education. Indicators
that typically characterize students at risk of educational failure, and who thus must
attend alternative schools and programs, include truancy, poor grades, disruptive
behavior, and pregnancy (NCES, 2010). Students can be transferred to a district-
administered alternative school or program solely for physical attacks or fights (61%);

39
possession, distribution, or use of alcohol or drugs (excluding tobacco) (57%); disruptive
verbal behavior (57%); continual academic failure (57%); chronic truancy (53%);
possession or use of a weapon other than a firearm (51%); possession or use of a firearm
(42%); pregnancy or teen parenthood (31%); and mental health needs (27%) (NCES,
2010). Students attend alternative schools and programs based on recommendations from
regular school staff (75%); a committee of teachers, administrators, and counselors
(71%); a district-level administrator (54%); a parent request (48%); a student request
(41%); a result of Functional Behavioral Assessment (FBA) (28%); or referrals by the
criminal justice system (23%) (NCES, 2010).
Funding and Personnel for Alternative Learning Environments
This section will discuss policy and funding issues related to the lack of reliable
funding sources and insufficient resources to meet the demand for alternative education.
The section will also examine teacher requirements and qualifications in alternative
education.
Policy and Legislation for Funding
Funding sources for alternative education are unreliable (NGA Center for Best
Practices, 2001). In a national study, Lehr et al. (2009) found that state-level funding was
most often referred to for alternative education, but a consistent mechanism across states
was not clearly specified. As mentioned earlier, a total of 48 states have legislation on
alternative education (Lehr et al., 2009). However, 40% of states with formal legislation
for alternative education do not address the issue of funding (Lehr et al., 2009). Only 34
states had legislation that included language identifying sources of funding for alternative

40
schools (Lehr et al., 2009). In addition to state-level funding, alternative education is
funded and administered by nonprofit organizations, private for-profit companies, K–12
public and private schools, charter schools, community schools for adults, juvenile justice
agencies, and federal, state, and local agencies (Aron & Zweig, 2003). To implement
high academic standards in alternative education systems and, at the same time, preserve
the elements that have made alternative schools and programs successful in the past
requires resources (NGA Center for Best Practices, 2001). Without adequate funding and
resources to support alternative learning environments, the needs of students who are at
risk of academic failure cannot be met.
Demand for Alternative Education
The number of slots available in alternative schools and programs do not
adequately meet the demand of students who need an alternative education (Kleiner,
Porch, & Farris, 2002). Fifty-four percent of school districts that offered alternative
education reported that demand had exceeded their capacity within the last three years
(Kleiner et al., 2002). District-administered alternative schools and programs were
unable to enroll new students because of staffing or space limitations. Thirty-three
percent of district-administered alternative schools or programs were unable to enroll
new students because of staffing or space limitations during the 2007–2008 school year
(NCES, 2010).
Teacher Requirements and Qualifications
According to Darling-Hammond (2010), “Substantial evidence suggests that,
among all school resources, well-prepared, expert, experienced, teachers are among the

41
most important determinants of student achievement” (p. 17). Compared to certified
teachers who are adequately prepared, teachers who lack preparation in their content area
or teaching pedagogy produce significantly lower results (Boyd, Grossman, Lankford,
Loeb, & Wyckoff, 2006; Darling-Hammond, 2000; Darling-Hammond, Holtzman,
Gatlin, & Heilig, 2005; Hawk, Coble, & Swanson, 1985; Goldhaber & Brewer, 2000;
Monk, 1994). On the other hand, students who are taught by fully certified teachers are
more likely to do better on required state tests, while controlling for variables such as
poverty (Betts, Rueben, & Danenberg, 2000; Fetler, 1999; Fuller, 1998, 2000; Goe, 2002;
Strauss & Sawyer, 1986).
With regard to teaching in alternative learning environments, 29 states had
legislation or policy that included language regarding staffing alternative schools (Lehr et
al., 2009). Sixteen states required alternative school teachers to be certified or to comply
with state standards (Lehr et al., 2009). Thirty percent of district-administered alternative
schools and programs had specific requirements for teaching in addition to regular
teacher requirements (NCES, 2010). Forty-eight percent of district-administered
alternative schools and programs had professional development requirements for teaching
in addition to those required of all teachers (NCES, 2010).
Evaluation of Alternative Learning Environments
A standards-based alternative education system holds students to the same
rigorous standards established for students in traditional settings (NCES, 1990).
Therefore, this section will begin with a discussion of data indicators to measure student
performance. The development of data-driven accountability measures is necessary to

42
implement high academic standards in alternative education systems (NGA Center for
Best Practices, 2001). However, evaluating student achievement, particularly in
alternative learning environments, is not an easy task. This section will also examine
problems associated with evaluation in alternative education.
Student Performance Data
State-level information on student outcomes is lacking. Only 19 of 36 states
indicated that their departments of education had a system in place documenting
outcomes for students who attend alternative schools (Lehr et al., 2009). Some state
departments of education, such as those in North Carolina, Vermont, Oklahoma, and
Kentucky, had reports summarizing information about their alternative schools (Lehr et
al., 2009). Thirty-five percent of district-administered alternative schools and programs
had a database to track students after they leave alternative schools and programs (NCES,
2010).
District-administered alternative schools and programs reported using various
indicators to measure student performance and to document the reasons why students
exit. Sixty-eight percent of districts indicated that, to a moderate or large extent, students
leave alternative schools and programs to return to regular school. Sixty-eight percent of
districts indicated that, to a moderate or large extent, students leave alternative schools
and programs because they graduate with a regular high school diploma. Sixteen percent
of districts indicated that, to a moderate or large extent, students leave alternative schools
and programs because they graduate with a nonstandard high school diploma or
certificate of completion. Nineteen percent of districts indicated that, to a moderate or

43
large extent, students leave alternative schools and programs because they are transferred
to an adult education or General Education Development (GED) program. Seventeen
percent of districts indicated that, to a moderate or large extent, student leave alternative
schools and programs because they dropped out of school. Five percent of districts
indicated that, to a moderate or large extent, students leave alternative schools and
programs because they are transferred to a criminal justice facility (NCES, 2010).
Validity of Findings
Students who attend alternative schools, particularly schools of their choice, show
positive gains in self-esteem, peer relationships, commitment to school, and overall
performance (Cox, Davidson, & Bynum, 1995; Dugger & Dugger, 1998; Gold & Mann,
1984; May & Copeland, 1998; Ruzzi & Kraemer, 2006; Smith, Gregory, & Pugh, 1981).
Such positive student outcomes from alternative schools appear more in nonexperimental
research studies than in research using experimental designs (Cox, 1999). Critics of the
research on alternative education argue that findings lack rigor, generalization, and focus
on long-term outcomes (Carruthers et al., 1996; Cox et al., 1995; Ruzzi & Kraemer,
2006). These critiques of research in this area make it difficult to generalize findings to
larger populations of alternative schools and programs.
How Alternative Learning Environments Work in Hawaii
In fiscal year 2010–2011, the total executive operating budget of the Department
of Education in Hawaii was $2.46 billion, and in 2011–2012, the budget was cut to $1.8
billion (State of Hawaii Department of Education Financial Reports). At the same time,
Hawaii public schools were required to meet higher Annual Measurable Objectives

44
(AMO) in 2011, such as increases in reading from 58% to 72%, in mathematics from
46% to 64%, and in graduation rates from 80% to 85% (State of Hawaii Department of
Education, 2011).
Theoretical Frameworks
This section presents the theoretical frameworks used in the study to compare
alternative learning environments (ALEs) and regular high schools. The study applied
two separate frameworks as lenses to analyze the combined impacts of the weighted
student formula’s resource reallocations and the state’s recent budget reductions on
resource adequacy levels, site-level programming, and student performance at different
school sites. This section will first introduce a framework, including school improvement
strategies, then present models of adequacy to identify the necessary resources for
effectively implementing these strategies to increase student performance.
School Improvement Strategies
The school improvement strategies presented in this section represent 10 themes
identified by Allan R. Odden and his staff at the University of Wisconsin-Madison, with
the consultation of Lawrence O. Picus and Associates, from an increasing body of
research on schools and districts that have dramatically improved student achievement,
and multiple cases in which schools and districts have actually doubled student
performance (e.g., Blankstein, 2004; Chenoweth, 2007; Fielding, Kerr, & Rosier, 2004;
Fullan Hill, & Crevola, 2006; Hightower, Knapp, Marsh, & McLaughlin, 2002; Odden,
Picus, Archibald, Goetz, Aportela, & Mangan, 2007; Supovitz, 2006). The 10 Strategies

45
for Doubling Student Performance (Odden, 2009) is a research-based framework to
improve student performance and will be further discussed in this section.
Strategy one: Analyze student performance data. Analysis of data on student
performance is important for educators, allowing them to develop a deep understanding
of the performance challenge in their schools and districts (Odden, 2009). Additionally,
data analysis helps leaders create a sense of urgency within the system to act on behalf of
improving student learning. Although educators might have access to a wide range of
performance data, in many cases, data from the state assessment serve as a launching
point for data analysis to occur (Odden, 2009). Initial data analysis will identify the
overall proficiency levels at which students achieve the state performance standards, and
further analysis will begin to reveal that gaps in student achievement areas of student
performance might be higher than other areas (Odden & Archibald, 2009). For instance,
test results can facilitate comparisons in performance levels among student subgroups as
well as in content area subtopics included on the assessment (Odden & Archibald, 2009).
In this way, data become a means to target specific areas and to focus action to improve
student achievement.
Strategy two: Set ambitious goals. Regardless of the performance challenges
identified in Strategy One, schools must set high academic performance goals for
students (Odden, 2009). Odden (2009) has also emphasized that high expectations must
apply to all students and transcend stigmas associated with student demographics,
particularly for students who are classified as minority or low income. Examples of
ambitious goals include pushing all students to achieve advanced proficiency levels, to

46
demonstrate proficiency on course exit examinations, and to graduate with a high school
diploma (Odden, 2009). Ultimately, striving toward ambitious learning goals is a
mindset on the part of teachers and leaders in education to both celebrate hard-earned
performance gains and, at the same time, relentlessly and fiercely pursue excellence.
Strategy three: Implement an effective curriculum and instruction program.
Attending to the curriculum and instruction program at the school site level is important
because it is an area over which schools have direct control (Odden, 2009). This aspect
of education engages teachers in the identification of important content for students to
learn and how they will learn it. More importantly, the curriculum and instruction
program at the site is a reflection of the academic expectations that teachers have for
students. Ensuring that curriculum and instruction program is effective ultimately
challenges schools to replace outdated curriculum with current materials, which may
mean investing in newer textbooks and/or technology software (Odden, 2009).
Strategy four: Use formative assessments to make data-based decisions.
Although results from the state assessment provide this sort of broad sense of student
proficiency at designated grade levels, formative assessments are typically administered
throughout the school year in addition to the state assessment (Odden &Archibald, 2009).
Odden and Archibald (2009) have also maintained that “Formative assessments are
instruments designed to provide detailed and concrete information on what students know
and do not know with respect to discrete curriculum units” (p. 67). Therefore, formative
assessments provide teachers with more detailed data on student performance than the
state assessment to inform instruction. In this way, alignment between instruction and

47
the learning targets that students aim to achieve is increased, giving way to the
implementation of strategies to address students’ specific learning needs.
Strategy five: Implement ongoing professional development. Odden (2009)
has maintained that effective professional development is ongoing as well as intensive
and mandatory. Therefore, all teachers are expected to engage in professional
development activities. Participation is not a matter of choice for teachers—nor is it
based on topics of their interest. Instead, Odden (2009) has recommended professional
development with a curricular focus on topics such as the textbooks being implemented
at the school as part of the curriculum and instruction program at the site. Furthermore,
Odden and Archibald (2009) asserted that effective professional development is
embedded in the process of collaborative analysis of data from formative assessments.
Findings from data analysis become the basis upon which refinements to instructional
practices and strategies to address the needs of students are made (Odden & Archibald,
2009).
Strategy six: Use instructional time efficiently and effectively. Schools that
were able to double student performance approached time as something that could be
reorganized and changed rather than as an aspect of education that was constant and
fixed. To increase student learning, schools must protect time for core subject areas
(Odden, 2009). Schools that experienced dramatic results also committed themselves to
focusing time on what would produce the greatest results in student outcomes, such as
students’ skills in reading and mathematics and uninterrupted periods of time designated
for those basic skills. Furthermore, high performing schools were not only able to

48
reallocate time effectively for student learning, but also for professional development and
teacher collaborative planning time.
Strategy seven: Provide extra help for struggling students. According to
Odden (2009), implementing extra help strategies is important, because some students
require time beyond what is provided through the regular school day to achieve
proficiency levels in rigorous performance standards. Others agree that most students
can achieve high standards given enough time (Bransford, Brown, & Cocking, 1999;
Cunningham & Allington, 1994; Donovan & Bransford, 2005a, 2005b, 2005c). Several
examples of extra help strategies that provide support beyond the regular school day—
and typical school year, for that matter— include tutoring, extended day programs, and
summer school.
Tutoring. One way of providing struggling students with extra help is to offer
tutoring. The key to effective tutoring is to provide the intervention as soon as possible—
when students begin to struggle—to reduce the need for more costly remedial services
later down the road (Odden, 2009). Tutoring can occur in a one-to-one setting or a group
setting that ideally does not exceed five students (Odden, 2009). Importantly, when
implemented by licensed teachers, tutoring is the most effective strategy to help
struggling students achieve standards (Shanahan, 1998; Shanahan & Barr, 1995; Wasik &
Slavin, 1993). Instructional aides can also provide tutoring if they are supervised and
trained to work with students with mild learning challenges rather than students with
more severe needs who perform at the bottom quartile. When the needs of students are

49
greater, licensed and specially trained teachers provide the most effective intervention
(Odden, 2009).
Because tutoring is an intensive intervention, teachers will likely spend only part
of their workday tutoring students. Thus, according to Odden and Picus (2008), a FTE
position can be used to tutor 18 students in a one-to-one setting for 20 minutes each day.
Furthermore, tutoring is not a permanent intervention. Most students will only require
tutoring periodically based on their performance on formative assessments that test their
understanding of the content and skills they are acquiring; therefore, tutoring services can
be adjusted to allow many students to benefit from tutoring throughout the school year
(Odden & Picus, 2008).
Extended day. Another approach to providing students with extra help is through
extended day programs. Extended day, as its name implies, provides opportunities for
learning beyond the regular school day but within the school year (Odden, 2009).
Extended days offer students extra time to complete assignments and to receive tutoring
before or after school and on weekends, in some cases (Odden, 2009).
Summer school. Lastly, summer school is another way to provide struggling
students with extra help. This strategy provides students with additional instructional
time not only beyond the school day, but also beyond the regular school year. Summer
school provides students time beyond the school year to achieve standards and earn
promotion to the next level (Borman, 2001, as cited in Odden & Picus, 2008).
Strategy eight: Create a collaborative and professional school culture.
According to Odden (2009), a collaborative and professional school culture evolves

50
through the implementation of other strategies discussed in this section. Although such a
culture can be planned and structured, its nature is emergent and dependent upon the
dynamics of individuals and groups who create the culture. Therefore, a key premise in
the promotion of this type of collaborative culture is teacher participation through
engagement rather than compliance.
The professional learning community (PLC) framework is a popular model
developed by Rick and Becky DuFour and others to promote collaboration and learning
among adults (DuFour, DuFour, Eaker, & Many, 2006). In professional learning
communities, teachers may analyze student performance data from formative assessments
and use the new knowledge they construct to inform practice and to form a link between
student performance and curriculum and instruction. The effective functioning of PLCs
requires teachers to take responsibility for the student outcomes that result from their
instructional practice and hold students to high expectations. Furthermore, PLCs
promote deprivatization of practice, which requires teachers to be transparent in
discussing their instruction and inviting others to observe them in action to ultimately
arrive at common approaches that many teachers use (Newmann & Associates, 1996).
PLCs also promote collaboration beyond the school level, as they include personnel from
the central office and school administrators in data-driven dialogue (Odden, 2009).
Therefore, the hope is that these professional conversations will naturally lend themselves
to instructional leadership roles that teachers can assume to increase their involvement
and, more importantly, their influence in curriculum and assessment decisions (Odden,
2009).

51
Strategy nine: Use research-based and proven strategies. This strategy is
really about schools and districts leveraging their own professional experience to
determine quality research evidence and best practices to improve student learning in
their particular setting (Odden, 2009). In other words, the implementation of research-
based practices represents the coming together of the craft knowledge and expertise of
school- and district-level educators with the most current findings from the broader
education community of researchers and experts. This strategy speaks to the theme that
improvement did not occur in isolation for schools and districts that have doubled student
performance. Instead, these dramatic gains were the result of the collective knowledge
and efforts of multiple stakeholders in the education community on behalf of a common
focus on improving student achievement.
Strategy ten: Develop talent and human capital. To successfully implement
these evidence-based strategies and produce dramatic results in student learning requires
human capital and investments in acquiring, developing, and retaining talent (Odden,
2009). Therefore, focused and strategic attention on the management of human capital is
key. The first element of managing human capital is to acquire talent in all areas of the
education system including the classroom, but also in leadership positions at the site and
district levels (Odden, 2009). An equally important aspect of talent management is the
ongoing development of capacity through professional development, mentoring,
coaching, evaluation, and compensation (Odden, 2009).

52
Evidence-Based Model
Implementing the strategies presented above requires access to adequate
resources. Therefore, the Evidence-Based Model will serve as a framework in the study
as a way of linking spending to student performance, thereby identifying the resources
necessary not only to implementing the improvement strategies, but also—more
importantly—to increasing student achievement. This section will discuss two variations
of the EB model, including the prototypical high school and the 1 Plus 1:7 model for
alternative learning environments (ALEs).
Prototypical high school. The prototypical high school contains two elements:
school characteristics and personnel resources. The first element identifies school
characteristics, including school configuration, school size, number of teacher workdays,
and percentages of students classified as special education, low-income, English language
learner (ELL), and minority. These characteristics of the student population are then
used to calculate personnel resources for schools. The second aspect of the prototypical
high school provides adequacy recommendations for staffing categories and dollar
categories that are described in more detail below.
Core teachers. In high schools, core teachers are oftentimes organized into
content area departments such as English/language arts, mathematics, science, and social
studies/history (Odden & Picus, 2008). These subject area distinctions among teachers
also reflect the curriculum they implement in their classrooms. The prototypical regular
high school includes 24.0 FTE licensed core subject-specific teachers based upon class

53
sizes of 25 students, which is the national class size average for secondary schools
(Odden & Picus, 2008).
Specialist teachers. Specialist teachers are licensed to teach noncore courses such
as art, music, and vocational and physical education. Offering elective courses such as
these allows schools to provide core teachers with the necessary time to engage in
professional development activities such as collaborative planning and curriculum
development (Odden & Picus, 2008). Specialist teachers require an additional 20%
resource allocation, which gives each core teacher at the elementary and middle school
level one planning and collaboration period during the regular school day (Odden &
Picus). However, high schools require an additional 33% allocation of specialist teachers
to give core teachers one block for planning and collaboration and three instructional
blocks within a block schedule configuration consisting of four 90-minute periods during
the typical school day (Odden & Picus, 2008). The 33% additional allocation provides
8.0 FTE for specialist or elective teachers in the prototypical high school.
Instructional facilitators/mentors. Instructional facilitators are also referred to as
teacher mentors, coaches, or curriculum coordinators who facilitate the implementation
of school initiatives and professional development. The prototypical regular high school
includes 3.0 FTE positions for instructional facilitators and mentors (Odden & Picus,
2008). Schools can divide the responsibilities of instructional facilitators and mentors
among multiple individual teachers. The EB model prototypical high school includes a
technology coordinator in this category to meet the technology support needs associated

54
with the implementation of school improvement designs and daily maintenance of
computer systems.
Tutors for struggling students. The prototypical regular high school includes 3.0
tutors for struggling students, which translates into 1.0 certified tutor for every 100
students who are eligible to receive free and reduced-price lunch, with a minimum of 1.0
tutor per school (Odden & Picus, 2008).
Teachers for ELL students. Bilingual education teachers are specialized to
provide instruction to students for whom English is not a primary language and who
therefore struggle in the regular education classroom. The prototypical regular high
school provides an additional 1.0 FTE teacher position for every 100 ELL students
(Odden & Picus, 2008).
Extended day. The prototypical regular high school includes 2.5 FTE to
implement extended day for struggling students that reflect 1.0 teacher position for every
15 students eligible for free and reduced-price lunch (Odden & Picus, 2008). The
staffing allocation for extended day is based on research that suggests providing services
for 50% of the students who are eligible for free and reduced-price lunch (Kleiner, Nolin,
& Chapman, 2004). The cost of the FTE for each extended day teacher position is equal
to 25% of the annual teacher salary, which provides a 2.5 to 3.0 hour extended day
program five days per week (Odden & Picus, 2008).
Summer school. The prototypical regular high school includes 2.5 FTE to
provide students with summer school (Odden & Picus, 2008). The staffing allocation for
summer school is based on the premise that 50% of students who are eligible for free and

55
reduced-price lunch will provide an estimate of the number of struggling students that
requires summer school (Capizzano, Adelman, & Stagner, 2002). The number of FTE
for summer school should be adjusted over time to match the actual number of students
who are eligible for free and reduced-price lunch (Odden & Picus, 2008). Additionally,
the cost of the stipend for each FTE summer school teacher position is equal to 25% of
the annual teacher salary, which provides an eight-week program for six hours per day
(Odden & Picus, 2008).
Teachers for students with learning and mild disabilities. The EB Model
advocates early and collaborative intervention with a census approach to determining
resources for special education students with lower-cost and high-incidence disabilities
(Odden & Picus, 2008). The prototypical regular high school includes four positions for
the census funding of special education teachers; thus services are provided at a standard
rate for all schools and districts based on the premise that the incidence of various
categories of disabilities is equal for all schools and districts.
Teachers for students with severe disabilities. The EB model encourages
clustering services to increase cost effectiveness where feasible, such as in large school
districts, for students who are severely emotionally disturbed (ED), severely mentally
and/or physically handicapped, and children on the spectrum of autism (Odden & Picus,
2008). Furthermore, the EB Model suggests state reimbursements to districts for 100% of
costs associated with students who are severely disabled, minus Federal Title VIB funds.
Substitutes. The Evidence-Based Model recommends an additional allocation for
substitutes when teachers require sick leave for one or two days, long-term illness,

56
pregnancy, or other reasons. The prototypical regular and alternative high school
includes a substitute allocation based upon 5% of previously discussed teacher positions
including core, specialist, tutors, ELL extended day, summer school, mildly and severely
disabled, gifted education teachers, and instructional facilitators and mentors (Odden &
Picus, 2008).
Pupil support staff. Personnel for student support, including guidance
counselors, social workers, psychologists, and therapists, facilitates the implementation
of schools’ student support and family outreach strategies (Odden & Picus, 2008). The
prototypical regular high school includes 5.4 FTE for pupil support staff, which reflects
1.0 FTE for every 100 students characterized as living in poverty plus 1.0 guidance staff
for every 250 students (Odden & Picus, 2008).
Other noninstructional aides. The EB Model includes staff to relieve classroom
teachers from nonteaching duties that detract attention from their primary instructional
focus. The prototypical regular high school recommends 3.0 FTE aide positions for
lunchroom duty and playground supervision (Odden & Picus, 2008).
Librarians and media specialists. The EBM recommends that each regular high
school have a librarian and library technician to operate the library system.
Principal (administrator). The Evidence-Based Model strongly recommends that
each school site or “school unit” has a principal (Odden & Picus, 2008, p. 118). The EB
Model suggests subdividing schools with large enrollments into separate school units
within the site (Odden & Picus, 2008). For the prototypical regular high school unit with
an enrollment of 600 students from grades 9–12, the EB Model recommends 1.0 FTE

57
licensed principal. Furthermore, the EB Model recommends a full-time principal for high
school units with as few as 150 students (Odden & Picus, 2008). The model prorates the
1.0 FTE principal position, either up or down by pupil counts, for schools larger than 600
students and smaller than 150, respectively (Odden & Picus, 2008).
School site secretary. The EB Model includes secretarial support for
administrators and teachers to provide administrative and clerical help in the school
office and with paperwork and other operational tasks. The prototypical regular high
school includes 3.0 secretary positions that can include a 12-month position for the senior
secretary and nine-month positions for clerk/typist staff (Odden & Picus, 2008).
Professional development. The purpose of professional development is to
improve teachers’ competencies in delivering high quality instruction. Because schools
receive funding to implement varying degrees of professional development, the
Evidence-Based Model suggests a reallocation of existing professional development
resources to support the improvement of instruction in core academic areas including
math, science, reading/language arts, and history (Odden & Picus, 2008). The model
separates professional development expenditures into several components: teacher time
for professional development, on-site coaches, collaborative planning time, and training
and conference expenses.
The first component of professional development involves time during the
summer for intensive training institutes. The Evidence-Based Model recommends 10
days dedicated to intensive training before the start of the school year (Odden & Picus,
2008). The prototypical high school calculates the cost of 10 days of professional

58
development by dividing the average teacher salary by 200 to determine the daily rate,
then multiplying that amount by 10, the number of professional development days. The
average teacher salary therefore changes to include the 10 days of professional
development.
The second component of professional development is on-site coaching for all
teachers. The prototypical high school recommends one coach for every 200 students,
which is the same as the 3.0 instructional facilitators/mentors mentioned above for the
prototypical high school of 600 students (Odden & Picus, 2008). The on-site coaching
helps teachers incorporate professional learning into their instructional practice.
The third component of professional development is collaborative planning and
preparation periods. These time blocks provide teachers with opportunities during the
school day to improve instruction. The prototypical high school addresses this need
through the school-level personnel resources provided for specialist teachers to create
collaborative planning and professional development.
The last component of professional development includes other related expenses,
including trainers, materials, equipment and facilities, travel and transportation, and
tuition and conference fees. The prototypical regular and alternative high school includes
$50 per pupil for these professional development expenses (Odden & Picus, 2008).
Funding for professional development is reflected as a dollar category resource allocation
in table below.
Technology and equipment. The prototypical regular and alternative high school
includes $250 per pupil for technology to purchase, maintain, and upgrade copiers,

59
computer hardware, and medium-priced software for administrative and financial systems
(Odden & Picus, 2008). The dollar-per-pupil allocation for technology will also provide
access to distance-learning and web-based testing programs and a computer for every
administrator, teacher, and key school-level staff while allowing a computer for every
four students (Odden & Picus, 2008).
Instructional materials. Instructional materials include up-to-date, accurate
textbooks and instructional supplies such as math manipulatives and science supplies to
demonstrate the relevant application of concepts within regular instruction and extra help
support for struggling students. The prototypical regular and alternative high school
allocates $175 per pupil for instructional materials, which includes $25 per pupil for
library text and electronic services and $150 for textbooks and consumable instructional
materials to support regular instruction and extra help strategies for most nonsevere
special education students who are covered by special education funds (Odden & Picus,
2008). The dollar-per-pupil amount for instructional materials is not adjusted for school
or district size, based on the assumption that contract decisions occur at the state level.
Student activities. The Evidence-Based Model suggests dollar-per-pupil
resources to pay teachers small stipends for supervising extra-curricular programs such as
clubs, sports, and band. The prototypical regular and alternative high school includes
$250 per pupil for student activities (Odden & Picus, 2008). Table 2, below, presents the
Evidence-Based Model’s recommendations for adequate resource levels necessary to
implement research-based strategies to improve student performance at prototypical high
schools.

60

Table 2

Adequate Resources for Prototypical High Schools
School Element Prototypical High School
SCHOOL CHARACTERISTICS
School configuration 9–12
School size 600
Full-day kindergarten NA
Number of teacher workdays 200 teacher workdays, including 10 days for
intensive training
% disabled 12
% poverty (free and reduced-price lunch) 50
% ELL 10
% minority (non-White) 30
STAFFING CATEGORY
Core teachers 24
Specialist teachers 8.0 (33% more)
Instructional facilitators/mentors 3.0
Tutors for struggling students 3.0 (one for every 100 poverty students)
Teachers for ELL students 0.60 (Additional 1.0 teachers for every 100
ELL students)
Extended-day 2.5
Summer school 2.5

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Table 2, Continued
STAFFING CATEGORY
Learning and mildly disabled students Additional 4.0 professional teacher
positions
Severely disabled students 100% state reimbursement minus federal
funds
Teachers for gifted students $25/student
Vocational education No extra cost
Substitutes 5% of previous personnel items
Pupil support staff 5.4 (1.0 for every 100 poverty students
plus 1.0 guidance/250 students)
Noninstructional aides 3.0
Librarians/media specialists 1.0 librarian
1.0 library technician
Principal 1.0
School site secretary 3.0
Professional development Included above: Instructional coaches,
planning and prep time, 10 summer days
Additional: $50/pupil for other PD
expenses—trainers, conferences, travel,
etc.
Technology $250/pupil
Instructional materials $175/pupil
Student activities $250/pupil

1 Plus 1:7 Model. This section presents the Evidence-Based (EB) 1 Plus 1:7
Model alternative high school and identifies the adequate resources necessary to
implement research-based improvement strategies to improve student performance in
alternative high schools. To determine adequate staffing levels for alternative learning
environments, the Evidence-Based Model includes the 1 Plus 1:7 Model, which presents

62
a slight deviation from the prototypical high school that is applied to regular high
schools. The alternative high school includes a 1.0 administrator position priced at the
level of an assistant principal. In addition to personnel for administration, the alternative
high school includes 1.0 full-time equivalent (FTE) position for every seven alternative
school students to encompass all staff at the site, including core teachers, specialist
teachers, instructional facilitators/mentors, tutors for struggling students, teachers for
ELL students, extended day, summer school, teachers for disabled students, substitutes,
pupil support staff, noninstructional aides, librarians, and a school site secretary.
Furthermore, the alternative high school includes the same dollar category allocations as
the prototypical high school for elements of the education program, including
professional development, technology, instructional materials, and student activities.
Table 3, below, shows the Evidence-Based 1 Plus 1:7 Model recommendations for
adequate resource levels necessary to implementing research-based strategies to improve
student performance within alternative learning environments.
Table 3

Adequate Resources for Alternative High Schools (1+1:7 Model)
School Element Alternative High School
(1+1:7 Model)
PERSONNEL RESOURCES
Teaching and support staff (1.0 teachers for every 7 alternative education
students)
Administrator 1.0 (priced at the level of an assistant principal)

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Conclusion to Literature Review
This literature review aimed to highlight the issues that emerge when
implementing alternative education as a solution to the problem of students dropping out
of our nation’s public schools. Historically, the early years of the alternative education
movement, across the United States and specifically in Hawaii, set the stage for trends we
see in today’s public schools and districts, including funding challenges, program
diversity, innovation, and choice in alternative learning environments. This chapter also
discussed research issues in alternative education and the evaluation of alternative
learning environments in Hawaii. Lastly, the chapter presented the theoretical
frameworks used to frame the problems examined in the study and to inform research
methodology and design, which are discussed in more detail in the next chapter.

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CHAPTER THREE:
RESEARCH METHODOLOGY
The purpose of the study was to compare the impact of resource reallocations and
budget cuts on alternative learning environments (ALEs) and regular high schools using
the Evidence-Based Model (Odden & Picus, 2008) and the 10 Strategies Framework for
Doubling Student Performance (Odden, 2009). To facilitate analysis of student
characteristics, personnel resource levels, site-level programming, and student
performance within different learning environments, the study examined the following
research questions:
• How do the characteristics of at-risk students in alternative learning
environments (ALEs) compare to those enrolled at regular high schools?
• How do resource adequacy levels at ALEs compare with regular high schools,
in relation to the Evidence-Based Model, and change as a result of resource
reallocations of the weighted student formula?
• What factors influence educational leaders’ decisions to allocate resources to
support struggling students?
• How effective are ALEs and regular high schools at helping struggling
students achieve the state’s performance goals?
This chapter begins with a discussion of the research design of the study. The unit of
analysis in the investigation is the school site; therefore, this section will also describe the
population of programs for at-risk students from which the sample in the study was
selected. The later sections of the chapter will discuss the instrumentation and methods

65
for data collection and analysis used to identify key findings among the learning
environments examined in the study.
Research Design
To examine the research questions, the study was designed as a mixed-method
case study. To validate findings, the study applied methodological triangulation. The
following approaches built upon the strengths of multiple designs and minimized the
limitations of using any one approach in isolation: naturalistic inquiry, quantitative and
qualitative data, and statistical and content analysis. The study aimed to compare
learning environments as they currently existed within the public school system in
Hawaii and was, therefore, considered naturalistic inquiry rather than experimental. The
researcher made no attempt either to manipulate or control variables in the study through
random sampling or to assign schools or districts to treatment and control groups. The
study also examined a combination of quantitative and qualitative data collected through
documents, websites, and oral interviews. Statistical analysis was conducted using
statistical software and content analysis based upon grounded theory.
This mixed-method approach was the most appropriate in comparison to
alternatives associated with basic/applied research, summative evaluation, or action
research. Basic/applied research approaches such as pure hypothetical-deductive
approaches and experimental designs were less appropriate for the study. The purpose of
the study was to produce findings that specific stakeholders, primarily educational
practitioners, could use to make decisions that may increase adequacy and accountability
for implementing extra help strategies to support struggling students. Rather than call

66
attention to societal concerns, as would be the case with applied research, the study
assumed that students’ academic failure and school dropout are societal issues worthy of
investigation. Unlike basic research, the study was not looking to generate new theories
or test existing theories that would generalize across time and space, nor did it attempt to
contribute to fundamental knowledge and theory. Moreover, no attempt was made to
manipulate or control variables in the study through random sampling or by assigning
some schools and districts to implement alternative learning centers while others served
as a control group. The case study design was designed using naturalistic inquiry
approaches because the aim was, again, to compare programs, as they currently existed
within the public school system.
Summative evaluation and action research approaches were less appropriate for
the study. The primary purpose of the study was not to evaluate outcomes to make a final
judgment of the overall effectiveness of the alternative learning centers. The purpose of
the study was, ultimately, to increase adequacy of support and to improve the
implementation of strategies and services for struggling students; therefore the study
focused on comparing programming and student performance at school sites. Without
knowledge of implementation, the results from summative evaluations, even pure
hypothetical-deductive approaches to evaluation, provided results that left school and
district administrators without the data necessary to inform decisions and take strategic
action. The results from an evaluation that focused on summative outcomes also lacked
valuable information about the factors that contributed to the observed outcomes—or

67
lack of outcomes. Furthermore, the purpose of the study was not to solve a specific
problem, as would be the case with action research.
A major strength of the multi-method qualitative approach was that it allowed
methodological triangulation to build on the strengths of each approach and minimize the
limitations of any approach used in isolation (Patton, 2002). A limitation of the study
involved the validity of findings and the inability to extrapolate them to other settings and
time periods, let alone make generalizations from the sample to the larger population of
alternative learning centers. No attempt was made in the formative evaluation to
incorporate any degree of control in the study, or to generalize findings beyond the
setting in which the evaluation took place.
Population
The study focused on the population of learning environments in Hawaii that
served struggling, at-risk students. As more traditional school environments have
become less capable of helping all students learn, the demand for quality alternative
schools and programs has increased. The regular school setting does not work for all
students, as reflected in national and local dropout rates. Policy 2131 in Hawaii
reinforced that some students have had difficulty succeeding in traditional learning
environments because of academic, social, emotional, or behavioral difficulties. In light
of current economic challenges in education, the lack of reliable funding sources for
alternative education has threatened the consistent identification of students, the quality
of evaluations of student achievement, and the survival of alternative schools and
programs altogether.

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Policy 2131 identified two models for alternative learning environments to serve
students in Hawaii who were not succeeding in traditional learning environments and
were at risk of dropping out of school. The two models included the Alternative
Learning Center (ALC) and the Special Motivation Class (SMC). ALCs served students
who tended to experience more academic, social, emotional, or behavioral difficulties
than their peers in SMCs. SMCs were often located on campus, whereas ALCs were
housed either on or off campus. During 2000–2001 school year, students were served by
a total of 103 alternative learning sites: 70 SMCs, 20 on-campus ALCs, and 13 off-
campus ALCs.
Alternative learning environments across Hawaii experienced an increase in
ESLL, SPED, and Free Lunch student populations, as did the general education
population, during the three school years, from 1998–1999 to 2000–2001. About 9% of
the at-risk student population was also identified as ESLL, about 21% as SPED, and
about 24% was on the free and reduced-price lunch program. During the three school
years, from 1998–1999 to 2000–2001, the top seven ethnic groups represented in the at-
risk population remained consistent; they were part Hawaiian, Filipino, Other, Caucasian,
Japanese, Samoan, and Hawaiian.
Sample
The study compared two high school sites on the island of Oahu, including a
district-administered alternative learning environment (ALE) and a non-ALE, or regular
high school setting, both of which received public funding from the state and served
struggling students in grades 9 through 12 who were at risk of school failure and of

69
potentially dropping out of school. The learning environments examined in the study
were selected using a method of purposeful, criterion-referenced sampling. The sample
selection process involved identifying common characteristics of the population of
alternative learning environments in Hawaii, then selecting a sample with characteristics
that aligned with the population. Although the small sample size limited the potential to
generalize findings to other settings beyond the scope of the study, the criteria to select
the sample for the study included the following: (a) administration and operation, (b)
grade levels served, and (c) funding sources.
The strength of using purposeful, criterion-referenced sampling was to reduce
variation in the sample to match the characteristics of the larger population of learning
environments that served at-risk students. According to Lehr and Lange (2003), local
schools and districts administered most alternative schools nationwide, with fewer
governed by community-based organizations or private companies. Therefore, the
sample focused on school- and district-administered learning environments, rather than
the array of programs administered by other public or private entities or postsecondary
institutions, such as charter schools, community schools for adults, or juvenile justice
agencies. The ALE examined in the study was classified as an alternative learning center
(ALC).
Additionally, most district-administered alternative schools and programs across
the nation focused on the secondary level, particularly serving grades 9–12 (NCES,
2010). In Hawaii, an evaluation conducted on publicly funded alternative programs
across the state found that high absenteeism and failure in academic courses were the two

70
most prevalent factors for identifying at-risk students, and that the top three grade levels
for absenteeism, academic failure, and grade levels behind were grades 9, 10, and 11, as
compared to grades 6 through 8 (Datawise, 2003). Consequently, the sample consisted of
learning environments that served students in grades 9–12, instead of the range of grade
levels served in alternative programs, beginning from early childhood through secondary
education. Lastly, Lehr et al. (2009) maintained that state-level funding was most often
identified as the primary source for alternative education nationwide. The sample,
therefore, focused on schools and programs that were publicly funded by the state,
excluding those funded by nonprofit organizations, private schools, or private companies.
Instrumentation
The instruments used to collect data in the study included a document request list,
data collection protocol, data collection codebook, and an open-ended interview protocol.
The document request list identified sources of personnel data, such as staff lists and
master schedules, and also de-identified student data. To examine how resource use
patterns changed as a result of the state’s budget reduction, the study focused on
documents over a two-year period, including school year 2010–2011 and 2001–2012.
The study requested two different types of staff lists: school staff lists and district staff
lists. School staff lists included the full-time equivalent (FTE) status and position titles
of individuals who worked in the physical space of the school. Complex area staff lists
provided data on the FTE status of district employees who provided direct services to
schools, such as psychologists and diagnosticians, but did not appear on the school staff
roster. To also study the characteristics of at-risk students who were served in an ALE

71
and a regular high school, the study requested data on current student enrollment,
students’ eligibility for free and reduced-price lunch, students’ ethnic backgrounds, and
the number of students who participated in tutoring, extended day, and summer school.
Furthermore, the study collected data on student attendance, graduation/completion, and
dropout rates to compare leaders’ perceptions of the effectiveness of alternative learning
environments with student performance data.
Used together, the data collection codebook and data collection protocol
facilitated the collection of data on resource use patterns at school sites. The codebook
provided descriptions of each item on the protocol. To examine how resource use
patterns in an alternative learning environment (ALE) and a regular high school aligned
with the Evidence-Based Model, the instruments gathered data on full-time equivalents
for core academic teachers, specialist and elective teachers, library staff, student services,
and administration. In the study, attention focused on examination of full-time
equivalents (FTE) to implement extra help strategies including certified teachers and
noncertified aides for tutoring, extended day program, and summer school.
The study also used an open-ended data collection protocol to gather data through
interviews. The protocol contained three sections. The first section aimed to describe
what and how extra help strategies were provided to struggling students at school sites as
part of the implementation of Policy 2131. Strategies included tutoring, extended day,
and summer school. To examine the factors that went into leaders’ resource decisions,
the second section focused on data regarding the resources allocated to support the
implementation of strategies, and how resource decisions were made and impacted by the

72
state’s budget reductions. The third section focused on finding out about leaders’
perceptions of the effectiveness and value of alternative learning environments in
supporting struggling students.
The interview protocol was designed using what Patton (2002) has referred to as a
standardized open-ended interview approach. Although the standardized open-ended
interview approach and the closed fixed response approach both require the interviewer
to outline important issues in advance and to develop questions for the interview, the
standardized open-ended approach was the most appropriate in comparison to the others
for several reasons.
The interview guide approach allowed the interviewer to make decisions about
the wording and sequence of questions to pursue certain topics in greater depth, to close
gaps in data, and to allow the interview to remain fairly informal and conversational.
Both the interview guide approach and the standardized open-ended interview ensured
that the interviewer established priorities to focus the interview and use time efficiently;
however, the standardized open-ended interview approach involved deciding the exact
wording and sequence of each question in advance. Therefore, the interview guide
approach allowed for greater flexibility and individualization. At the same time, it could
have produced a wide array of responses from different perspectives that could have
reduced the comparability of responses. Important topics may have been inadvertently
excluded. Greater flexibility could have also caused more information to be collected
from some interviewees than from others.

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The closed, fixed response interview approach included questions and response
categories that were also determined in advance. Responses were fixed, which meant
that respondents were forced to choose from a set of predetermined categories. The
closed, fixed-response interview approach allowed the interviewer to ask many questions
in a short period of time. A limitation of the closed, fixed response interview, however,
was that it restricted breadth and depth by limiting responses to predetermined categories.
Respondents could have perceived fixed-response approaches as mechanistic and
impersonal in forcing them to fit their responses into predetermined categories. Limiting
the choices in the interview could have distorted, if not eliminated altogether, the
underlying meanings respondents were attempting to communicate.
The standardized open-ended approach was, therefore, more appropriate than the
interview guide approach and the closed, fixed response approach for several reasons.
First, the detailed planning before conducting standard open-ended interviews ensured
that each interviewee was asked the same questions, in the same order, and in the same
manner, including probing questions—with the exception of instances where some
responses to questions may have already emerged in previous open-ended questions, in
which case the questions would not be repeated. Each person interviewed received the
same line of inquiry and answered the same questions, increasing the comparability of
responses. Second, the standardized open-ended approach also systematized data
collection for each respondent and maximized time by making data analysis easier, as
responses to the same question could be located quickly and clustered based on similarity
so that data could be easily compared and aggregated later. This approach made it

74
possible to compare responses across sites, which was especially useful with the multisite
design of the study. Third, the standardized open-ended approach was more appropriate
than the closed, fixed response approach in that it reinforced the core principle of
qualitative interviewing, which is to invite respondents to express their own perspectives
and understandings in their own voice.
Data Collection
The research study involved collection and examination of quantitative and
qualitative data on resource allocation, district and school enrollment, and student
performance. Data collection for the study occurred over a period of two months in Fall
2011. The study did not collect information about individual subjects, but rather content
about the practices of alternative learning environments.
The study examined quantitative data collected through district and school
documents and websites. Documents and records offered unobtrusive methods of
gathering data and promoted the relevance of interview questions based on existing
knowledge; however, some of these materials could have been difficult to access,
incomplete, or inaccurate. Therefore, the study also included oral interviews to increase
the validation of findings.
Interviews were conducted with district and school leaders who determined the
resource allocations for ALEs and regular high schools, such as the school principals or
area superintendents. Oral interviews occurred within short time frames between a half
hour to an hour. The interview planning process began with the identification of key

75
informants at school sites who were willing to provide informed responses to interview
questions. Then, potential respondents were contacted and interviews were scheduled.
During the interview, questions were asked using the interview protocol. The
interviewer recorded notes as the respondent answered questions with the intent of
managing questions that had already been asked and of capturing the perspective of the
interviewee as accurately as possible. Development of a system of abbreviations
facilitated note taking. It was important to use quotations only when recording verbatim
the words of the respondent. In this case, it was acceptable to interrupt and request that
the interviewee repeat his or her response and confirm the accuracy of the notes. Note
taking required the interviewer to separate description from interpretation by using
brackets to distinguish personal insights, feelings, and interpretations from the actual
responses of the interviewee. Recording these analytical thoughts played an important
role in data analysis later on.
After the interview, it was important to review notes to be sure they made sense,
and to schedule sufficient time to check back with the interviewee regarding any items
that required clarification. This reflection period was also an opportunity to capture
information about the context in which the interview took place, including the physical
setting, location, respondent’s reactions to questions, and rapport with the interviewee. If
clarification was unattainable, the areas of ambiguity become missing data.
The strength of conducting interviews was that they captured how others
experienced the world in their own words. A limitation was that interview data became
distorted by factors such as personal biases, the mood of the respondent, rapport with the

76
interviewee, and recall error on the part of the interviewer. Therefore, data from
documents validated qualitative data gathered through interviews. For instance, the study
compared leaders’ perceptions of the overall effectiveness of alternative learning
environments by comparing them to student performance data.
Data Analysis
The study involved both statistical and content analysis. Data analysis and the
development of findings and conclusions occurred in the Spring 2012. The study
involved statistical analysis (using Microsoft Excel and basic calculation) to validate
findings. The software provided the tools to perform statistical analysis on quantitative
data and to create visual representations from student participation and performance data.
De-identified demographics were cross-analyzed solely for the purpose of adding texture
to data on alternative learning environments. Quantitative data analysis included the
following questions:
• How does the number of FTE allocated to the ALE and regular high school in
SY 2010–2011 and 2011–2012 (to implement extra help strategies) align with
the Evidence-Based Model?
• How does the number of FTE allocated to the ALE and regular high school (to
implement extra-help strategies) in SY 2010–2011 compare that in to SY
2011–2012?
• What do student performance data suggest about the effectiveness of an ALE
compared to that of a regular high school?

77
• How do the attendance rates of at-risk students in the ALE compare to those
in the regular high school?
• How do the dropout rates of students in the ALE compare to those in regular
high school?
• How do the graduation/completion rates of students in the ALE compare to
those in regular high school?
• How does the number and percentage of at-risk students served in an ALE
compare to those in a regular high school/small school?
• How does the number of at-risk students who receive tutoring in an ALE
compare to that in a regular high school/small school?
• How does the number of at-risk students who participate in extended day in an
ALE compare that of a regular high school/small school?
• How does the number of at-risk students who are enrolled in summer school
through an ALE compare to that of a regular high school/small school?
• How does the number and percentage of at-risk students in the ALE who are
eligible for FRL compare to those of the regular high school/small school?
• How does the number and percentage of at-risk students who are classified as
minority compare to those in the regular high school/small school?
Content analysis facilitated the identification of themes in interview data that
examined the value and effectiveness of extra help strategies and the resource allocations
necessary to support struggling students. Qualitative data analysis included the following
questions:

78
• How do the positions and services being cut in an ALE as a result of the
budget reduction compare to those in a regular high school (counseling
services, tutoring, class sizes, etc.)?
• How do changes in the roles and responsibilities of personnel in the ALE
compare to those in the regular high school?
• How does the rationale of leaders’ for changes to the roles and responsibilities
of personnel at an ALE compare to that in a regular high school?
• How do the perceptions of leaders in ALEs about the overall effectiveness of
ALEs compare to those of leaders in regular high schools?
• How do the factors and rationale that influence education leaders’ decisions to
allocate resources for extra help strategies in an ALE compare to those in a
regular high school/small school?
Content analysis was conducted in the study using grounded theory as a
framework to identify patterns in qualitative data and then to turn those patterns into
meaningful categories and themes. Grounded theory was applied in the study to ensure
systematic rigor in the overall design of the study and in data collection and analysis.
The process of applying grounded theory to data analysis began with describing the
dimensions of data, and then conceptualizing data into categories based on those
dimensions. The aim of grounded theory was to build theory rather than to test theory.
Grounded theory involved both inductive and deductive reasoning. Inductive
analysis involved identifying concepts from data. One way to conduct inductive analysis
was to distill patterns as they were expressed in participants’ responses and then present

79
them back to the people who articulated them, to confirm accuracy. These patterns were
referred to as indigenous concepts. An alternative method when categories and labels did
not emerge from the data gathered involved the analyst identifying them—a procedure
referred to as sensitizing concepts. This approach provided a reference point for the
analyst to begin organizing data. It was important for the analyst to remember that the
intent was to understand the perspective of respondents and to construct meaning from
data rather than to simply identify or impose a concept or label.
The inductive aspect of data analysis focused on convergence or figuring out how
data fit together. Identifying convergence involved searching for recurring patterns in the
data. The patterns were sorted into categories. There were two ways to judge categories,
internal homogeneity and external heterogeneity. Internal homogeneity looked for the
degree to which the data held together, converged into a category, or came together in a
meaningful way. External heterogeneity looked at the extent to which distinct
differences emerged between categories. Additionally, checking for divergence involved
proposing new information that fit, and then verifying that it existed. Divergence also
included exploring connections between data that did not fit within emergent categories.
Analyzing for divergence continued until all information was exhausted and new sources
led to redundancies. The analysis of convergence and divergence did not necessarily
occur in a linear, mechanical fashion. During this phase, the analyst revisited the data
and the classification system to verify the categories and organization of data into
categories.

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Once categories were formed, the deductive aspect of grounded theory was
applied to the development of hypotheses about the attributes or characteristics that
distinguished categories from one another. Grounded theory culminated with theory
development. After establishing patterns, themes, and categories, data analysis shifted to
a more deductive approach in terms of testing the appropriateness of the patterns, themes,
and categories. Concepts become the elements upon which to build theory. This step
began the process of identifying indigenous typologies or classification systems
comprised of the categories. Indigenous typologies helped to clarify what was important
to the people and programs being studied, because organizations and programs developed
and used language that was meaningful and practical to them. The relationships between
categories helped to organize them into larger classification systems. After indigenous
typologies were identified, analyst-constructed typologies were formed using categories
already identified. At this point, the task was to make explicit those patterns that may not
be recognized by those who were studied. Notably, at this phase, careful consideration
was given to be sure not to identify patterns that did not really exist in the data.
The qualitative findings were then judged for their substantive significance. One
way significance was tested was to revisit categories to be sure they were conceptualized
in ways that made logical sense. Second, feedback from those who participated in the
study was considered. These tests proved consensual validation of findings.
Discrepancies could have given way to further questions to investigate. Notably,
qualitative analysis can result in errors when an analyst decides that findings are not

81
significant when they were, or conversely, attributes significance to results that are not
supported.
A strength of grounded theory as a framework for conducting qualitative analysis
is that it invites feedback from participants to validate patterns and themes; however, a
limitation of this approach to data analysis is that the analyst can impose his or her
constructs upon the data rather than allow the patterns and themes to emerge. In this
study, the data analysis process accounted for this limitation through the use of a
combination of inductive analytical approaches and quantitative statistical analysis.
Conclusion to Research Methodology
The study was designed as a mixed-method case study that applied a purposeful,
criterion-referenced approach to selecting a sample that matched the characteristics of the
larger population of alternative learning environments. Data was collected at alternative
learning centers and the Department of Education through oral interviews, documents,
and records, then analyzed using statistical software and content analysis based upon
grounded theory to identify patterns that revealed themes and categories with which to
compare alternative programs. Instrumentation to collect and analyze data involved a
document request list, data collection protocol, data collection codebook, and an open-
ended interview protocol. Although the naturalistic inquiry approach of the study did not
produce findings that could be generalized to the larger population of alternative learning
environments, a major strength of the study was the triangulation of methodology and
interview approaches that could increase validity by leveraging the positive elements of
each approach while minimizing the limitations of any single approach.

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CHAPTER FOUR:
FINDINGS
This chapter presents the analyzed results and themes that emerged from data
collected from individual school sites. Both of the sites were located on the island of
Oahu and publically funded as part of the Department of Education in Hawaii. The ALE
school was a district-administered program that served approximately 260 students
referred from six different high schools. At the time of the study, the school had been
started 45 years previously and resided on the north side of central Oahu in a wooden
trailer-style building on a separate campus from the schools it served. The regular high
school, on the other hand, was newer, built just over a decade before, and served
approximately 2,100 students within a developing community in west Oahu. The regular
high school also implemented an academy for at risk-students. For purposes of
comparing alternative learning environments and regular school settings, the chapter
analyzes data from the leadership academy separate from that of the regular high school.
Further information about each site can be found in the case studies in the appendix of
this study.
The results and themes presented in this chapter reflect data collected through
documents, websites, and oral interviews, gathered in order to compare school
characteristics, resource allocation patterns, student performance, and each site. The
interviews conducted in the study occurred over a two-month period in Fall 2011 and
involved district and school leaders who determined the resource allocations for these
sites. The aim of the interviews was to collect data to understand the school

83
improvement process at the sites, how resources were allocated to support improvement
strategies, and the factors that influenced resource decisions. The interviews were
conducted using an open-ended data collection protocol and averaged about an hour. The
protocol used during the interviews is also presented in the appendix. Furthermore,
interviews were recorded and then transcribed. Upon completion of each interview,
follow-up communication occurred to clarify data gathered from participants. The audio
transcriptions were analyzed for themes that are presented in case studies and subsequent
sections of this chapter. The interviews of the complex area superintendents were
conducted at their offices, located at their respective central district offices.
Overview of School Sites and Participants
This section describes several key factors, including the school sites, participants
in the study, and the researcher’s personal impressions from the site visitation, to provide
an understanding of the context in which interview data were collected and analyzed. A
total of four interviews were conducted, two of them with site leaders and the other two
with complex area superintendents who oversaw the districts within which the school
sites were located.
The superintendent of the district-administered ALE school was in her seventh
year as superintendent of the complex area and previously spent much of her career in
secondary education—as a principal of a middle school for six years and also as a high
school vice principal. She supervised principals from 14 elementary schools, three
middle schools, one high and intermediate school, two high schools, and one adult
school. On the other hand, the superintendent who oversaw the complex area within

84
which the regular high school was located was, at the time of this study, the interim
superintendent and had previously been a principal of a middle school for seven years.
Her complex area included 11 elementary schools, two middle schools, one intermediate
school, and two high schools. The interviews conducted with site-leaders were
conducted at their respective schools.
The principal was in his third year at the regular high school. For over 10 years,
he had served as an administrator at the high school level, with the exception of his
previous position as principal of an elementary school. The interview with the high
school principal was conducted after school. Therefore, only a few students remained on
campus in common areas near the main office. The campus was clean, and the clerical
staff was very friendly and welcoming to visitors. In the waiting area of the main office,
attractive bulletin boards communicated the school vision as well as the activities
occurring within the school community. The interview took place in the principal’s
office, which was spacious, decorated with school awards, and well lit with natural
sunlight coming through windows. Several comfortable chairs fronted the principal’s
desk, which faced the door, allowing visibility of visitors through the glass window in the
door.
At the ALE school, the interview was conducted with the site coordinator, who
served the dual-role of overseeing the administration of the program and providing
counseling for students at the site. She had worked at the ALE school for over 30 years,
since 1980, which provided her with much credibility and rapport with students and
families, as well as members beyond the school community. The interviews at the ALE

85
school occurred over the course of several visits to the site during the school day. On
each occasion, the school was bustling with students. The interview was conducted in a
conference room with two doorways along opposite walls. Because the room contained
no actual doors, the setting offered little privacy, as students and adults walked by during
the interview; however, the physical set-up of the site also allowed for many observable
interactions between students and adults, clearly showing that teachers and staff knew
students and their families on a personal level. These rich interactions demonstrated a
strong culture that emphasized caring relationships as a core value that promoted student
success at the program.
Frameworks for Data Analysis
This section presents the theoretical frameworks applied in the study to compare
alternative learning environments (ALEs) and regular high schools. As mentioned
previously, the 10 Strategies Framework and Evidence-Based Model were used as lenses
to analyze how resources were being used at schools to deliver quality educational
programming to help all students achieve state standards and graduate from high school.
This section will revisit the two frameworks that will facilitate analysis of the results and
themes that emerged from data before presenting the key findings of the study.
10 Strategies for Doubling Student Performance
The 10 Strategies Framework for Doubling Student Performance (Odden, 2009)
and the Evidence-Based Model (Odden & Picus, 2008) were used as lenses to analyze
data and highlight significant themes and results. Synthesis of data in this chapter is
organized into sections that begin with the research question under examination, followed

86
by a discussion of the significant results and themes in relation to the research question.
The chapter ends with a summary of results and themes that discusses the overall findings
in relation to each research question in the study. Additional data gathered through
interviews and school documents are included in case studies presented in Appendices H
and I and also in a resource-level comparison table later in the chapter.
The 10 Strategies Framework was developed by Allan R. Odden and described in
10 Strategies for Doubling Student Performance (2009). Odden and his staff at the
University of Wisconsin-Madison offices of the Consortium for Policy Research in
Education (CPRE), with the consultation of Lawrence O. Picus and Associates,
conducted research on districts and schools that showed dramatic improvement in student
achievement. The 10 Strategies Framework was developed through a rigorous process of
distilling themes from the growing body of research on schools and districts that had
dramatically improved student achievement. The research conducted in these proven
high-performing schools and districts revealed similarities regardless of school
demographics, location, or size (Odden, 2009). The framework from Doubling Student
Performance includes the following 10 Strategies (Odden, 2009):
1. Analyze student performance data
2. Set ambitious goals
3. Implement an effective curriculum and instruction program
4. Use formative assessments to make data-based decisions
5. Implement ongoing professional development
6. Use instructional time efficiently and effectively

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7. Provide extra help for struggling students
8. Create a collaborative and professional school culture
9. Use research-based and proven strategies
10. Develop talent and human capital
Importantly, these strategies represent actions that schools have direct control over,
unlike broader social issues, such as family poverty, lack of healthcare for children and
families, and community safety, or educational ones, including lack of funding and
student demographic factors, and No Child Left Behind and faults in the state assessment
system. To implement these strategies requires resources, along with a budget plan that
determines the necessary resources to adequately implement the strategies and double
student performance (Odden, 2009).
Evidence-Based Model
The Evidence-Based Model, developed by Odden and Picus (2008), offers an
approach to school finance that links spending with student performance (Odden & Picus,
2008). In this section, the Evidence-Based (EB) Model is used as a framework to
compare the school characteristics and resource levels of the regular high school and
alternative programs in school year 2010–2011. A number of states, including Kentucky,
Arkansas, Arizona, Wyoming, and Washington, have implemented the Evidence-Based
Model to calculate adequate spending levels for public schools and districts (Odden &
Picus, 2008).
The EB model calculates the total cost to operate a school, whether elementary,
middle, or high school, by determining and aggregating the adequate dollar amounts

88
within a comprehensive set of staffing categories needed to implement a research-based
instructional program, such as the “10 Strategies,” to improve student performance
(Odden & Picus, 2008). Personnel resources in the prototypical school are organized into
staffing categories and calculated based on school characteristics discussed above. The
staffing recommendations of the Evidence-Based Model are presented as personnel and
dollar category levels within a prototypical high school and alternative high school
(Odden & Picus, 2008). Adequate staffing levels for schools that differ in size from the
prototypical high school are calculated by prorating personnel resource levels to school
characteristics included in the EB school. The Evidence-Based Model’s prototypical
high school includes the following staffing categories: core teachers, specialist teachers,
instructional facilitators/mentors, tutors for struggling students, teachers for ELL
students, extended day, summer school, teachers for students with learning and mild
disabilities, teachers for students with severe disabilities, substitutes, pupil support staff,
other noninstructional aides, librarians and media specialists, principal (administrator),
school site secretary, professional development, technology and equipment, instructional
materials, student activities.
Results Research Question 1
Research Question One asked: How do the characteristics of at-risk students in
alternative learning environments (ALEs) compare to those enrolled at regular high
schools? In response to this question, the Evidence-Based (EB) Model was used to
compare the characteristics of the regular high school and alternative programs in school
year 2010–2011. The Evidence-Based Model’s prototypical high school identifies a set

89
of school characteristics that include school configuration, school size, percent disabled,
poverty, English language learners, and minority. The prototypical high school is based
upon a school configuration that serves 600 students in grades 9–12 and is separated into
two major sections, including school characteristics and personnel resources.
Two key results emerged in relation to this research question and highlighted the
similarities among the learning environments in the study. The first result called
attention to finding that the percentages of minority students in alternative programs were
far greater than in the prototypical high school, whereas the second result showed much
lower percentages for the populations of low-income students and ELL students. This
section will also discuss the significance of the results in relation to other research
questions that have implications for closer examination of models for allocating resources
to schools and achievement gaps related to race and poverty levels. The results were
identified by examining percentage differences and ranges in relation to student
characteristics in the EB prototypical high school including students who were classified
as ELL, disabled, minority, and eligible for free and reduced-price lunch at specific
school sites and within their respective school districts.
The first result was that student populations at the three sites were similar to one
another and significantly greater than the percentages of minority students included in the
EB school. These results are significant because similarities among characteristics better
lend themselves to comparisons of resource allocations and student performance in the
learning environments. According to data gathered from school records at each site, the
range in percentages for minority students was 5.4 among the regular high school

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(86.6%), ALE school (92%), and leadership academy (90%). These data show the
similarity among the three settings and also points toward the relative differences from
the 30% minority student population of the prototypical high school.
The percentages of minority students were significantly greater than not only the
EB prototypical high school within each of the three settings, but also among the other
high schools within their respective districts. This finding is significant because it
illustrates that the minority student populations are not only unique to the sites in the
study but also similar among other high schools. Based upon school records, the
percentages of minority students at the sites in the study, including the regular high
school, leadership academy, and ALE school, were 56.6%, 60%, and 63.9% greater than
the EB school. From a district-level perspective, the relative amount of minority students
at other high schools in their respective districts were 63.9% and 53.1% greater than the
EB Model for the regular high school and the ALE school (State of Hawaii, 2011).
The second result was that the percentages of low-income students and ELL
students enrolled at each site remained somewhat similar but consistently less than the
prototypical high school, with characteristics of each corresponding school. According to
data gathered from state- and school-level records, the largest range among
characteristics examined was 10.4, which encompassed the percentages for low-income
students between the regular high school (29.6%), ALE school (39%), and leadership
academy (40%). Greater similarities existed among the percentages of ELL students, as
illustrated in the range of 2.4, between the regular high school (2.4%), ALE school (0%),
and leadership academy (0%). Although the student populations at the sites were not as

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similar in this respect—as compared to their minority student population—these results
are important to note because ethnicity and socioeconomic classifications are key
indicators of students’ success in school and also contribute to the racial and poverty
achievement gaps present in Hawaii, as well as in many districts and schools across the
U.S (McKinsey & Company, 2009). Furthermore, they are important in light of the
implementation of a weighted-pupil program in Hawaii that provided funding to public
schools based upon student classifications such as poverty and ELL status.
The percentages of low-income students were not only similar, but also
consistently less than the prototypical high school at each site in the study and among
other high schools within their respective districts. For example, the percentages of
students eligible for free and reduced-price lunch at the sites, including the regular high
school, ALE school, and leadership academy, were 20.4%, 11%, and 10% less than the
50% low-income student population included in the prototypical high school. Within a
broader context, the average percentages of low-income students among high schools in
the same district as the regular high school were 46.58%, equivalent to 3.42% less than
the EB school (State of Hawaii, 2011). At the same time, the percentages of low-income
students enrolled at other high schools in the same district as the ALE school was 30.3%,
or equal to 19.7% less than the EB school. Whether examining the percentages of school
populations classified as low-income within the context of individual schools or among
other high schools in the districts within which they are located, the relative amount of
low-income students was below what is identified in the EB Model prototypical high
school.

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Likewise, data suggested that the relative amounts of ELL students within each
learning environment were similar and consistently less than the prototypical high school,
as applied to each site and also within the context of the districts in which they were
located. For instance, the percentages of ELL students at the sites, including the regular
high school, ALE school, and leadership academy, were 7.6%, 10%, and 10% less than
the 10% ELL student population included in the EB school. Neither the ALE school nor
the leadership academy served ELL students in school year 2010–2011, the year from
which data in the study was drawn. In relation to student populations of high schools
across their respective districts, percentages of ELL students in the districts where the
regular high school and ALE school were located were equivalent to 3.88% and 5.5%
less than the prototypical high school (State of Hawaii, 2011). Personnel resources for
ELL teachers were not allocated to either site. Table 4, below, shows a comparison of
high school and alternative program characteristics in relation to the Evidence Based
(EB) Model Prototypical High school for school year 2010-2011.

93
Table 4

Comparison of High School and Alternative Program Characteristics with Evidence
Based (EB) Model Prototypical High School (SY 2010-2011)
School Element
EB Prototypical
High Schools
Regular
High School ALE School
Leadership
Academy
School configuration 9-12 9-12 9-12 9-12
School size 600 2,107 261 181
Number of teacher
work days
200 teacher
workdays,
including 10 days
for intensive
training
180 days (10 PD days
cut by state furloughs)
180 days (10 PD
days cut by state
furloughs)
180 days (10 PD
days cut by state
furloughs)
% Disabled (IEPs) 12% 11.5% 17% 9.4%
% poverty (free and
reduced-price lunch)
50% 29.6% 39% 40%
% ELL 10% 2.4% 0% 0%
% Minority (non-
White)
30% 86.6% 92% 90%
* % At-Risk N/A 9.5% 100% 100%
* not included as school characteristic in the Evidence-Based Model prototypical high school.
Summary for Research Question 1
The two findings for this research question suggested that the sites in the study
were more similar than they were different. First, the percentages of the student
populations classified as minority within the three learning environments and their
respective districts were similar and also significantly greater than the EB prototypical
high school. Second, although the percentages of low-income and ELL students at the
sites were similar, they were consistently less than the EB prototypical high school when
applying the framework to individual school sites and the districts within which they
were located. The emergence of these similarities was an important part of the

94
foundation to make subsequent comparisons between sites regarding resource use
patterns and student performance results. The findings also have implications for
examining poverty and racial achievement gaps and the limitations of the current
weighted pupil program used to allocate funding to schools.
Results Research Question 2
Research Question 2 asked: How do resource adequacy levels at ALEs compare
with regular high schools, in relation to the Evidence-Based Model, and change as a
result of resource reallocations of the weighted student formula? In response to this
question, two types of Evidence-Based (EB) Models are used in this section to compare
the resource levels of the regular high school and alternative programs in school year
2010–2011. First, the EB prototypical high school is used to compare the resource levels
of all three learning environments included in the study. Then, the EB 1 Plus 1:7 Model is
used to compare the resource levels of the ALE school and the leadership academy at the
regular high school. Although school sites allocate resources for part-time teachers
(PTTs), data analysis will focus primarily on full-time equivalents (FTEs) and dollar
category resources.
Two key results emerged in relation to this research question. The first result was
that the pattern of staffing levels at the sites was less than the recommended adequacy
levels of the EB Model prototypical high school and the 1 Plus 1:7 model. The second
result concerned the resource decisions that district and school leaders made in their
efforts to continue supporting programs for at-risk students in order to sustain them. The
section will also discuss how leaders’ commitment has resulted in few changes in

95
resource levels that impact at-risk students despite the reallocation of resources that has
occurred in light of statewide budget cuts.
The first theme is that most personnel levels for each of the learning environments
are less than recommendations of EB, with the exception of several staffing categories at
the regular high school, in which resource allocations are the same or greater than EB.
Only in several instances were personnel resource levels the same as or greater than what
EB recommends. For instance, the 28.0 FTE that the regular high school allocated for
specialist teachers was the same amount that the EB model recommended for a school
with the same characteristics as the high school. At the high school, the staffing level of
ELL teachers was 100% greater than EB, and the dollar category allocation for teaching
positions for gifted students ($25/pupil) was 212% greater ($78/pupil). The dollar
category allocation for gifted education is calculated by converting the 3.0 FTE, priced at
$55,000 per position, to the dollar-per-pupil amount. At the ALE school, the resource
allocation level for special education teachers was 17.6% greater than EB, compared to
the regular high school (86% less) and the leadership academy (100% less). Notably,
none of the sites allocated FTE positions for tutors; however, they still offered tutoring at
each site through the allocation of part-time teacher (PTT) positions and existing
personnel to provide tutoring. Furthermore, the overall staffing level for specialist
teachers, including the high school and both alternative programs, was the most closely
aligned to EB, with a range of 16.7, among all three learning environments including the
high school (same as the EB), ALE school (14.3% less), the leadership academy (16.7%
less).

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Interestingly, the resource levels of the regular high school as a whole were also
less than adequacy recommendations, but most aligned to EB compared to the other two
sites. Of the four staffing categories that were either the same as or greater than
recommendations of EB, three were associated with the high school. In other words, the
traditional high school had staffing categories that were closest in alignment to EB. Data
revealed only three instances in which the ALE school or leadership academy had
staffing levels that were most aligned to EB in comparison to other sites. For instance,
the resource allocation levels for special education teachers was most aligned to EB at the
ALE school (17.5% greater), compared to the regular high school (86% less) and the
leadership academy (100% less). Another example was that the staffing levels for
instructional materials were most aligned to EB at the ALE school (35.6% less),
compared to the regular high school (46% less) and the leadership academy (100% less).
Lastly, the resource allocation for pupil support, or the high-risk counselor position at the
leadership academy (30% less), was the closest in alignment to EB, compared to the ALE
school (50% less) and the regular high school (46% less).
Furthermore, based upon the Evidence-Based (EB) 1 Plus 1:7 Model for
alternative high schools, the personnel resource allocations at the ALE school likewise
remain significantly lower than adequate levels included in EB recommendations. The
personnel resources allocations for the leadership academy (70.4% less) was slightly
more aligned to EB recommendations than the ALE school (73.7% less). Furthermore,
the leadership academy (6.0 PTTs) allocated nearly twice as many part-time teachers as
the ALE school (3.1 PTTs) to provide struggling students with additional instructional

97
support. The dollar category resources—professional development, technology,
instructional materials, and student activities—remained the same in the EB 1 Plus 1:7
Model for the ALE as they were in the EB prototypical high school. Notably, the
leadership academy was located on the campus of the regular high school, which allowed
it to share FTE resources, including administration and secretarial support, as well as
dollar category resources, including professional development and instructional materials.
Table 5 shows a comparison of resource levels of the ALE school and the academy with
the Evidence-Based (EB) 1 Plus 1:7 Model alternative school for school year 2010-2011.
Table 5

Resource-Level Comparison of ALE School and Leadership Academy with Evidence-
Based (EB) 1 Plus 1:7 Model Alternative School (SY 2010–2011)

ALE School Leadership Academy
Staffing
Category
EB 1+1:7 Model
School with ALE
School
Characteristics
(261 students)
Actual EB 1+1:7 Model
School with Academy
Characteristics
(181 students)
Actual
Teaching and
support staff
37.0 10.0

(3.1 PTT)
26.0 7.0

(6.0 PTT)
Administrator 1.0 0.0 1.0 1.0

Theme two posits that the decisions of district and site leaders to continue
supporting programs for at-risk students—despite budget reductions and resource
reallocations—served as evidence of their commitment to help all students succeed and
functioned as a primary reason why resource use patterns remained stable and unchanged
for the leadership academy and ALE school between school year 2010–2011 and 2011–

98
2012. Continued implementation of the ALE school and strategies to help struggling
students was a priority for administrators who were finding ways to sustain staffing
resources by reallocating resources when necessary to be sure resources were not taken
away from at-risk students. At the ALE school, site and district leaders also lobbied at
the state legislature and had met with success in obtaining the necessary personnel
resources to sustain programming for at-risk students within the district. However,
several changes in staffing patterns at the high school had occurred: a 25% decrease in
FTE for vice principals 4.0 to 3.0 positions, and a 12.5% increase for special education
part-time teachers from 7.0 to 8.0 positions and for ELL teachers from 0.0 to 1.0 FTE.
Lastly, the dollar category resources for professional development increased by 64.8%,
from $47,750 to $135,482. Especially notable was that some changes increased the level
of resources in some categories; however, increases can be the result of the reallocation
of existing resources rather than of increases in the school’s overall budget.
Summary for Research Question 2
Two significant findings emerged from data in relation to this research question.
First, the personnel resource levels at each of the sites were consistently less than
recommendations in the Evidence-Based Model, with the exception of several instances
in which resource allocations were the same or grater than the EB school with
characteristics of each corresponding school. Second, despite the state’s recent budget
reduction and reallocation of resources associated with the implementation of the
weighted student formula, district and site leaders were doing everything in their power
to ensure that these programs continued to receive the necessary resources to continue

99
serving at-risk students. This aim is important, because the school leaders were making
decisions that clearly showed they were rising above factors beyond their control—such
as limited funding—and, instead, reasserting their commitment to ensure that all students,
especially those who have historically struggled, experience success in school.
Themes Research Question 3
Research Question Three asked: What factors influence education leaders’
decisions to allocate resources to support struggling students? In response to this
research question, the 10 Strategies framework for Doubling Student Performance
(Odden, 2009) is used to highlight major themes that represent the research-based
practices that influence resource decisions for at-risk programs. Not all strategies are
commonly implemented by all of the learning environments examined in the study.
Therefore, the data collected through interviews and documents revealed evidence of the
common approaches sites have used to address the problem of student failure and dropout
and also the implementation of several strategies including Strategy 1 (analyze student
performance data), Strategy 3 (implement an effective curriculum and instruction
program), Strategy 7 (provide extra help for struggling students), and Strategy 8 (create a
collaborative school culture). This section will discuss several themes that emerged upon
examining the factors that influence the resource decisions leaders make. The first theme
addresses the current reality in schools with students at-risk of academic failure and of
potentially dropping out. The second and third themes will highlight the benefits for
students and teachers alike when implementing strategies that target the development of
basic skills in reading and math.

100
Theme one is that there were, indeed, students who were struggling and on the
verge of dropping out of school, and therefore needed help. According to the
Superintendent’s Report (State of Hawaii, 2011), the dropout rate in Hawaii was 16.6%
in school year 2009–2010. This statistic is significant; the problem is very real and
requires an urgent implementation of strategies to provide struggling students with the
additional support they need to achieve state standards and ultimately graduate from high
school. Data from school year 2010–2011 showed that the ALE schools served 261
students, and that the leadership academy served 181 students—equivalent to
approximately 10% of the total student population at the regular high school.
Theme two is that schools were taking action to provide additional support for at-
risk students and, more importantly, that students were taking advantage of the extra help
being provided. Notably, schools were using their limited resources to implement
educational programming and services that includes extra help strategies for struggling
students that reinforced the achievement of standards by focusing on improving students’
basic skills in reading and math. At the two sites, an average of 181 students participated
in tutoring, and 122 were in the extended day program. Table 6, below, illustrates the
enrollment at each site and also the enrollment for tutoring, extended day, and summer
school.

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Table 6

Student Enrollment for Extra Help Strategies (SY 2010–2011)
Extra Help
Strategy
ALE
High School
Regular
High School
Enrollment
(# at-risk served)
261 (261) 2,107 (181)
Tutoring 261 100
Extended Day 210 34
Summer School NA 33

Furthermore, although none of the sites allocated full-time equivalents (FTEs) to
provide tutoring, teachers at the ALE school provided tutoring to all students in basic
skills before and after school to reinforce the reading and math skills taught during the
regular class period. Similarly, the regular high school provided tutoring for all students
as well as specialized math tutoring to students who did not meet basic levels of
proficiency on math assessments. The sites also implemented extended day programs,
some of which incorporated online software to provide credit recovery to help students
earn the necessary credits to graduate on time. Notably, these extra help strategies were
designed to help students not only get caught up with their credits to graduate, but also
focus on developing the basic skills in reading and math that are necessary to meet high
academic standards. The high school also offered summer school as an option beyond
the regular school year.
Each of the sites implemented an effective curriculum and instruction program
that focused on the basic skills—an important factor because basic skills establish the

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foundation for developing higher order skills and for improving student achievement of
rigorous state standards as well. This opportunity also demonstrated that teachers
maintained the same high expectations for at-risk students as they did for students in the
regular school setting. The ALE school classroom teachers used direct instruction to
develop students’ reading and math skills across content areas. Also, the high school
implemented an array of school-wide reading and math interventions, some of them
implemented through direct instruction and some delivered through online curriculum.
The math department at the high school especially intensified its efforts to help students
through pullouts that targeted the students with the greatest needs, as reflected in
quarterly assessments.
Theme three is that the school-wide effort to support struggling students also
meant promoting teachers’ professional and leadership learning. Each site created a
collaborative and professional school culture. Although the implementation of these
strategies focused on improving student learning, they also promoted learning for those
who were charged with orchestrating the moving pieces of the school improvement
processes. This commitment is important because schools, if anything else, are learning
organizations, which means that adults must continue to learn in order to have any chance
at being successful in promoting learning in their students. At the ALE school, teachers
collaborated with colleagues to analyze student performance, discussed student progress
in different subjects, and identified ways to improve instruction and increase alignment in
curriculum. The high school implemented professional learning communities (PLCs) in
grade-level teams and career-focused academies, in which teachers constructed new

103
knowledge about their students performance based on data analysis, and then applied that
understanding to deprivatize their practice and inform improvements in their classroom
instruction. Furthermore, the high school had structures in place that promoted
collaboration with feeder schools to identify at-risk students moving up to the high
school. In this way, programs for at-risk students could serve as a model for
collaboration among adults.
The implementation of PLCs gave way to another theme common to the sites: the
analysis of student performance data. This step is important, because student
performance data can be used to inform improvements in classroom instruction and in the
implementation of school-wide interventions and strategies. For instance, the high school
used the Standards-Based Change process to collect and analyze student performance
based on test scores from the Hawaii State Assessment (HSA) and formative
assessments. Teachers used the data not only to adjust their classroom practice, but also
to determine which students need continued help and to match them to the most
appropriate support available. The ALE school also used data on individual students to
tailor instruction as well as to determine counseling supports to meet individual needs.
Lastly, a key factor that influenced leaders’ decisions to allocate resources to help
at-risk students was that the programs in place to support them actually showed positive
results, as discussed in more detail in the following section. The graduation rates at the
sites were especially high, evidence in itself that these programs were addressing the aims
for which they were designed: to keep students in school and help them earn high school
diplomas.

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Summary for Research Question 3
Several factors influenced the educational leaders’ decisions to allocate resources
to struggling students: First, the problem of students failing and dropping out of school;
second, the sites examined in the study demonstrated significant efforts to address the
issue through the implementation of strategies designed to improve students’ basic skills
in reading and math; third, efforts by teachers and school leaders to support at-risk
students promoted the development of their own professional and leadership learning
through collaboration around student performance data. These findings are important
because they demonstrate that the schools were taking steps to meet the academic needs
of students for which the regular school environment has proven ineffective, and in the
process are finding ways to leverage these efforts to promote adult learning.
Results Research Question 4
Research Question Four asked: How effective are ALEs and regular high schools
at helping struggling students achieve the state’s performance goals? Data to address this
research question was primarily collected from school-level documents of student
performance. This data showed that the three sites examined in the study were effective
at helping students to graduate, and at keeping them in school and persisting toward
graduation. This section will discuss the overall effectiveness of the learning
environments in relation to the state’s goals for graduation, attendance, and dropout rates.
All the sites in the study met the state’s graduation target of 80% in school year
2010–2011. This finding is significant because a primary reason why alternative
programs were first created was to address the problem of students falling behind in

105
credits and dropping out of school. The at-risk students enrolled at the leadership
academy and ALE school could graduate with a regular diploma rather than a
nonstandard high school diploma or certificate of completion. The sites not only met the
goal for graduation but they also exceeded the graduation target by 17.4% to 13%
between the regular high school (97.4%), the ALE school (93%), and the leadership
academy (97%). Notably, the graduation rates used in the study reflected the number of
seniors who completed the required coursework for graduation. The graduation rates
were not based on the four-year Adjusted Cohort Graduation Rate currently required by
the United States Department of Education (USDOE). If the cohort methodology were
applied to the 97.4% graduation rate at the regular high school, the graduation rate would
instead be 86.6% of the 432 freshmen entering in school year 2007–2008. The
calculation for the adjusted graduation rate included students who graduated on time from
their freshmen class and students who transferred into the school during the four-year
period. Nevertheless, the regular high school still met the state’s goal for graduation
using the cohort method.
The dropout rates show that the sites were effective in keeping kids in school.
The dropout rate is based on the four-year Adjusted Cohort Graduation Rate, which
includes students who transfer to the school or the state during the four-year period
beginning when they start their freshman year. The dropout rate at the ALE school was
1% in school year 2010–2011, and at the leadership academy and regular high school, the
dropout rates were 4% and 10.8%, respectively. With regard to attendance, only the
leadership academy met the state’s goal of 95%— a particular concern because

106
attendance is important to success in school. When students do not attend school, they
fall behind in their schoolwork, making it difficult for them to complete the necessary
assignments to earn credits. Once this setback occurs, students will likely begin to fail
classes and fall behind in credits. However, this pattern did not emerge with the sites
examined in the study. Despite attendance rates at the regular high school (93.7%) and
ALE school (91%) being below the state target, the data show that students were
nonetheless persisting and graduating from high school. Table 7, below, compares the
performance of students at the regular high school and alternative program sites in school
year 2010–2011.
Table 7

Comparison of Student Performance at High School and Alternative Program Sites
(SY 2010–2011)
Student
Performance
Indicators
Regular High
School %
ALE
School %
Leadership
Academy
%
Graduation Rate 97.4 93 97
Attendance Rate 93.7 91 95
Dropout Rate 10.8 1 4

Summary for Research Question 4
The findings for this research question revealed two ways that efforts to
implement additional support for struggling students produced positive results. First,
graduation rates at each site exceeded the state’s graduation target. Second, data show
that in spite of modest levels of performance with regard to attendance rates, the

107
programs were effective in keeping at-risk students from dropping out of school and
persisting toward a high school diploma. These findings are significant evidence of the
effectiveness of these programs at meeting the challenge of addressing student failure and
dropout, the primary reason for which they were initially developed.
Summary of Findings
A total of nine key findings emerged from the study. This section will summarize
the nine key findings identified through data analysis within the context of the four
research questions. Results and themes that emerged from data analysis presented in
previous sections, using the Evidence-Based Model (Odden & Picus, 2008) and the 10
Strategies Framework for Doubling Student Performance (Odden, 2009), are also
highlighted in this section to serve as evidence to validate each finding.
Research Question 1
Research Question One asked: How do the characteristics of at-risk students in
alternative learning environments (ALEs) compare to those enrolled at regular high
schools? The two findings for this research question focused on the relationships
between the Evidence-Based Model’s prototypical high school and the similarities in
student populations among individual school sites and the districts in which they were
located. Similarities are important to strengthen later comparisons of resource levels and
student performance among different learning environments.
Finding one. The percentages of minority students at the high schools in the
study were similar and significantly greater than the EB school—not only at each site but
also among the other high schools in their respective districts. Among the percentages of

108
minority students at each site, the range was 5.4 between the regular high school (86.6%),
ALE school (92%), and leadership academy (90%). In relation to the EB Model, the
regular high school, leadership academy, and ALE school had minority student
populations that were 56.6%, 60%, and 63.9% greater than the EB prototypical high
school. Furthermore, the districts in which the regular high school and ALE school were
located served populations of minority students that were 63.9% and 53.1% greater than
the EB Model.
Finding two. The percentages of low-income students and ELL students were
somewhat similar at each site but consistently less than the prototypical high school
within the context of individual high schools and the larger school districts in which they
were located. The range of percentages of low-income students was 10.4 among the
regular high school (29.6%), ALE school (39%), and leadership academy (40%). With
regard to the percentages of ELL students at each site, the range was 2.4 between the
regular high school (2.4%), ALE school (0%), and leadership academy (0%). Further
comparison with the prototypical high school showed that the student population
classified as low-income at the regular high school, ALE school, and leadership academy
was 20.4%, 11%, and 10% less than the prototypical high school. Within a broader
district-level context, the average percentages of low-income students among the high
schools within the districts where the regular high school and ALE school were located
were 3.42% and 19.7% less than the EB school. Similarly, the population of students
classified as ELL at the regular high school, ALE school, and leadership academy were
7.6%, 10%, and 10% less than the prototypical high school. In relation to other high

109
schools in their respective districts, the relative levels of ELL students in the districts in
which the regular high school and ALE school were located were 3.88% and 5.5% less
than the EB school.
Research Question 2
Research Question Two asked: How do resource adequacy levels at ALEs
compare with regular high schools, in relation to the Evidence-Based Model, and change
as a result of resource reallocations of the weighted student formula? The two findings
for this research question focused on the how the resource adequacy levels at different
sites aligned with the Evidence-Based Model’s prototypical high school and EB 1 Plus
1:7 Model for alternative learning environments, and how they changed as a result of the
combined impact of reallocation of resources (as part of the implementation of the
weighted student formula) and the state’s recent budget reductions.
Finding three. All sites in the study were resourced at levels far lower than what
is recommended by both the Evidence-Based Model’s prototypical high school and the
EB 1 Plus 1:7 Model for alternative learning environments, with the exception of several
instances. With regard to the sites that specifically served at-risk students, the ALE
school and the leadership academy, resource allocations at both sites were 100% less than
the EB prototypical high school in 10 staffing categories, including instructional
facilitators and mentors, tutors for struggling students, teachers for extended day, teachers
for summer school, substitutes, noninstructional aides, library and media specialists,
dollar-per-pupil funding professional development, technology, and student activities.

110
Similar findings of inadequate resource levels were revealed at the ALE school
and the leadership academy when applying the Evidence-Based 1 Plus 1:7 Model for
alternative learning environments. Given the enrollment of 261 students at the ALE
school, the 1 Plus 1:7 Model recommends 38.0 staffing positions, including 37.0 FTE for
teaching and support staff and 1,0 FTE for an administrator at the site. However, data
showed that only 10.0 FTE were allocated to the ALE school, including 10.0 for teaching
and support staff and 0.0 for an administrator, which is equivalent to 28.0 FTE or 73.7%
less than adequacy levels recommended by the model. Likewise, the staffing
recommendation for the leadership academy that served 181 at-risk students included
27.0 positions, 26.0 FTE of which were designated for teaching and support staff and 1.0
FTE for a site administrator. The leadership academy only allocated 8.0 FTE, which
included 7.0 for teaching and support staff and 1.0 FTE for an administrator. This
personnel resource level for the leadership academy indicated a difference of 19.0 FTE or
71.1% less than what is recommended for adequacy by the 1 Plus 1:7 Model.
There were several instances in which resource allocation met or exceeded
adequacy levels recommended by the EB Model prototypical high school. Of the four
categories that met EB adequacy levels, three were at the regular high school and one was
at the ALE school. For example, the EB recommends 28.0 FTE for specialist teachers for
a school the same size as the regular high school, which is the same amount of FTE the
regular high school allocated for specialist teachers. Of all staffing categories, staffing for
specialist teachers was the most closely aligned to the recommendations of the EB Model
across all sites in the study. The EB recommends 3.5 FTE for a school the same size as

111
the ALE school, which allocated 3.0 FTE, or 14.3% less than the staffing
recommendation for specialist teachers. For a school the same size as the leadership
academy, the EB allocates 2.4 FTE for specialist teachers. The leadership academy
allocated 2.0 FTE for specialist teachers, which is equivalent to 16.3% less than the EB
prototypical high school.
Other examples of the resource allocation levels that met the adequacy
recommendations of the Evidence-Based Model prototypical high school included
teachers for ELL students, teachers for gifted students, and special education teachers for
students with mild learning disabilities. For a school with the same number of ELL
students as the regular high school, the EB allocates 0.5 FTE for ELL teachers. The
regular high allocated 1.0 FTE for an ELL teachers, which is 100% greater that the EB
recommendation. The EB Model also recommends $25/pupil for teachers for gifted
students. The regular high school allocated $78/pupil, which is 212% greater that the EB
adequacy recommendation for that particular staffing category. Additionally, for a
school with the same number of special education students as the ALE school, the EB
recommends 1.7 FTE for special education teachers for student who have mild learning
disabilities. The ALE school allocated 2.0 FTE for special education teachers, which is
17.6% greater that the EB model.
Finding four. District and school leaders continued to help struggling students
by maintaining stability of resources and programming despite the state’s budget
reductions and reallocations—a clear demonstration of the commitment and steadfastness
of leaders to focusing on what they have control over, to making difficult decisions amid

112
competing priorities, and to fulfilling the promise of a quality education for all students,
including those who struggle in the regular school environment. Since the
implementation of the weighted student formula in school year 2005–2006, the
reallocation of resources away from these at-risk programs have threatened to eliminate
these programs, but this result has not been the case.
The personnel resource levels have largely remained the same for the ALE school
and the leadership academy between school year 2010–2011 and 2011–2012 as a result
of the state’s budget reductions. At the regular high school, the number of positions for
vice principals decreased by 25%, from 4.0 to 3.0 FTE. However, in other staffing and
dollar-per-pupil categories, resource allocation levels have actually increased. For
example, the number of ELL positions increased from 0.0 to 1.0 FTE. Professional
development resources increased from $47,750 to $135,482, which is equivalent to a
$87,732 or 64.8% increase. Notably, however, increases in some resource categories can
be the result of reallocation of existing resources, not necessarily of increases in the
school’s annual budget. Table 8, below, shows a comparison of resource levels of the
regular high school, ALE school, and leadership academy with the Evidence-Based (EB)
Model’s prototypical high school for school year 2010–2011.

113
Table 8

Resource-Level Comparison of Learning Environments with Evidence-Based (EB) Model Prototypical High School
(SY 2010-2011)
Regular High
School
ALE
School
Leadership
Academy
Staffing
Category
EB
Prototypical
High School
EB School with
Regular High
School
Characteristics
(2107 students)
Actual Difference EB School with
ALE High
School
Characteristics
(261 students)
Actual Difference EB School with
Academy
Characteristics
(181 students)
Actual Difference
Core teachers 24 84.3 57.0
(5.0
PTT)
27.3 FTE
(32.4 %
less than
EB)

5.0 (Part-
time
teachers)
10.4 3.0 7.4 FTE
(71.2% less
than EB)
7.25 4.0

(6.0
PTT)
3.25 FTE
(44.8%
less than
EB)

6.0 (Part-
time
teachers)
Specialist
teachers
8.0 (33%
greater)
28.0 28.0

(6.0
PTT)
Same as
EB

6.0 (Part-
time
teachers)
3.5 3.0 0.5 FTE
(14.3% less
than EB)
2.4 2.0 0.4 FTE
(16.7%
less than
EB)
Instructional
facilitators/
Mentors
3.0 10.5 3.0

(1.0
PTT)
7.5 FTE
(71.4% less
than EB)

1.0 (Part-
time
teacher)
1.3 0.0 1.3 FTE
(100% less
than EB)
0.9 0.0 0.9 FTE
(100%
less than
EB)

114
Table 8, Continued
Regular
High
School
ALE
School
Leadership
Academy

Staffing
Category
EB
Prototypical
High School
EB School
with Regular
High School
Charact-
eristics
(2107
students)
Actual Difference EB School
with ALE
High
School
Charact-
eristics
(261
students)
Actual Difference EB
School
with
Academy
Charact-
eristics
(181
students)
Actual Difference
Tutors for
struggling
students
3.0 (one for
every 100
poverty
students)
10.5 0.0 6.24 FTE
(100% less
than EB)
1.0
(102
students)
0.0 1.0 FTE
(100% less
than EB)
0.72
(72
students)
0.0 0.72 FTE
(100% less
than EB)

Teachers
for ELL
students
0.60
(Additional 1.0
teachers for
every 100 ELL
students)
0.5
(51 students)
1.0
(2.0 PTT)
0.5 FTE
(100% greater
than EB)

2.0 (Part-time
teachers)
0.0
(0.0
students)
0.0 NA 0
(0
students)
0.0 NA
Extended
-day
2.5 8.8 3.0

(3.0 PTT)
5.8 FTE (66%
less than EB)

3.0 (Part-time
teachers)
1.0 0.0
(3.1
PTT)
1.0 FTE
(100% less
than EB)

3.1 (Part-
time
teachers)
0.76 0.0 0.76 FTE
(100% less
than EB)
Summer
school
2.5 8.8 4.0
(4.0 PTT)
4.8 FTE (55%
less than EB)

4.0 (Part-time
teachers)
1.0 0.0 1.0 FTE
(100% less
than EB)
0.76 0.0 0.76 FTE
(100% less
than EB)

115

Table 8, Continued
Regular
High
School
ALE
School
Leadership
Academy

Staffing
Category
EB
Prototypical
High School
EB School
with Regular
High School
Characteristics
(2107 students)
Actual Difference EB School
with ALE High
School
Characteristics
(261 students)
Actual Difference EB School
with Academy
Characteristics
(181 students)
Actual Difference
Learning
and
mildly
disabled
students
Additional
4.0
professional
teacher
positions
14
(242 students)
2.0

(7.0 PTT)
12 FTE
(86% less
than EB)

7.0 (Part-
time
teachers)
1.7
(44 students)
2.0 0.3 FTE
(17.6%
greater
than EB)
1.2
(17 students)
0.0 1.2 FTE
(100%
less than
EB)

Severely
disabled
students
100% state
reimbursement minus
federal funds
NA 1.0

(3.0 PTT)
NA

3.0 (Part-time
teachers)
NA 0.0 NA NA 0.0 NA
Teachers for
gifted
students
$25/pupil $52,675 $78/pupil
($165,000
)
$53/pupil or
$112,325
(212% greater
than EB)
$6,525 $0/pupil
0.0
$25/pupil or
$6,525 (100%
less than EB)
$4,525 $0/pup
il
0.0
$25/pupil
or $4,525
(100%
less than
EB)
Vocational
education
No extra cost NA NA NA NA 0.0 NA NA 0.0 NA

116
Table 8, Continued
Regular
High
School
ALE
School
Leadership
Academy

Staffing
Category
EB
Prototypical
High School
EB School
with Regular
High School
Characteristics
(2107 students)
Actual Difference EB School
with ALE High
School
Characteristics
(261 students)
Actual Difference EB School
with Academy
Characteristics
(181 students)
Actual Difference
Substitutes 5% of previous
personnel items
NA 0.0 FTE
($68,358)
8.1 FTE
(100%
less than
EB)

($68,358
greater
than EB)
1.0 0.0 1.0 FTE
(100%
less than
EB)
0.7 0.0 0.7 FTE
(100%
less than
EB)
Pupil
support
staff
5.4 (1.0 for every
100 poverty
students plus 1.0
guidance/250
students)
14.7
(6.24 students)
8.0 6.7 FTE
(46% less
than EB)
2.0
(102
students)
1.0 1.0 FTE
(50% less
than EB)
1.4
(72 students)
1.0 0.4 FTE
(30% less
than EB)
Non-
instructiona
l aides
3.0 10.5 2.0 8.5 FTE
(81% less
than EB)
1.3 0.0 1.3 FTE
(100%
less than
EB)
0.9 0.0 0.9 FTE
(100%
less than
EB)

117
Table 8, Continued
Regular
High
School
ALE
School
Leadershi
p
Academy

Staffing
Category
EB
Prototypical
High School
EB School
with Regular
High School
Characteristics
(2107 students)
Actual Difference EB School
with ALE High
School
Characteristics
(261 students)
Actual Difference EB School
with Academy
Characteristics
(181 students)
Actual Differen
ce
Librarians/
media
specialists
1.0 librarian
1.0 library
technician
3.5 librarian
3.5 tech
1.0

(1.0 PTT)
1.5 FTE
(60% less
than EB)
2.5 FTE;
(100% less
than EB);
1.0 (PT
teacher)
0.4 librarian
0.4 tech
0.0 0.4 FTE
(100%
less than
EB)
0.4 FTE
(100%
less than
EB)
0.3 librarian
0.3 tech
0.0 0.3 FTE
(100%
less than
EB)
0.3 FTE
(100%
less than
EB)
Principal 1.0 3.5 1.0 2.5 FTE
(71.4% less
than EB)
1.0 0.0 1.0 FTE
(100%
less than
EB)
1.0 1.0 Same
as EB
School site
secretary
3.0 10.5 1.0 9.5 FTE
(90.5% less
than EB)
1.3 1.0 0.3 FTE
(23% less
than EB)
0.9 0.0 0.9 FTE
(100%
less than
EB)
Professional
development
Included above:
Instructional
coaches,
planning, prep
time, 10 summer
days
Add’l: $50/pupil
for other PD
expenses:
trainers,
conferences,
travel, etc.
$105,350 $23/pupil

($47,750)
$27/pupil
or $57,600
(54% less
than EB)
$13,050 $0/pup
il
$50/pupil
or
$13,050
(100%
less than
EB)
$9,050 $0/pupil $50/
pupil or
$9,050
(100%
less than
EB)

118

Table 8, Continued
Regular
High
School
ALE
School
Leadership
Academy

Staffing
Category
EB
Prototypical
High
School
EB School
with Regular
High School
Characteristics
(2,107
students)
Actual Difference EB School
with ALE
High School
Characteristics
(261 students)
Actual Differenc
e
EB School
with
Academy
Characteri
stics
(181
students)
Actual Difference
Tech-
nology
$250/pupil $526,750 $24/pupil
($50,000)
$226/pupil or
$476,750
(90.4% less
than EB)
$65,250 $0/pupi
l
$250/pupi
l or
$65,250
(100%
less than
EB)
$45,250 $0/
pupil
$250/
pupil or
$45,250
(100%
less than
EB)
Instructional
materials
$175/pupil $368,725 $95/pupil
($200,000)
$80/pupil or
$168,725
(46% less
than EB)
$45,675 $112/
pupil
($29,42
0)
$63/pupil
or
$16,255
(35.6%
less than
EB)
$31,675 $0/
pupil
$175/
pupil or
$31,675
(100%
less than
EB)
Student
activities
$250/pupil $526,750 $26/pupil

($55,000 is
allocated as
1.0 FTE)
$224/pupil or
$471,750
(89.5% less
than EB)
$65,250 $0/pupi
l
$250/pupi
l or
$65,250
(100%
less than
EB)
$45,250 $0/
pupil
$250/
pupil or
$45,250
(100% less
than EB)

119
Research Question 3
Research Question Three asked: What factors influence education leaders’
decisions to allocate resources to support struggling students? The three findings for this
research question emerged from comparisons of the site-level programming for at-risk
students with the 10 Strategies for Doubling Student Performance (Odden, 2009).
Overall, these findings demonstrate that schools in this study were identifying the needs
of at-risk students and addressing them in a way that benefitted not only students but also
the teachers and significant adults who supported them.
Finding five. The problem of students potentially failing and dropping out of
school, indeed, exists. In Hawaii, the dropout rate was 16.6% in school year 2009–2010
according to the 2010 Superintendent’s Report (State of Hawaii, 2011). Furthermore, the
ALE school and leadership academy served 261 and 181 at-risk students, respectively.
Collectively between the two sites, an average of 181 students received tutoring services
and 122 participated in the extended day program.
Finding six. Current supports that were in place actually helped students to
achieve standards by focusing on the development of their basic skills. The ALE school
and regular high school both provided tutoring before and after school that focused on
improving students’ reading and math skills. Extended day support at both sites also
focused on developing students’ basic skills while providing additional time for students
to complete assignments from their regular classes. In addition to general tutoring, the
regular high school provided specialized, direct instruction and implemented an intensive
pullout program that targeted students who were not performing at proficiency levels in

120
math, as reflected in quarterly assessments administered and scored by teachers
throughout the school year.
Finding seven. The implementation of strategies for at-risk students promoted
adult learning and the development of leadership capacity through professional
collaboration that involved data analysis. Data collected through interviews and school-
level documents showed that teachers were organized into professional learning
communities and engaged in analysis of student performance data to improve their
instructional practice. Knowledge constructed through data analysis also drove
refinements in the implementation of interventions and strategies discussed earlier that
were designed to improve students’ basic skills to help them achieve state performance
standards.
Research Question 4
Research Question Four asked: How effective are ALEs and regular high schools
at helping struggling students achieve the state’s performance goals? The two findings
for this research question showed that the schools that served at-risk students were
producing positive results and fulfilling the purpose for which they were developed,
which was to provide students with the skills they needed to achieve standards and earn
their high school diploma. Furthermore, the findings were significant indications that the
resources allocated to these programs for at-risk students were worth the investments.
Finding eight. Graduation rates were especially high at the schools in the study
and exceeded the state’s target. The graduation rates at the regular high school were the
highest at 97.4%, which was equivalent to 17.4% greater than the state’s 80% target for

121
graduation in school year 2010–2011. At the ALE school and leadership academy, the
graduation rates were similarly high and average, at 93% and 97%, respectively.
Finding nine. The dropout rates in the study showed that the programs were
effective at keeping students in school and helping them to graduate. For instance, the
dropout rate at the ALE school was 1% in 2010–2011. At the leadership academy and
regular high school, the dropout rates were 4% and 10.8%, respectively. Attendance
rates at the school sites were modest and did not meet the state target of 95%, with the
exception of the leadership academy, which had an attendance rate of 95% in school year
2010–2011. However, despite the attendance rates, the overall performance of students,
as reflected in dropout and graduation rates, ultimately showed that programs were
helping at-risk students stay in school and persist toward graduation.

122
CHAPTER FIVE:
DISCUSSION
The problem of students failing and dropping out of school is real and, indeed,
exists today. Findings from the study showed that approximately 10% of the student
population of the regular high school was identified as at risk, and that 261 at-risk
students were served at the ALE school in school year 2010–2011. This problem is not
new. Over a decade ago, between school years 1998–1999 and 2000–2001, an average of
17,512 out of the 81,304 secondary students in grades 6–12 were identified as at risk
(DataWise Hawaii, 2003). Even earlier, in the late 1950s and early 1960s, the issue
received national attention with the emergence of the alternative education movement in
the U.S. to help struggling students (Lange & Sletten, 2002). Hawaii was no exception.
With this same intent in mind, the Hawaii Department of Education initiated statewide
efforts in 1971 to establish alternative learning environments (ALEs) to support
struggling students through the implementation of the Comprehensive School Alienation
Program (CSAP). CSAP allocated resources directly to program sites for at-risk students,
using a form of the professional judgment approach whereby allocations were determined
at the central office level based upon such factors as the number of students served by
each site as well as student performance indicators, including graduation and attendance
rates among other considerations. However, the landscape changed dramatically for
ALEs in Hawaii with the statewide implementation of the weighted student formula in
school year 2005–2006.

123
Overview of the Study: Conclusions
As a result of the implementation of the weighted student formula, CSAP
resources that were once allocated directly to ALEs were reallocated to regular school
sites to be used at the discretion of principals as they saw fit to assist at-risk students.
Ultimately CSAP ended with the implementation of WSF. Some would argue that WSF
works against at-risk students by channeling resources away from the programs that
support them. And, as much as WSF might have threatened the existence of at-risk
programs, this result was not the case with the sites examined in the study. Therefore, the
purpose of the study was to compare the combined impacts of the WSF’s resource
reallocations and the state’s recent budget reductions on alternative learning
environments (ALEs) and regular high schools using the Evidence-Based Model (Odden
& Picus, 2008) and the 10 Strategies Framework for Doubling Student Performance
(Odden, 2009) to analyze student characteristics, resource use patterns, site-level
programming, and student performance.
To achieve the purpose of the study, the following research questions were
explored:
• How do the characteristics of at-risk students in alternative learning
environments (ALEs) compare to those enrolled at regular high schools?
• How do resource adequacy levels at ALEs compare with regular high schools,
in relation to the Evidence-Based Model, and change as a result of resource
reallocations of the weighted student formula?

124
• What factors influence educational leaders’ decisions to allocate resources to
support struggling students
• How effective are ALEs and regular high schools at helping struggling
students achieve the state’s performance goals?
This chapter will begin with a summary of findings that presents a synthesis of the main
points from the results and themes identified in Chapter Four. The following sections
will present discussions about the limitations of the study followed by implications for
various stakeholder groups to further the work of increasing equity and adequacy in
public schools.
Summary of Findings
Findings suggest that the sites in the study were more similar than they were
different. For instance, the percentages of low-income students and ELL students at each
site, and within the districts they were located, were consistently lower than the
Evidence-Based (EB) Model’s prototypical high school, whereas the percentages of
students classified as minority were significantly greater. This significant finding is
discussed in more detail later in the chapter upon closer examination of the implications
for research on the implementation of the weighted student formula. Regarding the
adequacy of resource allocations at the sites, findings revealed that staffing levels were
consistently lower than is recommended in the EB prototypical high school and the 1 Plus
1:7 model for alternative learning environments. However, since the state’s budget cuts
in Summer 2011, few changes occurred in personnel resource levels between school
years 2010–2011 and 2011–2012. Notably, the stability of resource allocations has been

125
largely due to the commitment of district and school leaders to make difficult budget
decisions amid competing priorities and shrinking budgets about how to redirect
resources back to at-risk programs. At the ALE school, site and district leaders also
lobbied for and received staffing positions directly through the legislature to ensure that
struggling students continued to have access to the support they needed to succeed in
school. Having these leaders recognize the need for such services and continue to
support these programs clearly demonstrated how they value struggling students and the
programs that support them.
Findings also suggested that programming and services for at-risk students are
valuable for two reasons. First, they are effective in promoting the learning of at-risk
students. The graduation rates at the regular high school and ALE school clearly
exceeded the target established by the state for graduation. Furthermore, dropout rates
illustrated that the sites were keeping students in school and helping them persist toward
graduation. For example, the 1% dropout rate at the ALE school was strong evidence
that at-risk students who were enrolled there remained in school rather than dropping out.
Findings also indicated that instructional programming at the sites focused on helping
students achieve the state’s academic standards by reinforcing the development of
students’ basic skills. Each site implemented common interventions and strategies across
content areas as part of classroom instruction and also via extra help strategies
implemented beyond the regular school day to improve students’ skills in reading and
math.

126
Second, the sites were designed to promote the learning of teachers who support
at-risk students. The implementation of programming at the sites was framed in ways
that facilitated professional collaboration and the development of leadership capacity
centered on analysis of student performance data. At the high school, collaboration was
embedded in the practices and organizational structure of the school. Teachers in grade-
level teams and career-focused academies analyzed data on the performance of their
students and made decisions to refine the implementation of interventions and strategies
for those who continued to struggle with skills in areas such as math. Ultimately, the
convergence of teachers’ competencies along with the conditions for collaboration
nurtured a professional culture at the site. Notably, the sites continued to demonstrate
effectiveness and add value to the learning of students and adults alike, despite the reality
that resource levels were far lower than was recommended for adequacy in the Evidence-
Based Model.
Limitations
Several factors associated with the sample size, scope, and data collection
methods limit the ability to make generalizations from the findings of the study to the
larger population of alternative learning programs across the state and outside of Hawaii.
First, a limitation was the small sample size examined in the study. All ALEs and
programs for at-risk students are feeling the financial pinch across school districts;
however, it cannot be assumed that other settings that serve at-risk students are similar to
the sites in the study. Unique contextual factors also set the stage differently for each
site. For example, a school might have a high percentage of at-risk students who are

127
classified as minority, but relative to the overall composition of the district, that statistic
might be the norm in some respects within the district—as was case with the sites
included in the study. For example, the demographics of the student population in
another district might reflect a disproportionate level of minority students in at-risk
programs compared to other student groups. Furthermore, schools and districts manage
their resources differently. The leaders in one district might decide to combine resources
to support a district-wide program such as the ALE school. In other districts, principals
might decide to address the needs of at-risk students within their own individual sites.
Other districts might implement a combination that includes both approaches, perhaps
with the support of outside service providers beyond the public education system
altogether. Also the sample selection process did not use random sampling or assigned
groupings to control variables, therefore limiting external and internal validity.
Another limitation is that the study did not examine the dollar-per-pupil amount
of funding allocated to sites through the weighted student formula. Because funding
levels were not within the scope of the study, conclusions cannot be drawn from findings
about the equity of funding levels that result from the implementation of the weighted
student formula. Therefore, analysis cannot occur regarding the extent to which the
weighted student formula increases equity among sites, particularly for students who are
classified as at risk. In light of these limitations, findings from the study by no means
suggest generalizations regarding adequacy levels beyond the sample in the study or offer
conclusions about the equity of funding levels at school sites.

128
A third limitation is the potential for interview data to be distorted by personal
biases, the mood of the respondent, politics, rapport with the interviewee, and potential
for inconsistent implementation of the interview protocol. Documents and records can be
difficult to access and might be incomplete or inaccurate. Also, the limitation of using
qualitative data analysis in the study is that the researcher/analyst can impose his or her
personal constructs on the data rather than allowing patterns and themes to emerge
naturally.
Fourth, the study used indicators such as graduation, dropout, and attendance rates
to analyze student performance. However, it is important to note that these indicators are
not proxies for learning. For example, a particular site might produce high graduation
rates, but a different picture might emerge upon closer examination of student
performance on specific state test scores. High levels of student performance as reflected
in a school’s graduation rates do not mean that students are learning.
Lastly, the Evidence-Based Model is used to determine how resources are
allocated and used at school sites through personnel allocations designated to implement
programming for students, however, does not account for caveats that ultimately impact
student learning. For example, identifying the number of full-time equivalents does not
take into consideration factors such as the effort put forth by teachers and staff members
that translates into improved student performance.
Implications
The findings of the study have implications for further work to increase equity
and adequacy in all schools. According to Odden and Picus (2008), adequacy levels are

129
important to note because positive gains in student performance cannot be expected to
occur by merely reallocating inadequate funding. Although the sites in the study were
producing results with inadequate funding, we cannot assume the same for other schools
and districts. Now is as appropriate a time as ever, with all shareholders strapped for
funding and resources, to be concerned with determining whether the investments in
schools are producing the desired student outcomes. Therefore, this section will discuss
the importance of a collective effort on the part of educational practitioners, researchers,
policymakers, and funders to ensure that schools are equitably and adequately resourced
to support the learning of all students.
Implications for Practice
An implication for practitioners, particularly for school and district leaders, is to
hold fast to their values to support all students including those who struggle in school.
As indicated by the leaders interviewed in the study, one way to value the success of
struggling students is to redirect resources to programs that prove they can consistently
increase the academic performance of at-risk students. State-level administrators also
play an important role by continuing efforts to refine data management systems that
promote early identification and intervention for struggling students and, at the same
time, facilitate data collection to support the evaluation and improvement of funding
programs. Another implication for state-level administrators is to rely on data to improve
practices that impact equity and adequacy in schools. To improve these aspects of
schooling will require the willingness of educational leaders to invest in ongoing
evaluation of the systems in place to evaluate the degree to which they increase equity

130
among public schools. The significance of such evaluation activities is that they focus on
what educators have direct control over to ensure that existing systems, such as the
weighted student formula, provide resources to students who need them and do not limit
the capacity of the system to respond to the needs of all students rather than just some.
Evaluation is particularly important considering the potential for systems to
unintentionally undermine even the most well-intended efforts to help students succeed.
Although these examples might not apply directly to the schools in the study, Odden
(2009) has enumerated several ways that school systems can work against themselves,
including implementing systems that give less funding to high-poverty districts and
schools and assign the least-qualified, least-expert, least-experienced teachers to the
toughest students (Odden, 2009).
In school year 2001–2002, the Department of Education in Hawaii engaged in an
evaluation of its budgeted alternative schools and programs to examine congruence
between programming and student achievement (DataWise Hawaii, 2003, p. i).
However, the findings presented in the report focused primarily on student performance
results and the need to further develop pre- and post-assessments that feed into larger data
management systems. The evaluation was conducted approximately 10 years ago, and in
the meantime, the weighted student formula was implemented, which significantly
changed the funding pattern for ALEs. Furthermore, the evaluation was conducted
without the use of an adequacy framework to link resource use to student outcomes.

131
Implications for Research
The findings from the study also have implications for researchers to apply an
adequacy framework to examine funding levels, resource use patterns, and—most
importantly—student learning at school sites. Further research to increase adequacy in
schools will require the application of a framework, such as the Evidence-Based Model,
to determine the extent to which funding levels from the weighted student formula and
other sources are adequate and also being used to implement research-based strategies
that improve student performance. Because all public schools are held accountable for
reaching the same student performance goals set forth by the state, resources and funding
must not only be adequate, but also equitably dispersed among schools and districts.
Therefore, another implication for research is to determine the impact of the
weighted student formula on the equity of funding to support the learning of all students.
The funding that schools receive through the weighted student formula is based on the
classifications of students into categories, including poverty level and ELL status.
Therefore, an assumption is that a group of students, whether classified as at-risk or
otherwise, with fewer ELL students and low-income students would receive less funding
from the weighted student formula than a group with higher percentages of students with
those classifications. Although many would argue that student and family demographics
are essentially beyond the control of educators and not directly actionable for schools, it
is important to recognize that the intent for considering these contextual factors is to
understand the complexity of the issue in order to identify the key levers that educators
can influence in service of improving student learning.

132
For example, findings from the study show that the population of at-risk students
at the regular high school has very few ELL students and low-income students and, at the
same time, consists of many students who are classified as minority. However, what
remains unknown is how the equity obtained through the implementation of the weighted
student formula relates to the funding levels at schools to support struggling students.
These implications do not suggest that inequities actually exist or that the weighted
student formula works against some groups of struggling students more than others, but
the issue is worth investigating to determine if similar scenarios are played out across the
district, and more importantly if monies are reaching the students who desperately need
them.
Implications for Policy and Funding
The findings of the study also have implications for policymakers and funders to
serve as advocates for struggling students who might be overrepresented in programs for
at-risk youth and whose voices are at the same time underrepresented in places such as
state legislatures, where critical decisions are made to address issues of fiscal equity and
adequacy in education. According to Odden and Picus (2008), the students who are most
harmed by inequalities and inadequacies in educational funding are from minority
backgrounds, because political factors limit their representation and influence in
legislature. These issues are important because sites in the study served populations of
at-risk students, many of whom were classified at minority, and low percentages of ELL
and low-income students, which are associated with additional funding for schools.
Because the degree to which similar student characteristics are the norm among other

133
sites and school districts has yet to be identified, it remains an important issue for
policymakers to consider as they make decisions to promote finance equity and adequacy
among all schools.
Conclusion to the Study
In sum, the implementation of the weighted student formula has tested the
commitment and resolve of leaders in education to provide all students with a quality
education—especially those students who might struggle in the regular school
environment. Findings from the study show that school and district leaders not only see
a problem, but also take responsibility for what they have control over so that they may
ensure struggling students are supported. Whether it is redirecting resources back to
programs for at-risk students or lobbying for staffing positions at the legislature, findings
reveal that resource levels have largely remained the same for at-risk programs, which is
evidence that leaders are doing everything in their power to secure resources for these
struggling students. The sense of urgency among leadership to act on behalf of the
struggling students makes clear that they deeply value these students and the programs
that support them.
The programs for at-risk students are fulfilling the purpose for which they were
developed. That school and district leaders continue to redirect resources to them gives us
reason to conclude that these programs are effective and help at-risk students to develop
the basic skills they need to achieve standards—and then go onto graduate with a
diploma. Furthermore, the fact that these programs are producing positive results in spite
of inadequate resources is a testament to the commitment and hard work of the teachers

134
and staff at the sites. The implementation of programming not only benefits at-risk
students at the sites, but also promotes adult learning through collaboration and analysis
of student performance data. Lastly, although the study is limited by the scope and
sample size of the study, findings have important implications for multiple stakeholders
whose collective efforts to increase equity and adequacy in public schools will largely
depend upon their continued commitment to all students and to investing in ongoing
evaluation using adequacy frameworks to determine the impact of funding and resource
allocation approaches on student learning.

135
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APPENDIX A:
IRB DETERMINATION OF NOT HUMAN SUBJECTS RESEARCH

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

Date: Mon Aug 15 15:54:35 2011
To: Kyle Shodai
From: Ryan Brooks
Project
Title:
_IRB Information Request - Fri Aug 5 15:44:37 PDT
2011 (IIR00001074)
The University Park Institutional Review Board (UPIRB) designee reviewed the
information you submitted pertaining to your study and concluded that the project does
not qualify as Human Subjects Research.*

This project focuses on evaluating various (school and district) alternative learning
centers (ALCs) to improve and better standardize the identification of enrollment
qualifications, equitable financial allocation and disbursement, and student
achievement results and accountability. This project is not collecting information about
the subjects, but rather content about how the various alternative learning centers'
practice. Also, de-identified demographics will be cross-analyzed solely for the purpose
of adding additional texture to the ALC's evaluation. The research activities as described
do not meet the Federal definition of a human subject and are not subject to the
requirements of 45 CFR 46 or continuing review.

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

Sincerely,

Ryan M. Brooks, M.A. Psy., IRB Administrator

143
*From 45 CFR 46.102, The Federal Regulations on Human Subjects Research

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

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

This is an auto-generated email. Please do not respond directly to this
message using the "reply" address. A response sent in this manner
cannot be answered. If you have further questions, please contact
your IRB Administrator or IRB/CCI office.
The contents of this email are confidential and intended for the
specified recipients only. If you have received this email in error,
please notify istar@usc.edu and delete this message.

144
APPENDIX B:
HAWAII DEPARTMENT OF EDUCATION APPROVAL TO CONDUCT
RESEARCH

145

146
APPENDIX C:
AGREEMENT TO PARTICIPATE IN RESEARCH

The research study is being conducted as a component of a dissertation for a doctoral
degree. The purpose of the study is to compare student performance in an alternative
learning environment (ALE) and non-ALE and to examine the factors that impact
educational leaders’ decisions to allocate resources to support struggling students amid
the state’s budget cuts. Participation in the project will consist of an interview with the
investigator. Interview questions will focus on how resources are allocated to support
struggling students. Interviews will be conducted with school and district leaders (e.g.,
area superintendents, principals, site coordinators) who make resource decisions and
oversee the implementation of extra help strategies. Data from the interview will be
summarized into broad categories. No personal identifying information will be included
in the research results. The interview should take no longer than 60 minutes.

The investigator believes there is little or no risk to participating in this research study.
However, there may be a small risk that you will experience psychological discomfort as
you participate in the interview. Participating in this study may be of no direct benefit to
you. However, results from the study will provide educational practitioners with findings
to promote adequacy of resources in schools.

Research data will be confidential to the extent allowed by law. Agencies with research
oversight, such as the University Park Institutional Review Board (UPIRB) at the
University of Southern California, have the authority to review research data. All
research records will be stored in a locked, password protected file in the primary
investigator’s office for the duration of the research project. Audio tapes will be
destroyed immediately following transcription. All other research records will be
destroyed upon completion of the project. Participation in this research project is
completely voluntary. You are free to withdraw from participation at any time with no
penalty, or loss of benefit to which you would otherwise be entitled.

If you have any questions regarding this study, please contact the researcher, Kyle Shodai
at (808) 258-1291, or kyle_shodai@notes.k12.hi.us. You may also contact the doctoral
committee chair, Lawrence Picus at (213) 740-2175 or lpicus@usc.edu. If you have any

147
questions about your rights as a research participant, please contact the University Park
Institutional Review Board at (213) 821-5276 or upirb@usc.edu.

Participant:
I have read and understand the above information, and agree to participate in this
research project.

I agree to have the interview audio recorded. ! Yes ! No

_________________________________
Name (printed)

_________________________________ ____________
Signature Date

148
APPENDIX D:
DOCUMENT REQUEST LIST

All of these documents should be for the current 2011-12 school year.

1. Staff List (School)

This list will likely include any person who works in the physical space of the school. It is
necessary to understand the full-time equivalent (FTE) status of each employee, as well as what
their job entails (for a principal or classroom teacher, this may be obvious, for special education
staff or student support staff, this is not readily clear). Some staff are paid to work less than 1.0
FTE with the school, yet are housed at the school full-time. Only the portion of the day that the
staff person provides services to the individual school should be recorded. Special education and
ELL staff, especially, may be dedicated to more than one project (e.g. 0.5 FTE reading coach, 0.5
FTE resource room). Distinguish how special education and ELL staff provide support (e.g. do
they work with an individual child or a classroom, etc.). Individuals who serve the school may
not be listed and instead are based out of the district or regional education agency (e.g. speech
therapy, visiting coaches) so you will need to ask them about these people—see below.
• Core academic teachers: mathematics, reading or English/LA, science, social studies,
foreign language
• Specialist and elective teachers: art, music, P.E./health, drama, technology, career and
technical education, drivers education, study hall, athletics
• Library staff: librarian, library media specialist, library aide
• Extra help:
o Number of certified teacher tutors, non-certified tutors
o Number of extended day teachers, extended day classified staff
o Number of summer school teachers, summer school classified staff
o Number of ELL class teachers, ELL aides
• Student services: guidance, attendance/dropout, social workers, nurse, parent
advocate/community liaison, psychologist, speech/O.T./P.T., health assistant, non-
teaching aides
• Administration: principal, assistant principal, other administrator, secretary, clerical staff,
technology coordinator, security, custodians
• Instructional facilitators/mentors
• Special Education (self contained teachers, inclusion teachers, resource room teachers,
self contained aides, inclusion aides, resource room aides)
• Teachers for gifted students

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2. Staff List (District)

A list of all district employees who do not appear on school staff roster, but who provide direct
services to schools (guidance counselors, psychologists, special education diagnosticians, etc) and
which schools they provide services to, expressed in FTE units. For instance, a special education
diagnostician who works with 3 schools might be listed three times on this sheet (0.5 FTE, 0.3
FTE, 0.2 FTE) depending upon the number of days she is allocated to the various schools. Note:
You will only be recording the proportion of FTEs that she spends providing services to the
individual school you are studying.

3. School Schedule (School)

It is helpful to have a copy of the bell schedule to talk through the amount of instructional time
for reading, math, etc.
• Total length of school day
• Length of instructional day
• Length of (mathematics, reading or English/LA, science, social studies, foreign
language) class
• Minutes per week of extended day program
• Minutes per week of summer school, length of summer school session (# weeks)

4. Academic/Financial Plans
• Consultants (School, District, and State)
i. Budgeted dollar amount for all other consultants other than professional
development contracted services.
• Professional Development Budget
i. Substitutes and Stipends (teacher time): Dollar amount for substitutes and
stipends that cover teacher time for professional development.
ii. Trainers/Consultants: Dollar amount for outside consultants who provide
training or other professional development services.
iii. Travel: Dollar amount of the costs of travel to off-site professional
development activities, and costs of transportation within the district for
professional development.
iv. Materials, Equipment, and Facilities: Dollar amount of the materials for
professional development including the cost of classroom materials,
equipment needed for professional development activities, and rental or other
costs for facilities used for professional development.
v. Tuition & Conference Fees: Dollar amount of tuition payments or
reimbursement for college-based professional development, and fees for
conferences related to professional development.
vi. Other Professional Development: Dollar amount for other professional
development staff or costs.
• Technology
• Instructional materials
• Student activities

5. School/District Records (de-identified student data)
• Current student enrollment

150
• Number of at risk students
• Number of ELL/Bilingual (at risk) students
• Number of (at-risk) students eligible for free- and reduced-price lunch
• Number of (at-risk) students with disabilities
• Number of (at-risk) students from minority backgrounds
• AYP
• Number of (at risk) students who participate in tutoring
• Number of extended day (at risk) students
• Description of extended day classified staff
• Number of school’s (at risk) students enrolled in summer school
• All (at risk) students in summer school
• Attendance data of (at risk) students
• Graduation/completion data of (at risk) students
• Dropout data of (at risk) students

6. Data on Budget Reductions/cuts
• Process for determining cuts
• Changes in staff ratios, etc.
• Loss of funding

7. Approach to dealing with categorical funds

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APPENDIX E:
DATA COLLECTION PROTOCOL

School Profile
School Name School’s State
ID Number

Address

City State Zip
HI
Phone Fax

Website

NOTES:

ADEQUACY IN EDUCATION: AN EVIDENCE-BASED
APPROACH TO RESOURCE ALLOCATION
IN ALTERNATIVE LEARNING ENVIRONMENTS
DATA COLLECTION PROTOCOL, DECEMBER 2011

152
School Contact (1)
Title
Principal
Honorific First Name
Last Name

Phone # Fax #

Email Address

NOTES:

School Contact (2)
Title

Honorific First Name
Last Name

Phone # Fax #

Email Address

NOTES:

School Contact (3)
Title

Honorific First Name
Last Name

Phone # Fax #

Email Address

NOTES:

153

District Profile
District Name

District State ID

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

Phone # Fax #

Email Address

NOTES:

District Contact (2)
Title

Honorific First Name
Last Name

Phone # Fax #

Email Address

NOTES:

154
District Contact (3)
Title

Honorific First Name
Last Name

Phone # Fax #

Email Address

NOTES:

School Resource Indicators
Current Student Enrollment

Pre-Kindergarten Student Enrollment

Grade Span

Number of At-Risk Students*
*Collect from district
Number of ELL/Bilingual Students

Number of High Mobility Students*
*Collect from district
Number of Students Eligible for Free- and Reduced-
Price Lunch (FRL)

Total Number of Special Education Students (IEPs)

Number of Special Education Students (self-contained)

Total Length of School Day

Length of Instructional Day

Length of Mathematics Class

Length of Reading or English/LA Class

155
Length of Science Class

Length of Social Studies Class

Length of Foreign Language Class

AYP

NOTES:

Core academic
teachers
(Self-contained
Regular
Education)
FTEs

Kindergarten
(Full day program)
Grade 1

Grade 2

Grade 3

Grade 4

Grade 5

Grade 6

Grade 7

156
Grade 8

Grade 9

Grade 10

Grade 11

Grade 12

English/Reading/L.A.

History/Soc. Studies

Math

Science

Foreign Language

NOTES:

Specialist and Elective Teachers
/Planning and Prep
FTEs
Art

Music

PE/Health

Drama

Technology

Career & Technical Education

157

Drivers Education

Study Hall

Athletics

Other Specialist & Elective Teachers

Other Specialist & Elective Teachers
Description:

NOTES:

Library Staff
FTEs
Librarian

Library Media Specialist

Library Aide

NOTES:

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

Non-Certified Tutors

ISS Teachers

158
ISS Aides

Title I Teachers

Title I Aides

ELL Class Teachers

Aides for ELL

Gifted Program Teachers

Gifted Program Aides

Gifted Program Funds
$
Other Extra Help Teachers

Other Extra Help Teachers Funded with Federal
Dollars:

Other Extra Help Classified Staff

Other Extra Help Classified Staff Funded with Federal
Dollars:

NOTES:

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

Special Ed. Inclusion Teachers

Special Ed. Resource Room Teacher

Special Ed. Self-contained Aides

Special Ed. Inclusion Aides

159
Special Ed. Resource Room Aides

NOTES:

Extra Help III
Number of Extended Day Students

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

Extended Day Classified Staff

Description of Extended Day Classified Staff

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

All Students in Summer School

Summer School Teachers

Summer School Classified Staff

NOTES:

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

Other Teachers

160

Other Instructional Aides

Funds for Daily Subs

$
NOTES:

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

Substitutes and Stipends (teacher time)

$
Instructional Facilitators/Coaches

Trainers/Consultants

$
Administration

Travel

$
Materials, Equipment and Facilities

$
Tuition & Conference Fees

$
Other Professional Development

$
Other Professional Development Staff
Funded with Federal Dollars:

NOTES:

Student Services FTEs
Guidance

Attendance/Dropout

Social Workers

161

Nurse

Parent advocate/community liaison

Psychologist

Speech/O.T./P.T.

Health Asst.

Non-teaching aides

Other Student Services

Description Of Other Student Services
Staff:

NOTES:

Administration FTEs
Principal

Assistant principal

Other Administrator

Description of Other Administrator:

Secretary

Clerical staff

Technology Coordinator/ I.T.

Security

Custodians

NOTES:

162

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

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

163
APPENDIX F:
DATA COLLECTION CODEBOOK

This Codebook is intended to be used for the research study Adequacy in Education: An
Evidence-Based Approach to Resource Allocation in Alternative Learning Environments.
It identifies data collection items and their definitions. This document is organized
according to the corresponding Data Collection Protocol and the web portal for data entry
(www.lopassociates.com).

I. School Profile

Each data item has a place for notes. This section is meant to be used for any
notations that you would like to record as a personal reminder. Notes fields will
not be used in data analysis.

A. School Name: In your training binder, there will be a group of schools for
which you are responsible. The school name and contact information are
located under the Schools tab.
B. School State ID: This is the identification number that the state has assigned
the school. You do not need to enter this; it has been entered for you.
C. Address Line 1: Street address of the school
D. Address Line 2: (optional) Second line of street address of the school
E. City: City of the school
F. State: “CA” is automatically entered for you.
G. Zip: Postal zip code of the school
H. Phone: Main office phone number for the school
I. Fax: Main office fax number for the school
J. Website: School’s official website

II. School Contacts

This section is for recording the contact people at the school. This will include
the principal, and most likely the secretary. Anyone else you interview should
also be recorded here. Any notes you’d like to make about this person (E.g.

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phonetic spelling of their name) should go in the notes sections, as well as what
the data source is.

A. Title: The job title of the person who you interview from the school.
B. Honorific: Mr., Mrs., Ms., Dr., Rev., etc.
C. First Name: Formal first name of school staff member (E.g. Michael instead
of Mike)
D. Initial: (optional) Middle initial of school staff member
E. Last Name: Surname of school staff member
F. Suffix: (optional) Jr., etc.
G. Phone #: Direct phone number to the school staff member
H. Fax #: Fax number for the school staff member
I. Email Address: Preferred email address of the school staff member
J. Mail Address: Street address of the contact person
K. Address Line 2: (optional) Second line of street address of the contact person
L. City: City of the contact person
M. State:
N. Zip Code: Postal zip code of the contact person
O. Zip + 4: Four digit extension of the zip code

III. District Profile

A. District Name: This is the name of the district where the school is located.
District State ID: This is the identification number that the state has assigned
to the district within which the school resides.

IV. District Contacts

This section is for recording the contact people at the district office. This will
include the superintendent, and possibly an assistant superintendent and/or
director of curriculum and instruction. Anyone else you interview should also be
recorded here. Any notes you’d like to make about these individuals (e.g.
phonetic spelling of their name) should go in the notes sections, as well as what
the data source is.

A. Title: The job title of the person who you interview from the school.
B. Honorific: Mr., Mrs., Ms., Dr., Rev., etc.
C. First Name: Formal first name of school staff member (E.g. Michael instead
of Mike)
D. Initial: (optional) Middle initial of school staff member
E. Last Name: Surname of school staff member
F. Suffix: (optional) Jr., etc.
G. Phone #: Direct phone number to the school staff member
H. Fax #: Fax number for the school staff member

165
I. Email Address: Preferred email address of the school staff member
J. Mail Address: Street address of the contact person
K. Address Line 2: (optional) Second line of street address of the contact person
L. City: City of the contact person
M. State: “WY” is automatically be entered for you.
N. Zip Code: Postal zip code of the contact person
O. Zip + 4: Four digit extension of the zip code

V. School Resource Indicators

School resource indicators should be collected for the 2009-2010 school year.
Enter personal notations pertaining to the data in the yellow notes fields.

A. Current Student Enrollment: Headcount of students enrolled at the school on
the day of the site visit minus any pre-kindergarten students.
B. Pre-kindergarten Student Enrollment: Headcount of students enrolled in any
pre-kindergarten programs at the school on the day of the site visit. These
students should not be included in the previous category, Current Student
Enrollment. Make sure to also ask this question at secondary schools.
C. Grade Span: Range of grades that the school provides instruction in. (E.g. K-
5)
D. Number of ELL/Bilingual Students: As of the day of the site visit, the number
of students eligible for services as an English language learner (ELL) as
defined by the federal No Child Left Behind Act of 2001
E. Number of Students Eligible for Free- or Reduced-Price Lunch (FRL):
Number of enrolled students who are eligible for the federal free- and
reduced-price lunch program.
F. Total number of Special Education Students (IEPs): As of the day of the site
visit, number of students in the school with an Individualized Education
Program (IEP) indicating their eligibility for special education services. (This
will most likely be a larger number than the number of students who are in a
self-contained special education classroom.) Does not include gifted and
talented students.
G. Number of Special Education Students (self-contained): Number of students
in the school with an Individualized Education Program (IEP) indicating their
eligibility for special education services.
H. Total Length of School Day: Number of minutes per day that students are
required to be present at school. If multiple grade spans are present for
different amounts of time, report the average length. (e.g. If the school day
begins at 8:30am and ends at 3:15pm, then the total length of the school day is
405 minutes.)
I. Length of Instructional Day: Number of minutes per day that students are
present for instruction. This information should be available from the school
bell schedule or a school staff member. Subtract recess, lunch, and passing

166
periods time from the total minutes in the school day. This calculation is
different from how the state measures the “instructional day.” (E.g. If the
length of the school day is 405 minutes, and the students have 20 minutes for
lunch and 25 minutes for recess, then the length of the instructional day is 360
minutes.)
J. Length of Mathematics Class: Number of minutes of mathematics class
periods per day. These include periods when students are specially grouped
for extended mathematics instruction. Report an average per day length.
K. Length of Reading/English/LA Class: Number of minutes of reading, English,
and language arts (LA) class periods. These include periods when students
are specially grouped for extended literacy instruction. (E.g. reading, writing,
comprehension) Report an average per day length.
L. Length of Science Class: Number of minutes of science class periods per day.
These include periods when students are specially grouped for extended
science instruction. Report an average per day length.
M. Length of Social Studies Class: Number of minutes of social studies and
history class periods per day. These include periods when students are
specially grouped for extended history or social studies instruction. Report an
average per day length.
N. AYP: This is a measure as to whether the school made Adequate Yearly
Progress (AYP) during the previous school year (2007-08). Enter “Y” or “N”
or “NA.”
O. API

VI. Core Academic Teachers

The classroom teachers primarily responsible for teaching a school’s core
academic subjects of reading/English/language arts, mathematics, science,
history/social studies, and foreign language. In elementary schools, core
academic teachers consist of the teachers in the self-contained regular education
classrooms. Some elementary schools may also departmentalize certain core
subjects such as math or science, especially in the upper grades. These teachers
are also to be included as core teachers. In middle schools, high schools, or any
other departmentalized school, core teachers consist of those teachers who are
members of the English/language arts, mathematics, science, social studies, and
foreign language departments along with special education or ESL/bilingual
teachers who provide classes in these subjects. The teachers should be entered as
full-time equivalents (FTEs), which may include decimals. (E.g. a half-time
teacher would be entered as 0.5) If teachers are assigned to multiage classrooms,
divide up the FTEs weighted by students per each grade. Enter each teacher’s
name that corresponds to the FTEs entered in the corresponding notes fields.
Indicate in parentheses if the teacher is not a 1.0 FTE in that category. Example:
Grade 1: Matthew Perry (0.5), Lisa Kudrow, Jennifer Aniston;

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Grade 2: David Schwimmer (0.25), Courteny Cox Arquette (0.33), Matt
LeBlanc

A. Grades K-12: Number of FTE licensed grade-level teachers who teach the
core subjects. The FTEs should not duplicate those in the individual subject
categories.
B. English/Reading/LA, History/Social Studies, Mathematics, Science, and
Foreign Language: Number of FTE licensed subject-specific teachers who
teach the core subjects. The FTEs should not duplicate those in the grade
categories.

VII. Specialist and Elective Teachers

This expenditure element consists of teachers who teach non-core academic
classes, and usually provide planning and preparation time for core academic
teachers. The teachers should be entered as full-time equivalents (FTEs), which
may include decimals. In the notes sections, enter each teacher’s name that
corresponds to the FTEs entered in the related fields. Indicate in parentheses if the
teacher is not a 1.0 FTE in that category.

A. Art/Music/PE: Number of FTE specialist teachers, such as art, music, and
physical education (PE) teachers, who usually provide regular classroom
teachers with planning and preparation time.
B. Drama/Technology/Health: Number of FTE teachers who provide instruction
in a subject area that represents a special academic focus.
C. Career & Technical Education: Number of FTE vocational education teachers
D. Driver Education: Number of FTE drivers education teachers.
E. Study Hall: Number of FTE teachers who monitor study hall.
F. Athletics: Number of FTE teachers who coach an athletic team during the
school day. This does not include time spent as an athletic director, which
would be captured under the Administration section.
G. Other: Number of FTE specialist teachers who are not specifically listed
above.
H. Other Description: Indicate the subject area that the “Other” specialist
teacher(s) instruct.

VIII. Library Staff

Library staff should be entered as full-time equivalents (FTEs), which may
include decimals. Enter each staff member’s name that corresponds to the FTEs
entered in the related fields. Indicate in parentheses if the staff member is not a
1.0 FTE in that category.

168
A. Librarian/ Library Media Specialist: Number of FTE licensed librarians or
media specialists who instruct students
B. Library Aide: Number of FTE library aides who help instruct students

IX. Extra Help Staff

This category mainly consists of licensed teachers from a wide variety of
strategies designed to assist struggling students, or students with special needs, to
learn a school’s regular curriculum. The educational strategies that these teachers
deploy are generally supplemental to the instruction of the regular classroom.
Extra help staff should be entered as full-time equivalents (FTEs), which may
include decimals. Do not include volunteers in the FTE counts. Enter each staff
member’s name that corresponds to the FTEs entered in the related fields.
Indicate in parentheses if the staff member is not a 1.0 FTE in that category.

A. Certified Teacher Tutors: Number of FTE tutors who are licensed teachers
and provide help to students one-on-one or in small groups of 2-5.
B. Non-Certified Tutors: Number of FTE tutors who are not licensed teachers
and provide help to students one-on-one or in small groups of 2-5.
C. ISS Teachers: Number of FTE licensed teachers who monitor/teach In-School
Suspension (ISS) students.
D. ISS Aides: Number of FTE Title I funded aides who monitor/teach In-School
Suspension (ISS) students.
E. Title I Teachers: Number of FTE non-special education teachers who provide
small groups of students with extra help as a function of the Title I program.
F. Title I Aides: Number of FTE non-special education aides who provide small
groups of students with extra help as a function of the Title I program.
G. ELL Class Teachers: Number of FTE licensed teachers of English as a second
language (ESL) who work with non-English speaking students to teach them
English.
H. Aides for ELL: Number of FTE aides of English as a second language (ESL)
classes who work with non-English speaking students to teach them English.
I. Gifted Program Teachers: Number of FTE teachers who instruct students in
the gifted program.
J. Gifted Program Aides: Number of FTE aides who instruct students in the
gifted program.
K. Gifted Program Funds: Dollar amount budgeted for the gifted program for the
2008-09 school year
L. Other Extra Help Teachers: Number of FTE teachers who provide
supplemental instructional assistance to students to learn the school’s
curriculum. (Use this category sparingly.)
M. Other Extra Help Teachers Description: Indicate what the “Other” extra help
staff do.

169
N. Other Extra Help Classified Staff: Number of FTE classified staff who
provide supplemental instructional assistance to students to learn the school’s
curriculum. (Use this category sparingly.)
O. Other Extra Help Classified Staff Description: Indicate what the “Other” extra
help classified staff do.
P. Special Ed. Teacher (Self-contained for students with severe disabilities):
Number of FTE licensed teachers who teach in self-contained special
education classrooms and work with “severely” disabled students for most or
all of the school day. These teachers may teach a modified version of a
school’s curriculum or other learning goals required by their students’
Individualized Education Programs (IEPs).
Q. Special Ed. Inclusion Teachers: Number of FTE licensed teachers who assist
regular classroom teachers with mainstreamed students who have physical or
mental disabilities, or a learning problem. These students generally have “less
severe” disabling conditions.
R. Special Ed. Resource Room Teachers: Number of FTE licensed special
education teachers who provide small groups of students in special education
with extra help in specific areas.
S. Special Ed. Self-contained Aides: Number of FTE aides who assist in self-
contained special education classrooms and work with “severely” disabled
students for most or all of the school day.
T. Special Ed. Inclusion Aides: Number of FTE aides who assist regular
classroom teachers with mainstreamed students who have physical or mental
disabilities, or some learning problem. These students generally have “less
severe” disabling conditions.
U. Special Ed. Resource Room Aides: Number of FTE special education aides
who provide small groups of students in special education with extra help in
specific areas.
V. Number of Extended Day Students: Number of students who participate in the
extended day program.
W. Minutes per Week of Extended Day Program: Number of minutes per week
that the extended day program is offered.
X. Teacher Contract Minutes per Week: Number of work minutes per week in
the teacher contract.
Y. Extended Day Teachers: Number of FTE licensed teachers who provide
students with extra instructional time to achieve to the standards in the regular
curriculum after school.
Z. Extended Day Classified Staff: Number of FTE staff who provide students
with extra instructional time to achieve to the standards in the regular
curriculum after school.
AA. Description of Extended Day Classified Staff: Description of classified
staff’s role in the extended day program.

170
BB. Minutes Per Week of Summer School: Number of minutes per day
multiplied by the number of days per week that students attend summer
school.
CC. Length of Session: Number of weeks that summer school is in session.
DD. School’s Students Enrolled in the Summer School Program: Number of
students from the individual school who are enrolled in the summer school
program (a subset of the following item).
EE. All Students in Summer School: Total number of students enrolled in the
summer school program.
FF. Summer School Teachers: Number of FTE teachers who provided
students with extra instructional time to achieve to the standards in the regular
curriculum during summer 2008.
GG. Summer School Classified Staff: Number of FTE classified staff who
provided students with extra instructional time to achieve to the standards in
the regular curriculum during summer 2008.

X. Other Instructional Staff

Included here are instructional staff members that support a school’s instructional
program, but do not fit in the previous categories. Other instructional staff should
be entered as full-time equivalents (FTEs), which may include decimals. Enter
each staff member’s name that corresponds to the FTEs entered in the related
fields. Indicate in parentheses if the staff member is not a 1.0 FTE in that
category.

A. Consultants (other than PD contracted services): Dollar amount for all other
consultants other than professional development contracted services.
B. Building Substitutes: Number of FTE permanent substitutes.
C. Other Teachers: Number of FTE teachers who instruct, but were not included
in previous categories.
D. Other Instructional Aides: Number of FTE aides who assist instruction, but
were not included in previous categories.
E. Funds for Daily Subs: Daily rate for daily certified teacher substitutes who
replace sick teachers. (This is not for substitutes who replace teachers who
are participating in professional development.)

XI. Professional Development Staff & Costs

This expenditure element includes spending on the professional development of a
school’s staff and the staffing resources necessary to support it. Professional
development staff should be entered as full-time equivalents (FTEs), and cost
figures should be entered as a dollar amount, both of which may include decimals.
Enter each staff member’s name that corresponds to the FTEs entered in the

171
related fields. Indicate in parentheses if the staff member is not a 1.0 FTE in that
category.

A. Number of Professional Development Days in the Teacher Contract: Number
of days the teacher contract specifies for professional development.
B. Substitutes and Stipends (teacher time): Dollar amount budgeted for
substitutes and stipends that cover teacher time for professional development.
For time outside the regular contract day when students are not present before
or after school or on scheduled in-service days, half days or early release days,
the dollar amount is calculated by multiplying the teachers’ hourly salary
times the number of student-free hours used for professional development.
For planning time within the regular contract, the dollar amount is calculated
as the cost of the portion of the salary of the person used to cover the teachers’
class during planning time used for professional development. For other time
during the regular school day, including release time provided by substitutes,
cost is calculated with substitute wages. For time outside the regular school
day, including time after school, on weekends, or for summer institutes, the
dollar amount is calculated from the stipends or additional pay based on the
hourly rate that the teachers receive to compensate them for their time.
C. Instructional Facilitators/Coaches: Number of FTE instructional facilitators
and coaches. This may include on-site facilitators and district coaches
(though only the FTE for the specific school should be recorded). Outside
consultants who provide coaching should be captured in an estimated FTE
amount depending on how much time they spend at the school.
D. Trainers/Consultants: Dollar amount for outside consultants who provide
training or other professional development services. If trainers are from the
district, convert to a dollar amount.
E. Administration: Number of FTE district or school-level administrators of
professional development programs. (Again, only the FTE for the specific
school should be recorded).
F. Travel: Dollar amount of the costs of travel to off-site professional
development activities, and costs of transportation within the district for
professional development.
G. Materials, Equipment, and Facilities: Dollar amount of the materials for
professional development including the cost of classroom materials,
equipment needed for professional development activities, and rental or other
costs for facilities used for professional development.
H. Tuition & Conference Fees: Dollar amount of tuition payments or
reimbursement for college-based professional development, and fees for
conferences related to professional development.
I. Other Professional Development: Either FTEs or Dollar amount for other
professional development staff or costs. (Use this category sparingly.)
J. Other Description: Specify what the “Other” professional development is, and
indicate whether it is a FTE or dollar amount.

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XII. Student Services Staff

This expenditure element consists of school-based student support staff, as well as
school expenditures for extra-curricular activities and athletics. Student services
staff should be entered as full-time equivalents (FTEs), which may include
decimals. Enter each staff member’s name that corresponds to the FTEs entered in
the related fields. Indicate in parentheses if the staff member is not a 1.0 FTE in
that category.

A. Guidance: Number of FTE licensed guidance counselors.
B. Attendance/dropout: Number of FTE staff members who manage attendance
and report dropouts.
C. Social Workers: Number of FTE licensed school social workers.
D. Nurse: Number of FTE registered nurses or nurse practitioners
E. Parent advocate/community liaison: Number of FTE staff members who serve
as the parent advocate and/or community liaison, often working with parents
to get their children to attend school.
F. Psychologist: Number of FTE licensed school psychologists or educational
diagnosticians.
G. Speech/OT/PT: Number of FTE licensed speech, occupational (OT), and
physical therapists (PT) who provide services to the school’s students
H. Health Asst.: Number of FTE health assistants
I. Non-teaching aides: Number of FTE non-teaching aides. (E.g. Lunchroom
aides, Aides who help students board buses; DO NOT include cooks – the
defining difference is whether the staff member is supervising students or
not.)
J. Other Student Services: Number of FTE other student services staff. (Use this
category sparingly.)
K. Other Description: Indicate what the “other” student services staff member
does.

XIII. Administration

This expenditure element consists of all staffing resources pertaining to the
administration of a school. Administrators should be entered as full-time
equivalents (FTEs), which may include decimals. Enter each staff member’s name
that corresponds to the FTEs entered in the related fields. Indicate in parentheses
if the staff member is not a 1.0 FTE in that category.

A. Principal: Number of FTE licensed principals.
B. Assistant Principal: Number of FTE assistant principals.
C. Other Administrators: Number of FTE other administrators. (Use this category
sparingly.)
D. Other Description: Indicate what the “Other” administrators’ duties are.

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E. Secretary: Number of FTE Secretaries.
F. Clerical Staff: Number of FTE clerical staff members.
G. Technology Coordinator: Number of FTE technology coordinators and IT
staff.
H. Security: Number of FTE security staff.
I. Custodians: Number of FTE staff who provide custodial services

XIV. Elementary Class Sizes (We are NOT collecting this data for middle and high
schools.)

Sometimes it is easiest to get this information when you get the staff list, but other
times the secretary can just copy the sheet that tells them how many students are
in each classroom (we don’t want student names). You want a (preferably
electronic) copy of the master class schedule to enter this data. When entering
the data online, make sure to enter the class size for every class that is taught at
the school. Click on the Class Size option from the main menu and a new menu
will be displayed on the left. This menu will have options for grades Pre-8 plus
Special Education. When you click on a grade, the page with that grade's sections
will be displayed where you can enter the individual class sizes.

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APPENDIX G:

OPEN-ENDED DATA COLLECTION PROTOCOL

SCHOOL AND DISTRICT SITES

Following are open-ended questions intended to capture how learning environments
support struggling students and the resources necessary help them reach standards. Ask
the questions in the order that they appear on this protocol. Record the answers as the
interviewee gives them and focus on getting the key elements of the implementation and
evaluation of extra help strategies.

I. Tell me the story of how struggling students are being supported
A. What “interventions” or Extra Help Strategies are provided for struggling
students?
1. Tutoring: Specify 1:1, in small groups (2-4), or in medium groups (3-
5)
2. Extended day: How frequently (Number minutes & Number of times
per week), Academic focus, Who instructs (certified teachers or aides),
Who participates, What is the description of classified staff’s role,
3. Summer school: How Frequently (Number hours a day, Number
weeks), Who instructs (certified teachers or aides), Who participates
4. ELL
5. Scheduling: (E.g. double periods in secondary schools)
B. How did the implementation of strategies begin (or not)?
1. Was the implementation of strategies centrist (central office
orchestrated) or bottom up?
2. What significant events and conversations occurred during the
process?

II. How are resources allocated to support struggling students?
A. What resources (FTE) are allocated to implement extra help strategies?
B. What are personnel hired to do? What are their roles and responsibilities?
C. How long have resources been in place?
D. How does the state’s budget reduction change the following:
1. Allocation and use of resources (e.g., categorical funds, FTE)
2. Roles and responsibilities of personnel
3. Services and supports students receive (What is being given up? What
positions and services are being cut? Counseling services, tutoring,
class sizes etc.)
E. What is the rationale for adjusting resource allocations?
F. What factors influence decisions to allocate resources for extra help strategies?
1. Program effectiveness (student performance)
2. Program value (student participation)

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3. Competing priorities and initiatives that consume resources
G. What additional resources would be needed to continue to support struggling
students?
H. What are the resource projections for next year SY 2012-2013?

III. How effective and valuable are alternative learning environments?
A. In your opinion, how effective are alternative learning environments?
1. Increasing attendance and graduation/completion rates
2. Increasing parent involvement and community support
3. Decreasing dropout rates
B. In your opinion, what is the value of ALEs?
1. Number and percent of at-risk students who are served
2. Number and percent of at-risk students served from low socio-
economic backgrounds and historically low performing ethnic groups

IV. Closing
A. Is there anything else you would care to add?
B. Was there a question that I didn’t think to ask you?

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APPENDIX H:
CASE STUDY: REGULAR HIGH SCHOOL
The regular high school opened its doors in 2000 and in 2011 served 2,107
students in grades 9 through 12 within a developing urban community on the island of
Oahu. Currently, the 650-acre city center is zoned for commercial, mixed, and residential
use to accommodate a growing population. In 2000, the city’s population was
approximately 67,000, and population projections anticipate an increase to between
170,000 and 185,000 by 2025. In 2006, the number of homes in the region was estimated
at 26,000, and by 2025 urban development plans aim to build an additional 25,000
residential units. Nearly 25,000 jobs existed in 2006, and estimates project an additional
40,000 jobs to the area by 2020.
The district in which the school is located serves students from preschool through
adult education. The district, which is separated into 2 complex areas, has 30 elementary
schools, 2 middle schools, 4 intermediate schools, 1 high and intermediate school, 5 high
schools, 3 charter schools, and 1 adult school. The total enrollment among the 6 schools
that serve high school students is 11,873 students, and an average of 46.6% of those
students were classified as low-income, 6.1% were English language learners (ELL),
13.8% were special education (SPED), and 93.9% were identified as minority or non-
White in school year 2010-2011 (State of Hawaii, 2011). Specifically at the regular high
school, 29.6% of the students in the regular high school are classified as
Socioeconomically Disadvantaged (SED), 2.4% were ELL, and 11.5% were SPED in

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2011 (State of Hawaii, 2011). Furthermore, 9.5% of the student population at the regular
high school is identified as at-risk (Regular High School Records, 2012).
In 2011, 86.6% of the student population is classified as non-White. Filipino
students historically comprise the largest ethnic group at the high school; however, the
population of Hawaiian students has steadily increased since school year 2007-2008 as
the population of Filipino students decreases. Other minority subgroups at the high
school include Native Hawaiian (29.2%), Filipino (24.8%), Japanese (7.3%), African-
American (5%), Multiple two or more (5%), Samoan (4.9%), Hispanic (4.2%),
Portuguese (1.8%), Chinese (1.6%), Indo-Chinese (0.7%), Guamanian/Chamorro (0.6%),
Korean (0.5%), Micronesian (0.5%), Other (0.5%), Tongan (0.3%), and Native American
(0.2%). Figure 1 shows the ethnic breakdown of all students at the regular high school
(State of Hawaii, 2011).

Figure 1. Ethnic breakdown of school population at regular high school.

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The improvement process at the regular high school is anchored in a comprehensive
school-level system of supports that includes the implementation of the leadership
academy, extra-help strategies, and reading and math interventions across all content
areas to help struggling students achieve rigorous academic standards. The purpose of
the case study is to compare the student characteristics and resource allocation levels
necessary to implement the system of supports at the high school with the Evidence-
Based (EB) Model’s prototypical high school and the 1 Plus 1:7 Model for alternative
schools. Resource level comparisons between all sites examined in the study are
presented in Table 4.5.
Test Scores
The regular high school is close to meeting adequate yearly progress (AYP) and
entered into restructuring status in 2008 when it did not meet AYP by 3 cells. Figure
RHS.2 shows the school’s AYP Cell Count Results over the last five years.

Figure 2. AYP cell count results for regular high school (school years 2007–2011).

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The regular high school demonstrates proficiency in achieving the state’s Annual
Measurable Objective (AMO) for reading each year since school year 2002-2003 from
which assessment data are available. However, in 2011 the average proficiency scores
of all students do not meet the state’s reading targets for the first time. An important
point to note is that the AMO for reading increases in 2011 to 72%, and the aggregate
score of all students is 3.2% below the reading target. The previous reading target is 58%
in school years 2008-2010 during which time the average reading scores of all students
who are tested range from 74.5 to 79.9%.
Several key trends emerge. First, the reading scores of the special education and
Hispanic subgroups at the regular high school show significant increases of 14.5% and
36.9% respectively from 2007 to 2009. Second, students within the Hispanic and White
subgroups consistently achieve the state reading target with the exception of 2011 when
the Hispanic subgroup scores 3.6% below the target. Third, Asian/Pacific Islander and
Disadvantaged subgroups show an 11.5% and 16.5% decline respectively from 2009 to
2011, and the English language learner (ELL) subgroup scores the lowest of all
subgroups tested in 2011.
It is importation to mention, however, that the number of ELL students at the
regular high school is extremely small. Therefore, the scores are not considered a trend
that represents the performance of the overall school. In 2011, Black students do not
qualify as a subgroup. Figure RHS.3 shows the high school’s Reading AYP since 2007
disaggregated by subgroups.

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Figure 3. Reading AYP for regular high school (school years 2007-2011).

Figure Regular High School.4 displays the math AYP for the high school. The AMO for
math increases in 2011 to 64% from 46% during the three previous school years from
2008 to 2010. Over the past five years from 2007 to 2011, the math scores of all students
average about 32%.
A key trend is that Black students are the only subgroup that achieves the state’s
math objective within the past five years, specifically in 2007, 2008, and 2010. Some
student subgroups in 2011, with the exception of Hispanic and Black subgroups show a
decline in math proficiency that ranges from 10.9 to 1.6%. Important points to highlight
are that the Hispanic subgroup increases 14.9% in math in 2011, and the smallest decline

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occurs in the largest subgroup comprised of Asian/Pacific Islander students. Figure 4
displays the performance of significant subgroups in math since 2007.

Figure 4. Math AYP for Regular High School (School Years 2007-2011).

Introduction of the Key Elements of the Improvement Process
The high school was designed upon a research-based foundation for small
schools/learning communities, and was therefore structured into grade-level teams from
its inception. The school first opened in 2000 to its first cohort of 9
th
graders and then
phased in subsequent grade levels thereafter with each successive year. Today, each 9
th

and 10
th
grade team consists of teachers from several content areas including social
studies, English and science who team teach with special education teachers in an
inclusionary setting that serves students with learning and mild disabilities in a regular
education environment. The school is also structured into career-focused academies at

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the upper divisions where, based upon students’ personal interests, they and their parents
choose a course of study from a selection of 10 academies including: Business, Creative
Media, Fine Arts, Graphics, Health Careers, Leadership, Human Services, Industrial
Technology, Professional Science, and the Learning Center for Applied Technology
(LCAT). All academies are designed to serve students in grades 11 and 12, with the
exception of the leadership academy.
The implementation of grade-level teams and career-focused academies at the
high school require an array of personnel resources. In school year 2010-2011, the
regular high school has a total of 114.5 full-time equivalents (FTE) including personnel
for regular and special instruction. The high school allocates 57.0 FTE and 5.0 part-time
teachers (PTT) to teach core subjects. PTTs provide additional classroom support for the
full-time teacher who assumes the lead in the implementation of instruction. The PTTs
play a particularly important role in supervising the hands-on work that students do in the
garden or woodshop for instance to minimize injuries and ensure students safely engage
in authentic learning experiences. To teach elective or specialty courses, the high school
allocates 28.0 FTE and 6.0 part-time temporary teachers (PTTs). Additionally, the high
school allocates 1.0 FTE and 2.0 PTTs for ELL teachers, 2.0 FTE and 7.0 PTTs to teach
students with learning and mild disabilities, 1.0 FTE and 3.0 PTTs to teach students with
severe disabilities, 3.0 FTE teachers for gifted students, 8.0 FTE for pupil support staff,
2.0 FTE for non-instructional aides, 1.0 FTE and 1.0 PTT for librarians, and 1.0 FTE for
a student activities coordinator. Furthermore the high school allocates, $200,000 for
instructional materials and $50,000 for technology.

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The implementation of the leadership academy is a key element to the
improvement process at the regular high school particularly for students at-risk of
academic failure and potentially dropping out of school. The leadership academy is
located on the campus of the regular high school, the only one that serves students from
grades 9 to 12, and 100% of the students in the academy are classified as at-risk. The
academy was developed 4 years ago as a grassroots response to solve the problem of
failing students that continued to emerge in student data, despite the implementation of
Special Motivation Classes (SMCs) for at-risk students. Prior to the leadership academy,
the high school offered a SMC program.
Unfortunately, the design of the SMC itself was problematic. Besides serving
only 30 students while requiring 3 teachers and other personnel supports that rotated
between two classes, the SMC was a reactive approach to solve the student failure
problem. Only when students began to fail classes or create discipline problems for
teachers in the regular classroom setting were they referred to the program. The previous
SMC program did not address the growing problem of students failing multiple courses.
Rather than continue to take a reactive approach to supporting at-risk students, a group of
teachers led by a teacher who currently teaches English in the academy, together with the
support of the previous principal, committed themselves to the development and
implementation of a model that provides at-risk students with timely assistance when
they enter as freshmen and most importantly before they begin to fail classes.
The teachers also believe that maintaining contact and remaining involved in the
learning of their students during school suspensions, for instance, creates a smoother

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transition for students back into the mainstream learning environment rather than
temporary off-campus alternatives. Off campus alternatives remove students from the
potentially problematic environment, but it also detaches students from the curriculum
and exacerbates disruptions in the continuity of instruction and academic support they are
entitled to along with their peers. According to the principal at the high school, “They
[at-risk students] should be in the least restrictive environment just like special education
students.” The academy provides a more effective alternative than off-campus
placements to maintain contact with students for whom disciplinary consequences,
oftentimes for substance abuse, are enforced.
In school year 2010-2011, 9.5% or 201 of the 2107 students enrolled at the high
school are classified as at-risk. The academy is designed to serve approximately 200
students with 50 slots available for each grade level, an amount that is equivalent to 10%
of freshman class sizes ranging from 450 to 500 students. Since the academy can only
serve a limited number of students, the high school and middle school continues to build
a collaborative relationship through the process of identifying at-risk students who will
likely benefit from the learning environment created in the academy. Based upon the
recommendations of the middle school, a team of teachers from the high school identifies
potential candidates for the academy and then speaks with students and their parents to
provide them with information about the academy. This approach to student
identification and intervention allows the enrollment of the academy to remain relatively
stable throughout the school year. Furthermore, 90% or 181 of the 201 students
identified as at-risk are enrolled in the leadership academy. Not all at-risk students

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choose to enroll in the leadership academy which consequently contributes in part to the
90% enrollment rate of students in the academy from the total number of at-risk students
identified a the high school. Ultimately, the choice to enroll in the academy rests upon
students and their parents.
The implementation of the leadership academy requires personnel resources.
Although not exclusively designated to support the leadership academy or any specific
program, the high school allocates 1.0 FTE position for a principal whose responsibilities
encompass overseeing the implementation of all academies, teams, and programs, as well
as providing supervision over the operations of the entire high school. To staff the
academy, 7.0 FTE are allocated for teaching and support staff, and also part-time teacher
positions to provide instructional support. More specifically, 4.0 of the positions are
designated for core teachers, 2.0 for specialty teachers, and 1.0 for pupil support staff.
The high-risk counselor position is assigned solely to the academy to manage credit
counts, to address students’ issues associated with family problems and drug addiction
that impact their academic performance, and to implement credit recovery programs for
at-risk students while increasing parent involvement. The academy also allocates 6.0
part-time teacher positions to provide additional instructional support for classroom
teachers in the academy and to communicate with parents through individualized phone
calls home that notify them when their child is absent from school or tardy to class
periods.
The high school also conducts an annual evaluation of the leadership academy.
Data from the evaluation make it possible to determine the impact that the academy is

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making for the population of at-risk students in relation to the larger high school, and also
to inform program improvements that address the current needs of struggling students. In
school year 2010-2011, data show the leadership academy and the high school as a whole
were effective in helping students to graduate and in keeping them in school and
persisting toward graduation. Students enrolled in the leadership academy graduate with
a regular high school diploma rather than a nonstandard high school diploma or
certificate of completion. The leadership academy (97%) and regular high school
(97.4%) exceed the state’s graduation target of 80%. In the academy, 43 out of 44,
graduate on time, which is 17% higher than the state standard. Similarly, the high school
graduates 440 out of 452 seniors, including graduates with diplomas (95.6%) and with
individually prescribed programs (1.8%), which is 17.4% higher than the state standard.
Although the overall high school (93.7%) does not meet the state target for attendance,
the attendance rate in the academy is slightly higher at 95%, which is equivalent to the
state standard. The dropout rate is lower in the academy (4%, or 7 students) than at the
overall high school (10.8%, or 54 students). Table 9 compares the performance of
students at the regular high school and leadership academy (Regular High School
Records, 2012).

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Table 9

Comparison of Student Performance at Regular High School and Academy (SY 2010-
2011)
Student
Performance
Indicators
Academy at Regular
High School
%
Regular High
School
%
Graduation Rate 97 97.4
Attendance Rate 95 93.7
Dropout Rate 4 10.8

Themes of the Improvement Process
The themes discussed in this section emerge from school wide efforts at the
regular high school that aim to improve student performance particularly for at-risk
students who historically struggle in the regular classroom setting.
An important theme that emerges at the high school is the emphasis on highly
qualified teachers. Of the 114.5 full-time equivalents (FTE) the regular high school
allocates for regular and special instruction personnel, 109 teachers or 94.8% are fully
licensed in school year 2010-2011. Two teachers (1.7%) have a provisional credential,
and 4 teachers (3.5%) have an emergency credential. Teachers’ average years of
experience is 11.1 years, and 44 teachers have advanced degrees. There are 75 teachers
with 5 or more years at the regular high school, and there have been 2 principals within
the past 5 years. The previous principal retired 3 years ago.
Quality teachers are key to student success; and in addition to being qualified in
content or specialty areas, effective teachers also possess a certain set of characteristics
particularly those teachers who work with at risk students. The principal and complex

188
area superintendent both agree that it takes a special type of person who has the desire
and is committed to help at risk students find success in school. According to the
principal of the high school, “It’s gotta be people who want to collaborate, work together,
and have passion” (E. Esmeralda, personal communication, December 9, 2011). Novice
teachers cannot simply be assigned to classrooms with at-risk students who are
historically more difficult to teach. The principal has observed the teachers in the
leadership academy actively recruit teachers to replace a colleague because they
recognize the importance of hiring an effective teacher while considering their
compatibility with the population of at-risk students.
To promote the development of highly qualified teachers on site, the school also
implements a Mentor Program for teachers who are identified as novice, non-highly
qualified, and marginal as determined by administration. The Mentor Program involves a
summer orientation, ongoing professional development, classroom observations, and
support from a full time mentor whom models instructional strategies and multiple forms
of assessments. An important element of the program is the ongoing, descriptive
feedback the mentor provides to the classroom teacher regarding instructional and
assessment practices they observe during classroom visits and discuss during pre-
conferences.
Another important theme at the high school is the implementation of professional
learning communities (PLCs). PLCs provide the conditions for adult learning to occur
based upon analysis of student data to inform professional and leadership practices. At
the high school, teachers will analyze data from assessments such as the Hawaii State

189
Assessment (HSA), quarterly assessments, and teacher developed formative assessments.
In some instances, they will analyze samples of student work, such as constructed
responses from formative assessments, using common rubrics. The new knowledge that
is construction through data analysis is then applied to refine strategies built into their
repertoire of classroom instruction. In other words, to sustain what is working and adjust
what is not is a core function of the PLCs.
The organization of the high school into grade-level teams and career-focused
academies facilitates adult learning by providing a natural structure embedded into the
collaborative culture of the school. Teachers in teams and academies aim to develop and
implement curriculum from multiple disciplines. In 9
th
and 10
th
grade teams,
collaboration also occurs among regular education teachers and special education
teachers who team-teach within an inclusionary classroom setting. In this way, PLCs
provide teachers with time to engage in reflective data-driven dialogue with colleagues to
make decisions regarding improvements to their classroom practice. Furthermore, the
collaborative culture at the high school permeates the complex and feeder schools as the
case when teachers from the middle and high schools come together to analyze student
performance data as part of the early identification process inherent to the leadership
academy.
Another theme is the implementation of the Standards Based Change (SBC)
process, the conceptual frame within which data collection and analysis of student
performance occurs at the high school with teacher leaders and facilitation support from
SchoolRise. The SBC process facilitates the examination of students’ achievement of

190
content area benchmarks to make data-based decisions. While HSA scores provide the
high school with information that suggest minimal gains in overall student performance,
particularly in math, over the past 5 years, data from DSI quarterly assessments and
teacher developed formative assessments reveal to departments and professional learning
communities a more detailed picture of the achievement gaps in basic skills among
specific student groups. For example, the math department is able to recognize a specific
subgroup of students who continue to struggle with basic skills in math despite school
wide efforts to incorporate math instruction across all content areas through the sustained
silent math strategy. Analysis of formative data reveals that current strategies are
ineffective for some students. Therefore, the math department decides to reinforce
existing interventions with a 3-week math pullout program during the regular school day
that targets these students with the greatest needs in math. Data from formative
assessments that are conducted several times per year are used to continuously
differentiate reading and math interventions to match students’ skill levels as they work
to master new content.
Data analyzed through the SBC process are also used to adjust and align
curriculum in courses such as math. Based upon student performance on math
assessments, the math department recognized gaps in the sequence of the math
curriculum and assumed the lead in reorganizing math courses and shifting personnel to
align math content and coursework to state assessments and the graduation requirements
for math to earn the Board of Education recognition diploma. Algebra 1 was changed to
precede algebra 2 and then geometry. Clearly a demonstration of teachers’ commitment

191
to support struggling students, upper level algebra teachers agreed to teach algebra 1
courses based upon their familiarity of algebra 2 course expectations and algebra 1 credit
exam requirements.
Another theme is the school wide, instructional focus on the basic skills through
the implementation of differentiated reading and math strategies in the content areas to
close the achievement gaps among targeted student subgroups. The high school
implements an array of school-wide reading and math interventions such as sustained
reading and math, Achieve 3000, Read 180, Reading: Keys to Comprehension. Some of
them incorporate technology through supplemental software and curriculum including
Accelerated Math, Bridge to Algebra, Cognitive Tutor. Worthy of note is that these
strategies are implemented with all students during the regular school day because the
high school also provides additional support beyond regular instructional hours, which
are discussed in more detail later in the section on extra-help strategies.
The school also promotes higher-order thinking, in addition to basic skills,
through a curricular program anchored in project-based learning. The aim of project-
based learning is for teachers to develop authentic learning experiences that engaged
students in unpredictable situations that challenge them to think critically and solve
problems that adults and professionals face in the real world. The project-based
curriculum in the leadership academy, for example, is built upon Hawaiian principles to
increase relevance for students in the academy, many of whom are Hawaiian, Part-
Hawaiian or Pacific Asian Islander. The academy promotes learning outdoors while
teaching student in the lo’i or garden to provide students authentic, hands-on experiences

192
with concepts such as sustainability and cycle. Students sell their products at the
farmers’ market and learn through an interdisciplinary curriculum that examines the
cultural and historic aspects of farming in Hawaii, the financial elements of sustaining
and managing a viable business, and the impact of chemicals on the environment and
society as a whole.
The last theme discussed in this section is the implementation of additional
support beyond the regular instructional day at the high school. These extra-help
strategies include tutoring before-and-after school, extended day, and summer school.
For example, the school offers math tutoring after school for students who do not meet
levels of proficiency on math assessments. Some extended day programs at the school
such as Twilight Academy, NovaNet, Plato, and E2020, focus specifically on credit
recovery to help students who lack the credits necessary to graduate on time. It is
important to highlight that these additional supports are recommended to students based
on their performance on assessments, and likewise reinforce the reading and math
interventions students receive during the regular school day to improve their basic skills
and close the achievement gap. Therefore, a student might receive help during the school
day and/or before and after school as well through these extra-help strategies. These
additional supports are especially important for students who decline the services of the
academy and other supports provided during the school day and also for students who are
not identified as at-risk but nevertheless require additional help, beyond the assistance
offered during the regular class period.

193
In school year 2010-2011, 100 students receive tutoring, 34 participate in
extended day, and 33 attend summer school. To implement extra-help strategies, the high
school allocates 3.0 FTE and 3.0 PTT positions to implement the extended day program,
4.0 FTE and 4.0 PTT for summer school, 3.0 FTE and 1.0 PTT for instructional
facilitators/mentors, and $47,750 for professional development. Although the high
school does not allocate personnel resources for tutors, all teachers are expected to serve
a dual-role as teacher-tutor to help struggling students in all teams and academies.
Comparison of Resource Use With the Evidence Based Funding Model
The case study will first discuss the school characteristics and personnel resources
at the regular high school as a whole for all teams and academies, and then focus on
examining the leadership academy at the regular high school. The Evidence-Based
Model is used in this section in two ways. The first is to analyze the school
characteristics against the prototypical high school. The second will use the school
characteristics of the prototypical high school as a framework to calculate the relative
resource levels for personnel at an EB school with the characteristics of the regular high
school. Table 4.5 presents resource level comparisons between the regular high school,
leadership academy, and ALE school. The following sections will then use these relative
resource levels to analyze the school site.
School Characteristics of the Regular High School
This section compares school characteristics by first identifying similarities
between the regular high school and the Evidence-Based Model’s prototypical high
school for school year 2010-2011. The school configuration of the high school is the

194
same as the EB prototypical high school ranging from grades 9 to 12. Furthermore, the
percentage of students at the high school who are disabled is slightly less than the relative
amount identified in the EB prototypical high school. At the high school, 11.5% of the
students are classified as disabled, equivalent to 0.5% less than the 12% of disabled
students identified in the prototypical high school.
In addition to these similarities mentioned above, significant differences exist
between the EB prototypical high school and several school characteristics of the regular
high school. First, the high school enrolls 2107 students, which is 251.2% larger than the
school size of the 600-student prototypical high school. Additionally, 86.6% of the
students are classified as minority, equivalent to 56.6% greater than the 30% of non-
White students included in the prototypical high school. It is also important to note that,
among the other high schools within the district, 93.9% are classified as minority, which
is 63.9% greater than the EB school. Other differences are less than the percentages
presented in relation to characteristics of the EB school and also less distinctive than
overall enrollment and ethnicity. For example, 29.6% of the students in the high school
are eligible for free and reduce-price lunch, which is 20.4% less than the 50%
consideration included in the prototypical high school. Among all high schools in the
same district as the regular high school, the average percentage of low-income students is
46.58%, which is 3.42% less than the EB school but nevertheless lower than the
prototypical high school. Finally, the 2.4% of ELL students enrolled at the high school is
7.6% less than the 10% included in the EB prototypical high school.

195
Also important to note is the number of teacher workdays at the regular high
school is determined through collective bargaining between the Hawaii State Teachers
Association (HSTA) and the Hawaii State Department of Education (HIDOE). Each site
in the sample for the study is funded and administered through the HIDOE and therefore
includes the same number of teacher workdays and professional development (PD) days.
The HSTA contract includes 180 teacher workdays and zero professional development
(PD) days as a result of state furloughs that eliminate 10 professional development days
implemented prior to state budget reductions. The number of teacher workdays in the
HSTA contract is 20 teacher workdays or 10 percent less than EB and 10 PD days or 100
percent less than the 10 PD days included in the EB prototypical high school. Table 10
shows a comparison of school characteristics of the regular high school with the
Evidence-Based (EB) Model’s prototypical high school for school year 2010-2011.

196
Table 10

Comparison of School Characteristics of Regular High School with Evidence-Based (EB)
Model Prototypical High School (SY 2010-2011)

School Element
EB
Prototypical
High Schools

Regular High
School

Regular High School –
EB Comparison
School
Configuration
9 - 12 9 - 12 Regular high school has
same configuration as EB
School size 600 2107 251.2% greater than EB
Number of teacher
work days
200 teacher
workdays,
including 10
days for
intensive
training
180 days (10
PD days cut by
state furloughs)
20 teacher workdays or
10% less than EB
10 PD days or 100% less
than EB
Full-day
kindergarten
NA NA Same as EB
% disabled 12% 11.5% 0.5% less than EB
% poverty (free and
reduce-price lunch)
50% 29.6% 20.4% less than EB
% ELL 10% 2.4% 7.6% less than EB
% minority
(non-White)
30% 86.6% 56.6% greater than EB

Personnel Resources of the Regular High School
The overall FTE and dollar category allocation levels to administer and staff the
high school and to implement extra-help strategies to improve student performance at the
high school are significantly lower than adequate resource levels recommended by the
Evidence-Based Model, with the exception of several staffing categories discussed in
more detail below. This section compares the relative amounts of personnel resources
allocated within various staffing categories with the Evidence-Based Model’s
prototypical high school for school year 2010-2011.

197
The personnel resource levels for principals and school site secretaries at the high
school are significantly less than EB recommendations for adequate resources. The
personnel allocation for principal positions is 71.4% less than the EB school with
characteristics of the regular high school. The high school allocates 1.0 FTE for a
principal, a difference of 2.5 FTE less than the 3.5 principals included in the EB school
unit. The relative amount of school site secretaries is 90.5% less than the EB school with
characteristics of the high school. The high school allocates 1.0 FTE for a school site
secretary, a difference of 9.5 FTE less than the 10.5 school site secretaries included in the
EB school. It is important to note that the administration at the site supports the entire
high school including all 6 teams and 10 academies on campus.
The relative personnel allocation levels to adequately staff the school with
specialist teachers are the same as the 28 FTE positions included in the EB school with
characteristics of the regular high school. However significant differences emerge among
several types of teachers in relation to the EB school, the largest of which exists with
teachers for students with learning and mild disabilities. The personnel allocation for
special education teachers is 86% less than the EB recommendation. The 2.0 FTE the
high school allocates to teach students with learning and mild disabilities is 12.0 FTE less
than the 14 special education teachers included in the EB school. Although not as
pronounced as with special education teachers, the relative amount of pupil support staff
is 46% less than the EB recommendation, and the 8.0 FTE the high school allocates is 6.7
positions less than the 14.7 FTE included in the EB school for pupil support staff.
Finally, the personnel allocation for core teachers is 32.4% less than the resource level

198
recommended by the Evidence-Based Model. The 57.0 FTE the high school allocates to
teach English, social studies, math, and science is 27.3 FTE less than the 84.3 core
teachers included in the EB school.
The personnel resource levels to adequately implement extra-help strategies in the
regular high school are significantly less than the recommendations of the Evidence-
Based Model, the largest difference of which exists with tutors for struggling students.
The positions allocated for tutors is 100% less than the EB school with characteristics of
the regular high school. The 0.0 FTE the high school allocates for tutors is 6.24 FTE less
than the recommended positions included in the EB school. Other relative differences for
personnel to implement extra-help strategies are not as substantial as the case with tutors;
however, the differences between the EB recommendations and resource levels for
extended day and summer school are nevertheless significant. The relative amount of
personnel for extended day is 66% less than the EB school with characteristics of the
regular high school. The 3.0 FTE the high school allocates for extended day is 5.8 FTE
less than the 8.8 positions included in the EB school. The personnel allocation to
implement a summer school program at the high school is 55% less than what is included
in the EB school. The 4.0 FTE the high school allocates for summer school is 4.8 FTE
less than the 8.8 teachers for summer school recommended by the Evidence-Based
Model.
The relative levels of dollar category resources are likewise less than the
recommendations of the Evidence-Based Model, the largest of which exist for student
activities. The dollar-per-pupil amount for student activities is 100% less than the EB

199
school with characteristics of the high school. The high school allocates $55,000 to
student activities through the allocation of 1.0 FTE for a student activities coordinator. It
is important to note that the high school offers a student activities program that operates
on student dues. The relative amount of dollar category resources for technology is
slightly less than the allocation for student activities. The dollar-per-pupil amount for
technology is 90.4% less than the recommendation for the EB school. Furthermore, the
high school allocates approximately $24/pupil ($50,000) for technology, a difference of
$226/pupil ($476,750) less than the $250/pupil ($526,750) for technology included in the
EB school.
The differences between the dollar category resources for professional
development and instructional materials are not as distinctive as with student activities
and technology, but nonetheless equal to approximately half of what is recommended for
the EB school. The dollar-per-pupil amount for professional development at the high
school is 54% less than recommendations for the EB school with characteristics of the
regular high school. The high school allocates approximately $23 per pupil ($47,750) for
professional development, a difference of $27/pupil ($57,600) less than the $50/pupil
($105,350) for professional development included in the EB school. The dollar category
resources for instructional materials are 46% less than the EB school recommendations.
The high school allocates approximately $95 per pupil ($200,000) for instructional
materials, a difference of $80/pupil ($168,725) less than the $175/pupil ($368,725)
included in the EB school. Table 11 shows a comparison of school personnel resources

200
of the regular high school with the Evidence-Based (EB) Model’s prototypical high
school for school year 2010-2011.
Table 11

Comparison of Personnel Resources of Regular High School with Evidence-Based (EB)
Model Prototypical High School (SY 2010–2011)
Staffing
Category
EB Prototypical High
Schools
EB School
with
Characteristics of
Regular High
School
(2107 Students)
Regular High
School
Regular High
School – EB
Comparison
Core Teachers 24 84.3 57.0
(5.0 PTT)
27.3 FTE (32.4 %
less than EB)
5.0 (Part-time
teachers)
Specialist
teachers
8.0 (33% greater) 28.0 28.0
(6.0 PTT)
Same as EB
6.0 (Part-time
teachers)
Instructional
Facilitators/
mentors
3.0 10.5 3.0
(1.0 PTT)
7.5 FTE (71.4%
less than EB)
1.0 (Part-time
teacher)
Tutors for
struggling
students
3.0 (1.0 for every 100
poverty students)
6.24
(624 students)
0.0 6.24 FTE (100%
less than EB)
Teachers for
ELL students

0.60 (Additional 1.0
for every 100 ELL
students)
0.5
(51 students)
1.0
(2.0 PTT)
0.5 FTE (100%
greater than EB)
2.0 (Part-time
teachers)
Extended day 2.5 8.8 3.0
(3.0 PTT)
5.8 FTE (66% less
than EB)
3.0 (Part-time
teachers)
Summer School 2.5 8.8 4.0
(4.0 PTT)
4.8 FTE (55% less
than EB)
4.0 (Part-time
teachers)

201
Table 11, Continued
Staffing
Category
EB Prototypical High
Schools
EB School
with
Characteristics of
Regular High
School
(2107 Students)
Regular High
School
Regular High School –
EB Comparison
Learning and
mildly disabled
students
Additional 4.0
professional teacher
positions
14
(242 students)
2.0
(7.0 PTT)
12 FTE (86% less
than EB)
7.0 (Part-time
teachers)
Severely
disabled
students
100% state
reimbursement minus
federal funds
NA 1.0
(3.0 PTT)
NA
3.0 (Part-time
teachers)
Teachers for
gifted students
$25/pupil $52,675 $78/pupil
($165,000)
$53/pupil or $112,325
(212% greater than
EB)
Vocational
education
No extra costs NA NA NA
Substitutes 5% of previous
personnel items
8.1 0.0 FTE
~ $68,358 is
allotted
8.1 FTE (100% less
than EB)
($68,358 greater than
EB)
Pupil support
staff
5.4 (1.0 for every 100
poverty students plus
1.0 guidance/250
students)
14.7
(624 students)
8.0 6.7 FTE (46% less
than EB)
Non-
instructional
aides
3.0 10.5 2.0 8.5 FTE (81% less
than EB)
Librarian/Media
specialists
1.0 librarian
1.0 library technician
2.5 librarian
2.5 tech
1.0
(1.0 PTT)
1.5 FTE (60% less
than EB)
2.5 FTE (100% less
than EB)
1.0 (Part-time teacher)
Principal 1.0 3.5 1.0 2.5 FTE (71.4% less
than EB)
School site
Secretary
3.0 10.5 1.0 9.5 FTE (90.5% less
than EB)
Professional
Development
Included above:
Instructional coaches,
planning and prep
time, 10 summer
days
Add’l: $50/pupil for
other PD expenses:
trainers, conferences,
travel, etc.

$105,350
$23/pupil

($47,750 is
allotted)

$27/pupil or $57,600
(54% less than EB)

202
Table 11, Continued
Staffing
Category
EB Prototypical High
Schools
EB School
with
Characteristics of
Regular High
School
(2107 Students)
Regular High
School
Regular High School –
EB Comparison
Technology $250/pupil $526,750 $24/pupil

($50,000 is
allotted)
$226/pupil or
$476,750 (90.4% less
than EB)

Instructional
materials
$175/pupil $368,725 $95/pupil

($200,000 is
allotted)
$80/pupil or $168,725
(46% less than EB)
Student
activities
$250/pupil $526,750 $26/pupil

($55,000 is
allocated as 1.0
FTE)
$224/pupil or
$471,750 (89.5% less
than EB)

School Characteristics of the Leadership Academy at the Regular High School
This section begins by comparing school characteristics and highlighting
similarities between the academy at the regular high school and the Evidence-Based
Model’s prototypical high school for school year 2010-2011. The leadership academy
serves students from grades 9 to 12, which aligns with the school configuration of the EB
prototypical high school. Also, the percentage of students in the academy who are
disabled is slightly less than the relative amount identified in the EB prototypical high
school. In the academy, 9.4% of the students are classified as disabled which is 2.6% less
than the 12% of disabled students identified in the prototypical high school.
On the other hand, several differences are worth noting between the leadership
academy and the EB prototypical high school. In the academy, 90% of the students
enrolled are classified as minority or non-White, which is 60% greater than the 30%

203
included in the prototypical high school. Other school characteristics are less than the
percentages included in the EB prototypical high school. The academy enrolls 181
students, which is 69.8% less than 600-student prototypical high school. The proportion
of students in the academy who live in poverty and who are classified as ELL are equally
less than the relative amounts identified for each respective characteristic in the
prototypical high school. In the academy, 40% of the students are eligible for free and
reduce-price lunch, and 0% of the students are classified as ELL, both of which are
equivalent to 10% less than the recommendations of the EB prototypical high school.
Table 12 shows a comparison of characteristics of the leadership academy with the
Evidence-Based (EB) Model’s prototypical high school for school year 2010-2011.
Table 12

Comparison of Characteristics of the Leadership Academy with Evidence-Based (EB)
Model Prototypical High School (2010-2011)
School Element

EB Prototypical
High Schools
Leadership
Academy
Leadership Academy
– EB
Comparison
School Configuration 9 - 12 9 - 12 Leadership Academy has same
configuration as EB
School size 600 181 69.8% less than EB
Number of Teacher work
days
200 teacher
workdays,
including 10
days for
intensive
training
180 days (10 PD
days cut by state
furloughs)
20 teacher workdays or 10% less
than EB
10 PD days or 100% less than EB
Full-day kindergarten NA NA Same as EB
% disabled 12% 9.4% 2.6% less than EB
% poverty (free and reduce-
price lunch)
50% 40% 10% less than EB
% ELL 10% 0% 10% less than EB
% minority (non-White) 30% 90% 60% greater than EB

204
Personnel Resources for the Leadership Academy
This section compares the EB prototypical high school to the relative amounts of
personnel resources allocated to the leadership academy at the regular high school in
various staffing categories for school year 2010-2011. The allocation levels for FTE and
dollar category resources to implement the academy are significantly lower than
adequacy recommendations of the EB model, with the exception of administrator
positions allocated to the academy.
The allocation level to adequately staff a high school unit the relative size of the
leadership academy with a principal is equivalent to the 1.0 FTE included in the
Evidence-Based Model. However, the 0.0 school site secretaries allocated to the
academy are significantly lower, by 100%, than the recommendation of 0.9 FTE for
school site secretaries included in the EB school. Although the academy is not allocated
with clerical staff specifically assigned to support the program, the academy remains part
of the school and therefore receives the same administrative support available to all
academies at the site.
Significant differences exist among several types of teacher positions in relation
to the EB school with characteristics of the leadership academy, the largest of which is
for special education teachers. The personnel allocation for special education teachers is
100% less than the amount included in the EB school. The academy allocates 0.0 FTE to
teach students with learning and mild disabilities, a difference of 1.2 FTE less than the
1.2 special education teachers recommended by the Evidence-Based Model.

205
Although the difference is not as substantial as with special education teachers,
the relative level of personnel resources for core teachers, pupil support staff, and
specialist teachers in the leadership academy is nevertheless significant. The personnel
allocation for core teachers is 44.8% less than the EB school. The 4.0 core teacher
positions is allocated to the academy is 3.25 FTE less than the 7.25 core teachers
recommended by the Evidence-Based Model. Moreover, the personnel allocation for
pupil support staff is 30% less than recommendations of the Evidence-Based Model. The
1.0 pupil support staff position allocated for a high-risk counselor for the academy is 0.4
FTE less than the 1.4 pupil support staff included in the EB school. The high-risk
counselor focuses solely on supporting students in the academy rather than required to
assume additional responsibilities outside of the academy as previously the case. Finally,
the personnel allocation for specialist teachers is 16.7% less than the EB school with
characteristics of the academy. The 2.0 specialty teacher positions for elective courses in
the academy is 0.4 FTE less than the 2.4 specialist teachers recommended by the
Evidence-Based Model.
The relative allocation levels for extra-help strategies and dollar category
resources at the leadership academy are equally less, by 100%, than the recommendations
for each category included in the EB school with characteristics of the academy. The
academy allocates 0.0 FTE for each strategy, relative differences of 0.76 FTE less for
extended day and summer school and 0.72 FTE less for tutoring in comparison to
recommendations of the Evidence-Based Model. Also, the academy allocates $0 for each
dollar-per-pupil category, differences of $250 per pupil ($45,250) less for student

206
activities and technology and also $175 per pupil ($31,675) and $50 per pupil ($9,050)
less for instructional materials and professional development respectively. Table 13
shows a comparison of school personnel resources of the academy at the regular high
school with the Evidence-Based (EB) Model’s prototypical high school for school year
2010-2011.
Table 13

Comparison of Personnel Resources for the Leadership Academy with Evidence-Based
(EB) Model Prototypical High School (SY 2010-2011)
Staffing
Category
EB Prototypical High
Schools
EB School
with
Characteristics of
Leadership
Academy
(181)
Leadership
Academy
Leadership
Academy – EB
Comparison
Core Teachers 24 7.25 4.0
(6.0 PTT)
3.25 FTE (44.8%
less than EB)
6.0 (Part-time
teachers)
Specialist
teachers
8.0 (33% greater) 2.4 2.0 0.4 FTE (16.7%
less than EB)
Instructional
Facilitators/
mentors
3.0 0.9 0.0 0.9 FTE (100%
less than EB)
Tutors for
struggling
students
3.0 (1.0 for every 100
poverty students)
0.72
(72 students)
0.0

0.72 FTE (100%
less than EB)

Teachers for
ELL students

0.60 (Additional 1.0
for every 100 ELL
students)
0
(0 students)
0.0 0.0 FTE (same as
EB)
Extended day 2.5 0.76 0.0 0.76 FTE (100%
less than EB)
Summer School 2.5 0.76 0.0 0.76 FTE (100%
less than EB)
Learning and
mildly disabled
students
Additional 4.0
professional teacher
positions
1.2
(17 students)
0.0 1.2 FTE (100%
less than EB)

207
Table 13, Continued
Staffing
Category
EB Prototypical High
Schools
EB School
with
Characteristics of
Leadership
Academy
(181)
Leadership
Academy
Leadership
Academy – EB
Comparison
Severely
disabled
students
100% state
reimbursement minus
federal funds
NA 0.0 NA
Teachers for
gifted students
$25/student $4,525 $0/pupil
0.0
$25/pupil or $4,525
(100% less than EB)
Vocational
education
No extra costs NA 0.0 NA
Substitutes 5% of previous
personnel items
0.7 0.0 0.7 FTE (100% less
than EB)
Pupil support
staff
5.4 (1.0 for every 100
poverty students plus
1.0 guidance/250
students)
1.4
(72 students)
1.0 0.4 FTE (30% less
than EB)
Non-
instructional
aides
3.0 0.9 0.0 0.9 FTE (100% less
than EB)
Librarian/Media
specialists
1.0 librarian
1.0 library technician
0.3 librarian
0.3 tech
0.0 0.3 FTE (100% less
than EB)
0.3 FTE (100% less
than EB)
Principal 1.0 1.0 1.0 Same as EB
School site
Secretary
3.0 0.9 0.0 0.9 FTE (100 % less
than EB)
Professional
Development
Included above:
Instructional coaches,
planning and prep
time, 10 summer
days
Add’l: $50/pupil for
other PD expenses –
trainers, conferences,
travel, etc.
$9,050 $0/pupil $50/pupil or $9,050
(100% less than EB)
Technology $250/pupil $45,250 $0/pupil $250/pupil or
$45,250 (100% less
than EB)
Instructional
materials
$175/pupil $31,675 $0/pupil $175/pupil or
$31,675 (100% less
than EB)
Student
activities
$250/pupil $45,250 $0/pupil $250/pupil or
$45,250 (100% less
than EB)

208
This part of the discussion compares the relative amount of FTE at the leadership
academy with the Evidence-Based (EB) 1 Plus 1:7 Model Alternative High School for
school years 2010-2011. The personnel resource levels at the academy are significantly
less, by 70.4%, than the recommendations of the EB 1 Plus 1:7 Model for alternative high
schools. The 7.0 FTE for teaching and support staff and 1.0 FTE for an administrator is
19.0 positions less than the 27.0 FTE included in the EB alternative high school. In
addition to the FTEs for teaching and support staff and administrator positions, the
academy allocates 6.0 part-time teachers to assist teachers in the classroom. The dollar
category resources—professional development, technology, instructional materials, and
student activities—remain the same in the EB 1 Plus 1:7 Model for the academy as the
recommendations in the EB prototypical high school. Table 14 shows a comparison of
personnel resources for the academy with the Evidence-Based (EB) 1 Plus 1:7 Model
alternative high school for school year 2010-2011.
Table 14

Comparison of Personnel Resources for the Leadership Academy with Evidence-Based
(EB) 1 Plus 1:7 Model Alternative High School (SY 2010-2011)
Staffing
Category
EB 1+1:7 Model
Alternative High
Schools
ALE 1+1:7 Model
School
with
Characteristics of
Leadership
Academy
(181 students)
Leadership Academy
Actual

Teaching and
support staff
1.0 FTE for every 7
alternative education
students
26.0 7.0
(6.0 PTT)
Administrator 1.0 FTE (priced at the
level of an assistant
principal)
1.0 1.0

209

Lessons Learned
Key elements and themes based on the 10 Strategies framework from Doubling
Student Performance are used to highlight the lessons learned from studying the regular
high school and leadership academy. The data analyzed above does not contain evidence
of each of the 10 strategies; therefore, this section will summarize the improvement
process by using the framework to discuss the strategies for which data was collected.
Analyze Student Performance Data
The high school collects and analyzes student performance through the
implementation of the Standards Based Change (SBC) process that uses data from
various sources including the Hawaii State Assessment (HSA), DSI quarterly
assessments, and teacher developed formative assessments. The high school also
conducts an annual evaluation of the leadership academy that includes student
performance indicators such as graduation, attendance, and dropout rates.
Implement an Effective Curriculum and Instructional Program
The curriculum and instruction program at the high school focuses on improving
students’ basic skills. The high school implements a variety of strategies to differentiate
reading and math instruction and interventions across content areas, some of which
incorporate technology applications and computer software to enhance instructional
curriculum. A curriculum that incorporates project-based learning is also a major point
of emphasis at the school.

210
Use Formative Assessments to Make Data-Based Decisions
Decisions that have implications for curriculum, instruction and assessment are
anchored in data analysis as part of the SBC process at the high school. Furthermore,
analysis of data from formative quarterly assessments is a norm at the school, which is
embedded in the improvement of instructional practices, current strategies and course
curriculum particularly in the area of math.
Implement Ongoing Professional Development
Professional development at the high school is ongoing and focuses on
implementing reading interventions and instructional strategies for special education
teachers through Literacy Institutes and Literacy Learning Networks including classroom
observation and mentoring to implement assessments that target IEP goals and objectives,
and also Math Institutes and Math Learning Networks for 9
th
and 10
th
graders on
instructional strategies for differentiation, multiple forms of assessment, mentoring.
Additionally, the high school implements ongoing professional development by
providing teachers with time to reflect and document their professional learning on the
following topics:
• AVID Strategies
• Standards Based Change Process
• Project Based Learning
• Inclusion Strategies/Co-Teaching
• Rigor/Relevance Framework
• Critical Thinking

211
• Learning Styles
• Differentiated Instruction
• Reading and Math Interventions
• Edline/Web Locker
Provide Extra-Help for Struggling Students
The high school provides extra help for struggling students through the
implementation of tutoring, extended day, and summer school. The extended day
program incorporates technology and online applications for credit recovery programs for
students.
Create a Collaborative and Professional Culture
A collaborative and professional school culture is promoted at the high school
through professional learning communities. The PLCs are organized into grade level and
career-focused groups that bring teacher together from multiple disciplines to develop
and implement integrated curriculum based on student data.
Use Research-Based and Proven Strategies
The high school implements research-based and proven strategies such as small
school/learning communities, inclusion, and project-based learning. Additionally, the
school implements strategies for integrating technology tools into curriculum and
instruction for students to access information, manipulate data, and stimulate creativity.
The high school also has increased the use of interactive whiteboards and clickers. For
teachers, the high school is expanding the usage of Edline Web Locker and EPortfolio

212
software to display student work online and also continues use of Achieve 3000 as
supplemental software program to collect and analyze data to adjust instruction.
Develop Talent and Human Capital
Talent and human capital is developed through the hiring and professional
development of highly qualified teachers. Additional support is provided through the
Mentor Program to help teachers become highly qualified and improve their overall
classroom practice.
Implement Widespread and Distributed Instructional Leadership
The high school demonstrates widespread and distributed instructional leadership
in a variety of ways. Teacher leaders facilitate the collaborative development of
curriculum in teams and academies, and others are given opportunities to influence
processes associated with the development, implementation, evaluation, and ongoing
improvement of the leadership academy. Teachers from the math department take the
lead on the development and implementation of school-wide math interventions.
Members of the technology cadre attend a national conference for technology integration
and then train and mentor colleagues on technology integration. At the district level,
resource teachers train teachers in 9
th
and 10
th
grade academies on strategies for
differentiating instruction in inclusion classrooms, which builds the leadership capacity
of the district system.
Impact of Recent Budget Reductions
The personnel resource levels at the regular high school largely remain the same
between school year 2010-2011 and 2011-2012 as a result of the state’s budget

213
reductions that occur in the summer of 2011 and are altogether unchanged for the
leadership academy. Although the number of FTE for vice-principals at the high school
decreases by 25% from 4.0 to 3.0 positions, in some instances the relative amounts of
FTE and dollar category resources increase, the largest of which is the proportion of ELL
teacher positions allocated from one school year to the other. The amount of positions
for ELL teachers increases from 0.0 to 1.0 FTE and for special education part-time
teachers by 12.5%, from 7.0 to 8.0 positions. The amount of dollar category resources
for professional development also increases by 64.8% or $87,732, from $47,750 in SY
2010-2011 to $135,482 in SY 2011-2012. It is important to consider the possibility that
the increase in professional development resources is attributed to the reallocation of
existing resources rather than necessarily an increase in the school’s overall budget.

214
APPENDIX I:
CASE STUDY—ALTERNATIVE LEARNING ENVIRONMENT (ALE) SCHOOL
The ALE school originated in the house of an innovative teacher 45 years ago and
has helped thousands of at-risk students over the years to earn a regular high school
diploma giving them a fighting chance at pursuing the education and careers of their
dreams. Today, the ALE currently resides in a humble, wooden-trailer-style building on
the north side of central Oahu. The school is located in the business district of a town
with a population of approximately 16,500 in July 2007. Prior to increasing urbanized
development, the region was predominantly used for agriculture, and the area continues
to host multiple military facilities. In 2009, the median household income of residents in
the area was $52,153.
The district in which the school is located serves students from elementary
through adult education. The district, which is separated into 2 complex areas, has 30
elementary schools, 5 middle schools, 1 intermediate school, 1 high and intermediate
school, 5 high schools, and 2 adult schools. The total enrollment among the 6 schools
that serve high school students is 9,547 students, and an average of 83.1% of those
students were identified as minority or non-White, 30.3% were low-income , 4.5% were
classified as ELL, and 11.22% were SPED in school year 2010-2011 (State of Hawaii,
2011). The ALE school specifically served 261 at-risk students in grades 9 through 12
during the same school year, 92% of the students were classified as minority or non-
White, 39% eligible for free and reduce-price lunch, 0% were ELL, and 15% were SPED
(ALE School Records, 2012).

215
The improvement process that is examined in this case study began as a
grassroots response to a community concern nearly half a century ago, and today
continues to effectively address the problem of student dropout in spite of statewide
budget reductions and resource reallocations that threaten its very existence each school
year. This case study compared the resource allocation levels necessary to sustain the
implementation of the ALE school with the Evidence-Based (EB) Model’s prototypical
high school and the 1 Plus 1:7 Model for alternative schools. Resource level
comparisons between all sites examined in the study are presented in Table 4.5.
Introduction of the Key Elements of the Improvement Process
The concept for the ALE school was as a response to a growing concern in many
communities across the country. In the late 1960s, students nationwide were failing
school and dropping out at increasing rates from middle- and upper middle-class families,
not only from low socioeconomic levels (Duke & Muzio, 1978). Rather than attending
school, these truant students could be found loitering in front of stores and businesses in
some communities. Subsequently, they fell behind in credits by missing school to the
extent that the regular school day did not provide enough hours for them to earn the
requisite credits to graduate. To address the increasing number of students failing and
dropping out of school, the concept for the ALE school began to take form in the mind of
a teacher who envisioned a solution unlike any other at the time during the civil rights
movement in the United States.
The history of the ALE school began with a social studies teacher in the district
who recognized students were failing and was not satisfied with the support the school

216
provided, or lack thereof. The improvement process was a bottom-up attempt to address
the problem, rather than one initiated by the district or central office. Upon returning
from a training conducted on the mainland on the “storefront” model of alternative
education, the teacher organized students and staged a demonstration at his intermediate
school with students picketing and holding signs they made expressing their
dissatisfaction with their school. The school and district insisted that he take his
philosophy and teach elsewhere. Soon thereafter, the ALE school was started from his
home. Building upon this notion of gathering the youth from storefronts to teach them
through an outreach program or alternative learning environment (ALE), the ALE school
was able to extend the regular school day to allow students more time to earn and recover
credits toward graduation. In the beginning, the ALE school was sparsely funded and
struggled to find a permanent location. As referrals increased, it moved to a larger
location at a church in the local community.
In 1971, the alternative learning environment concept was brought to scale in
Hawaii with the statewide implementation of Comprehensive School Alienation Program
(CSAP). The ALE school, along with other programs across the state, received public
funding directly from the state DOE based on student data collected from each site that
included indicators such as the number of students served and rates of graduation and
attendance. The funding source for ALEs was secure with CSAP. Eventually, the ALE
school was established where it currently resides today. In 1980, the ALE program
served approximately 100 students with 3.0 FTE allocated for classroom teachers, 1.0
FTE for a program coordinator, and part-time teacher (PTT) positions to implement the

217
extended day program. The ALE school, during this time, provided students with
extended day services everyday using personnel resources allocated through CSAP;
however, this is not the case today.
The implementation of the weighted-student formula (WSF) in school year 2005-
2006 changed the stability of the ALE school and others like it that no longer received
funding directly from the state. Instead, the WSF prompted the reallocation of resources
directly to schools rather than designating them to ALEs as previously practiced.
Reallocated resources under ‘the weight’ are then used at the discretion of school
principals. Therefore, the personnel resources an ALE receives, if any, become
dependent upon the decisions of principals and their leadership teams to support ALEs
versus competing priorities and other approaches to support struggling students.
The implementation of the ALE school including extra-help strategies requires
personnel resources. The ALE does not allocate a FTE position for an administrator.
However, it currently allocates 1.0 FTE for a counselor to provide pupil support and to
oversee administration of the program, 3.0 FTE for core teachers, 3.0 FTE for specialist
teacher, 2.0 FTE for special education teachers, 1.0 FTE for a school site secretary, and
$29,420 for instructional materials and supplies. To implement an extended day
program, the ALE school allocates the equivalent of 3.1 part-time teacher (PTT)
positions. The resources that the ALE school currently receives come from multiple
sources such as the legislature (6.0 FTE for teachers), two high schools in the district (2.0
FTE for special education teachers), and the school district (funding for PTTs and
instructional materials).

218
Themes of the Improvement Process
The ALE school started with a teacher who felt strongly enough about the
problem of failing students to challenge existing beliefs about educating at-risk students
and then take action to develop a solution that was a radical departure from the traditional
and outdated mode of doing business in schools. The teacher is retired today, but his
vision lives on through the ALE school that has evolved over the years and serves over
260 at-risk students per year from all six high schools within the district. The number of
students at the site varies over the course of the school year and also during a particular
school day. At the ALE school, the overall enrollment tends to increase over the duration
of the school year, as high schools refer students to the program. Furthermore, some
students are enrolled at the ALE school on a full-time basis while others report to their
regular schools in the daytime and then attend the ALE on a part-time basis in the late
afternoon or evening to make up credits through the extended day program. The themes
discussed in this section emerge from program wide efforts to improve the performance
of at-risk students enrolled at the ALE school.
A major theme that emerges at the ALE school is the importance of hiring highly
qualified teachers. The highly qualified teacher must have the necessary content
knowledge to teach students, but within the context of the ALE school, they must also
value a balance between content knowledge and personalization with students. The
students who are referred to the ALE school are at-risk of school failure and potentially
dropping out of school, yet many of them are extremely bright. What holds them back
are the multiple issues in their lives that other students their age do not have to endure.

219
When these issues begin to consume the resources they would otherwise be able to direct
towards their academic schoolwork, school becomes less of a priority in comparison to
the issues they face.
Effective teachers at the ALE school care for students, and take the time and extra
effort to know their students on a personal level. They know what goes on the lives of
their students and can empathize with them. At the ALE school, teachers are also patient
and willing to help students work through these issues to find success in school that they
can apply to other arenas of their lives beyond academics. Ultimately, students need to
know teachers care, and the teachers at the ALE are special individuals who embody the
dedication and commitment necessary to work with the unique and challenging
circumstances at-risk students face. Teachers at the school want to work there and
understand the importance of positive relationships with students as the foundation for
promoting academic success.
Another theme at the ALE school is the development of students’ basic skills in
reading and math. The instructional goal at the ALE school is for students to improve in
reading and math and experience academic success that they can build upon to pursue
their personal and career aspirations beyond high school. Several approaches are used to
emphasize this academic focus on reading and math. Classroom teachers implement
direct instruction using instructional strategies for reading and math across content areas
and also provide tutoring to develop these basic skills during the regular class period.
For these students, another important theme at the ALE is the implementation of
extra-help strategies beyond the regular school day through the extended day program

220
that likewise incorporates reading and math instruction in the curriculum. This is
significant considering the high number of students at the program who are behind in
credits and require credit recovery to earn the required number of credits for graduation.
At the ALE school, 261 students receive tutoring and 210 participate in extended day.
The ALE does not implement summer school nor provide ELL services because there are
no students who are classified as ELL at the school. However, classroom teachers
provide tutoring in basic skills during the class period and also before and after school.
Typically, tutoring will extend upon the reading and math skills taught through direct
instruction during the regular school day.
Collaboration among adults is another theme that emerges at the ALE. The
faculty and staff at the site works as one team. Although teachers deliver instruction in
content areas, they collaborate with other teachers to analyze student performance,
discuss student progress in different subjects, and identify ways to improve and
coordinate instruction to maximize student learning. The counselor plays an important
role in these conversations to provide additional information to inform instruction and
also to gather notes from teacher observations that can be used to in counseling sessions
to help students process issues that impact their academic success. In this way,
collaboration is embedded in the culture of the ALE school and occurs informally
throughout the day among the faculty and staff. The physical layout of the building
contributes to the collaborative nature of the school’s daily functioning. There are no
actual doors that separate the structure into classrooms although there are implied areas
for separate instructional spaces designated by dividers and walls. The close proximity of

221
workstations for adults contributes to the way collaboration occurs at the school.
Furthermore, the capacity to work in a collaborative environment is a key characteristic
of quality teachers at the ALE school because teachers also explore approaches to
integrate their practice through the development of interdisciplinary units.
Another theme at the ALE is the strict enforcement of a structured discipline
policy. The rules are explicit and consequences are enforced immediately along with
counseling support to address concerns when rules or agreements are breached. The ALE
school does not receive personnel resources for an administrator position. Therefore, the
counselor plays an integral part in the student support system and also the enforcement of
discipline. Disciplinary cases are approached differently based on individual
characteristics of the student in order to understand problems holistically and leverage
them as opportunities for learning and character development. Counseling at the ALE is
based upon the premise that the issues students exhibit originate in the factors that
influence them rather than students themselves being the problem. This allows the
discipline process to uncover features of problems and arrive at the best possible solution
for students.
The ALE also collects data on student performance to evaluate the extent to
which its instructional programming meets the current needs of students. The
implementation of the ALE including extra-help strategies shows positive outcomes for
at risk students as reflected in graduation and dropout rates which meet state targets
established for the school year 2010-2011. Students enrolled at the ALE school graduate
with a regular high school diploma rather than a nonstandard diploma or certificate of

222
completion. Ninety-three percent of seniors, or 109 out of 117, graduate on time, which
is 13% higher than the state standard of 80%. The attendance rate in the academy is 91%,
which is 4% below the state standard of 95%. However, the impressive dropout rate of
1%, or 4 out of 261 students, suggests students at the ALE school continue to persist
through challenges in attendance and eventually graduate. Table 15 shows the
performance of at-risk students at ALE school (ALE School Records, 2012).
Table 15

Student Performance at ALE School (SY 2010-2011)
Student Performance
Indicators
ALE School
%
Graduation Rate 93
Attendance Rate 91
Dropout Rate 1

Comparison of Resource Use with the Evidence-Based Funding Model
This section presents the school characteristics and personnel resources at the
Alternative Learning Environment (ALE) school. In the Evidence-Based Model, the
school characteristics of the prototypical high school are used to calculate personnel
resource levels within various staffing categories for schools of different sizes. By
prorating personnel resources in this way, staffing levels can be determined for an EB
school with the characteristics of the ALE school. These relative resource levels are used
in this section to analyze the allocation patterns for personnel at the ALE school.

223
School Characteristics of the Alternative Learning Environment (ALE) School
School characteristics are compared between the ALE school and the Evidence-
Based Model’s prototypical high school for school year 2010-2011 from the most to least
similar, beginning with relative amounts that are more than EB recommendations
followed by percentages that are less. First, the school configuration of the ALE school
is the same as the EB prototypical high school ranging from grades 9 to 12. The ALE
school has two characteristics that are greater than what is identified in the prototypical
high school. The percentage of students at the ALE who are disabled is 5% higher than
the 12% of disabled students identified in the EB school, and 62% greater than the 30%
of minority or non-White students. Within a larger context, it is also important to note
the percentages of minority students at other high schools within the district is 83.1%, or
equivalent to 53.1% greater than the prototypical high school. There are three
characteristics of the ALE school that are less that the prototypical high school. In school
year 2010-2011, the ALE does not serve ELL students, which is 10% less than the EB
school. In relation to the district, the percentage of ELL students at other high schools
within the district is 4.5%, or equal to 5.5% less than the prototypical high school. The
percentages of students who are eligible for free and reduce-price lunch at the ALE
school are 11% less than the 50% EB consideration, and 30.3% among all high schools in
the district, which equivalent to 19.7% less than the prototypical high school.
Furthermore, the enrollment at the ALE school is 56.5% less than the prototypical high
school.

224
Also important to note is the number of teacher workdays at the ALE school is
determined through collective bargaining between the Hawaii State Teachers Association
(HSTA) and the Hawaii State Department of Education (HIDOE). Each site in the
sample for the study is funded and administered through the HIDOE and therefore
includes the same number of teacher workdays and professional development (PD) days.
The HSTA contract includes 180 teacher workdays and zero professional development
(PD) days as a result of state furloughs that eliminate 10 professional development days
implemented prior to state budget reductions. The number of teacher workdays in the
HSTA contract is 20 teacher workdays or 10 percent less than EB and 10 PD days or 100
percent less than the 10 PD days included in the EB prototypical high school. Table 16
shows a comparison of school characteristics of the ALE school with the Evidence-Based
(EB) Model’s prototypical high school for school year 2010-2011.
Table 16

Comparison of Characteristics of ALE School with Evidence Based (EB) Model
Prototypical High School (SY 2010–2011)

School Element
EB Prototypical High
Schools

ALE School

ALE School – EB
Comparison
School configuration 9-12 9-12 ALE School has same
configuration as EB
School size 600 261 56.5% less than EB
Number of teacher
workdays
200 teacher workdays,
including 10 days for
intensive training
180 days (10 PD
days cut by state
furloughs)
20 teacher workdays
or 10% less than EB
10 PD days or 100%
less than EB
Full-day kindergarten NA NA Same as EB
% disabled 12% 17% 5% greater than EB
% poverty (free and
reduce-price lunch)
50% 39% 11% less than EB
% ELL 10% 0% 10% less than EB
% minority (non-
White)
30% 92% 62% greater than EB

225
Personnel Resources for the Alternative Learning Environment (ALE) School
This section compares the EB prototypical high school to the relative amounts of
personnel resources allocated to the ALE school in various staffing categories for school
year 2010-2011. The allocation levels for FTE and dollar category resources for the ALE
school are significantly lower than adequacy recommendations of the EB model, with the
exception of positions for special education teachers.
The ALE does not allocate a position for an administrator. The personnel
allocation for principal positions is 100% less than 1.0 FTE principal position included in
the EB school with characteristics of the ALE school. . The ALE allocates 1.0 FTE for a
school site secretary. The allocation level to adequately staff a high school the relative
size of the ALE school with school site secretaries is 23% (0.3 FTE) less that the 1.3
positions included in the EB prototypical high school
The personnel resource levels, to adequately staff the ALE school with teachers
and support staff, are significantly less than EB recommendations for adequate resources,
except for teachers who instruct students with learning and mild disabilities. The relative
level of personnel for special education teachers is 17.6% more than the EB school. The
ALE allocates 2.0 FTE to teach students with learning and mild disabilities, a difference
of 0.3 FTE more than the 1.7 special education teachers included in the EB school. Other
staffing categories for teachers are less than the EB school, the largest of which is for
core teachers. The personnel allocation for core teachers is 71.2% less than the EB
school with characteristics of the ALE. The ALE allocates 3.0 FTE to teach English,
social studies, math, and science, a difference of 7.4 FTE less than the 10.4 core teachers

226
included in the EB school. Although not as pronounced as with core teachers, the
relative level of personnel resources for pupil support staff, teachers for students with
learning and mild disabilities and specialist teachers are nonetheless significant. The
personnel allocation for pupil support staff is 50% less than the EB school. The 1.0 FTE
the ALE allocates for pupil support staff is 1.0 FTE less than the 2.0 positions for pupil
support included in the EB school. The personnel for specialist teachers is 14.3% less
than the recommendations of the Evidence-Based Model. The 3.0 FTE the ALE allocates
to teach elective or specialty courses is 0.5 less than the 3.5 specialty teachers included in
the EB school. Lastly, 6 of the FTE positions are allocated directly from the legislature
as a result of the lobbying efforts of school and district leaders.
The relative allocation levels for extra-help strategies and dollar category
resources at the ALE school are equally less, by 100%, than recommendations for each
category in the EB school, with exception of resources for instructional materials. The
academy allocates 0.0 FTE for each extra-help strategy, 1.0 less for each category of
positions for tutoring, extended day, and summer school. It is important to note that the
ALE allocates approximately 3.1 part-time teacher positions for extended day. The
number of PTT positions are calculated by dividing the $54,130 allocated for PTTs by
$17,500 which is the average annual cost for a PTT. For dollar-per-pupil resources, the
allocation for instructional materials and supplies is 35.6% less than the EB school with
characteristics of the ALE school. The ALE allocates approximately $112/pupil or
$29,420 for instructional materials, a difference of $63/pupil and $16,255 less than the
$175/pupil or $45,675 included in the EB school. Finally, the academy allocates $0 for

227
the remaining dollar per-pupil categories, differences of $50 per pupil ($13,050) less for
professional development and $250 per pupil ($65,250) for technology and student
activities. Table 17 shows a comparison of school personnel resources of the ALE school
with the Evidence-BaseD Model’s prototypical high school for school year 2010-2011.
Table 17

Comparison of Personnel Resources for the ALE School with Evidence-Based (EB)
Model Prototypical High School (SY 2010–2011)
Staffing
Category
EB Prototypical High
Schools
EB School
with
Characteristics of
ALE School
(261)
ALE School ALE School – EB
Comparison
Core Teachers 24 10.4 3.0 7.4 FTE (71.2% less
than EB)
Specialist
teachers
8.0 (33% greater) 3.5 3.0 0.5 FTE (14.3% less
than EB)
Instructional
Facilitators/
mentors
3.0 1.3 0.0 1.3 FTE (100% less
than EB)
Tutors for
struggling
students
3.0 (1.0 for every 100
poverty students)
1.0
(102 students)
0.0 1.0 FTE (100% less
than EB)
Teachers for
ELL students

0.60 (Additional 1.0
for every 100 ELL
students)
0.0
(0.0 students)
0.0 Same as EB
Extended day 2.5 1.1 0.0
(3.1 PTT)
1.1 FTE (100% less
than EB)
3.1 (Part-time
teachers)
Summer School 2.5 1.0 0.0 1.0 FTE (100% less
than EB)
Learning and
mildly disabled
students
Additional 4.0
professional teacher
positions
1.7
(44 students)
2.0 0.3 FTE (17.6%
greater than EB)
Severely
disabled
students
100% state
reimbursement minus
federal funds
NA 0.0 NA
Teachers for
gifted students
$25/student $6,525 $0/pupil
0.0
$25/pupil or $6,525
(100% less than EB)

228
Table 17, Continued
Staffing
Category
EB Prototypical High
Schools
EB School
with
Characteristics of
ALE School
(261)
ALE School ALE School – EB
Comparison
Vocational
education
No extra costs NA 0.0 NA
Substitutes 5% of previous
personnel items
1.0 0.0 1.0 FTE (100% less
than EB)
Pupil support
staff
5.4 (1.0 for every 100
poverty students plus
1.0 guidance/250
students)
2.0
(102 students)
1.0 1.0 FTE (50% less
than EB)
Non-
instructional
aides
3.0 1.3 0.0 1.3 FTE (100% less
than EB)
Librarian/Media
specialists
1.0 librarian
1.0 library technician
0.4 librarian
0.4 tech
0.0 0.4 FTE (100% less
than EB)
0.4 FTE (100% less
than EB)
Principal 1.0 1.0 0.0 1.0 FTE (100% less
than EB)
School site
Secretary
3.0 1.3 1.0 0.3 FTE (23% less
than EB)
Professional
Development
Included above:
Instructional coaches,
planning and prep
time, 10 summer
days
Additional: $50/pupil
for other PD
expenses – trainers,
conferences, travel,
etc.
$13,050 $0/pupil $50/pupil or
$13,050 (100% less
than EB)
Technology $250/pupil $65,250 $0/pupil $250/pupil or
$65,250 (100% less
than EB)

Instructional
materials
$175/pupil $45,675 $112/pupil
($29,420)
$63/pupil or
$16,255 (35.6% less
than EB)

Student
activities
$250/pupil $65,250 $0/pupil $250/pupil or
$65,250 (100% less
than EB)

229
This section compares the relative amount of FTE at the ALE school with the
Evidence-Based (EB) 1 Plus 1:7 Model Alternative High School for school years 2010-
2011. The personnel resources levels at the ALE for school years 2010-2011 are 73.7%
less than recommendations of the EB 1 Plus 1:7 Model for alternative high schools. The
10.0 FTE the ALE allocates for teaching and support staff and 0.0 FTE for an
administrator position is 28 positions less than the 38 FTE included in the EB alternative
high school. In addition to the FTEs for teaching and support staff and administrator
positions, the ALE allocates the equivalent of 3.1 part-time teachers to implement
extended day for struggling students. The dollar category resources—professional
development, technology, instructional materials, and student activities—remain the
same in the EB 1 Plus 1:7 Model for the ALE as the recommendations in the EB
prototypical high school. Table 18 shows a comparison of personnel resources for the
ALE school with the Evidence-Based (EB) 1 Plus 1:7 Model alternative high school for
school year 2010-2011.
Table 18

Comparison of Personnel Resources for the ALE School with Evidence-Based (EB) 1
Plus 1:7 Model Alternative High School (SY 2010-2011)
Staffing
Category
EB 1 Plus 1:7 Model
Alternative High
Schools
ALE 1+1:7 Model
School
with
Characteristics of
ALE School
(261 students)
ALE School
Actual

Teaching and
support staff
1.0 FTE for every 7
alternative education
students
37.0 10.0
(3.1 PTT)
Administrator 1.0 FTE (priced at the
level of an assistant
principal)
1.0 0.0

230
Lessons Learned
Key elements and themes based on the 10 Strategies framework from Doubling
Student Performance are used to highlight the lessons learned from studying the ALE
school. The data analyzed above does not contain evidence of each of the 10 strategies;
therefore, this section will summarize the improvement process by using the framework
to discuss the strategies for which data was collected.
Set Ambitious Goals
The high school maintains high academic standards for all at-risk students that
align with state requirements for a high school diploma and prepare them for mainstream
into the regular high school setting.
Implement an Effective Curriculum and Instructional Program
The high school implements an effective curriculum and instruction program that
includes reading and math strategies across content areas through direct instruction to
improve students’ basic skills.
Provide Extra-Help for Struggling Students
Classroom teachers provide tutoring in the basic skills during the class period to
supplement the direct instruction they implement that focuses on developing reading and
math skills. The ALE also implements and extended day program to provide students
with more time to earn and recover credits toward graduation.
Create a Collaborative and Professional Culture
The ALE creates a collaborative and professional culture through analysis of
student performance data in the content areas to inform improvements in instructional

231
practice and counseling services. Teachers also engage in collaborative development of
integrated projects.
Use Research-Based and Proven Strategies
The ALE school applies research-based approaches that emphasize the
development of positive relationships that create a safe and nurturing learning
environment for students. Conversations between students and adults are informal and
clearly show that teachers know students and their families on a personal level. The
adults know what is going on in students’ lives and know what is important to them.
These one-to-one interactions help to create a sense of belonging for students and also
increase accountability when students are aware that teachers are in close communication
with their families. Teachers and counselors can also leverage what they know about
students to develop personalized consequences tailored to each student’s likes and
dislikes. Observation of the interactions between adults and students clearly demonstrate
that healthy relationships are valued and embedded in the culture and have a positive
impact on students at the ALE school.
Impact of Recent Budget Reductions
The personnel resource levels the ALE allocates for teaching and support staff,
administrator positions, and dollar-per-pupil categories remain the same from SY 2010-
2011 to SY 2011-2012.

Abstract (if available)

Abstract The problem of students dropping out of school continues today in schools and districts across the nation, particularly for students whose needs are not being met in regular school settings. Therefore, the development of standards-based systems in alternative learning environments requires funding and resources that match or exceed those of traditional schools. It is no longer sufficient to merely focus on equitable inputs, as is the case with the implementation of the weighted student formula. Rather, we must begin analyzing how resources are used so that we may provide educational programming that produces adequate outputs for all students. ❧ The purpose of the study was to compare the combined impacts of the weighted student formula and the state’s recent budget reductions on adequacy levels, student characteristics, student performance, and instructional programming in public schools. The study compared two high school sites, including a district-administered alternative learning environment (ALE) and a regular high school, both of which served struggling students in grades 9–12 who were at risk of school failure and of potentially dropping out of school. The study was designed as a mixed-method case study that examined data, from interviews, district records, and school documents, using adequacy frameworks including the Evidence-Based Model (Odden & Picus, 2008) and the 10 Strategies Framework for Doubling Student Performance (Odden, 2009). Although the study was limited by the scope and sample size of the study, findings showed that personnel resource levels largely remained the same for at-risk programs between school years 2010–2011 and 2011–2012. However, staffing levels were consistently less than the adequacy levels recommended by the Evidence-Based Model. Despite inadequate resources, schools continued to implement instructional programming that reinforced the development of the basic skills students needed to achieve standards and graduate with a diploma. The implementation of programming at the sites also promoted adult learning and built leadership capacity through professional collaboration and analysis of student performance data. Although graduation and dropout rates were not considered proxies for student learning, they provided evidence that schools were fulfilling the purpose for which they were developed—to help students persist toward graduation. ❧ The study concluded that educational leaders were doing everything within their power to stabilize resources for struggling students, amid shrinking budgets and funding reallocations of the weighted student formula, by redirecting resources to programs for at-risk students and lobbying for staff positions at the legislature. Furthermore, the fact that these programs produced positive results in spite of inadequate resources was a testament to the commitment and hard work of teachers and staff at each site. Notably, positive gains cannot be expected by merely reallocating inadequate funding. Therefore, findings from the study are important for multiple stakeholders to promote ongoing evaluation using adequacy frameworks to ensure that schools and districts receive the adequate funding and resources necessary to help all students meet rigorous academic standards.

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Asset Metadata

Creator Shodai, Kyle Y. (author)

Core Title Adequacy in education: an evidence-based approach to resource allocation in alternative learning environments

School Rossier School of Education

Degree Doctor of Education

Degree Program Education (Leadership)

Publication Date 07/30/2012

Defense Date 04/26/2012

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

Tag adequacy,alternative education,Education,evidence-based,OAI-PMH Harvest,resource allocation,staffing

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Picus, Lawrence O. (committee chair), Brewer, Dominic J. (committee member), Sundt, Melora A. (committee member)

Creator Email kyleshodai@gmail.com,kyleshodai@hotmail.com

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c3-75209

Unique identifier UC11289848

Identifier usctheses-c3-75209 (legacy record id)

Legacy Identifier etd-ShodaiKyle-1057.pdf

Dmrecord 75209

Document Type Dissertation

Rights Shodai, Kyle Y.

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