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School leaders' use of data-driven decision-making for school improvement: a study of promising practices in two California charter schools

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School leaders' use of data-driven decision-making for school improvement: a study of promising practices in two California charter schools

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SCHOOL LEADERS’ USE OF DATA-DRIVEN DECISION-MAKING FOR
SCHOOL IMPROVEMENT: A STUDY OF PROMISING PRACTICES IN
TWO CALIFORNIA CHARTER SCHOOLS

by

Guadalupe H. Simpson

_________________________________________________________

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 2011

Copyright 2011 Guadalupe H. Simpson

ii
DEDICATION
To my children Katherine and Derek who will always have my unconditional
love.

iii
ACKNOWLEDGEMENTS
This dissertation would not have been possible without the patience and
guidance of Professor Priscilla Wohlstetter my committee chairperson. Her
commitment to school reform and her knowledge of research regarding charter
schools kept me focused on the goals and objectives of this study. Her attention to
detail and extraordinary organizational skills helped me concentrate on the important
findings of this work.
To the members of my committee my sincere gratitude: Professor Rudy
Castruita whose knowledge of school leadership taught me that the art of
compromise was as important as having a vision that every child is entitled to an
equitable education. The awareness and research gained in your course is
continuously shared with my students. To Dr. Sylvia Rousseau whose life goal to
close the achievement gap has contributed to my focus as a school leader. I admire
your determination to provide every child with the education they deserve. To other
professors in the USC School of Education, Dr. Stuart Gothold, Dr. Gabriela Mafi
and Dr. Courtney Malloy I am thankful for your support, advice and inspiration. You
were all amazing professors.
Dr. William De La Torre, my mentor, whose advice inspired me to become a
professor in the California State University System. To Dr. Ilda Jimenez y West who
believed in my ability to complete this work and continuously kept me on task; Dr.
Edlyn Pena whose assistance and guidance was unfaltering; to Cassandra Jackson
whose smile and positive outlook were invaluable.

iv
I am sincerely appreciative and grateful to the administrative and teachers
leaders at Coastal Academy and Synergy Academies for allowing me to experience
innovation and to observe school sites that use data-driven decision-making as a tool
to unconditionally focus on student learning and to improve the instructional
program. Your work is significant to educational reform.
This dissertation would not have been written without the support of my
family. I am appreciative to my daughter Katherine for her encouragement and
giving me hope when I needed it; to my son Derek for not allowing me to lose
prospective on the purpose of my study and for his work on all the tables and figures.
Finally, I wish to thank my husband for his support in my endeavor to obtain a
doctoral degree and in his never-ending confidence in me through this journey.

v
TABLE OF CONTENTS
Dedication ii
Acknowledgements iii
List of Tables vi
List of Figures vii
Abstract viii
Chapter One: Overview of the Study 1
Chapter Two: Literature Review 17
Chapter Three: Methodology 47
Chapter Four: Findings 61
Chapter Five: Conclusion 118
References 140
Appendices 151
Appendix A: Contents of the Compendium: Types of Data to be 151
Collected
Appendix B: Principal Pre-Site Interview Protocol 152
Appendix C: On-Site Principal Interview Protocol 154
Appendix D: Other School Leader - Interview Protocol 157
Appendix E: Professional Development Observation Protocol 160

vi
LIST OF TABLES
Table 1. Identified Barriers to Use of Data-Driven Decision-Making 36
Table 2. Triangulation Information Across Data 60
Table 3. Demographic Profile of Coastal Academy (2010-2011) 65
Table 4. Demographic Profile of Synergy Charter Academy (2010-2011) 88
Table 5. Demographic Profile of Synergy Kinetic Academy (2010-2011) 89

vii
LIST OF FIGURES
Figure 1. School Leaders’ Use of Data for Planning and School 12
Improvement
Figure 2. Theory of Action: Coastal Academy School Leaders’ Use of 69
Data-Driven Decision-Making
Figure 3. Theory of Action: Synergy Academies: School Leaders Use of 96
Data-Driven Decision-Making

viii
ABSTRACT
The current interest in using data-driven decision-making in schools has
focused on how best to use student achievement data to meet the demands of current
accountability requirements. The purpose of this study was to investigate promising
practices specific to school leaders’ use of data-driven decision-making for school
improvement at two California charter schools.
The following data sources were included in this qualitative case study that
applied descriptive research and design: interviews of charter school principals and
other administrators, interviews with teacher leaders, review of archival documents,
and observation of professional development meetings related to the use of data to
influence teaching and promote student achievement. The case study answered the
following questions: How do charter school leaders use data for decision-making and
school improvement? How are resources allocated to effectively implement the use
of data for decision-making and school improvement? What challenges have charter
schools faced in implementing the use of data for decision-making and school
improvement and how were they addressed? What evidence exists that the use of
data for decision-making resulted in positive educational outcomes?
The study found that the greatest impact of using data-driven decision-
making was on results of high student achievement and on the improvement of
teaching strategies to meet student needs. By establishing a strong data-driven school
culture, daily classroom observations, professional development, and providing

ix
teachers with ongoing support, school leaders experienced a profound impact on
student achievement.
In order to implement the effective use of data-driven decision-making the
findings suggested several practical strategies. First, the total school community
(parents, students, teachers, school leaders) had a common understanding of how
data was used and analyzed to meet individual student learning needs. Additionally,
the principals and other school leaders embraced the data-driven decision-making
process, had strong skills in curriculum and instruction, provided ongoing
professional development, and analyzed data with connections to improved teaching
strategies and improvement of student achievement. Classroom visits were
conducted on a daily basis allowing principals to provide immediate support or
model a lesson if necessary. Finally, a culture of trust and collaborative inquiry was
established where teachers were able to learn, question and share the relationship
between data and good teaching practices.
The findings of this study have been incorporated into the Center on
Educational Governance Web-Compendium of Promising Practices designed to
disseminate innovative best practices beyond the school site and assist other policy
makers and educators who wish to gain knowledge on leaders’ use of data-driven
decision-making for school improvement.

1
CHAPTER ONE
OVERVIEW OF THE STUDY
Background to the Problem
Raising academic standards and increasing student achievement in public
schools have been national priorities since the 1980s, when poor academic
performance received national attention after the publication of two major reports: A
Nation at Risk (1983) and the Carnegie Task Force Report on Teaching (1986).
These reports called for higher academic standards, with specific attention on
improving student achievement. In turn, this led to an increased concern about the
lack of academic competitiveness in American schools and the weaknesses in the
public educational system (Jazzar & Algozzine, 2006). Public pressure on legislators
at both the state and federal levels resulted in a call for improved and more
comprehensive educational standards, which in turn, mandated school administrators
and teachers to accelerate the gains in student achievement. In the past 25 years, a
number of educational reform efforts to enhance performance and accountability
have been initiated with great determination and energy (Jazzar & Algozzine, 2006).
The path of educational reform has taken many twists and turns from the
1980s to the present day. These reforms include: state accountability systems; clearly
defined state standards and assessment systems; shared decision-making and local
school-based management; charter school legislation; and most recently, at the
federal level, the No Child Left Behind (NCLB) Act of 2002. Waves of restructuring
efforts have been undertaken, such as the “strategic alignment of the chief

2
components of education, establishment of academic goals, curricula, instruction,
and exams to arrive at heightened accountability” (Jazzar & Algozzine, 2006, p. 88),
but based upon numerous state and national studies little effective change has
occurred. NCLB represents the biggest step toward bringing accountability to
schools and requires that all students, regardless of socio-economic status or
ethnicity reach the level of proficiency or above in reading and mathematics by 2014
(Jazzar & Algozzine, 2006). Data must be disaggregated by subgroup (gender,
ethnicity, English learners, and students with disabilities) and all subgroups must
meet the federally-mandated Annual Yearly Progress (AYP) standards. Furthermore,
NCLB uses the chartering process as a way to reinvent failing schools (EdSource,
2006). The critical elements of these reforms were to hold schools, educators,
parents, and students more accountable for educational outcomes (Wells, 2002).
NCLB requires states to conduct annual assessments in reading and
mathematics for third through eighth grades in elementary through middle schools
and for the tenth grade in high schools. As a result, all states have adopted testing
and reporting procedures that provide districts with a vast array of test data. In
California mandated testing begins at the second grade. The State of California’s
data system, the Student Accountability Report Card (SARC), provides online access
to the assessment results for all student categories by county, school district, and
individual school (Hanson, 2007).
Data from the California Department of Education (CDE, 2009) suggests that
many public school students in California are not meeting academic benchmarks.

3
The Department of Education reported that of all students tested in the second
through eighth grades on the California Standards Tests (CST) for the 2009 school
year, only 46% reached at least the proficient level in language arts and 47.5%
reached at least the proficient level in mathematics. In 2009, 44.5% of high school
students reached proficiency level in language arts and 43.5% reached proficiency
level in mathematics. For the 2009 school year, 48% of all California schools failed
to reach AYP standards, and 2,796 schools were identified as being in “program
improvement status” an increase of 533 schools from the 2008-09 school year
(EdSource, 2009; National Alliance for Public Charter Schools, 2009).
The results from the CSTs indicate that California schools and policymakers
must revisit existing efforts and devise new methods and policies to improve student
achievement. Prior to NCLB, individual schools were given a measure of autonomy
over instructional methods, budgeting and staffing. As a consequence of NCLB,
individual schools are now rated as either successful or failing and thus the
responsibility for improving student achievement rests largely with districts to create
systems for ensuring local school accountability (Datnow, Park, & Wohlstetter,
2007; Halverson, Grigg, Prichett, & Thomas, 2005; Mandinach, Honey, & Light,
2006). In this era of high-stakes accountability, policymakers are under enormous
pressure to “trade off school autonomy in exchange for greater accountability”
(Wells, 2002, p. 5). The pressure created by this wave of accountability has led many
school leaders and district administrators to embrace the use of data inquiries to

4
inform their practices (Johnson, 2002). The role of charter schools that use data to
improve student achievement will be discussed in the section that follows.
The Role of Charter Schools
California continues to struggle with student achievement and has looked a
charter schools as a promising movement to contribute to school improvement
(EdSource, 2007). Charter schools were created with the idea that greater autonomy
would provide greater innovation and improved student outcomes (Wohlstetter,
Malloy, Smith, & Hentschke, 2004). Charter schools may represent a promising
venue for data-driven decision-making due to the autonomy-for-accountability
framework state and federal laws have provided. However, the current wave of
educational reform has placed charter schools at the leading edge in replacing public
schools (Ravitch, 2010).
In 1991, Minnesota launched the charter school movement when it enacted
the first charter law in the United States (Finn, Manno, & Vanourek, 2000). Charter
schools are publicly funded schools guided by a petition or contract that sets forth
goals to be accomplished by the end of a contract period, which is generally three to
five years. According to the National Alliance for Public Charter Schools (2009)
4,900 charter schools educating 1.5 million of the nation’s students opened in the
United States during the 2009-10 school year. California leads the nation in the
number of charter schools, having 786 schools that serve approximately 290,645
students (EdSource, 2009; NAPCS, 2009).

5
Findings from a 2010 study by the Center for Research on Education
Outcomes (CREDO) indicate that the typical student in a New York City charter
school learns more than their counterparts in traditional public schools in both
reading and mathematics. The study further revealed that “in math more than half the
charter schools are showing academic growth that is statistically larger than their
students would have achieved on their regular public schools” (CREDO, 2010, p. 2).
The findings from the CREDO study (2010) amplify earlier findings reported
by Hoxby et al. in their 2009 report, How New York City’s Charter Schools Affect
Achievement. The results of Hoxby’s study acknowledged:
On average, a student who attended a charter school for all of grades
kindergarten through eight would close about 86 percent of the “Scarsdale-
Harlem achievement gap” in math and 66 percent of the achievement gap in
English (Hoxby et al., 2009, p. viii).

California has instituted accountability systems such as charter school laws
that provide schools with freedom and flexibility to enhance and improve student
learning (Wells, 2002). Charter schools comply with the autonomy-for-
accountability framework because they provide autonomy in a broader accountability
context (Wells, 2002). The local autonomy of charter schools allows them to decide
the school mission; school personnel, curriculum, how resources will be deployed,
and governance structure (Brewer & Wohlstetter, 2005).
According to the authors of an early federal charter school study:
The school’s charter gives the school autonomy over its operation and frees
the school from regulations that other public schools must follow. In
exchange for the flexibility afforded by the charter, the schools are held

6
accountable for achieving the goals set out in the charter including improving
student performance (RPP International, 2000, p. 1).

Autonomy coupled with accountability empowers charter schools to make site-based
curricular choices and act as laboratories of innovation with the “potential to
improve student performance through the development of high-quality learning
communities, and more rigorous curricula” (Wohlstetter & Griffin, 1998, p. 2).
The promise of charter schools was that they would be laboratories for
promising practices disseminated beyond the individual school that created them
causing a chain reaction as other charter and district run schools adopt such practices
(Bulkley, 1998; Wohlstetter & Kuzin, 2006). If charter schools produce student gains
as a result of innovation, promising practices will likely spread to other public
schools (Brewer & Wohlstetter, 2005; U.S. Department of Education, 2004). It is
important to examine the extent to which such innovations in using data for planning
and improving school performance have been successfully implemented by charter
school leaders. In sum, by examining new ideas and practices in data-driven
decision-making produced in charter schools, the feasibility and promise for other
schools can be ascertained. The following section will describe the use of data by
school leaders’ for planning and assessing school improvement.
Use of Data by School Leaders
Since the inception of NCLB the school leaders’ role has changed
dramatically from the managerial responsibilities of maintaining facilities, ensuring
student discipline, and meeting state reporting requirements to instructional

7
leadership (National Association of Secondary School Principals, 2002). Research
indicates that when school leaders are engaged in instructional leadership, student
achievement is more likely to occur (Murphy & Louis, 1999). Moving into the role
of instructional leader is pivotal to transforming schools into data-driven learning
communities in order to increase student outcomes. The role of an effective data-
driven instructional leader includes: collecting relevant and useful data, having
district support for the use of data, participating in professional development on how
to use data in decision-making, analyzing the use of data practices, establishing
measurable instructional goals, and restructuring the school to improve learning
through the use of data (Datnow et al., 2007; Jazzar & Algozzine, 2006; Knapp,
Swinneton, Copland & Monpas-Huber, 2006; Johnson, 2002).
Past research has shown that schools acquire a more accurate perspective of
the learning needs of students when a variety of data are collected and analyzed.
Bernhardt (2003) and other researchers have recommended that schools gather four
types of data: a) demographic data that describe the students, school staff and
surrounding community; b) student learning data including state test scores, teacher-
made examinations, teacher-assigned grades and authentic assessments; c)
perception data gathered from questionnaires, interviews, and observations from
parents, students, teachers, and communities; and d) school processes data that
describe instructional strategies and classroom practices. School districts and school
leaders are responsible for providing school staff with quality data that will allow for
quality decision-making to improve student learning (Bernhardt, 1998). Unless

8
school leaders have the knowledge, skills and district support to use the wide-range
of available data, leaders will be ill prepared to respond to the demands for
accountability (Bernhardt, 2003; Darling-Hammond & Orphanos, 2007; Datnow et
al., 2007).
A study by Armstrong and Anthes (2001) highlighted elements for effective
data use by school leaders including “having a district-wide culture that supports the
use of data for continuous improvement and leadership at the district-level that
supports using data successfully for school reform” (p. 3). The use of data and the
establishment of goals must be supported and reinforced by district support staff
(Armstrong & Athens, 2001; Datnow et al., 2007; Halverson et al., 2005; Englert,
Fries, Goodwin, Martin-Glenn, & Michael, 2004).
Consequently, if school leaders are to champion using data to increase
student achievement, investment in professional development for school
administrators regarding data-driven decision-making, use of data, and data
management systems is an essential strategy (Datnow et al., 2007; Englert et al.,
2004). School systems successful in the use of data have established structural
procedures that invest in professional development where educators are provided the
opportunity to share strategies with one another and collaborate (Armstrong &
Athens, 2001; Datnow et al., 2007). The leaders’ expertise in accessing, generating,
interpreting, managing and acting on data is contingent upon the leader receiving the
appropriate professional development and support to facilitate its use (Knapp et al.,
2006).

9
In past studies, principals assert that professional development programs need
to emphasize the relevance of data, assessment, and evaluation to student
improvement and student learning; the use of effective teaching strategies; and how
to apply data to improve student performance (Creighton, 2001; Darling-Hammond
& Orphanos, 2007; Johnson, 2002; Englert et al., 2004; Wade, 2001). Although these
studies indicated that school leaders are eager to use data for planning and school
improvement, principals cited a lack of adequate training as a barrier to effective
data use (Englert et al., 2004; Wade, 2001).
Data Informed Leadership
Numerous scholars note that the ability of school leaders to interpret and
apply data plays a major role in their using data to inform action on school
improvement (Bernhardt, 2003; Earl & Fullan, 2003; Wayman & Stringfield, 2006).
Furthermore, school leaders require training to develop data literacy, which means
developing an ability to use data effectively and wisely to support student
achievement (Knapp et al., 2006). The use of data requires an understanding not only
of the use of technological tools, but also of how to organize ideas on using data and
how to turn them into meaningful action (Knapp et al., 2006). The leader brings
participants together in the act of seeking, interpreting, and acting on the data
presented and making informed decisions that improve student learning (Knapp et
al., 2006).
Hence, the new challenge facing school leaders is establishing a culture of
data-driven decision-making, which enable them to react intentionally to data

10
provided by federal, state and district accountability systems (Datnow et al., 2007;
Halverson et al., 2005; Lachat & Smith, 2004). The process of shifting schools from
cultures of internal, individual accountability to those of external accountability is
the challenge for current school leaders given that school leaders shoulder the
responsibility of a school’s accountability and student achievement (Halverson et al.,
2005). Policymakers and the public expect school leaders to draw upon their role as
change agents to provide expected outcomes for students. School leaders have also
acknowledged the significance of using data for school improvement, but emphasize
that before committing to system-wide efforts for improvement, standards must be in
place with measurable goals for the district, school, classroom and students (Datnow
et al., 2007).
Setting and maintaining high standards for students is not a sufficient
condition for improving student achievement. High standards must be accompanied
by a system of academic support to achieve the objectives in place (Hubbard, Mehan,
& Stein, 2006). It is imperative to establish specific, measurable goals at the district,
school, and classroom level that align to content standards prior to building a
foundation to improve student achievement (Datnow et al., 2007; Jazzar &
Algozzine, 2006). Setting meaningful student achievement goals is a precondition
for using data for effective decision-making (Datnow et al., 2007). High performing
districts and schools appropriate considerable financial resources and human capital
to set instructional goals, assess student performance, and utilize a variety of

11
assessments in order to use data to make decisions about goals for academic progress
(Datnow et al., 2007; Supovitz & Taylor, 2003; Togneri & Anderson, 2003).
The school district and school leader are responsible for providing school
staff with quality data that will allow for quality decision-making to reshape the core
instructional practices of schools (Bernhardt, 1998; Johnson, 2002). Charting
standards-based assessment in order to improve instructional practices can be a
challenging and daunting process (Datnow, et al., 2007). Changing performance
standards and establishing measurable goals without fundamentally transforming the
teaching practices and processes of educators cannot lead to student academic
success (Fullan, 1993; Johnson, 2002). School leaders must lead the instructional
path, provide effective professional development and continuously support staff
efforts in using data to implement successful instructional practices that lead to
improved student achievement (Elmore, 2000; Johnson, 2002). The theory of action
linking school leaders’ use of data for planning and school improvement is
graphically depicted in Figure 1.

12

Figure 1. School Leaders’ Use of Data for Planning and School Improvement

13
Purpose of this Study
The significant educational challenges facing the nation today call for
continued research into promising practices that will lead to greater student
achievement and school success. The purpose of this study is to answer the following
research questions: (1) How do charter school leaders employ data-driven decision-
making to improve student achievement? (2) What factors influence the effective use
of data by school leaders?
This study is part of a thematic dissertation group that consisted of eight
doctoral students in education who each researched promising practices in charter
school settings in one of the following areas: (a) adult mentoring of at-risk students,
(b) increasing redesignation rates of English-language learners, (c) school leaders’
use of data for planning and school improvement, (d) teacher evaluation, (e) the
integration of academics into career/technical education, (f) the use of technology to
increase parental involvement, (g) uses of school time and (h) writing across the
curriculum. Schools selected for the study were self-nominated or nominated by
others and provided evidence of successful implementation.
Data on promising practices gathered as part of the dissertation process were
incorporated into the University of Southern California’s (USC) Compendium of
Promising Practices under the auspices of the Center on Educational Governance
(CEG). The purpose of the compendium is to document the implementation and
effects of promising practices in California charter schools (CEG, n.d.). Through the
compendium, which includes a search function, innovative practices can be widely

14
shared with other charters and district-run schools (CEG:
www.usc.edu/dept/education/cegov/).
To date, the compendium includes promising practices related to the
following topical areas: (a) arts-themed education, (b) high school reform, (c)
integration of technology into math and science, (d) literacy for English-language
learners, (e) parent involvement, (f) project-based learning, (g) teacher leadership
development, (h) school-university partnerships, (i) special education, and (j) student
discipline. By conducting a multisite case study on the use of data by school leaders
for planning and school improvement, this research provides schools, educators, and
other educational stakeholders with the strategies for improving school performance.
Significance of the Study
If American schools are to maintain a competitive edge in the global
economy, low student achievement cannot be allowed to persist. Schools must use
data effectively to generate and to examine promising practices that lead to increased
student achievement. Because they face the possibility of being closed down and
losing the consumer, charter schools have greater accountability to demonstrate
increased student achievement (Brewer & Wohlstetter, 2005) and often serve as
laboratories for new educational ideas, and have the potential to offer a substantial
amount of data on innovative practices (Hassel, 1999).
The notion that charter schools could serve as laboratories of innovation
emerged during a difficult time when American public schools lacked “good ideas”
(Hassel 1999, p. 7) and the incentives to capitalize on them. Policymakers were

15
hopeful that public schools would see the successes of charter schools and replicate
their promising practices (Nathan, 1999). However, the promising practices and
educational innovations that have been generated in charter schools are not being
shared with school districts or other learning centers (Bulkley & Fisler, 2003). For
noncharter schools to emulate charter schools as “laboratories of innovation,”
promising practices must be identified and transformed into a form useful to
practitioners (Manela & Moxley, 2002). With continued pressure from the passage
of NCLB and state accountability demands, school administrators are acknowledging
the use of data in decision-making can drive improvement in student learning (Wade,
2001). Although studies reveal a correlation between strong instructional leadership
and student achievement there is a dearth of rigorous research on how leaders
facilitate the use of data to improve instructional practices (Datnow, et al., 2007).
The finding from this thematic dissertation will be incorporated in the USC
Compendium, created in 2006 by the Center on Educational Governance, to assist
charter and public schools in the dissemination of innovative programs and practices
currently implemented in California Charter Schools (Wohlstetter & Kuzin, 2006).
Organization of the Dissertation
This dissertation is organized into five chapters. Chapter One provides a
description of the importance of using data for planning and school improvement.
Chapter Two reviews the research literature on this topic, including the factors that
promote data-driven decision-making and the challenges leaders face in using data.
Chapter Three describes the study’s research questions, design, data collection and

16
analysis processes. Chapter Four presents findings from the investigation of data use
in two charter schools in California, examining the strategies the school leaders used
to encourage data use. In sum, Chapter Five presents the key findings and
conclusions related to the study’s research questions and examine the implications of
the study for school leaders, policymakers, and researchers.

17
CHAPTER TWO
LITERATURE REVIEW
Introduction
The purpose of this study is to investigate promising practices that focus on
school leaders’ use of data for planning and school improvement in two California
charter schools. According to research by Sutherland (2004) charter schools by the
nature of their mission statements, and guided by requirements to accomplish goals
within a fixed time period, use data on an ongoing basis to improve teaching
strategies that motivate student learning, which increase student achievement. As
discussed in Chapter One, leaders using data to improve instruction play a pivotal
role in transforming schools into learning communities that have the potential to
increase student achievement. Yet an overarching challenge for many school leaders
is how to change the culture of their schools so that data are used to improve school
performance. The Springboard Schools Report (2006) asserts that decision-making
by school leaders is highly influenced by politics, intuition and feelings, rather than a
careful analysis on how to use data to influence change (Springboard Schools
Report, 2006). The fact is that “school leaders rarely examine data in a systematic
way to assess the quality of teaching and learning at their school” (Creighton, 2007,
p. 2). As national pressure for accountability continues, school districts and schools
are increasingly called to use data to make decisions regarding personnel, attendance,
intervention, student achievement, discipline and curriculum (Brunner et al., 2005;
Jazzar & Algozzine, 2006).

18
The underlying assumption of accountability policies such as No Child Left
Behind (NCLB) is that “educators know how to analyze, interpret and use data to
make informed decisions in all areas of education, ranging from professional
development to student learning” (Datnow et al., 2007, p. 10). However, such
accountability implies that decision-makers have access to data at the appropriate
levels of disaggregation. It implies that school leaders who are able to interpret these
data, have the ability to understand the information data provide and to use data
effectively to serve students (Halverson et al., 2005; Knapp et al., 2006). Using data
for planning and decision-making involves a multitude of demands that will be
discussed subsequently in the chapter.
This chapter reviews literature on the effective use of data, uncovering how
public and charter school leaders use data to make informed decisions related to
planning and school improvement. In order to identify relevant literature, a variety of
journal articles, government studies and technical reports were researched.
Presentations from the American Educational Research Association (AERA) and
papers presented at other educational conferences within the last ten years were also
included in the review. Some of the resources were education specific whereas others
were of general interest. The electronic databases searched included the Consortium
for Policy Research in Education, ERIC, Google Scholar, JESPAR, Mid-Continent
Research for Education and Learning (McREL), National Alliance for Public Charter
Schools, National Charter School Clearinghouse, the National Staff Development
Council Website, and The H. W. Wilson/Wilson Website. Examples of key words

19
used in searches for this study included, accountability, charter schools, charter
school leaders’ use of data, data use and professional development, data use in
schools, data-driven decision making, data-driven leadership education, data and
student achievement, teacher leaders and data use and principal’s use of data.
Chapter Two begins with an operating definition of data-driven decision-
making and the various data school leaders can use to inform their practices. The
next section discusses factors and conditions that facilitate effective data use. Further
discussion includes: federal government mandates, establishing state accountability
systems, district support, leadership buy-in to data use, and the effective professional
development leaders’ need to promote data use. Next the study examines
establishing a data-driven school culture, and how school leaders influence decision
rights of teachers to improve student learning. Barriers that impede data use will be
interwoven throughout the chapter. In summary, the chapter will review the relevant
literature, identify gaps, and point out the areas in need of further study.
Definition of Data
In its report on data use as a school improvement tool, Learning Points
Associates (2006) stressed that, “Before data can be used to improve decision-
making, it is important to understand exactly what data are” (p. 3). The operational
definition of “data” adopted by this study includes multiple sources of information
and knowledge used by school districts and school leaders about: student grade level,
demographics, language proficiency, state standards assessment, authentic
assessment, teacher made tests, teaching practices, homework, curriculum, grade

20
point average, school perception, and discipline (Bernhardt, 2003, 2004; Combs &
Edmonson, 2006; Mandinach & Honey, 2008). Learning Points Associates (2006)
concluded that, “Data can be defined as any information that when taken together
and analyzed can be used to produce knowledge” (p. 1) that, in this case will lead to
ongoing school change and improve student performance.
Moving Beyond Standardized Test Data
Many forms of data exist and there is consensus in the literature that data are
not solely defined as an accumulation of state standardized test scores or attendance
statistics to satisfy administrative requirements to receive federal funding or reach
the Annual Yearly Progress (AYP) required by NCLB (Bernhardt, 2004; Combs &
Edmonson, 2006; Creighton, 2007; Wayman, Conoly, Gasko & Stringfield, 2008).
Despite the multitude of available data, school leaders are focused on using state
standardized assessment data as their major source for decision-making (Creighton,
2007). Although standardized test results are important, according to Bernhardt
(2003, 2004) to begin an effective data-driven decision-making process, school
leaders should collect and analyze multiple types of data. Thus, while state-mandated
testing data is often used by school leaders for accountability purposes, its sole use as
a tool for data-driven decision-making needs to be addressed (Bernhardt, 2003;
Mandinach & Honey, 2008). By encouraging the selection of appropriate data, not
just state assessment results, school leaders will see an impact on student
achievement and the quality of teaching in schools (Creighton, 2007; Supovitz &
Klein, 2003). The overarching purpose for data use is to inform actionable

21
knowledge with specific goals for transforming, learning and improving instruction
(Johnson, 2002; Love, 2009).
The Practice of Using Data to Drive Decision-Making
For the purposes of this study, effective data use means school leaders have
the skills and a clear vision to gather and use a broad range of student information.
Specifically, leaders use data to impact and address students’ learning needs
(Wayman et al., 2008). Looking at assessment scores by grade level, and
disaggregating the data can give information about the impact of the teaching
strategies used by the school with students. Disaggregating data involves the
separation of results by different demographic groups (e.g. gender, grade level and
socio-economic level) enrolled in the school. It helps decision-makers determine if
all students are achieving and experiencing school equally (Bernhardt, 2004).
Furthermore, demographic data provides a profile of who the students are and how
the school processes are aligned to meet their needs (Bernhardt, 2003, 2004). In
decision-making, demographic data helps school leaders comprehend the context of
the school and offers a critical understanding of all the numbers at a fine-grained
level, such as enrollment, ethnicity, gender, home background and language
proficiency (Bernhardt, 2003, 2004).
Combs and Edmondson (2006) in their research explain that school leaders
must consider using data based on the impact they wish to generate on specific
issues. Consequently, data examination and analysis should be guided by specific
goals, keeping in mind that different kinds of data reveal different things. For

22
instance, perceptual data will provide a school leader with information based on how
students, staff and parents feel about the learning environment, which will provide
insights to improve the learning environment. Information on discipline can assist a
school in the improvement of their discipline policies. Data obtained on teaching
practices, homework, teacher made tests, and grade point average will guide school
leaders on how the instructional system meets the learning needs of students (Combs
& Edmondson, 2006).
An important role of school leaders in using data in decision-making is to
encourage participation among teachers and administration to ask critical questions
about the data, analyze the data carefully and apply results accordingly (Mandinach
& Honey, 2008). If school leaders are to encourage quality data-driven decision-
making it is important to recognize that data are representations of ideas that require
thought, considerable discussion and collaborative inquiry (Earl & Katz, 2006;
Knapp et al., 2007). Earl and Katz (2006) state that “data can offer a vehicle for
investigating tacit knowledge to refine and even transform it as it is converted into
explicit knowledge for use in making decisions” (p. 21). Leaders must establish
conditions where all members of the decision-making process can make sense of the
data, are encouraged to question and are provided answers in a meaningful,
respectful way. The inquiry process according to the research creates a “hunger for
data” and develops a deep understanding of inquiry to include the use of data in new
and different ways (Feldman & Tung, 2001). Participants in this type of decision-
making process will ask for data prior to planning or implementing any given project

23
in their schools and become more reflective about using data (Earl & Katz, 2006;
Feldman & Tung, 2001; Knapp et al., 2006).
By analyzing the results of authentic standards and language proficient
assessments, school leaders can use the information to embark upon instructional
decision-making that will meet state and federal accountability measures and at the
same time help support instructional planning (Mandinach & Honey, 2008). It is
essential to examine data to inform decisions. In sum, schools where a data inquiry
decision-making system is in place, have participants that ask questions about a
problem who find the answer by analyzing data from multiple information sources,
which allows the school to focus on the improvement of daily practices and student
academic success (Knapp et al., 2006).
Factors and Conditions that Facilitate Effective Data Use
This section discusses critical factors and conditions that facilitate the school
leaders’ effective use of data. The theory of action framework, presented on p. 12
guides the discussion. First, federal and state accountability standards and provisions
will be discussed; in particular, expectations established by the federal government
with the passage of NCLB. The use of data for decision-making and the role of a
state’s accountability system in distributing effective data to districts and schools
will be explored. The role of school districts’ in providing school leaders with
support to implement data-driven leadership at the school level will follow. Factors
and conditions that facilitate effective use of data by the school leader will be
considered. The importance of a school leaders’ buy-in to the use of data will be

24
discussed. Next, professional development school leaders need to effectively use
data will be examined. The final section considers school leaders establishing a data
friendly culture for data use followed by how leaders influence teacher decision
rights by using data to improve learning. Barriers that impede the use of data are
covered within these sections.
Federal Government Mandates
The role of the federal government in the educational system has until
recently been relatively minor. Historically, the rights and responsibility for
schooling were left entirely to the states. Passage of the Elementary and Secondary
Education Act of 1965 (ESEA) began the involvement of the federal government in
public school policy (Rebell & Wolff, 2008). The role of the federal government
dramatically increased with the passage of No Child Left Behind (NCLB) in 2002
(Rebell & Wolff, 2008). NCLB handed school districts and school leaders an array
of accountability tools, from meeting the requirement to hire “highly qualified
teachers” to a mandate to disaggregate a wide variety of data (Springboard Schools,
2006).
Most importantly, NCLB requires data to be collected and disaggregated in
order to track the achievement of different groups of students. States are mandated
by NCLB to report disaggregated student data, individual student progress, state
standards test scores, and demographic data to all schools and districts. NCLB
required states to develop a data system to effectively use data and only 18 states are
currently able to align K-12 student records with postsecondary educational systems,

25
or have a standardized student code or identifier following students (Hansen, 2007;
Springboard Schools, 2006; Vernez, Krop, Vuollo, & Hansen, 2008). Furthermore,
the emphasis on data aims to support the development of a data-driven decision-
making culture in local districts and schools (Springboard Schools, 2006). Prior to
NCLB data-driven decision-making was a concept that did not explicitly exist.
In establishing mandates for data use the federal government shouldered the
responsibility of school accountability on the school leader (Jazzar & Algozzine,
2006). High stakes accountability is not a new concept in American public
education, however, NCLB intensifies external scrutiny and places serious
consequences on districts and schools if performance is not met (Jazzar & Algozzine,
2006). Accountability measures embedded in NCLB were made with the assumption
that school leaders had the training, skills, and support to use student data for
decision-making and to improve teaching and learning (Mandinach, Honey & Light,
2006). Whereas, school leaders have routinely used data to make managerial
decisions such as hiring, ordering textbooks, purchasing instructional materials and
balancing budgets, the role of the school leader under NCLB is focused on the use of
data for instructional leadership and improvement (Jazzar & Algozzine, 2006). The
NCLB mandate has created a need for school leaders to use data---not just for
managerial purposes---but to utilize data to improve student outcomes and change
instructional strategies (Springboard Schools Report, 2006). Although federal
mandates have created opportunities for school leaders to use data to understand,
predict and improve student performance on state assessments, placing data in the

26
appropriate required NCLB format is still a major challenge for most states, districts
and schools, and has created a barrier against effective data use.
Establishing State Accountability Systems to Facilitate Data Use
Another factor that impacts the success of data-driven decision-making by
school leaders are state accountability systems. Research supported by Hanson
(2007), Springboard Schools (2006), and Vernez et al. (2008) suggests that
California has focused on establishing a data system designed to collect and support
NCLB comprehensive mandated data and has deemphasized collecting data to
encourage local decision-making. Research affirms that it is critical for states to
foster the development of a longitudinal data accountability system that follows
students to another school or district, which provides schools and districts with
appropriate data to tailor instruction to meet specific student needs (EdSource, 2008;
Hansen, 2007; Laird, 2006; Vernez et al., 2008).
Completion of the California Longitudinal Pupil Achievement Data System
(CALPADS) in 2009 was a major milestone for the state in compiling and analyzing
student data (EdSource, 2009; Los Angeles Times, 2009). The system tracks and
provides districts and schools with individual student enrollment history, program
participation, and achievement on annual standards assessments. CalTIDES a second
major component, is a teacher and administrative database that is scheduled for
completion in 2012 (EdSource, 2009; Los Angeles Times, 2009). Due to political
and fiscal constraints, California continues to lag far behind other states and
continues with a lukewarm commitment toward data use.

27
The literature maintains school districts need the state to provide quality and
timely data on student enrollment, retention, standardized test scores, and the
effectiveness of school programs, to achieve the objective of improving student
progression, and instructional quality (Hansen, 2007; Vernez et al., 2008). For school
and district educators to use data for decision-making the study by Hansen (2007)
emphasizes the importance of having timely and quality data that will provide the
following elements: student identifiers, student-level enrollment, demographics and
program participation; ability to match student test records year to year to measure
student growth; information on untested students; student transcripts with update
course completion and grades; college readiness test; standardized test data and
student level graduation and drop-out rate (Hansen, 2007). Notwithstanding the leaps
in establishing state assessment systems and investment in longitudinal data systems,
most schools and districts are a long way from acquiring the data they require
(Hansen, 2007; Vernez et al., 2008). Since most states have not been truly
successful in providing schools with timely high quality data from multiple sources
on student outcomes and data on instructional practices schools have limited data to
support local decision-making (Halverson et al., 2005; Hansen, 2007; Springboard
Schools, 2006). The inevitable result is that many school districts have developed
their own data system in an effort to acquire quality and timely data to support
school improvement (Armstrong & Anthes, 2001; Halverson et al., 2005; Schmoker,
2003; Springboard Schools, 2006).

28
The research study conducted by Hansen (2007) emphasizes the importance
of developing data systems capable of assisting policymakers to understand the
performance of schools. In addition the data system should provide information on
how to effectively allocate budgets to improve student learning. Hansen (2007)
asserts California has made some progress in data collection and dissemination of
data. The state now has approximately 125 data collection systems in the California
State Department of Education alone.
The state is moving forward by putting in place a few key systems such as:
The California Basic Education Data System (CBEDS), which collects student
demographic data; Standardized Account Code Structure (SACS), which offers a
common data framework for local schools; School Accountability Report Cards
(SARCS), which reports the conditions and performance of each local school;
student achievement data, reported by test vendors and California School
Information Services (CSIS), which is building local capacity for the use of state
data (Hansen, 2007; Springboard Schools, 2006; Vernez et al., 2008). Despite the
plethora of databases available in California the state currently cannot answer basic
questions regarding public schools such as: The type of classes that best prepare
students for college; what type of professional development make teachers better;
which credentialing programs are most effective in preparing teachers; and tracking
teacher performance individually with links to student performance (Hansen, 2007;
Los Angeles Times, 2009). With an effective state accountability system, school

29
leaders would be equipped to deploy school resources most effectively to increase
student learning (Hansen, 2007; Vernez et al., 2008).
District Support
School districts are in a position to play a vital role in providing school
leaders with leadership, support and professional development to effectively use data
in schools (Englert et al., 2004). Research studies suggest that districts that make
wise use of data have the following characteristics: strong leadership from the
superintendent in establishing a commitment to collecting and using data; a
supportive district culture for using data for continuous improvement with a well
defined school improvement plan; support for principals, including training in data
literacy, promising practices and improvement strategies; and a management
information system for timely and quality data storage (Armstrong & Anthes, 2001;
Datnow et al., 2007; Springboard Schools, 2006). Moreover, with district office
support school leaders begin to establish goals and objectives for data use as the
initial step in the school improvement process (Englert et al., 2004; Datnow et al.,
2007; Hansen, 2007; Lachat & Smith, 2004).
Researchers agree that strong district support is a factor in encouraging data
driven leadership by school leaders. A study by Armstrong and Anthes (2001) linked
strong leadership at the district level as the key element to using data in schools by
school leaders. The report further stated that district level support of school leaders’
use of data is essential for continuous student achievement to occur (Armstrong &
Anthes). In the work by Datnow et al. (2007) each school district studied put in place

30
established norms for data use. Furthermore, in partnership with school leaders, the
district instituted explicit norms and expectation that were developed to facilitate
data use in each school. District level support influenced the schools and influenced
how data was used in each school to improve classroom practice (Datnow et al.,
2007). External support helped keep school leaders on track. District support further
encouraged a commitment toward developing a team approach to data use and
focused the school leader on providing the appropriate professional development at
the school for continuous data use (Datnow et al., 2007; Feldman & Tung, 2001).
The findings by Datnow et al. (2007) corroborate the fact that district support is
essential if leaders are to use data effectively to improve instruction.
A study by Englert et al. (2004) found that principals believe using data to
improve instructional practices is an important outcome of accountability. According
to Englert et al. (2004) school leaders are capable of becoming instructional leaders
and encouraging the use of data in their schools if district assistance is available. The
report by Englert et al. (2004) provided several recommendations where district
support of school leaders would enhance data use. These included: engaging school
leaders on aligning school data to state standards; designing district data systems that
match the data needs of the school; offering assistance on analyzing data and
identifying instructional strategies; and providing school leaders with time to work
with data (Englert et al., 2004). A noteworthy study by Springboard Schools (2006)
determined that districts, which provide school leaders the support to meet the
demands of NCLB are able to make rapid and effective use of data for school

31
improvement. School districts committed to the use and collection of data provide
school leaders with district goals for data use. These districts are committed to
providing disaggregated data, summarizing data in useful ways, and identifying
appropriate teaching strategies for the effective use of data (Wayman & Stringfield,
2006). In addition data-driven districts, provide school leaders with support in
learning how to interpret, analyze, and use data to inform instruction (Armstrong &
Anthes, 2001; Datnow et al., 2007).
Likewise, districts utilize support personnel to assist with the management
and use of data, assist school leaders in building capacity of learning communities to
use data, and ensure that district data systems include information from various sets
of local assessments (Datnow et al., 2007; Springboard, 2006). Wayman and
Stringfield (2006) emphasize the importance of district staff support. They suggest
that district staff provide school leaders with frequent opportunities to use data
systems for instructional improvement. Furthermore, district staff could support
principals with recalcitrant local staff who are mistrustful of data, to encourage such
staff to use data to inform practices. While these studies affirm that NCLB places the
responsibility of accountability on the school leader, the school district can provide
focused, purposeful support to assist school leaders in developing expertise in data-
driven decision-making (Armstrong & Athens, 2001; Datnow et al., 2007; Wayman
& Stringfield, 2006).
Researchers conclude that if school leaders are expected to use data for
decision-making and improvement of student achievement, school boards and

32
districts must offer support in the effective use of data. Districts must provide
resources and assist schools in developing the essential skills for data-driven
decision-making. Research evidence suggests that when leaders receive support from
the district office and are provided with useful professional development, the use of
data is facilitated within the school. If higher student achievement is to occur, strong
school leadership and district support is essential in the use of data to drive decision-
making (Armstrong & Anthes, 2001; Datnow et al., 2007; Feldman & Tung, 200l;
Wayman & Stringfield, 2006).
Leadership Buy-in to Data Use
In addition to federal mandates, state and district support, effective data-
driven decision-making requires school leader buy-in. The literature emphasizes the
school leaders’ role as the major instructional leader within a school. In schools
where strong instructional leadership exists, with data-driven decision-making in
place, student achievement thrives (Jazzar & Algozzine, 2006). Identifying the
school leaders’ buy-in to data use in informing school choices is fundamental to the
success of data-driven decision-making in a school setting (Lachat & Smith, 2004;
Mandinach et al., 2006; Ontario Principals Council, 2009). This is because, as Lachat
and Smith (2004) acknowledge in their research on Data Use in Urban High
Schools, the school leader strongly influences the use of data in schools. Without the
school leader as champion, the efforts of data use are non-existent.
In their research, Mandinach et al. (2006) emphasize the importance of
principal buy-in to data use, “A principal who is data-driven can exert substantial

33
influence on the faculty, communicating the importance and thereby stimulating use”
(p. 13). The Ontario Principals Council (2009) maintains that by having a strong
sense of ownership over the use of data, effective school leaders can construct a
strong instructional compass, coupled with a data plan to improve the instructional
program. The school leader makes things happen in a school. If the school leader is
knowledgeable in data use and models the use of data in everyday activities, then the
teachers and school community are more likely to embrace the philosophy (Lachat &
Smith, 2004; Mandinach et al., 2006; Ontario Principals Council, 2009).
The Ontario Principals Council (2009) determined that by making a decision
to use data, the school leader puts forth a shared vision for using data to improve
learning. Leaders communicate the vision to the whole school community, provide
professional development to all stakeholders and take action on using data.
Therefore, the principal is a strong force behind data use and can be instrumental
from changing numbers on a piece of paper to action in school reform. As school
leaders’ buy into the use of data, the school community begins to value the impact
that collecting and analyzing specific data has on meaningful decision-making and
upon the culture of the school (Alwin, 2002).
Professional Development
While district support and school leaders’ buy-in to utilizing data is critical, it
is not sufficient for the effective use of data. In the research by Englert et al. (2004)
principals felt there was a lack of understanding on how to use data and knowing
how to interpret data reports. Without the appropriate professional development to

34
learn how to properly collect, analyze, and use data to inform school choices, buy-in
by the school leader is insufficient. Research to date suggests that school leaders
continue to receive most of their training on the importance of technology and
software use (Creighton, 2007) rather than on developing skills that teach them “how
to ask instructionally relevant questions of data and how to answer such questions”
(Sharkey & Murnane, 2003, p. 78).
School leaders articulate that the productive use of data in schools requires
effective professional development, provided by the school district, which will guide
them in making sound planning decisions to improve student performance (Brunner
et al., 2005). A study by Englert et al. (2004) found that school leaders expressed the
need for professional development in areas such as: acquiring data literacy,
developing data use cultures, interpreting and manipulating data, translating data into
instructional practices, prioritizing data in order of importance, interpreting, and
applying data to achieve student improvement, and techniques for summarizing data
in meaningful ways.
In the report by Englert et al. (2004), Understanding How Principals Use
Data in a New Environment of Accountability, one measure focused on the
perception of principals from rural, urban, and suburban locales on their professional
development needs to implement data-driven school improvement. The study
reported principals “desire to receive more training and assistance from their district
in analyzing data and identifying instructional strategies” (Englert et al., p. 13).
Virtually all principals in the report wanted training on how to use data to improve

35
pedagogical strategies in the classroom. Principals pointed out that using data to
improve instruction was an important element of accountability (Englert et al.,
2004). Wayman and Stringfield (2006) in their research, Data Use for School
Improvement: School Practices and Research Perspectives, state that school leaders
“are implementing a variety of methods for gathering, storing, analyzing, and using
data, but are moving forward with strikingly little guidance or training from any
quarter” (p. 463). For data to be usable for accountability and instructional
improvement, leaders must learn strategies that align data to practice that will result
in changes in teaching that will lead to improvements in student achievement
(Mandinach & Honey, 2008).
In a study conducted by the Consortium for School Networking (2006),
public school leaders indicated the lack of training and the inability of systems to
share or exchange data were the dominant barriers to data-driven decision-making.
Also, school leaders lacked the training and knowledge about what to do with data
once they were received. Furthermore, the study concluded that with the appropriate
professional development as requested by principals, the possibility of using data for
decision-making was likely to occur. The results of this study are shown in Table 1.

36
Table 1. Identified Barriers to Use of Data-Driven Decision-Making

Barrier Percent
Lack of training 50%
Inability of systems to share data 42%
Lack of understanding what to do with data 39%
Clear goals on what data to collect 36%
Failure to collect data in a uniform manner 35%
Outdated technology systems 31%
Low quality data 24%
Timely data collection 24%
Complicated data reports 22%
*Responses do not sum to 100%; respondents were able to select several barriers (Consortium for
School Networking, 2006, p.3)

The study confirms that school leaders need to receive professional
development relevant to the accountability requirements of NCLB and their own
school needs. Moreover, with appropriate professional development and support
from district offices school leaders can build a strong culture of collaborative data
use for data-driven decision-making and improving student achievement
(Consortium for School Networking, 2006; Englert et al., 2004; Holcomb, 2004;
Lachat & Smith, 2004; Love, 2009).
While understanding how to use data effectively and developing data literacy
are important, it is also necessary to train school leaders on how to motivate staff to

37
use data to drive decision-making (Knapp et al., 2006). Strong instructional
leadership requires that school leaders receive training on how to encourage, support
and uphold conditions that motivate staff members and other school leaders to use
data, analyze data, and ask questions about using data to make systemic and
instructional changes (Knapp et al., 2006).
Undoubtedly, the most important challenge for school leaders is acquiring
professional development that connects data to instructional problem solving.
According to Knapp et al. (2006), investing in professional development of school
leaders in data literacy will provide the foundation to work effectively with data and
compel leaders to use data in daily practice. Becoming a skilled user of data requires
school leaders to become informed about the nature of evidence, from how it is
collected and interpreted to how it is analyzed and used to inform change (Katz,
Sutherland & Earl, 2005). School leaders also need the skills to access and use data
to evaluate new approaches to instruction and curriculum (Lachat, 2005). Although
research is still limited on the type of professional development school leaders
receive regarding data-informed leadership on teaching and learning, Schmoker
(2003) recommends that school leaders receive training on establishing data teams,
sharing test results and other school data, refining lessons and strategies targeted at
low performance areas, and carrying out discussions about where substantial
improvements can be made in teaching strategies to effect change. In general, high-
quality professional development should be linked to schoolwide improvement and
sustained use over time (Knapp et al., 2006; Knapp, Copland & Talbert, 2003).

38
The literature maintains the importance of professional development for
school leaders and in obtaining support to establish data-driven school cultures,
connecting instructional strategies with solutions to data, selecting appropriate
interventions based on data, and aligning data with state standards (Knapp et al.,
2003; Goldring & Berends, 2009; Katz et al., 2005). Developing such a culture is a
key leadership element in the improvement of school performance (Knapp et al.,
2006). School districts that provide ongoing support and training to school leaders in
building a culture that is performance-driven create explicit norms and expectations
regarding data use, making it difficult for school leaders to fall back on old routines
of making decisions on instinct (Datnow et al., 2007).
Setting Goals and Objectives for Data Use
Districts that set goals and objectives for data use provide school leaders with
the conditions to create a data-driven school culture. By establishing organizational
goals and objectives for school improvement, data can improve school planning,
instruction and student achievement (Datnow et al., 2007; Schmoker, 1999). The
research maintains that for school leaders to build sound assessment practices into
the school culture, districts must work with school leaders to establish goals and
objectives for data use (Datnow et al., 2007). In setting the expectation for data use
these districts create the right conditions for school leaders to use data effectively at
the school site. Furthermore, these districts establish a partnership with school
leaders helpful for determining school instructional and data needs (Armstrong &
Anthes, 2001; Datnow et al., 2007; Englert et al., 2004; Halverson et al., 2005;

39
Lachat & Smith, 2004). School leaders and teachers understand that data are
meaningless without focusing on stated goals and standards for student achievement.
Goldring and Berends (2009) agree that it is essential for school leaders to be trained
in establishing objectives for data use that focus on students receiving quality
instruction connected to district benchmarks and state standards. Such actions lead to
the establishment of a culture conducive to the use of data to drive results (Datnow et
al., 2007).
Datnow et al. (2007) and Love (2009) conducted studies in rural and urban
K-12 school districts that set conditions, by establishing goals and objectives to
implement and sustain school improvement through the use of data. District leaders
in these school systems created specific expectations and norms regarding data use
and expected school leaders to establish a performance-based system where the use
of data was common. School districts that provided school leaders with strong
support included identifying promising practices and curricula, and jointly setting
achievement targets. Student scores in these districts increased significantly (Datnow
et al., 2007; Love, 2009).
How School Leaders Establish a Data-Friendly Culture for Data Use
According to Knapp et al. (2006) organizational cultures are motivated by
data-driven leaders who “make data a prominent feature of deliberation about the
myriad issues that confront them on a daily basis” (p. 15). By developing buy-in and
establishing basic conditions for data use, school leaders will be better equipped to
focus on creating a schoolwide culture of data inquiry; a process promoted with the

40
staff, where open discussion on the practices and structures of the school are
analyzed by using data from multiple sources to assess the school’s strengths and
weaknesses (Feldman & Tung, 2001; Knapp et al., 2006). The process of continual
systemic change requires school leaders to be committed to challenging existing
beliefs and practices, and to include all stakeholders in the conversation (Earl &
Katz, 2006; Feldman & Tung, 2001; Knapp et al., 2006).
Also important to a data-friendly school culture is an atmosphere of trust and
data-informed inquiry (Goldring & Berends, 2009; Knapp et al., 2003; Sutherland,
2004). The research suggests that teachers associate trust with empowerment,
keeping commitments, and reliability of leadership (Knapp et al., 2006; Thornton &
Perreault, 2002). Trust is defined as, “open communication of results, sharing of
data, candid discussion of improvement plans, and establishment of a supportive
environment for data use” (Thornton & Perreault, 2002, p. 88). The degree of trust
teachers and staff have in the school leader will determine the degree of progress
made with data use (Jazzar & Algozzine, 2006; Knapp et al., 2006).
In a study by Sutherland (2004) of two Edison Project Schools, it was noted
that “fostering the spirit of inquiry” (p. 288) allowed the staff to be creative with the
use of data, and also kept staff focused on continuous instructional improvement. A
teacher in an Edison Project School commented:
Data is probably the number one thing we use for planning, it’s reliable and
it’s factual, there’s nothing subjective about it. And so, we set out goals, both
long term and short term, based on available data from the previous years and
the current year. What better evidence could you have than data (Sutherland,
2004, p. 285)?

41
In the research of Goldring and Berends (2009), a compilation of inquiry-
based questions were created for use by school leaders. In developing a data based
culture, these questions serve as a guide to analyzing data in meaningful ways:
1. What are the data telling us?
2. What can we learn from the data?
3. How can we change our practices in light of the data?
4. What other data do we need to collect?
5. How does the information from standardized assessments compare with
teachers’ grades and other more local information about student
performance and development (Goldring & Berends, 2009, p. 15)?
By pursuing such questions leaders begin to develop a culture of learning for
students and adults. This inquiry process offers teachers and staff the opportunity to
include data from classroom observations. It moves the conversation away from a
reliance on standardized test data and toward a professional climate focused on
teaching and learning (Goldring & Berends, 2009).
In practice, this process is difficult. Lachat (2001) and Lachat and Smith
(2004) concluded that a barrier to effective data use in high schools is resistance to a
change in culture. In their research Lachat and Smith (2004) acknowledge that high
schools are often mistrustful of school leaders and their ability to develop a culture
driven by inquiry and trust. Lachat (200l), however, contends that the resistance “is
not just a high school phenomenon” (p. 21) but one that state education offices and
school districts throughout the United States have experienced, since the requirement

42
for data use began with NCLB. As previously mentioned, it is critical that school
leaders establish a climate of trust and develop a culture of collaborative inquiry in
which the faculty can learn, question, and share with one another the relationship
between the data, their practices and student achievement (Earl & Katz, 2006;
Goldring & Berends, 2009; Love, 2009).
Data Influence on Teacher Decision Rights
Another key element to successful data-driven decision-making is teacher
buy-in; increasing the value of data occurs when teachers participate in collaborative
discussions that use data to focus on teaching and learning (Goldring & Berends,
2009). The leader must offer resources and support to motivate faculty to use data on
a regular basis (Supovitz & Klein, 2003). Past research suggests many teachers have
mixed feelings about accountability systems, including the efficacy of using data to
improve student achievement and to make changes in instructional practices
(Heritage & Chen, 2005; Lachat & Smith, 2004).
Teacher willingness to become involved in data-driven decision-making
increases and apprehension diminishes when participants believe data initiatives
respond directly to the learning needs of students and when decisions are
implemented soundly (Lachat & Smith, 2004). Teacher participation in the data-
driven decision-making process is further encouraged when school leaders offer
teachers guidance on creating measurable goals, provide support, resources, time to
analyze data, and reflect on the learning of all students and adults (Goldring &
Berends, 2009; Krovetz & Arriaza, 2006). Furthermore, communicating with

43
teachers and engaging them in the conversation is important in every step of the
data-driven process (Goldring & Berends, 2009; Holcomb, 2004). In schools where
successful use of data is implemented, teachers support and use the data-driven
decision-making process when they are provided the data needed to make effective
decisions. In these schools, a shared understanding of the purpose and value of data
use has been developed, and meeting to share promising strategies to strengthen
teaching and learning is ongoing (Datnow et al., 2007; Feldman & Tung, 2001;
Love, 2009).
In schools where the collection and analyzing of student data is important,
school leaders have established the vision and persistence to use data as an effective
learning tool (Johnson, 2002; Mandinach et al., 2006; Supovitz & Klein, 2003). They
are careful to have ongoing discussions on data use, guide teachers and other
informal leaders in setting goals, provide the necessary resources and encourage
collective, schoolwide discussions, of data use (Supovitz & Klein, 2003). Studies
emphasize the important role school leaders’ play in encouraging teacher buy-in to
successful implementation of data-based decision-making. Using data effectively for
decision-making to improve student performance is a process that must be
implemented collectively, if teaching and learning are to improve (Krovetz &
Arriaza, 2006; Love, 2009; Supovitz & Klein, 2003). A report by Technology
Alliance (2005) regarding data-driven decision-making in schools across Seattle,
Washington concluded that when school leaders interpreted data on their own and
then provided it to teachers, there was serious resistance from teachers.

44
According to research findings a significant barrier to teacher buy-in to data
use is “fear” (Bernhardt, 2000; Holcomb, 2004; Schmoker, 1999). Many faculty
members are afraid that data will be used against them, and with the continued
emphasis on accountability they fear data will be used to determine their
effectiveness as teachers. Holcomb (2004) expresses these concerns more explicitly
in her research stating, “The threats of evaluation with negative consequences are
more real in the 21
st
century than they have been, but coping with the fear requires
the same discipline of focusing on the goal and doing what is right for children for
their own sakes…” (p. 31). Teachers will be reluctant to use data if judgmental and
punitive retributions are attached (Goldring & Berends, 2009; Lachat & Smith,
2004). However, at this point the implementation of NCLB does not call for tying
student achievement to teacher evaluation (Holcomb, 2004).
Additional barriers to effective data-driven decision-making include limited
access to collaborative planning time for teachers; limited time to share effective
assessments and teaching strategies; and limited time for targeted professional
development (Englert et al., 2004; Holcomb, 2004; Lachat, 2001; Supovitz & Klein,
2003). Since teachers are faced with numerous demands on their time, a critical
challenge is for school leaders to provide the time necessary for meaningful
discussions among teachers (Thornton & Perreault, 2002). This is critical for school
leaders committed to a data-driven approach to decision-making.

45
Summary
Understanding and knowing how to use data regarding student and school
performance are fundamental requirements of current school leaders. The call by the
federal government for data-driven decision-making and for states to establish
stronger accountability systems has prioritized data use in school reform efforts
(NCLB, 2002). Data-driven decision-making means that schools leaders have access
to a management information system with timely and varied data. As discussed
throughout this chapter, it requires the district office to provide school leaders with
support for establishing goals and objectives related to data use, and to offer
appropriate professional development (Wayman et al., 2005). School leaders must
have buy-in to data use; they also must have influence over reshaping the central
practices and cultures of their schools. Lastly, school leaders must motivate teacher
buy-in to data use. In school districts where time and effort were invested in the
development and support of the school leader to motivate teachers, schools showed
significant improvement in student achievement (Bernhardt, 2001; Datnow et al.,
2007; Holcomb, 2004; Love, 2009).
As identified in the literature, challenges exist to leaders encouraging data
use to make decisions and improve student learning. What is missing from the
literature is how school leaders can effectively carry out successful data-driven
decision-making. Case study research into the processes of implementing data-driven
decision-making is limited and little is known about the practices used by educators
when using data. The present study investigated two charter schools in California

46
whose leaders were successful in using data for school improvement. The following
chapter, Chapter Three provides a detailed description of the research design and
methods for this study.

47
CHAPTER THREE
METHODOLOGY
Introduction
The purpose of this study was to investigate promising practices specific to
school leaders’ use of data for decision-making and school improvement in two
California charter schools. The research was conducted as part of a thematic
dissertation group that examined a variety of promising practices in California
charter schools. The researchers visited school sites and collected information on
implementation of the promising practices using qualitative methods that were
developed collaboratively. As stated in Chapter One, the data collected from these
studies contributed to the University of Southern California’s Compendium of
Promising Practices under the direction of the Center on Educational Governance
(CEG: www.usc.edu/dept/education/cegov/).
This chapter describes the research design, data collection instruments and
processes, and data analysis procedures used during the investigation. Chapter Three
begins with an explanation and justification for the chosen research design based on
promising practices related to school leaders’ use of data for decision-making in two
California charter schools. The research questions used to guide the study and the
data instruments used to obtain multiple sources of evidence (Yin, 2005) are also
presented. Finally, how the data were analyzed will be explained.

48
Research Design
The study examined school leaders’ use of data for decision-making and
school improvement in two California charter schools. The study design sought to
understand and share knowledge of promising practices in data use found in charter
schools, which arguably have more freedom to innovate (Brewer & Wohlstetter,
2005). For purposes of this study promising practices were defined as ideas that have
not been broadly disseminated which have the potential to benefit and improve
schools and influence the educational community (Wohlstetter & Kuzin, 2006). As
previously noted, the findings from this study contributed to USC’s Web-based
Compendium of Promising Practices allowing other educators to experiment,
replicate or adapt the promising practices (Bardach, 2004; Grayson, 2007).
The units of analysis for this study were strategies used by the school leaders
at each charter school to bring about effective data-driven decision-making. The
study was guided by the following four research questions:
1. How do charter school leaders use data for decision-making and school
improvement?
2. How are resources allocated to effectively implement the use of data for
decision-making and school improvement?
3. What challenges have charter schools faced in implementing the use of
data for decision-making and school improvement and how were they
addressed?

49
4. What evidence exists that the use of data for decision-making resulted in
positive educational outcomes?
To fully understand how leaders’ use data for decision-making, a qualitative
case study methodology was used. Case study research allowed the researcher to
investigate the complexities of program implementation within its real life context
without disruption to the natural setting (Merriam, 1998; Yin, 2003). According to
Patton (2002), case study research is an approach in qualitative methodology that
provides a specific way of collecting, organizing, and analyzing data to present an
understanding of an experience or program. The case study approach allows for the
creation of a holistic, content sensitive and descriptive product, while permitting
flexibility in conditions when conducting the investigation (McEwan & McEwan,
2003; Merriam, 1998; Patton, 2002). In the present study, case study methods were
used to analyze and examine schools that had successfully implemented program
goals (Manela & Moxley, 2002), which included an educational innovation
(Merriam, 1998).
Selecting a case study approach for investigation provides numerous
strengths. For example, the data are connected to real-life contexts. Further, the
examination is holistic in nature which offers a comprehensive view of the
phenomenon under study (Merriam, 1998) - school leaders’- and data-driven
decision-making. The case study design allowed for an analysis of the many factors
that contributed to the use of data as well as an understanding of the processes a

50
school leader must undertake for effective data use (Stake, as cited by Merriam,
1998).
Since the researcher is the primary data collector, the research may not be
free from bias. According to Merriam (1998), issues may arise with regard to
reliability and validity since a single person is collecting and analyzing the data
(Merriam, 1998). Furthermore, in case study research, information cannot be
generalized to other situations, because data are obtained from a limited system
consisting of many variables (Merriam, 1998; Patton, 2002).
Notwithstanding its limitations, case study research provided detailed
knowledge and meaningful information on the process of implementation. The
information collected from site visits to schools revealed how school leaders put in
place the processes, structures, supports, and resources that contributed to effective
use of data. The focused inquiry of the case study method also proved useful in
studying educational practices that can “affect and even improve practice” (Merriam,
1998, p. 41). When done effectively, case study research is an exhausting and a
rigorous endeavor. It is a descriptive process focused on meaning (McEwan &
McEwan, 2003), “well constructed case studies are holistic and context sensitive”
(Patton, 2002, p. 447). The case studies also were designed to provide social
contextual information to construct “naturalistic generalization”. From this, the
reader is able to make generalizations, and recognize similarities and differences of
the case study situation and their own experience (Patton, 2002). As a result, findings
from the case study can be applied to other settings, customized or adapted (Patton,

51
2002). In sum, the purpose of this study was to examine and disseminate promising
practices related to school leaders’ use of data for decision-making and school
improvement. Case study research focuses data collection on the accumulation of
new knowledge, and facilitates sharing and discussion beyond the original
knowledge creator.
Data Collection Processes and Procedures
As stated in Chapter One, this study was part of a thematic dissertation group
that investigated a range of promising practices in California charter schools.
Findings from each case study were synthesized for the Center on Educational
Governance Wed-based Compendium of Promising Practices at USC. Since this is
the second round of site visits to collect information for the compendium, the
dissertation group of which this researcher was a member refined data collection
procedures developed by the first thematic dissertation group. The process included
revising and updating interview instruments for a variety of stakeholders. The group
also worked to standardize data collection procedures by using the contents of the
compendium to determine which types of information to collect during site visits
(see Appendix A). The contents included a profile of each charter school, the goal of
the promising practice, the theory of action, implementation details, resource
(financial and human) requirements, supporting documents and recommended
resources for additional information about the promising practice. The information
collected during site visits was guided by the data required for the compendium, in
addition to the research questions.

52
Nomination Process
An e-mail advertisement was sent through two California professional
organizations for charter schools---the California Charter Schools Association
(CCSA) and the Charter Schools Development Center (CSDC). The California
Charter Schools Association, comprised of 809 charter schools, provides advocacy
and resources for its membership. The Charter Schools Development Center, located
in Sacramento, offers statewide technical assistance and training for charter schools
in California. Email advertisements from the organizations requested members to
nominate charter schools that offered promising practices in the areas under study by
the thematic dissertation group: adult mentoring of at-risk students, integrating
academics into career and technical education, school leaders’ use of data for
decision-making and school improvement, teacher evaluation, the use of technology
to increase parent involvement, uses of school time and writing across the
curriculum.
In addition to the two advertisements, referrals were sought by members of
the dissertation group, based on research obtain from the California Department of
Education and others active with charter schools, such as EdSource and RAND. In
order to be nominated, an online form was completed and submitted through the
USC Center on Educational Governance Website (see Appendix A) or faxed into the
CEG offices. In the area of school leaders’ use of data for planning and school
improvement, ten nominations were received.

53
Selection of Case Study Sites
Once the nominations were received, the researchers underwent a careful
process to select the schools for study. The review included the school’s charter
petition, renewal petition, student demographic information, assessment data, and
evidence submitted about the promising practice--how long it has been implemented
and with what effects. As a result of the screening process, the ten nominations for
school leaders’ use of data for planning and school improvement were narrowed to
two. In accordance with the guidelines of the Institutional Review Board (IRB) at the
University of Southern California, an application to IRB was submitted and
approved prior to data collection (UP-IRB #10-00171).
Pre-Site Interview
Prior to visiting the school site, each researcher conducted a pre-site
telephone interview with the school principal to explain the study and to request
participation in the study by the school, as well as to collect general information
regarding the school and the promising practice. This interview with the school
principal lasted approximately fifteen minutes. In addition to introducing the study,
the interviewer discussed the scheduling and logistics of the site visits (see Appendix
B). To assist with the site visit, principals during the pre-site interview were asked to
identify other individuals the researcher should interview. Once the pre-site
interview was completed, principals were faxed or emailed a scheduling grid to
facilitate data collection during the site visit.

54
Site Visit
Visits to each school were conducted during the summer and fall of 2010,
July – October. The schools visited were Coastal Academy (K-8), Synergy Academy
Charter (K-5) and Synergy Kinetic Academy (6-8). Site visits were scheduled to
accommodate the schedules of administrative and teacher leaders. Principals were
interviewed for a second time using the principal onsite interview protocol. During
the visits, the following procedures were used for data collection: an interview with
each principal, interviews with teacher leaders, observation of professional
development meetings related to the promising practice and analysis of relevant
documents. The research questions guided the data collection process.
Interviews/Observations
According to Merriam (1998), qualitative research relies heavily on
interviews because they provide insightful information that may not be readily
observed. Since the promising practice was implemented for at least a year at each
school site, the interviews helped the researcher gain valuable knowledge about the
development, implementation and evaluation of the promising practice. Because of
the focus on school leaders’ use of data for decision-making extensive interviews
were conducted with the principal. Other leaders including the Chief Executive
Officer; Chief Achievement Officer; grade level chairperson or school coordinator;
and other teacher leaders. In case studies interviews are one of the most important
ways of gathering information about the promising practice (Merriam, 1998; Yin,

55
2003). Finally, professional development sessions that focused on building capacity
related to data use were observed.
Principal Interview
The first interview conducted was at the school site with each school
principal or administrator and lasted approximately 60 minutes. An on-site protocol
was used to gather information about the implementation details of the promising
practice, details of implementation, goals, lessons learned, including benefits and
challenges, sustainability, resources and recommended resources of data-driven
decision-making (Appendix C). Each interview took place in an informal
conversation format, with each principal sharing general thoughts and knowledge on
the use of data-driven decision-making to improve student achievement and
teaching. Principals shared details on the history of program implementation. At
Coastal Academy and Synergy Academies the founders and Chief Executive
Officers were also interviewed.
Promising Practice Leader
Interviews were conducted with approximately five teacher leaders at each
site, which included Core- subject Department Chairpersons, Lead Educational
Specialist, Leadership Coordinator, and the Beginning Teacher Support and
Assessment (BTSA) Coordinators.
1
The purpose of the interviews with other
promising practice leaders was to understand their role in the implementation to

1
The California Beginning Teacher Support and Assessment (BTSA) Induction Program
provides formative assessment, individualized support and advanced content for newly-credentialed,
beginning teachers.

56
data-driven decision-making. Interviews lasted approximately 60 minutes, which
included obtaining information regarding implementation details, benefits and
challenges, lessons learned, sustainability, and recommended resources. An
interview protocol for other school leaders was used to conduct each interview
(Appendix D).
Professional Development Observation
The researcher observed professional development meetings at each site that
offered training specifically related to the promising practice. Participants were
aware of the researcher’s presence; and the researcher assumed the role of an
observer. The observation lasted approximately 90 minutes in each session.
Participants in the professional development sessions included the principal and
other school administrators, all teachers, and school aides. A professional
development observation protocol was used to conduct the observation (Appendix
E).
Data from observations provides additional sources of information when
conducting case study research. According to Merriam (1998), observations offer an
immediate account of the promising practice being studied and are considered an
excellent opportunity to garner evidence of relevant behaviors or environmental
conditions (Yin, 2003). Information collected from observations was combined with
data from interviews and document analysis to provide a holistic view of the
phenomenon under study (Merriam, 1998).

57
Document Analysis
According to Yin (2003) various data sources increase the reliability and
validity of research by corroborating evidence. Document analysis was guided by the
research questions (Merriam, 1998). Key documents that were collected and
analyzed included: the school’s charter application, STAR test scores, school created
assessments, evaluation reports, professional development agendas, SARC report,
demographics and other documents related to data-driven decision-making. Some of
the documents were collected from Internet Web sites; other information was
collected during the site visits.
Data Analysis
As previously mentioned, case study research is a collection of raw data that
must be analyzed and organized to present its findings (Patton, 2002). The data
collection methods centered on gathering information related to the research
questions and drew upon interviews, document analysis and observations. Interviews
were taped by the researcher and a professional transcriber assisted in the document
analysis process. In this study, data were collected, coded by research question and
analyzed simultaneously as suggested by Merriam (1998). According to Merriam
(1998) and Patton (2002) the first step of document analysis is to develop
predetermine questions and establish specific procedures for coding process scheme
to assist is the management and classification of data. The coding process for this
study was guided by the research questions and predetermined topics, which were
used by the entire thematic dissertation group. Each member of the dissertation

58
group used the same coding process, adapted to their specific research questions and
themes. The coding process enhanced the consistency and reliability of the study by
triangulating information across multiple sources of data (Patton, 2002). Table 2
provides a detail description of how each data source corresponded to the research
questions. Information on the evidence of impact of the promising practice was
collected through the nomination form, the interviews with principals, promising
practice teacher leaders, observation of professional development, and analysis of
archival documents. Lastly, data from the nomination form, interviews, and
professional development observation, disclosed the impact and benefits of the
promising practice.
Summary
The purpose of Chapter Three was to provide a description of the study
design, the data collection process, instrumentation and procedures used during the
investigation. The use of a qualitative case study design offered a comprehensive
look at leaders’ use of data for decision-making from two high-performing California
charter schools. Schools were nominated and selected using a systematic process.
Data collection occurred during a five-day site visit to each school. The information
collected for this study will contribute to USC’s Web-based Compendium of
Promising Practices, which provides educators, policymakers and the general public
with information about promising practices in California charter schools. The
following chapter describes in detail the findings from this study focused on the

59
development, implementation and evaluation of how school leaders use data-driven
decision-making to improve school performance.

60
Table 2. Triangulation Information Across Data

Data Sources
Research Questions and Type of Data
Nomination Form
Principal Pre-site
Interview
Co-Principal On-site
Interview
Other School Leaders
Prof. Dev. Observation
Sessions
Archival Documents
1. How do charter school leaders use data for
decision-making and school improvement?

Description of Promising Practice X X X X X
Goal X X X X X
Theory of action X X
History X X X
2. How are resources allocated to effectively
implement the use of data for decision-making
and school improvement?

Time X X X X
Budget X X X X
Staffing X X X X
Technology Needs X X X
Facilities/Space X X X
Professional Development X X X
3. What challenges have charter schools faced
in implementing the use of data for decision-
making and school improvement and how were
they addressed?
X X X
Implementation Details: Lessons Learned X X X X
4. What evidence exists that the use of data for
decision-making resulted in positive
educational outcomes?
X X
Implementation Details: Evidence of
impact
X X X X
Implementation Details: Benefits X X X X
Implementation Details: Sustainability X X

61
CHAPTER FOUR
FINDINGS
The purpose of this study was to examine the effective use of data-driven
decision-making as a promising practice by charter school leaders to increase student
achievement. This study was conducted in two California Charter Schools.
Qualitative descriptive case study methods were applied to conduct the investigation.
Each school was visited within a five day period during the months of July, August,
September and October, 2010. At each school the Executive Directors, principals,
and other significant instructional leaders were interviewed. Findings for the study
were drawn from interviews, observations, Web sites of each school and document
analysis. The results of this research will be incorporated into a Web-based
compendium of promising practices hosted by the USC Center on Educational
Governance.
Chapter Four was divided into two sections that presented the research
findings from Coastal Academy Charter School (K-8) and Synergy Charter
Academies, which included Synergy Charter Academy the elementary school (K-5)
and Synergy Kinetic Academy the middle school (6-8). The section begins with a
background description of each school, followed by a discussion of the promising
practice: data-driven decision-making. The goal of using data-driven decision-
making and the implementation of details, as related to the theory of action described
in Chapter One follows. Next, benefits, resources requirements, challenges, and
lessons learned of the promising practice will be covered. Lastly, recommended

62
resources instrumental in using data to make decisions and improve student
achievement will be listed.
Coastal Academy Charter School
Introduction to the School
Coastal Academy Charter School opened in August, 2003 and is located in
Oceanside, California. Oceanside is a forty-two square mile coastal community in
San Diego County adjacent to the Pacific Ocean. The mission of Coastal Academy is
“To provide access to all students and will assist parents in their mission to inspire
their children to acquire a love and passion for learning” (California Distinguished
School Application, 2010, p. 4). To achieve its mission the school was committed to
creating a personalized academic environment achievable by all students. Coastal
Academy implemented and prepared instructional programs that challenged and
inspire students to reach personalized academic growth (Distinguished School, 2010,
p. 4). Student academic growth was monitored by an ongoing analysis of at least
three points of academic data to make instructional decisions for students, which
included: Measure of Academic Progress (MAP), Reading Plus, teacher made
assessments, teacher observation, and STAR results (Principal, interview, July 9,
2010).
Coastal Academy utilized an independent study approach with a Personalized
Learning model. Average Daily Attendance (ADA) was not generated based on “seat
time” but on the number of assignments completed in accordance with Independent
Study requirements established by the California Department of Education (CDE)

63
(Coastal Academy WASC Self-Study Report, 2005).This was accomplished by
providing rigorous and flexible academic programs that partnered with parents in
their mission to educate their children. Instructional focus was based on CDE
frameworks and state standards (Coastal Academy WASC Self-Study Report, 2005).
Coastal Academy utilized four main strategies to differentiate instruction of all
students, which included: assessment, personalized learning, small class size and a
focus on learning styles (Distinguished School Application, 2010). Students attended
classes at the school two days per week, were home schooled two days, and one day
was dedicated to school workshops such as: arts and crafts, painting, music, drama,
foreign language, science enrichment, leadership development, computers and
intervention in mathematics and language arts.
School Demographics
Coastal Academy Charter School is a suburban school and had an enrollment
of 710 students in grades K-8. The majority of students were White with Latino and
African-American students as a substantial number. The special education
enrollment was six percent. The school did not receive compensatory Title One or
Bilingual funds. Twenty-two percent of students qualified for free or reduced lunch
(CDE, Accountability Progress Report, 2010). State funds were sent directly to
Coastal, not to the district first. The school was overseen by a board of five trustees.
The trustees were elected to the board by existing board members. The Board
complied with the requirements of the Brown Act (California Distinguished Schools,
Application, 2010).

64
Coastal Academy operated on a modified school calendar in which staff and
students were placed on three tracks, operating from late August to June. The school
employed one school administrator, the principal, one technology media specialist,
22 full-time and three part-time teachers. Teachers were hired on an “at will” basis.
Coastal Academy was a part of the Classical Academies Network and all business
and operational aspects of the schools were handled by the Executive Director of the
Classical Academies Network. The principal was responsible for the selection of
personnel, budget and operations of the school as well as; the instructional program
to include: daily classroom visits, professional development, teacher support and
classroom instruction. Meeting and training parents, participation in Student Success
Team and Individualized Educational Program meetings were also included in the
duties of the principal. The principal at Costal Academy was also called upon to
provide professional development to all principals of the Classical Academies
Network in the areas of using and interpreting data to make decisions and use of data
to affect instruction and student achievement. Table 3 provides a demographic
profile of Coastal Academy.

65
Table 3. Demographic Profile of Coastal Academy (2010-2011)

Variable Descriptor
Charter status Start-up
Charter authorizer Oceanside Unified School District
Year chartered 2003
Grades served K-8
Students served 710
Student ethnic population African-American 10%
Asian 8%
Hispanic 17%
White 61%
Biracial 2%
Other 2%
Special Student Populations Students with disabilities 6%
English Learners 0
Gifted 0
Free/reduced lunch 22%
Number of full-time
administrators
1
Out of classroom personnel 1
Number of full-time teachers 22
Number of part-time
teachers
3
Per-pupil spending $4,700
Collective bargaining unit No
Type of school Site based/independent study
Web-site coastal@classicalacademy.com
Source: CDE website and School Accountability Report, 2010

66
Description of Data-Driven Decision-Making
Data-driven decision-making at Coastal Academy Charter School consisted
of administering and evaluating the results of multiple measures of student academic
performance data. The Measures of Academic Progress (MAP) a national standards
examination in reading, language arts and mathematics was given to all students at
the beginning of the year and again at the end of the year in the spring to evaluate
academic growth. Struggling students were tested at mid-semester to determine
growth or changes in curricular strategies as needed (Principal, interview, July 9,
2010). Other assessments used and evaluated were Reading Plus and Lexia, an
online reading progress assessment that denoted student comprehension levels, and
Saxon Math, where students were tested on a weekly to biweekly basis to evaluate
standards based math proficiency (Teacher IV, interview, September 27, 2010).
Teacher made assessments, connected to State Standards, were reviewed by teachers
on an ongoing basis and were considered a significant data resource (Teacher III,
interview, September 27, 2010). Other data used included the review and analyses of
formative assessment (student portfolios, group projects, journaling, and enrichment
games). Results of STAR testing were discussed and reviewed by the total staff in
August. The results were dissected and discussed thoroughly in professional
development sessions at the beginning of the year in order to begin the year with
improved standards driven instruction at each grade level (Observation of
Professional Development session August 16 & August 17, 2010). Finally, the day to

67
day progress of the student as observed by the teacher and parent were important
tools in the data driven process (Principal, interview, July 9, 2010).
Goal of Using Data-Driven Decision-Making
The main purpose of data-driven decision-making at Coastal Academy was to
customize the instructional program for each child and to develop a learning program
that was neither too difficult nor too easy. The principal stated, “We do not create
any artificial ceilings or barriers for kids to be able to move forward” (Principal,
interview, July 9, 2010). The principal also noted that teaching was about
concentrating on the individual learning needs of each child and data provided the
staff with unbiased information. It allowed the conversation to focus on specific
individual learning needs rather than general assumptions. According to the fourth
grade teacher, who served on the Leadership Council, “Data is a way to view the
child as an individual for their personal and individual education needs. It also helps
the teacher create a positive connection with parents and takes the “Drama out of
parent conferences because data provides us something quantitative to look at and I
can show parents specifically where and how their child is succeeding or struggling”
(Teacher Leader III, interview, September 27, 2010).
As a result of data use a transparent communication system was in place for
all stakeholders, allowing them to focus on the child’s learning strengths and
weaknesses. Most importantly, the teachers and parents learned to develop strategies
to help the child strengthen their learning weaknesses. This was accomplished by the
principal meeting with parents and offering a training session on specific teaching

68
strategies and or standards and offering professional development on explicit
teaching strategies teachers felt they needed (Teacher IV, interview, September 27,
2010). Figure 2 details how data-driven decision-making is used at Coastal Academy
to improve student achievement in connection with the Theory of Action.

69

Figure 2. Theory of Action: Coastal Academy School Leaders’ Use of Data-Driven Decision-Making

70
Implementation of Data-Driven Decision-Making
History of Implementation
Data-driven decision-making was used at Coastal Academy since the opening
of the school seven years ago in 2003 (Executive Director, interview, September 24,
2010). According to the principal, the school began by using the Measures of
Academic Progress (MAP), a national standards assessment to measure growth in
mathematics, reading, and language arts. At its inception Coastal Academy was a
small fledgling school with approximately 100 students. MAP was a way of
measuring students against national norms until the school had enough data over a
three year period to observe how their students were doing over time. Within the last
three years the school delved closely into using data as a means to focus on the
learning process of each child (Principal, interview, July 9, 2010).
Since the inception of Coastal Academy in 2003 data use to make decisions
and focus on student achievement was a process led and driven by the principal. The
Executive Director and five teacher leaders interviewed at Coastal Academy all
agreed and emphasized the principal was the driving force in the use of data-driven
decision-making. As stated by Teacher Leader I (August 27, 2010), “The principal
motivated the team and it was definitely her influence and her expertise that placed
everyone onboard in using data-driven decisions and making it happen”. Teacher
leaders interviewed noted the principal was knowledgeable on the use of data to
drive instruction and engaged the staff in discussion about their students based on
data results. Furthermore, the principal focused on student achievement and

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motivated the staff to alter their teaching practices to enhance the learning of each
child. The principal also led professional development sessions at the beginning and
throughout the school year on data results, the interpretation of data, and using data
to improve teaching strategies. Additionally, the principal used staff meetings to
have informal data sharing on what was going on in the classroom and provided
ideas for improved instructional practices (Teacher Leaders I, III & IV, interviews,
September 27, 2010).
Evidence of Impact
All stakeholders felt strongly that data-driven decision-making had a positive
impact on students based on two sources of student outcome data: 1) high test score
results of 860 on the 2010 California Academic Performance Index (API), and 2)
most students were proficient or above in English/language arts 69.1% and
mathematics state standards 65.9% (CDE, Accountability Progress Report, 2010). At
Coastal Academy, STAR test scores increased consistently since the school opened
in 2003. Also evident was the increased enrollment to over 700 students at the
beginning of the 2010-2011 school year from 100 six years ago. Teacher leaders
believed the increase of enrollment was an indication of public support on how data
were used at Coastal Academy to promote student achievement (Teacher IV,
interview, September 27, 2010). According to the Executive Director, using data-
driven decision-making indicated to the leaders of the organization and to the public
that students were accessing the important information which led to success on State

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Standards and ensured that students were learning what was expected by the State of
California (Executive Director, interview, September 24, 2010).
Teacher leaders expressed that although State data denoted high scores on the
California Standardized Tests, what the results did not show was that data helped
them focus on the specific learning needs of each child. The BTSA coordinator who
also taught mathematics stated that on a smaller scale data showed the smaller gains
of the child, “Little achievements where a student is below grade level coming into
the school and by the end of the year leaves at grade level…just seeing those happy
moments are well worth the consistent use of data” (Teacher Leader II, interview,
August 17, 2010).
Another teacher stated that data definitely helped her in working with
students on an Individual Educational Program (IEP). It provided her the opportunity
to observe ongoing growth or lack thereof in each student with an IEP. She could
immediately amend the plan or knew if she was on the correct track with the students
(Teacher Leader III, interview, September 27, 2010). This teacher further noted:
Data-driven decision-making has led to student achievement and overall
school success because using data to make decisions fits the need of specific
children’s learning goals. Taking a look at where students are on a daily,
monthly, bi-yearly basis and analyzing that data lends itself for teachers to
make objective decisions based on what students need, rather than where they
really are not or where the teacher thinks they are, which leads to subjective
decision-making. (Teacher Leader III, interview, September 27, 2010)

Additional evidence of impact, as shared by another teacher leader was that
focusing on observational data helped her meet the individual learning styles of each
child. Observations offered her an awareness of which students needed to get up and

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walk around, or stretch from time to time or who needed to work with his/her hands.
The visual learners, made her cognizant of using media, technology and other visual
aids to explain a concept. Observational data helped her adapt and personalize her
teaching to meet learning style of each student (Teacher Leader IV, interview,
September 27, 2010).
Finally, a teacher leader mentioned the excitement in using objective
classroom assessments to watch the continuous growth of students in content areas,
“We have students that are so involved in the learning process that they do not want
to leave at the end of the day” (Teacher Leader III, interview, September 27, 2010).
The teacher attributed this behavior to using teaching strategies that focused on the
learning needs of each child. It was further noted that teachers were aware that the
journey of learning would never go as planned and were constantly altering their
teaching as data were evaluated. The objective of using varied instruments was noted
in the California Distinguished School Application 2010:
Students are increasingly opting to show their knowledge through use of
technology, visual presentations, and project based activities. This provides
students with the opportunity to demonstrate knowledge in a variety of ways;
encourages student ownership, skill development, and academic achievement
(p. 2).
Teacher leaders interviewed felt they were fully supported by the principal in
developing unique and creative lessons that met student learning.
Benefits of Data-Driven Decision-Making
All teacher leaders interviewed embraced the use of data-driven decision-
making as a tool for improving student achievement. They felt strongly that using

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data were a factor in the high STAR testing results and the results contributed to
assuring parents they had chosen the right school for their children (Teacher Leader
IV, interview, September 27, 2010). Data provided an unbiased look at the child and
warranted total focus on the learning needs of the student (Principal, interview, July
9, 2010). The principal and teacher leaders shared their professional views on the
benefits of data-driven decision-making to students, teachers, school administrator
and parents in the following segment.
Students
The most commonly cited benefit by both teacher leaders and the principal
was that being transparent with students about their assessment results allowed them
buy-in to the instructional program, fostered ownership of the learning process, and
helped students set learning goals. Appropriate resources and teaching strategies
were put in place that met student specific needs; students understood where they
stood and what objectives were expected of them to succeed. They could focus on
areas of weakness in a non-threatening manner and as students saw improvement,
learning became an exciting and positive venture (Teacher Leaders I, III & IV,
interviews, September 27, 2010). According to the principal, when students were
involved in setting goals for their learning, they saw self-improvement and the idea
of academic growth became exciting (Principal, interview, July 9, 2010).

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Teachers
Teacher leaders specified that the most beneficial aspects of using data were:
• Data allowed them to pinpoint and narrow the focus on the specific
learning needs of each student.
• Analyses of results on an ongoing basis helped teachers know if they
were on the right track and doing an adequate job, which provided
fulfillment in the teaching experience.
• Uses of data to make decisions in lesson planning created student success,
making teachers feel good about their work.
• Data results helped teachers determine what professional areas needed
improvement. (Teacher Leaders, I, II, III, IV, interviews, August,
September, 2010)
The principal felt strongly that at Coastal Academy, teachers liked having evidence
that indicated they were making a difference in the learning process and lives of
children, “Data shows that they’re making a difference and that brings meaning and
fulfillment to their experience as teachers” (Principal, interview, July 9, 2010).
School Administrator
The school principal noted that using data, “Gives me a forum to have
ongoing, similar conversations, with the same language, between kids, parents and
teachers. Everyone is using the same language and takes personalities out of focusing
on the specific needs of the child” (Principal interview, July 9, 2010). Teacher
leaders acknowledged that using data allowed everyone to work as a team for student

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success with the same objectives and goals for the student. Additionally, teacher
leaders mentioned that it helped the administrator make necessary changes in the
school program when appropriate; know if teachers were doing a good job; and
where to provide teacher support. Finally, one teacher stated, “Administrators like
doing a good job also and feel secure in knowing that everyone is making a
difference with the children served…it makes the parents happy, the children happy
and the teachers happy…What is there not to like?” (Teacher IV interview,
September 27, 2010)
Parents
Parents worked in partnership with Coastal Academy, in home schooling
their children two days per week. Using data showed them that the teaching
strategies used at home were appropriate and the decision to partner with this charter
school was the right one (Principal, interview, July 9, 2010). Likewise, the principal
spent considerable time providing parents with professional development to enhance
their skills in using effective standards driven strategies when working with their
children (Principal, interview, July 9, 2010). Teacher leaders felt strongly that data-
driven decision-making took the drama out of parent conferences and kept the
conversation focused on the learning needs of the child. Data allowed teachers to
pinpoint the areas parents needed to reinforce at home with their children.
Furthermore, by sharing data with parents they were more accessible to adopting
teaching strategies, shared by teachers, to benefit their child’s learning needs

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(Teacher Leader II, interview, August 17, 2010; Teacher Leader III, interview,
September 27, 2010).
Resource Requirements
Budget
The three large expense items in carrying out data-driven decision-making at
Coastal Academy were: time, professional development and the licensing for MAP.
Time was defined as the participation by teachers and staff to look at reports, analyze
data results, ask questions and have the conversation about how data affects each
child. Teachers were expected to use data and to use data results when speaking with
parents. Teachers were highly encouraged to participate in NWEA-MAP online
training designed to help the teaching team get the most out of data, which provided
support to improve student learning through the use of data generated NWEA-MAP
reports. Therefore, it was likely to see teachers having discussions about student data
in the morning, after school, in small groups or with the principal. Time for further
discussion was provided during faculty meetings (Observation of Professional
Development Session-School visit, August 17, 2010).
Teachers were paid their salary rate for attending the required professional
development at the beginning of and throughout the school year. The principal had
not generated the exact cost but stated Classical Academies Network supported the
importance of using data-driven decision-making and the costs were sustained as part
of the organizational budget (Principal, interview, July 9, 2010).

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Lastly, the licensing fee for MAP was twelve dollars per student or
approximately $8500 (eighty-five hundred dollars) per year. The cost included the
use of the assessment instruments all year, individual student reports, teacher class
reports, schoolwide and district reports (Principal, interview, July 9, 2010). Online
professional development was available to teachers and staff, which could be
completed at home, at no cost. All teacher leaders interviewed were unaware of
budgetary expenditures to carry out the data-driven decision-making process.
However they all indicated that regardless of the NWEA-MAP cost, it was worth the
expense as a necessary tool in a school that looked at data to serve children.
Facilities
A computer lab was required to carry out MAP testing. The lab technician
uploaded the data to NWEA and they downloaded the results to Coastal Academy.
The school was equipped with an updated computer lab with 30 stations (Principal,
interview, July 9, 2010).
Professional Development
Professional development was an essential component at Coastal Academy
and was carried out at the beginning of each semester in August and February. The
school year began with one week of required professional development presented by
the principal on STAR results, interpretation of testing results, analyses of testing
data , how to use data, and setting yearly goals for children by using data
(Observation of Professional Development Session, August 17, 2010). Data-driven
topics such as: Looking at our STAR Data and Standards, Deciphering Data,

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Reading STAR and MAP Reports, Using MAP Data Effectively, Reading Plus/Lexia
were scheduled into the training session (Professional Development Agenda, August
16-20, 2010). Aside from required professional development for all staff, new
teachers also participated in: Dance with Your Data and Sparkle with the Standards:
Implementing Effective Research-Based Strategies to Maximize Student Learning,
training sessions led by the principal (Observation of Professional Development
Session, August 17, 2010; Professional Development Agenda, August 17, 2010).
Although the majority of professional development topics focused on the
data-driven process, training on instructional strategies were important in order to
help teachers make the connection between data and learning. Professional
development included the following areas: Cores Standards Based Curriculum, Math
and Reading Support, First in Math, Everything Science, Quantum Learning Tips
and How to: Jerry John’s Reading Inventory (Observation of Professional
Development Sessions, August 17, 2010; Professional Development Agenda, August
16-20, 2010). The principal also participated in professional development throughout
the year within several charter organizations: the California Charter Schools
Association, and the National Charter School Association. She attended principal
training through Quantum Learning to update her knowledge in the area of effective
middle school teaching strategies and maximizing teacher use of classroom time
(Principal, interview, July 9, 2010).
Since teachers were expected to implement the use of data to drive
instruction, monthly staff meetings included discussion on various data-driven topics

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such as: participation in NWEA webinar, teachers sharing strategies to improve test
scores, or discussion on using data to assist a struggling student improve his/her
skills (Teacher III, interview, September 27, 2010). Teacher leaders expressed a need
to have professional development sessions on using the NWEA- MAP system at
higher levels and on analyzing formative assessment data more effectively.
Challenges
Overall the staff and administration at Coastal Academy welcomed the use of
data as an instructional tool. They strongly believed it took intuition and hear-say out
of the decision-making process. However, there were some challenges expressed by
teacher leaders and the principal.
A challenge cited by the school principal was to convince the public that
data-driven decision-making was not teaching to the test, an added teacher duty, or a
way to get rid of personnel. It was not to show that one teacher was better or worse
than the other but rather a culture of everyone working collaboratively to develop
successful teaching strategies that made learning exciting for children (Principal
interview, July 9, 2010). The principal further noted:
I think here on this campus it’s different than…I immediately put on my hat
as a former traditional public school or district office administrator and
they’re very different. They’re very different. If I put on my district hat or my
traditional public school hat, the challenges of implementing data-driven
decision-making, is people see this as just one more extra thing that they have
to do. It’s an add-on. It’s something that they didn’t sign up for. It’s
something that they see as a gotcha kind of thing. The data is used to get rid
of me or to somehow make me look bad or to make someone standout better
than someone else. This is not part of this culture and I know those are the
huge impediments in a traditional public school. Here there really haven’t
been any challenges in using data because it’s always been an expectation

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and the challenge is to get this information out to the public. (Principal,
interview, July 9, 2010).

The Executive Director felt the greatest challenge was to keep parents
actively involved in the teaching process as partners with the school. It was
important the school leader kept enthusiasm high for the use of data when new
parents entered the organization. To address this challenge he advised principals to
develop a personal relationship with new parents and explain the importance of
embracing the data-driven process (Executive Director, interview, September 24,
2010).
Consequently, for teachers the greatest challenge was finding an assessment
that would pinpoint the learning needs of some children. According to teacher
leaders interviewed, MAP, and STAR did not always show the actual growth of a
child’s learning capabilities (Teacher Leader I, interview, August 17, 2010; Teacher
Leader III, interview, September 27, 2010). As one teacher leader stated, “It can be
disheartening for both teacher and student if they are both working very hard and the
data does not reflect growth…It’s finding an assessment for some children that really
does not fit the traditional testing model or traditional assessment” (Teacher Leader
III, interview, September 27, 2010).
Lessons Learned
In addition to the challenges mentioned, the principal shared some lessons
learned about the data-driven decision-making process, including its sustainability.
According to the principal who worked in the regular public school sector for over

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30 years as a teacher, school site administrator, and whose prior position was
Assistant Superintendent of Instruction, before coming to the charter school, “data-
driven decision-making works if carried out in a collaborative way that is not hostile
to any one group. It helped everyone do a better job due to the ongoing analysis of
data connected to teaching and learning” (Principal, interview, July 9, 2010).
Furthermore, an important lesson learned by all staff members, as stated by the
principal, was that when standards were raised students always met or surpassed the
challenge as long as they were taught what was expected. When achieved, standards
could be measured with data. Moreover, an array of data on a child could serve as a
toolbox of resources to help the student become a successful learner. With the use of
data; as teachers gained experience the resources became more plentiful (Principal,
interview, July 9, 2010).
Sustainability
A continual embrace of data use were essential if its sustainability was to be
maintained. Teachers, parents and students currently looked at data automatically.
Although API had increased over the years to 870 the school goal was to reach 900.
A continuation of data use, data analysis and discussion would continue at Coastal
Academy along with professional development that was central to meeting the
instructional needs of each child. According to the principal, using data was part of
the school culture and it would be difficult to imagine the lack of data use to drive
instruction and meet the specific learning needs of each child in the school
(Principal, interview, July 9, 2010).

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Recommended Resources
The following list of resources assisted Coastal Academy Charter School in
their system of data-driven decision-making:
Marzano, R. J. (2000, December). Implementing Standards-based Education.
Teacher Librarian, 28(2), 30-32.
Marzano, R. J. (2003). The art and science of Teaching: A comprehensive
framework for effective instruction. Alexandria, VA: Association for Supervision and
Curriculum Development.
Marzano, R. J., Waters, T., McNulty, B. A. (2005). School Leadership that
Works: From Research to Result. Alexandria, VA: Association for Supervision and
Curriculum Development.
Northwest Evaluation Association website: http://www.nwea.org/
Reeves, D. B. (2009). Leading Change in Your School: How to Conquer
Myths, Build Commitment and Get Results. Alexandria, VA: Association for
Supervision and Curriculum Development.
Reeves, D. B. (2002). The Leader’s Guide to Standards: A Blueprint for
Educational Equity and Excellence. San Francisco, CA: Jossey-Bass Publishing.
Wiggins, G., & McTighe, J. (2001). Understanding by Design. Upper Saddle
River, NJ: Merrill Prentice Hall, Inc.
Schlechty, P. C. (2009). Leading for Learning: How to Transform Schools
into Learning Organizations. San Francisco: CA: Jossey-Bass Publishing.

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Synergy Academies
Introduction to Synergy Academies
The Synergy Academies network consisted of Synergy Charter Academy
elementary (K-5) and Synergy Kinetic Academy middle school (6-8). Synergy
Charter Academy elementary school opened in August, 2004 and Synergy Kinetic
Academy middle school began in 2007. Synergy Quantum Academy high school
will begin operation in 2011(WASC Self-Study Report, 2010). The Synergy
elementary and middle charter schools were start-up charters granted charter status
by the Los Angeles Unified School District (LAUSD). Both schools were located in
the City of Los Angeles serving zip code area 90011. Zip code area 90011 was
approximately 4.5 square miles in one of the most densely populated areas in the
inner-city of Los Angeles. The median household incomes of $23,861 significantly
lower than the US population of $56,604, qualified the area as one of the most
depressed in Los Angeles (US Census, 2010). The mission of the Synergy
Academies network was “To eliminate the achievement gap that has persisted for
generations among educationally disadvantaged students” (WASC Self-Study
Report, 2010, p, 35). Synergy’s vision is that “All students will meet or exceed
California Content Standards and be prepared to take college-preparatory classes in
secondary schools in order to attend a four-year university or college of their choice”
(WASC Self-Study Report, 2010, p. 35). Both schools achieved this mission by
teaching to a rigorous standards based curriculum with strong emphasis on language
arts and mathematics as well as promoting comprehensive standards-based

85
instruction in science, health, history/social science, the arts and physical education
(WASC Self-Study Report, 2010). A traditional approach to teaching in all core
subject areas was driven by its vision that all students would excel on the California
State Standards and be academically prepared to take college preparatory courses in
high school that would gain them admission to a four year college or university
(School Plan, 2008-2011). Academic student growth was monitored on an ongoing
basis by analyzing several points of academic data such as: California Standards Test
(CST), Open Court Reading Assessments, Harcourt Math Assessments (elementary),
McDougal Littell Assessments (middle school), Reading Counts quizzes, Scholastic
Reading Inventory, teacher observation, periodic assessments and teacher created
subject tests (WASC Self-Study Report, 2010). In addition, Synergy Academies
embodied the motto, “Together We Are Better” and put in place a systemic approach
practiced by all members of the “Synergy Family”, parents, teachers, classified staff,
administrators and the broader community, which motivated and focused all students
to excel in the learning process together, with each other, and as a team (WASC
Self-Study Report, 2010).
School Demographics
Synergy Charter Academy elementary and Synergy Kinetic Academy middle
school were urban schools, part of the Synergy Academies network, located in the
center of the City of Los Angeles. Enrollment at the elementary school was 312
students with 355 students at the middle school. The ethnic student enrollment at
each school was approximately: 89%, Latino, 10% African-American with two

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Filipino and one White student (CDE, Accountability Progress Report, 2010).
Approximately, nine percent of the students had an IEP for special education and
54% of the students were categorized English Learners. Eighty-nine percent of
students at the elementary and 96% at the middle school participated in the
free/reduced lunch program (CDE, Accountability Progress Report, 2010).
The Synergy Academies network operated on a traditional calendar from
August to June. Three week summer school was held for ongoing students who did
not meet state standard proficiency by the end of the school year, for all new
incoming sixth grade students regardless of their ability level; to become acquainted
with school culture, and development of academic foundations; and for all new
students in all grades not meeting proficiency in English and mathematics on the
baseline examination (Chief Executive Officer, interview, August 25, 2010). The
elementary school employed thirteen teachers, and one principal. There were 15 full-
time teachers in the middle school and one principal. Both schools employed a small
number of campus aides (Middle School Principal, interview, September 2, 2010).
The principals at each school were responsible for the instructional program
to include: weekly professional development; dissemination and analysis of ongoing
data; classroom instructional procedures; daily visits to classrooms; modeling of
effective teaching practices; leading interventions groups (during the day or after
school) to address any deficiencies in math or reading faced by a small group of
students; teacher support; and conducting IEP and Student Success Team (SST)
meetings (Elementary, Middle School Principal, interviews, September 2, 2010;

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WASC Self-Study Report, 2010). Principals were also responsible for student
supervision, discipline and parent participation. A Chief Achievement Officer and
part-time BTSA Coordinator were hired by the network to serve both schools. The
Synergy Academies network has one Chief Executive Officer, and a Director of
Operations. All employees serve on an “at will” basis with one year contracts
(Synergy Academies Documents). Table 4 summarizes the demographic profile of
Synergy Charter Academy and Table 5 offers a demographic profile of Synergy
Kinetic Academy.
The school received compensatory Title One funds in addition to regular state
funding. The school was overseen by a board of directors, which included eleven
members. The board members were elected to the board by existing board members.
The Board of Directors included one non-voting member from the authorizing
agency, LAUSD. Compliance of the Brown Act, which ensures public meeting and
public deliberation of all issues, was required of the Board of Directors (WASC Self-
Study, 2010).

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Table 4. Demographic Profile of Synergy Charter Academy (2010-2011)

Variable Descriptor
Charter status Start - up
Charter authorizer Los Angeles Unified School District
Year chartered 2004
Grades served K-5
Students served 312
Student ethnic population African-American 9%
Asian 0
Filipino 0
Hispanic 89%
Native American 0
White 0
Other 1.94%
Special Student Populations Students with disabilities 5%
English Learners 28%
RFEP (Reclassified Fluent English
Proficient)
13%
Gifted 2%
Free/reduced lunch 86%
Number of full-time
administrators
1
Out of classroom personnel 2
Number of full-time teachers 13
Number of part-time teachers 0
Per-pupil spending $6506
Collective bargaining unit No
Type of school Independent site charter
Web site synergyk12@gmail.com
Data obtained from: CDE website and School Accountability Report Card, 2010

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Table 5. Demographic Profile of Synergy Kinetic Academy (2010-2011)

Variable Descriptor
Charter status Start - up
Charter authorizer Los Angeles Unified School District
Year chartered 2007
Grades served 6-8
Students served 355
Student ethnic population African-American 9%
Asian 0
Filipino 0
Hispanic/Latino 91%
Native American 0
White 0
Other 0
Special Student Populations Students with disabilities 4%
English Learners 26%
RFEP (Reclassified Fluent English
Proficient)
34%
Gifted 10%
Free/reduced lunch 96%
Number of full-time
administrators
1
Out of classroom personnel 2
Number of full-time teachers 15
Number of part-time teachers 0
Per-pupil spending $5235
Collective bargaining unit No
Type of school Independent site charter
Web-site synergyk-12@gmail.com
Source: CDE website and School Accountability Report Card, 2010

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Description of Data-Driven Decision-Making at Synergy Academies
An overarching belief of the leadership at Synergy Academies was that
everyone working together with the same goals and objectives, fostered learning
success to students; was everyone’s responsibility (WASC Self-Study, 2010). At
Synergy Charter Academy and Synergy Kinetic Academy data-driven decision-
making consisted of using multiple assessments and evaluating tools. The same
assessments were used at both schools. The key instruments for evaluating reading
proficiency were Reading Counts and the Scholastic Reading Inventory (SRI).
Reading Counts was an independent reading assessment program in addition to the
prescribed reading program, Open Court Reading (OCR) offered at the elementary
school. Reading Counts scores were monitored on a weekly basis by teachers and
the principals with a weekly report sent home to parents. Students were expected to
reach 80% proficiency on the weekly reading quizzes. Scholastic Reading Inventory
was administered quarterly to continuously examine student reading improvement.
SRI scores were used to determine the Lexile reading level of each child, facilitating
placement in the correct independent reading level in the Reading Counts program
(Chief Executive Officer, interview, August 25, 2010; Elementary, Middle School
Principal, interviews, September 2, 2010).
All new students enrolled at Synergy Charter Academy from grades 2nd - 5th
and Synergy Kinetic Middle School grades 6th-8
th
were given a school developed
math assessment packet. Results from the examination were used to determine the
student proficiency on number sense and computational skills for the purpose of

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math placement and intervention (Middle School Principal, interview, September 2,
2010). In keeping with the mission to end the achievement gap each child entering a
Synergy Academy was met where they were academically. Both schools pursued
effective strategies in an effort to have each child reach grade level as quickly as
possible. Therefore, the urgency to administer baseline examinations in
reading/language arts and mathematics prior to the beginning of summer school and
begin the intervention process immediately was critical. In addition, to the placement
examination, mathematics teachers at Synergy Kinetic Academy administered the
mathematics standards based assessments provided by McDougal Littell at the end of
each unit along with teacher made tests given each week (School Plan, 2008-2011).
During the Spring, 2011 both schools adopted the Scholastic Mathematics Inventory
in an effort to increase the mathematical levels of all students in preparation for high
school (Middle School Principal, email document, January 30, 2011). Analyses of
STAR-CST testing results prior to the beginning of the school year were an essential
process of data-driven decision-making at Synergy Academies. At the beginning of
the school year the Chief Achievement Officer provided the professional
development on STAR-CST results in language arts, reading and mathematics. The
results were presented and analyzed. Furthermore, teacher analysis of ‘teacher made
subject tests’ based on state standards was an ongoing course of action (Teacher
Leader I, interview, October 10, 2010).
In regard to data-driven decision-making at the schools, the Chief
Achievement Officer stated, “We consider ourselves data-driven schools, so we love

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looking at data and figuring out how kids are doing and how to get them to the next
level” (Chief Achievement Officer, interview, July 26, 2010). He further explained
that along with using standardized test data, the school looked at how students
performed on specific assignments, reading fluency patterns of struggling readers,
grades earned in core subjects, homework assignments, and overall motivation in the
learning process. Data was used to focus on where each student fell in the
achievement process. Through data use such as: English language arts testing and
mathematics placement exams the learning needs of each child were determined. The
use of data allowed staff and teachers to engage in very specific conversations
regarding the learning process as it related to individual students (Chief Achievement
Officer, interview, July 26, 2010).
Goal of Using Data-Driven Decision-Making
One of the fundamental goals in the use of data-driven decision-making at
Synergy Academies was to guarantee the effort made by staff and teachers were
focused on student learning needs. By analyzing the learning accomplishments of
students on lessons taught, the staff was instantly aware if the lessons and strategies
used in the teaching process were successful or if re-teaching and altering of
strategies were necessary. Without constant evaluation and feedback teachers were
unaware of their effectiveness or lack thereof (Chief Achievement Officer, interview,
July 26, 2010).
Another goal for using data-driven decision-making practices was to
demonstrate constant growth in the child’s learning process. As an example, both

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schools established the goal that 95% of students would be at grade level in reading
and mathematics (Teacher leader V, interview, August 25, 2010). Therefore, as
previously mentioned it was essential at the Synergy Academies to focus on the test
placement levels of each student and immediately begin to excel their learning to
grade level or above. Prompt identification of the academic level was core to the
teaching philosophy at Synergy Academies; since data demonstrated that students
from Synergy Academy elementary accounted for only 20% of the enrollment at the
middle school, and the remaining 80% were new to the middle school. The data
validated that it was impossible for the middle school to have carry-over enrollment
of students from elementary school (Chief Achievement Officer, email document,
January 28, 2011). Therefore, it was critical to monitor the learning steps of each
child from beginning, middle, to end; as the ultimate goal at the Synergy Academies
was to, close the achievement gap and guarantee that every student who graduated
from Synergy Quantum Academy in 2015 had the opportunity to complete a college
education (Chief Executive Officer, August 25, 2010). As the principal of the
elementary school stated, “We want our kids to be good kids and we focus on that a
lot, but data-driven decision-making is especially about increasing student
achievement at each level of the learning process” (Elementary Principal, interview,
September 2, 2010).
The elementary and middle school principals stated that student achievement
was the ultimate goal in the use of data-driven decision-making and looking at data
to establish appropriate student intervention, improve teaching strategies, and

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maximize teacher time were crucial (Elementary, Middle School Principals,
interviews, September 2, 2010). The elementary school principal noted that
observational data were optimal in assisting teachers to improve classroom
procedures. By observing basic classroom techniques like, how much time it took the
teacher to pass out papers, grade homework, quiet the students, work with a group of
struggling learners, the principal might be able to find an extra five to ten minutes to
make the learning process more efficient or assist in altering classroom management
procedures (Elementary Principal, interview, September 2, 2010).
Several teacher leaders noted that among teachers in their grade level,
monitoring student progress and monitoring the effectiveness of their lessons was the
goal of the data-driven decision-making process. Analyzing data helped teachers
evaluate how close they were toward reaching school goals; further analysis helped
them determine specific student learning needs. It also provided them with
information to share with students and their parents on the progression of their
learning (Teacher Leaders II, V, interviews, August 25, 2010). One teacher stated the
goal succinctly:
The goal of data-driven decision-making at this school is to create an
effective learning environment for our students; to optimize learning for our
students. We realize that not all students are at this uniform ability, and that
not all students can learn by one particular mode or method of teaching, so by
using the data that we garner from our assessments, we are allowed to, again,
break students off into level groups, based on their math or reading
assessments and skill level, and then teach a curriculum to them that is
streamlined to their pacing or learning needs. (Teacher Leader III, interview,
August 25, 2010)

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Another teacher leader mentioned the goal was to improve student progress in
mathematics and language arts and to break down the achievement gap, which data-
driven decision-making was “helping us accomplish” (Teacher Leader I, interview,
October 10, 2010). Finally, data were used to view the social and behavioral process
of the child. According to the Chief Achievement Officer, social and behavioral
problems were in many cases the result of academic frustration or a reflection that
the child was behind academically. By analyzing academic data, school personnel
were able to pinpoint the academic needs of the child and focus on learning, easing
behavioral and social issues. With a further investigation of data such as: home visits
and interviewing parents, other social and behavioral problems could be determined
and mitigated. It was important to note that many times behavioral problems went
hand-in hand with a student’s academic struggle (Chief Achievement Officer,
interview, July 26, 2010). At Synergy Academies the founders who serve as the
Chief Executive Officer and the Chief Achievement Officer were highly involved in
offering support to carry out the mission of the school as related to the Theory of
Action. Figure 3 is a graphical representation of data-driven decision-making at
Synergy Academies as related to the Theory of Action.

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Figure 3. Theory of Action: Synergy Academies: School Leaders Use of Data-Driven Decision-Making

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Implementation of Data-Driven Decision-Making
History of Implementation
Prior to the approval of Synergy Academy using data was a process used by
the founders of the school. The Chief Achievement Officer, who was one of the
founders stated:
We’ve always used data at our school. As we were going through our charter
petition process, we were already using data. We looked up data to describe
the students to be served; we looked up data to evaluate how the schools
around us were performing, and based on that, we identified the learning
needs that students had in the neighborhood. So, data has always been used to
guide what we do and it gives us direction and purpose. (Chief Achievement
Officer, interview, July 26, 2010)

Since establishing the first Synergy Academy, Synergy Charter Academy
elementary school in 2004 using data-driven decision-making to improve student
achievement was a process led by the co-founders who now serve as the Chief
Executive Officer, the Chief Achievement Officer and the elementary school
principal. After the second year in operation the school scored highest in the
demographic area, among all public elementary schools, with an API score of 709
(CDE Accountability Progress Report, 2010). Further analyses of data indicated that
only 28% of students scored at the State standard highest reading levels of proficient
or advanced. This realization required school leaders and teachers to look at data in a
more meaningful way. It spurred the asking of critical questions such as:
• What do these data mean?
• Where do the data come from?
• What are the significant interpretations of the data?

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• How do we use data to improve instruction and change teaching
strategies?
This process provided the momentum to collect and use data in a serious manner by
all staff, which continued to accelerate to this day (Elementary Principal, interview,
September 2, 2010). According to the elementary school principal, using data at
Synergy schools was the cornerstone of student achievement. Without the use of data
a school leader or teacher found it difficult to center on the learning needs of children
or where to center improvement on the teaching and learning process (Elementary
Principal, interview, September 2, 2010).
School principals, teacher leaders and the Chief Executive Officer all agreed
that the person who drove the focus on data-driven decision-making and maintained
the “big picture” on how a student progressed from K-8
th
grade; looked for trouble
spots and focused on fixing the trouble spots, was in the hands of the Chief
Achievement Officer (Chief Executive Officer, interview, August 25, 2010;
Elementary, Middle School Principal, interviews, September 2, 2010; Teacher
Leader I, interview, October 10, 2010; Teacher leaders II, III, IV, V, interviews,
August 25, 2010). As indicated by the middle school principal, “The Chief
Achievement Officer was ‘totally data-driven’, he breaks down the scores on all state
standards exams, analyzes teacher created exams, reviews textbook exam results, and
looks at periodic assessments” (Middle School Principal, interview, September 2,
2010). The Chief Achievement Officer led professional development regarding the
use and meaning of data for the total school community (on separate occasions),

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which included parents and students (Middle School Principal, September 2, 2010).
Furthermore, he led the beginning of the year professional development sessions in
such areas as: Purposeful Use of Data at Synergy Schools, Results and Analyses of
Year-End STAR Testing, and Uses of Data to Improve Instruction; primarily, in the
areas of reading and reading comprehension (Personal Observation of Professional
Development, August 23, 2010; Power Point Presentation IV, August, 23, 2010).
Although each school principal was responsible for informal sharing of data and
ideas for improved teaching practices, at weekly professional development sessions,
the Chief Achievement Officer planned and prepared with the principals on a weekly
basis. Lastly, when both schools came together at the beginning of each semester, the
Chief Achievement Officer was the major professional development presenter and it
was he who led buy-in to data use at the beginning of the school year (Chief
Executive Officer, interview, August 25, 2010; Middle School Principal, interview,
September 2, 2010; Observation of Professional Development, August, 23, 2010).
The school year began with, the Chief Achievement Officer presenting one week of
professional development for new teachers, and another week for all teachers and
campus aides from the elementary and middle school together, to include school
leaders from both schools (Observation of Professional Development session,
August 23, 2010).
Evidence of Impact
Inevitably, all persons interviewed for this study felt the California Academic
Performance Index (API) scores were strong evidence that data-driven decision-

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making was successful at Synergy Schools (Teacher Leader I, interview, October 10,
2010; Teacher Leaders II, III, interviews, August 25, 2010; Chief Achievement
Officer, interview, July 26, 2010; Elementary Principal, interview, September 2,
2010). The 2010 API for Synergy Charter Academy was 897; 74 % of students and
66% of English Learners met proficiency or above in English/language arts and 90%
of students met proficiency or above in mathematics with 86.9% of English
Learners. In 2010 Synergy Kinetic Academy received an API of 802; with 53% of
students meeting proficiency or above in English/language arts and 45.8% of English
Learners; in mathematics 47% met proficiency or above with 42% of English
Learners (CDE Accountability Progress Report, 2010). Scores on the California
State Standards examination consistently increased in the six year history of Synergy
Charter Academy. Synergy Kinetic Academy opened its doors in 2008 with
graduating students from Synergy Charter Academy elementary accounting for only
20% of the middle school student body (Chief Achievement Officer, interview, July
26, 2010).
As a result of schoolwide participation in Reading Counts an independent
reading assessment and Scholastic Reading Inventory, which tracks the reading level
and Lexile of students; reading comprehension increased (Chief Executive Officer,
interview, September 2, 2010). Students were expected to pass weekly reading
examinations at 80% proficiency. Any score below this required a retake of the
examination. In addition, at the beginning of the year students were given the
Scholastic Reading Inventory to determine their grade reading level; this test was

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given four times a year and each quarter the reading growth of students was palpable
(Teacher IV, interview, August 25, 2010). Over 70% of elementary school and over
54% of middle school students scored proficient or above in English/language arts
on the state standards examination (CDE, Accountability Progress Report, 2010).
These results were evidence to school leaders, teachers and parents that following
weekly reading data on each student and monitoring the proficiency results helped
students achieve.
School leaders and teachers interviewed for this study indicated that State and
other inventory results did not show the observed achievements of students. The
Chief Achievement Officer stated, “Observing students engage in rigorous
conversations in the classrooms, seeing that students are doing well in classroom
assignments and incorporating the knowledge of skills from previous classes into
new concepts are all indications that the data-driven approach is working” (Chief
Achievement Officer, interview, July 26, 2010). In addition, the Elementary
Principal (Interview, September 2, 2010) pointed out that watching student growth in
communication skills, developing self-confidence, looking at the pride in parents,
and the pride students have for their community and their school is an indicator that
what Synergy schools are doing works. Similarly, a teacher leader indicated,
We think that data-driven learning boosts student morale. We use data to
create curriculum that is challenging for our students. Our student rise to the
challenge, teachers rise to the challenge; we’re assessing them (students) in
rigorous, meaningful ways, our students are receiving a fair and equitable
education and they tell me how good it feels to be successful. (Teacher
Leader III, interview, August, 25, 2010)

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Lastly, the middle school principal stated that academic success was not measured
only in the numbers seen on paper but on how the kids felt in coming to school. The
principal concluded, “The kids enjoy coming to Synergy schools, they are happy,
they know they are learning, that they can learn and will learn; what is important is
how you feel inside your heart about the learning process…and the kids are always
talking about how much they are learning” (Middle School Principal, interview,
September 2, 2010).
Benefits of Data-Driven Decision-Making
The use of data-driven decision-making was embraced as invaluable in the
quest to close the achievement gap at Synergy Academies. Administrative and
teacher leaders interviewed for this study expressed their views on data-driven
decision-making as it benefitted students, teachers, school administrators and parents
as follows.
Students
School leaders felt strongly that the use of data held students accountable in
keeping track of their own learning, especially in the Reading Counts program. In
Reading Counts students were given immediate and timely data indicating pass or
fail on the weekly examination, which included their word count, how many books
they needed to read for the following week and how many books were required to
advance to the next grade level. Every Tuesday students carried home a printout with
results on Reading Counts in addition to reports from teachers such as weekly
subject tests (Middle School Principal, interview, September 2, 2010; Teacher

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Leader III, interview, August 25, 2010). From the first day of enrollment students
entering a Synergy Academy, were advised of their proficiency levels in reading and
mathematics. All students were briefed on the process of using data and their
responsibility in using data to monitor their learning (Chief Executive Officer,
interview, August 25, 2010).
One teacher leader mentioned that data, “Helps students know where they
were and what steps they needed to climb to reach proficiency” (Teacher leader I,
interview, October 10, 2010). In addition, a teacher acknowledged that using data-
driven decision-making allowed students to self-monitor their learning. Students kept
track of their own grades and progress on exams, homework, class work and reading
(Teacher leader IV, interview, August 25, 2010). Furthermore, the process created a
system of transparency where students were always aware where they stood
academically and how much work they needed to accomplish to improve, “There’s
no subjective grading, students can expect fair and systematic results, there are no
surprises for students or their parents” (Teacher leader III, interview, August 25,
2010). Next, the Chief Achievement Officer stated:
Students are just like everyone else, they want to know how well they are
doing, so if the child goes through the day and doesn’t have a clue of how
well they’re performing… we’re providing a disservice to them; we share the
information with them to validate them and to say, ‘Hey, because of your
hard work look at how much you’ve learned and improved.’ (Interview, July
26, 2010)

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Teachers
Teacher leaders expressed the following aspects as the most beneficial in
using data:
• With a technological system in place that provided timely and instant
student assessment results; allowed teachers more time to focus on
instruction.
• Data defined the specific learning needs of each child.
• Data allowed teachers to pinpoint specific questions students missed on a
test making re-teaching more effective.
• Success shown by students bolstered feelings of effectiveness and success
as teachers.
• Ongoing evaluation of data for each child helped teachers adjust their
lessons and/or teaching strategies immediately (Teacher Leader I,
interview, October 10, 2010; Teacher leaders II, III, IV, V, interviews,
August 25, 2010)
The elementary school principal emphasized that having a trusting relationship with
teachers was important and that by using data to make decisions affirmed that she
used concrete evidence on which to base her decisions. This brought more credibility
to her decision-making, which were evidence-based and legitimate, and not based on
hearsay, intuition, or whim, therefore generating trust and strong teacher buy-in for
data use (Elementary Principal, interview, September 2, 2010).

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School Administrator
An overarching belief at Synergy Academies was that sharing and using data
kept everyone (teachers, administrators, students, and parents) accountable to the
academic achievement of all students. Data-driven decision-making offered school
leaders’ the information to provide the tools and support teachers needed for success
with students especially those below grade level (Chief Executive Officer, interview,
August 25, 2010). In addition, school leaders used data to keep the school
community focused on the Synergy Academies mission to “Close the Achievement
Gap” (Chief Achievement Officer, interview, July 26, 2010).
Other school leaders, such as the elementary and middle school principals
explained that continuously using data benefited their evaluation of the instructional
program such as: intervention, use of appropriate teaching strategies and providing
effective teacher support. Most importantly, using data kept the conversation focused
on student achievement; everyone had the same data, read the same data and
interpreted it in the same way (Elementary, Middle School Principals, interview,
September 2, 2010).
Parents
It was a wide spread belief among the leadership and staff at Synergy
Academies that every parent wanted their child to succeed. Therefore information on
the accomplishments of their children was shared weekly (Chief Achievement
Officer, interview, July 26, 2010). Parents were directly responsible to carry-out the
Reading Counts objectives. Receiving weekly data allowed them to monitor the

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ongoing progress of their child and hold the child accountable of required school
standards (Middle School Principal, interview, September 2, 2010). According to
one teacher,
Prior to being accepted to a Synergy Academy most parents did not know the
academic level of their children. At Synergy Academies sharing information
with parents is critical, providing parents with data helps them learn how they
can help their child succeed, why their child is struggling, when their child
has met and completed the required benchmarks, and creates buy-in into our
learning philosophy. (Teacher Leader I, interview, October 10, 2010)

Parents received the Reading Counts progress report each Tuesday, a
progress report every mid-quarter, quarter report cards, and a semester report card
(Teacher Leader III, interview, August 25, 2010). All teachers required the signature
of a parent or guardian on all test quizzes and final exams, which was an added
sharing of data. Parents could expect fair and objective grade reporting for their child
(Teacher Leader III, interview, August 25, 2010). The Chief Achievement Officer
explained, “The more information we share with parents, we prove that their kids are
being successful, that brings a lot of pride to the parents when they see that their
child is improving and learning” (Interview, July 26, 2010).
Resource Requirements for Replicating the Promising Practice
Budget
The actual cost in replicating the promising practice was difficult to calculate
since the use of data-driven decision-making was embedded into the school culture.
Using data-driven decision-making was how everyone functioned at a Synergy
Academy. Additional pay for attendance to professional development sessions or

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analyzing data with colleagues and school leaders was an expectation in the school
leader and teacher contracts. According to the Chief Achievement Officer, “The
biggest cost to each individual in using data at Synergy Academies was ‘personal
time;’ time spent on data use and analysis” (Interview, July 26, 2010). The licensing
of PowerSchool a data system used by the middle school, which stored achievement
data, report card information and grades, costs approximately $10,000 (ten thousand)
annually (Chief Achievement Officer, interview, July 26, 2010).
Facilities
An initial investment of two updated computer labs equipped with thirty
stations and software, one in each school was made for the Reading Counts and
Scholastic Reading Inventory programs. Software for Reading Counts cost
approximately $3,000 and Scholastic Reading software cost $5000 at each school. In
the summer of 2011-2012 the installation of a new data system, Illuminate Education
will cost approximately $5000-10,000 dollars per school each year. Illuminate a data
and educational assessment management system will centralize all student records to
include student’s longitudinal data (Chief Executive Officer, interview, August 25,
2010).
Professional Development
Professional development was an important component of the culture at the
Synergy Academies. Data results were eminent at professional development sessions
at schools. The training included a shared understanding of test results, the
importance of using data at Synergy Academies and how it related to instruction

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(Personal observation, of Professional Development, August 23, 2010). This process
provided the direction and set the instructional tone for the year. As stated by the
Chief Achievement Officer, “A shared understanding of data is important in building
continuous buy-in into the data-driven culture” (Chief Achievement Officer,
interview, July 26, 2010).
The leadership at Synergy Academies was committed to ongoing professional
development throughout the year. All teachers participated in professional
development every Tuesday. Weekly sessions were never void of focused
conversation on augmenting student learning through improved instructional
strategies, improved lesson plans, or attention to student academic needs as
demonstrated by weekly results of data-driven assessments (Elementary Principal,
interview, September 2, 2010). Tuesday meetings were an opportunity for the
teaching staff and school leaders at both schools to reflect on where teaching and
learning had accelerated or digressed on any given week as indicated by one teacher
leader, “In general, meetings on Tuesday are short and succinct, we look at weekly
assessment results, we share any ideas and techniques that could be useful in our
classroom, look at the strategies and tools to improve and we move on. There is
never any wasted time or conversations that are not focused on improving” (Teacher
Leader I, interview, October 10, 2010). It was not uncommon for the principals or
Chief Achievement Officer to offer professional development sessions on a Tuesday
on topics such as: reading comprehension techniques, inferential reading, word
origins, numerical fluency, and making math visual. These areas were determined as

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a result of teacher expressed needs, weaknesses identified through varied
assessments, or ongoing observations by school leaders of the instructional delivery
process (Teacher Leaders II, III, interview, August 25, 2010).
Challenges
School administrators and teacher leaders interviewed, valued data-driven
decision-making as a tool to improve student learning. They further valued the level
of trust created by having data informed decision-making. Nevertheless, several
challenges were encountered by school and teacher leaders. One of the immediate
challenges of the Chief Executive Officer and Chief Achievement Officer was
putting in place a longitudinal data system and training everyone to use data to meet
student needs while at the same time keeping the culture of data-driven decision-
making in place. As the network grew collecting vast amounts of data and using it
effectively was becoming a challenge (Chief Achievement Officer, interview, July
26, 2010; Chief Executive Officer, interview, August 25, 2010). Other challenges
were expressed by school and teacher leaders.
Being careful not to present data in a misleading manner to teachers without
prior analyses and a thorough understanding of what the data meant and how it
affected the instructional program was a challenge stated by the elementary school
principal. School leaders must thoroughly understand the data to guarantee its
effectual use (Elementary School Principal, interview, September 2, 2010). A
challenge met by the middle school principal was prioritizing efforts such as time

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and resources to use data effectively to meet the large array of needs experienced by
students (Middle School Principal, interview, September 2, 2010).
For teacher leaders finding the time to learn how to analyze data properly and
then planning how to use it to enhance teaching strategies created a challenge
(Teacher leader III, V, interviews, August 25, 2010). In addition, teacher leaders felt
there were times when teachers put too much emphasize on assessment data and
were stressed and disappointed when their students failed to meet the expectations.
Teachers needed to learn how to balance assessment data with other learning
inventories such as homework, formative assessments, and class assignments
(Teacher leader I, interview, October 20, 2010; Teacher leaders III, IV, V,
interviews, August 25, 2010). Since many teachers came from teaching
environments where data were not used effectively; instructional support was
limited; and a trusting relationship was non-existent; it was a challenge to break from
past experiences; and ask the school leader for assistance when the need to improve
teaching strategies or learn to analyze data more thoroughly was evident (Elementary
Principal, interview, September 2, 2010). Finally, the expectation to continuously
move students up the academic ladder was necessary, demanding and hard work
(Teacher Leader III, interview, August 25, 2010).
Middle school students appeared to have the most challenges in taking data
seriously and adjusting to its use, in a timely manner. Among the small number of
middle school students trained at Synergy Academy elementary school, the use of
data and understanding how it affected their learning was a part of their paradigm.

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However since the majority of middle school students were new to the school it was
a challenge to instill the meaningfulness of data use and its importance in their
learning process (Chief Achievement Officer, interview, July 26, 2010; Teacher
Leader IV, interview, August 25, 2010). Another challenge was that once students
understood the importance of using data in their learning process, there were some
students who took the approach too seriously. The students felt stressed in not
meeting expectations. As stated by the Middle School Principal, “Some students take
the use of data too seriously and are devastated when and if they are not excelling.
The important lesson to teach students is that they need to do their best and that
100% is not always possible at school and in life” (Middle School Principal,
interview, September 2, 2010).
All individuals interviewed agreed that explaining data to parents in a
meaningful and understandable way that made sense and did not overwhelm them
was another challenge. The Synergy Network leadership and principals felt that
having parents understand the importance of the data and its urgency in the
achievement of their children’s learning was crucial. In addition to explaining the
meaning of data other challenges included:
• Workshops for parents to explain the State competency categories of: far
below basic, basic, proficient and advance; what it meant and how it
affected their children.
• The importance of using data-driven decision-making in the attainment of
their children’s learning.

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• The usefulness of data in developing high learning standards and
expectations in the learning process of their children.
• Workshops to understand and use data as an accountability measure in
the learning and future success of their children.
Lastly, as the network expanded to include a high school and the task of meeting
individually with each parent to review their child’s progress and assessments might
be a challenge due to the increase in enrollment and time constraints (Chief
Executive Officer, interview, August 25, 2010).
Lessons Learned
The Chief Achievement Officer and school principals noted that the lessons
learned from analyzing and using data, were that when used appropriately,
frequently, and consistently with specific goals in place, data helped improve student
achievement (Chief Achievement Officer, interview, July 26, 2010; Elementary,
Middle School Principal, interviews, September 2, 2010). Another lesson learned
was that working with data was a fulltime job. School leaders mentioned that they
learned to interpret and analyze data in a more thorough and effective manner. Also
the use of a varied amount of data was important to determine student learning
needs. Moreover, in planning sessions among school leaders the following questions
were developed to guide them in the using data:
• What are the data telling us?
• How can they be dissected properly?
• What are the specific areas of focus?

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• How do we use data effectively?
• What goals do we need to establish in using the data?
• How are data going to be implemented?
• How much time is needed for the implementation of the data?
• What results can be expected?
• How are the results going to be accomplished?
• How can the data be presented to make it understandable and create a
sense of urgency?
• What support will teachers need to use the data appropriately and
implement the goals (Chief Achievement Officer, interview, July 26,
2010; Elementary, Middle School Principals, interviews, September 2,
2010)?
Teacher leaders stated that due to the use of data there were ongoing
improvements in their teaching strategies. Having a school philosophy that “together
we are better” allowed individuals to seek advice from another member of the staff, a
teacher, the principal or another school leader. Teachers learned what areas they
were good at teaching and where improvement was needed (Teacher leader I,
interview, October 20, 2010; Teacher leader III, interview, August 25, 2020). As one
teacher stated:
It (data) has definitely helped me improve my teaching strategies. If I want
my students to be successful on a test or learn certain concepts I need to use
the correct strategies where students will learn the subject matter and show
success on an assessment. If success is not shown then I need to learn the

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strategies that will help them succeed. (Teacher leader III, interview, August
25, 2010)

Finally, the English/Social Studies Department Chairperson stated that he had
learned that data could be used for positive results in the following manner:
• To gain more effective student learning results by using multiple sources
of data.
• To measure teaching practices in a concrete way.
• To raise expectations of what students could achieve.
• To pinpoint the struggles and accomplishments of students on an exam
and enable the teacher to re-teach more effectively, if necessary.
• Most importantly, data was never used for evaluation or reprimand of a
teacher but only to improve teaching and student learning. (Teacher leader
II, interview, August 25, 2010)
Sustainability
As the network has grown the sustainability of data use to make decisions
and drive instruction has become a priority of the Synergy Academies. Although
Synergy Charter Academy and Synergy Kinetic Academy had API scores of 897 and
802 respectively, the goal of the network was to reach a score of 1000 (Chief
Executive Officer, interview, July 26, 2010). Getting Illuminate Education System in
place was a major development for the network. With a longitudinal system in place
the multiple storage of data on various spreadsheets, excel and paper and pencil
systems would be eliminated. All data would be centrally collected rather than

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having to spend entire working days looking for data; allowing more time for the
Chief Achievement Officer to act on the data and decide how to use it more
efficiently to improve the instructional program and student achievement. According
to both the Chief Executive Officer and the Chief Achievement Officer, this was a
major step in sustaining data-driven decision-making at Synergy Academies (Chief
Achievement Officer, interview, July 26, 2010; Chief Executive Officer, interview,
August 25, 2010).
Principals felt that ensuring sustainability would be accomplished by
continually communicating and educating teachers, new staff, parents and students
on the importance of data use to drive instruction; reviewing its historical
significance; and keeping the strong data-driven culture in place. Furthermore,
principals stated that data must always be kept as a priority in driving the learning
and teaching processes. Principals must continuously make the connection for
teachers on the importance of using data to improve teaching strategies, good
teaching and learning (Elementary, Middle School Principal, interviews, September
2, 2010).
Continued communication and focus on using data effectively was paramount
to the sustainability of data use for teacher leaders. It was important that school
administrative leaders continue to keep the total school community on the same
page, working together, providing support, looking and analyzing more data in
reading, language arts and mathematics according to teachers. In addition having
someone with the extensive knowledge in data and data use as the Chief

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Achievement Officer was essential (Teacher Leader I, interview, October 10, 2010;
Teacher leaders II, III, IV, V, interviews, August 25, 2010). In general, teacher
leaders appreciated the consistent use of data, high expectations for students and
teachers, plus the continual sharing of information and strategies for success, as
important factors in sustainability. They further indicated that as long as students and
parents were part of the process and understood the importance of data use, data-
driven decision-making would be maintained (Teacher Leaders II, III, IV,
interviews, August 25, 2010).
Chapter Five, which follows, is organized around the four originals research
questions and demonstrates how findings from this study compare to the research
presented in Chapter Two.
Recommended Resources
A number of instructionally driven resources were used by the staff at
Synergy Academies in meeting achievement needs of students. They are listed
below:
California Charter Schools Association- Data Director. Creating Real Data-
Driven Instruction and Culture Change in Charter Schools. Sacramento: CA.
California Department of Education. Testing and Accountability website
Center for the Improvement of Early Reading Achievement (CIERA). Put
Reading First: The Research Building Blocks for Teaching Children to Read.
Publication Award Number R305R70004. Washington, DC: Office of Research and
Improvement (OERI) U S Department of Education.

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Jones, F. (2010). Tools for teaching. Los Angeles, CA: Frederic H. Jones and
Associates.
Lemov, D. (2010). Teach Like a Champion. San Francisco, CA: Jossey-Bass.
Moats, L. C. (2010). Speech to Print: Language Essentials for Teachers.
Baltimore, MD: Paul H. Brookes Publishing Company, Inc.
National Reading Panel (2000). Teaching Children to Read. Publication
Number 00-4769. Washington, DC: U S Government Printing Office.
Roach, R (2009). A Critical Mission: Making Adolescent Reading an
Immediate Priority in SREB States. Fairfax, VA: Diverse Education, Inc.

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CHAPTER FIVE
CONCLUSION
The purpose of this study was to investigate promising practices of data-
driven decision-making for school improvement in two California charter schools:
Coastal Academy (K-8) and Synergy Academies (Synergy Charter Academy K-5;
Synergy Kinetic Academy 6-8). While each school served completely different
socio-economic populations, the study uncovered similarities between both programs
as well as similarities to previous research on data-driven decision-making. This
chapter examined the similarities and related them to the research questions,
presented in Chapter Three and under each section; findings from Coastal Academy
and Synergy Academies were compared to the literature on data-driven decision-
making, presented in Chapter Two. The results of this study were a contribution to
USC’s Compendium of Promising Practices with the purpose of disseminating
innovative programs, policies and practices to California charter schools
(Wohlstetter & Kuzin, 2006) implications for policymakers and practitioners were
further discussed. The chapter concluded with recommendations for future research
on data-driven decision-making.
Connections to Prior Research
Research Question One: How do charter school leaders use data for decision-
making and school improvement?
Decision-making at each charter school was made by a careful analysis on
using data to influence student learning and improve the quality of teaching, which

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according to Springboard Schools Report (2006) and Creighton (2007) was the most
effective process in using data. The influence by principals in the use of data was
emphasized in the research by Mandinach et al. (2006), as important in stimulating
data use. Principals at both Coastal and Synergy Academies used data to drive
instruction and made decision that focused on the learning needs of students; which
improved student achievement. Student achievement excelled at both charter
networks. In each charter network: Coastal and Synergy Academies the principals
were data-driven and exerted considerable influence in the use of data to drive
student learning and instruction.
According to the research by Knapp et al. (2006) schools with a data-driven
decision-making process in place, where teachers are free to ask questions about a
problem and data is used to find the answer, student achievement occurs.
Establishing an atmosphere of trust and transparency was important to the school
principals at both charter networks and teachers were eager and willing to look at
data and ask questions of school leaders to improve student learning (Elementary &
Middle School Principal, interviews, September 2, 2010). Most importantly teacher
leaders interviewed mentioned they were not hesitant to ask the principal for
assistance in learning new teaching strategies or to have the school principal model a
lesson (Teacher Leader II, interview, Coastal Academy, August 17, 2010; Teacher
Leader III, interview, Coastal Academy, September 27, 2010; Teacher Leader I,
interview, Synergy Academy, October 10, 2010; Teacher Leaders I, IV, V,
interviews, Synergy Academy, August 25, 2010).

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According to the research by Bernhardt (2003, 2004), Combs and Edmonson
(2006), and Mandinach and Honey (2008), it is important to use multiple sources of
information about students such as: state standard assessments, teacher made test,
homework, and authentic assessment in using data to make decisions. School leaders
at both Coastal and Synergy Academies focused daily on improvement of student
learning and instruction by using multiple sources of data to find the answers to any
pressing problems regarding the delivery of instruction that reflected on student
learning (Principal, interview, July 9, 2010; Elementary, Middle School Principal,
interviews, September 2, 2010). The research by Springboard Schools Report (2006)
emphasized the importance of using data to change instructional strategies, which
improved student achievement. Principals at both networks commonly visited all
classrooms on a daily basis with immediate feedback to teachers and offered needed
support to facilitate change in instructional strategies if necessary (Principal,
interview, Coastal Academy, July 9, 2010; Elementary, Middle School Principal,
interviews, September 2, 2010). At Synergy Charter Academy and Charter Kinetic
Academy principals modeled lessons, taught appropriate strategies, and caught
teaching problems right away (Elementary, Middle School Principal, interviews).
Research maintained that principals needed to receive professional
development that guided them in making sound decisions to implement a plan for
student achievement (Brunner et al., 2005). In addition, the research by Englert et al.
(2004) found that principals indicated a willingness to use data in their schools if
appropriate professional development in such areas as: developing data use cultures,

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translating data into instructional practices, prioritizing data in order of importance,
interpreting, and applying data to student achievement was offered. School leaders at
both networks received or attended minimal professional development and were in
fact the professional development presenters of data-driven instructional strategies
and effective data use, for other principals and teachers in their schools (Principal,
interview, Coastal Academy, July 9, 2010; Chief Achievement Officer, interview,
Synergy Academies, July 26, 2010). Likewise, they had a vision on using a broad
range of data, knew how to analyze data thoroughly and were knowledgeable in
techniques for summarizing data in meaningful ways; sharing test results; and using
data to enhance student learning in low performing areas (Personal observation
Professional Development, Coastal Academy, August 16, 2010; Personal observation
Professional Development, Synergy Academies, August 23, 2010).
It is important to note, school administrative leaders at both Coastal Academy
and Synergy Academies came from public school districts that provided them with
substantial professional development as recommended by research (Principal,
interview, Coastal Academy; Chief Achievement Officer, interview, Synergy
Academies). Ongoing professional development that focused on using data to
improve instruction and data analysis of student achievement was a priority in both
charter networks. Professional development was carried out on a school-wide basis
each week with intensive training at the beginning of the school year and winter
semester (Principal, interview, Coastal Academy, July 9, 2010; Chief Achievement
Officer, interview, July 26, 2010; Elementary, Middle Principal, interviews,

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September 2, 2010). Teacher leaders from each school stated that using data to meet
student needs; attending weekly professional development sessions to discuss weekly
assessment results; learning new teaching strategies; and improving the delivery of
instruction was one of the unique features of their schools (Teacher Leader III,
interview, Coastal Academy, September 27, 2010; Teacher Leader I, interview,
Synergy Academy, October 20, 2010).
Research Question Two: How are resources allocated to effectively implement
the use of data for decision-making and school improvement?
Research indicated that limited access to time to target effective professional
development; analyzing data; and sharing teaching strategies; could be a factor in the
use of data-driven decision-making to inform instruction (Englert et al., 2004;
Holcomb, 2004; Lachat, 2001; Supovitz & Klein, 2003). Resources such as time,
professional development, a computer lab, and licensing of standardized academic
assessments were the major resources allocated to implement the data-driven
decision-making process at both charter networks. A major resource item at both
networks was undoubtedly ‘time’ (Principal, interview, Coastal Academy, July 9,
2010; Chief Achievement Officer, interview, Synergy Academies July 26, 2010).
Although the cost of ‘time’ was difficult to generate at both Coastal Academy and
Synergy Academies setting aside a significant amount of personal and school time
by school leaders and teachers to review data on a regular basis; learn to interpret
data; review assessment reports; ask questions; and have a conversation on using
data to improve student achievement was essential. Teachers at Coastal Academy

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were expected to use data when meeting with parents, whereas at Synergy
Academies data packets were prepared and sent home every Tuesday for parental
review (Principal, interview, Coastal Academy, July 9, 2010; Chief Achievement
Officer, interview, Synergy Academies, July 26, 2010).
Past research indicated the importance of obtaining effective professional
development to maintain a culture of data-driven decision-making that made the
connection of data with solutions to instructional strategies (Knapp et al., 2003;
Goldring & Berends, 2009; Katz et al., 2005). Professional development at both
Coastal Academy and Synergy Academies was an essential component of effectively
carrying out the data-driven decision-making process and creating a data-driven
culture. At both networks school leaders carried out professional development for
teachers and additional costs for outside professional development experts were non-
existent. At Coastal Academy teachers were paid an additional stipend for attending
professional development sessions at the beginning of the school year and during the
winter semester. Weekly training sessions were required. As stated by the principal,
“You know time, licensing and professional development really those are the three
big expenses” (Interview, July 9, 2010). Synergy Academies required teachers to
attend professional development at the beginning of the summer, during winter
semester and every Tuesday. This requirement was included in the yearly teacher
contact and compensation was not a factor. On Tuesday students at Synergy
Academy and Synergy Kinetic were dismissed at 1:15 PM from their normal

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dismissal of 3:00 PM to allow teacher to participate in training (Chief Achievement
Officer, interview, Synergy Academies, July 26, 2010).
Both Coastal Academy and Synergy Academies initially invested in a
computer laboratory of 30 stations. Coastal used the computer stations to conduct the
MAP assessment inventory and Synergy Academies to administer Reading Counts
and Scholastic Reading Inventory. In-house assessments in developmental stages at
both sites in mathematics and writing will be disbursed through the computer
laboratory during the 2011-2012 school year (Principal, interview, Coastal Academy,
July 9, 2010; Chief Achievement Officer, interview). Another resource requirement
at Coastal Academy and Synergy Academies was the licensing fee for assessment
inventories. As mentioned in Chapter Four Coastal paid approximately $8500
(eighty-five hundred dollar) per year for the MAP assessment plus the salary of a lab
technician. At Synergy Academies $3,000 dollars was spent on the software for
Reading Counts and $5,000 dollars at each school for the Scholastic Reading
Inventory. PowerSchool a comprehensive data system used at the Synergy
elementary school cost approximately $5,000-$10,000 dollars per school each year
(Chief Executive Officer, personal communication, Synergy Academies, February
26, 2011; Chief Achievement Officer, interview, Synergy Academies, July 26,
2010).

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Research Question Three: What challenges have charter schools faced in
implementing the use of data for decision-making and school improvement and
how ere they addressed?
According to research, additional barriers to effective data-driven decision-
making include limited access to collaborative planning time for teachers; limited
time to share effective assessments and teaching strategies; and limited time for
targeted professional development (Englert et al., 2004; Holcomb, 2004; Lachat,
2001; Supovitz & Klein, 2003). This is critical for school leaders committed to a
data-driven approach to decision-making. Although, both networks Coastal
Academy and Synergy Academies experienced benefits by the school leaders’ use of
data-driven decision-making and both had strong data-driven cultures however, a
few challenges were mentioned during the interviews. Although ‘time’ was
considered a resource by school leaders, they were also aware of the challenge a lack
of available time created to carry-out the demands of using and analyzing data to
improve instruction to meet individual student needs. At Coastal Academy the
principal collected and interpreted disaggregated data received from the State such as
standard based assessments; analyzed the results of authentic assessments and MAP
testing. In professional development sessions the principal presented and explained
assessment results to teachers, trained them in the analytical and interpretive process.
Teachers worked on teams to gain further knowledge on the interpretation of
assessment results and shared information with each other, economizing time. They
were encouraged to ask questions on the meaning of data at weekly training sessions

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or asked questions privately of the principal. By taking the lead on obtaining data,
leading the conversation and offering training on the interpretive process the
principal hoped to ease the pressure of time constraints expressed by teachers.
Furthermore, the principal felt that in her role as instructional leader it was important
to provide teachers with data and conduct professional development sessions that
created an atmosphere of trust and buy-in for the data-driven decision-making
process (Principal, interview, Coastal Academy, July 9, 2010; Personal observation,
professional development, August 16, 2010).
The school principals at Synergy Academies and Chief Achievement Officer
felt it was important to take the lead in obtaining, desegregating, interpreting data,
and conducting professional development sessions to continue with student
achievement. Although obtaining the data, and understanding its use to improve
instruction was extremely time consuming, school leaders were willing to accept the
challenge to alleviate teacher time (Interviews, July 26, 2010 and September 2,
1010). As stated by the middle school principal, “Using data always needs to be a
priority, we need to continuously revisit it and make sure it’s always on our minds”
(Interview, September 2, 2010). Both the elementary and middle school principals
believed their enthusiasm for the data-driven decision-making process created a
trusting relationship with teachers, which helped in establishing a high degree of
buy-in for using data (Elementary, Middle School Principal, interviews, September
2, 2010). At Synergy Academies the philosophy “Together we are better”
emphasized a purposeful team driven culture where everyone shared in data

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interpretation and shared ideas and strategies, helping teachers conserve time
(Teacher Leader I, interview, October 10, 2010). The literature maintained that
quality and timely data must be available to use for decision-making and improved
student achievement (Hansen, 2007; Vernez et al., 2008). The Synergy Network
further addressed the challenge of time by investing in Illuminate Education a
longitudinal data system that would cut back on the time it took to collect and
disseminate multiple sources of student data (Chief Achievement Officer, interview,
July 26, 2010).
Another challenge faced by both Coastal and Synergy Academies was the
perception by parents in using data to drive instruction and to train them to
understand data and use it to improve their children’s academic achievement.
According to the principal at Coastal Academy, upon enrollment of their child,
developing immediate relationships with parents was important, to rid them of the
perception that data was used to teach to the test or to compare teachers, but to
develop a culture where everyone was working collaboratively to meet the learning
needs of each child (Principal, interview, Coastal Academy, July 9, 2010). Coastal
Academy had a unique situation where parents worked as partners in the teaching
process of their children, therefore is was important for the principal to offer and
require parents to attend ongoing training on interpreting data and how it was used to
measure the learning of the child. Also, the principal provided continuous
professional development for parents on using effective standards driven teaching
strategies that improved the academic results of their children (Principal, interview,

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July 9, 2010; Parent training brochures and schedules, 2010). Finally, parents and
teachers were scheduled to meet together every five weeks, a total of seven
conferences per year, reviewed lessons, school data results, and discussed any
challenges the child was experiencing (Teacher Leader II, interview, August 17,
2010).
A belief at Synergy Academies was that all parents cared and wanted their
children to succeed in school (WASC Self-Study Report, 2010). Therefore, all
school and teacher leaders interviewed at Synergy Academies acknowledged that
training sessions for parents in understanding what data meant; the importance in
monitoring data in the learning process of their child; and how high test results were
used to afford their children greater educational opportunities were crucial (Chief
Achievement Officer, interview, July 26, 2010; Elementary, Middle School
Principal, interviews, September 2, 2010; Teacher Leader I, interview, October 10,
2010; Teacher Leader III, IV, interviews, August 25, 2010 ). Synergy Academies
met the challenge of communicating with parents (in English and Spanish) by
offering monthly workshops on such topics as: Explaining the competency
categories of STAR testing; Understanding the results and expectations of Reading
Counts and Scholastic Reading Inventory; Teaching parents to understand data as a
measure of their child’s learning process; Understanding API and what it means in
the learning process of the child (Chief Achievement Officer, interview, July 9,
2010). In addition, the Chief Executive Officer and principals met with each parent
and child at the beginning of the year to explain State standard scores, and other

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reading and mathematical assessments (Chief Executive Officer, interview, August
25, 2010; Elementary, Middle School Principal, interviews, September 2, 2010).
Moreover, parents received a total of eight progress reports a year informing them of
the continuous progress of their children, which kept data results frequent (Teacher
Leader III, interview, August 25, 2010).
Research Question Four: What evidence exists that the use of data for decision-
making resulted in positive educational outcomes?
In California, the Academic Performance Index (API) is the keystone of the
performance based accountability system that measures school achievement and
indicates how well students mastered state standards. The State established a
performance target of 800 API out of a possible 1000 for all California public
schools (CDE, Adequate Yearly Progress Report Information Guide, 2010). Both
Coastal Academy (K-8) and Synergy Charter Academy (K-5) met the target for the
past five years with a score of 860 and 897 respectively in 2010. Synergy Kinetic
Academy (6-8) in existence for two years met the target in 2010 with a score of 802
an increase of 16 points from a score of 786 in 2009 (CDE, Accountability Progress
Reports, 2010). All persons interviewed for this study at both schools felt the API
was a strong indicator that data-driven decision-making made an impact on the
positive results at their schools.
Research stated that for a data-driven culture to exist it must be driven by the
school leader, who was supportive, exudes trust, and allowed for data-driven inquiry
(Goldring & Berends, 2009; Knapp et al., 2003, 2006; Sutherland, 2004; Thornton &

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Perreault, 2002). School leaders at both Coastal Academy and Synergy Academies
established a culture and atmosphere of trust and data-informed inquiry. The
environments at both networks were supportive, open communication of results
existed, candid discussion for improvement was ongoing and data-use was
emphasized (Personal Observations, Coastal Academy, August 16, 2010; Synergy
Academies, August 23, 2010). Teacher leaders at both Coastal Academy and
Synergy Academies expressed that what results did not indicate was that looking at
varied data allowed them to focus on the specific learning needs of students and had
a significant impact on constantly improving their teaching strategies (Teacher
Leader II, interview, Coastal Academy, August 17, 2010; Teacher Leader I,
interview, Synergy Academies, October 10, 2010; Teacher Leader IV, Synergy
Academies, August 25, 2010). One teacher leader at Coastal Academy stated: “The
benefits of using data are being able to pinpoint the specific learning needs of each
student. It is nice to have that focus; it helps me stay on the right track or to see the
areas where I need to change” (Teacher Leader II, interview, August 17, 2010).
The research by Bernhardt (2003, 2004) stressed the importance for school
leaders to review and collect multiple types of data in order to effectively put the
data-driven decision-making process in place. As mentioned in Chapter Four,
multiple assessment measures were in place at both Coastal Academy and Synergy
Academies that helped monitor the specific learning needs of each child and kept the
networks focused on continued academic growth. Test results, along with class work
and course assessments were also reviewed to provide appropriate intervention. At

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Coastal Academy, The Measure of Academic Progress (MAP) a national standards
examination in mathematics, reading and language arts was given to each student at
the beginning of the year. Additional assessments included Reading Plus and Lexia,
online reading assessments that were used to denote student comprehension levels
(Principal interview, July 9, 2010). Saxon Math was given on a weekly or biweekly
basis to evaluate mathematics proficiency and move the child to appropriate levels if
suitable. Added data resources included teacher created standards bases tests and
formative assessments (Teacher Leader IV, interview, September 27, 2010).
Both Synergy Charter Academy and Synergy Kinetic Academy used the
identical primary assessment Reading Counts for evaluating reading levels and
reading comprehension. Reading Counts was a take-home reading program that
evaluated each child’s reading competency weekly. The schools established an
expected proficiency level of 80%. The Scholastic Reading Inventory was
administered quarterly to keep abreast of reading improvement and determined lexile
scores, which connected to the Reading Counts program. In the elementary school
Open Court Reading (OCR) periodic assessments were administered as required. A
school developed math assessment was given to all students in both Synergy schools
at the beginning of the school year. At Synergy Kinetic Academy the mathematics
unit assessment provided by McDougall Litttell was administered to each student at
the end each chapter unit. Uses of multiple assessments were important at both
Coastal Academy and Synergy Academies. The data-driven decision-making process

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was driven by the principal at Coastal Academy and by the Chief Achievement
Officer and principals at Synergy Academies.
Implications for Policy and Practice
School and teacher leaders at both Coastal Academy and Synergy Academies
acknowledged that the use of data-driven decision-making had made an impact on
student achievement; the improvement of teaching strategies; and on creating a
trustful and professional working environment respectful of all members of the
school team. Implications for further best practices and policies could be inferred
based on the findings from this study and the research indicating that data-driven
school cultures were motivated by school leaders that established transparent
conditions; where open discussion took place; and a school structure was set-up to
have ongoing discourse on multiple sources of data (Feldman & Tung, 2001; Knapp
et al., 2006). The implications of this study confirmed the importance of using data-
driven decision-making to increase student achievement. The primary consideration
of school leaders at both Coastal Academy and Synergy Academies was to use data
to set goals and objectives that focused on student learning needs to improve their
achievement. Secondly, as emphasized in the research by Knapp et al. (2003),
Goldring & Berends (2009), and Katz et al. (2005), school leaders improved
instruction and school planning with connections to data. The two school networks
surpassed the target of 800 API in mastering standards based learning set by the
State of California. The findings of this study took on an additional meaning in
considering the context of Synergy Academies (Synergy Charter Academy and

133
Synergy Kinetic Academy), located in one of the lowest socio-economic and
transient areas of South Central Los Angeles with a population that is approximately
87% Latino, 12% African-American and 1% other and close to 45% of the students
are classified as English Language Learners and nine percent classified with special
educational needs (CDE, Accountability Progress Report, 2010). This network
surpassed the State of California API average of 800 in grades (2-6) by 97 points and
the average of 765 in grades (7-8) by 42 points (CDE, Base API State Report, 2010).
Definition of Data-Driven Decision-Making
For the purposes of this study the operational definition of data was that
school leaders would adopt and analyze multiple sources of information and
knowledge and use it to develop ongoing change and improved student achievement
(Bernhardt, 2003, 2004; Combs & Edmonson, 2006; Learning Points Associates,
2006; Mandinach & Honey, 2008). Both Coastal Academy and Synergy Academies
used multiple sources of data to concentrate on student learning needs, to improve
instruction and change teaching strategies. Using data was the foundation of the
instructional program. In regard to using data to improve teaching and learning at
Coastal Academy the principal stated:
I spend a great deal of time looking at the data and then asking questions of
the teachers. We have conversations in professional development meetings,
sort of like doctors, where I’ll say I analyzed certain data and saw this going
on in a classroom. I like teachers to share what’s going on. We use that kind
of informal data sharing to drive instructional practices (Principal, interview,
July 9, 2010).

134
The Chief Achievement Officer at Synergy Academies regarding the use of data as a
tool for improving instruction noted:
We use multiple sources of data to create a culture where data is used as a
teaching tool, and not as something that we use to criticize someone’s
teaching, for example, but if it’s used as a tool to understand students’ needs
and use it in a proactive way then it is important to everyone and to our work.

Using data to improve student achievement and teaching practices was aligned to the
data-driven culture found in each school network.
Role of the School Leader
The school leader in this study was defined as the school principal or Chief
Achievement Officer. The principal at Coastal Academy and the principals and Chief
Achievement Officer at Synergy Academies played a key role to implementing a
data-driven school culture. Other school leaders were teachers in positions such as
department chairpersons, BSTA coordinators, educational specialists, and leadership
coordinators. At both networks school principals motivated buy-in among all
stakeholders, focused on developing a process of inquiry, and were responsible for
acquiring and analyzing all data. School principals in both school networks
prioritized their time to visit all classrooms daily from one to thirty minutes
depending on the need. In addition, all school leaders were instructional experts,
provided ongoing feedback to teachers, modeled lessons, and conducted professional
development sessions. This was in addition to operational duties such as:
supervision, student discipline, meeting with parents, and heading IEP meetings.
School leaders at both Coastal Academy and Synergy Academies established a

135
climate of trust and collaborative inquiry where teachers were able to learn, question
and share with one another the relationship between data and good teaching
practices. According to past research effective leaders established a school culture of
trust, collaboration and provided teachers with the support if the data-driven
decision-making process was going to succeed to improved student achievement
(Golding & Berends, 2009; Earl & Katz, 2006; Knapp et al., 2006; Feldman & Tung,
2001; Lachat, 2001).
Professional Development
Professional development at both Coastal Academy and Synergy Academies
was an essential component in committing to sustainability and continuous buy-in of
data-driven decision-making. Past research indicated that continuous professional
development on how to use data to inform instruction, improve teaching strategies
and knowing how to analyze data properly was essential to sustain ongoing buy-in of
data use (Creighton, 2007). As discussed in Chapter Four teachers attended one week
intensive professional development in the summer; where they reviewed and
analyzed schoolwide State standard scores, individual student scores and other
assessment data. The principal at Coastal Academy was responsible for carrying out
most of the training at the beginning of the year and at all weekly professional
development sessions. However, individual teacher leaders had a role in presenting
successful teaching strategies in areas such as: history, science, mathematics, use of
technology, and test-taking strategies (Personal observation, professional
development, August 16, 2010; Professional Development Agendas and personal

136
notes, August 16, 2010). At Synergy Academies training was conducted by the Chief
Achievement Officer, with a review of school-wide State standardized test data,
student scores, Scholastic Reading Inventory and mathematics assessments. At
Synergy Schools, school principals, teachers, teacher assistants, and schools aides
attended professional development sessions together at the beginning of the school
year (Personal observation, professional development, August 23, 2010; Professional
Development Agendas, personal notes, and PowerPoint presentations, August 23,
2010).
A key factor affecting the use of data-driven decision-making was that at
both charter networks all data information was analyzed with connections made to
teaching strategies. A review of all assessments used by the schools followed, with
instructions on how to administer a variety of tests, analyze results, and their
importance to the instructional program and student achievement. Greater emphasis
throughout the week of professional development was a review of good teaching
practices; how strategies were used to enhance student learning needs; with an
introduction to new strategies to meet the learning needs of students such as: English
Learners and Special Education students. Using data to make connections to
instruction was eminent at both schools (Observation professional development,
agendas, personal notes, Coastal Academy, August 16, 2010; Observation
professional development, Agendas, personal notes, PowerPoint presentations,
Synergy Academies, August 23, 2010). Principals at Synergy Charter Academy and
Synergy Kinetic Academy were responsible for Tuesday professional development

137
sessions; where teachers and principals’ shared teaching strategies making
connections to data. If necessary discussions led to data use and analyses depending
on student performance during the week; these meetings also served to provide
teachers with the tools to enhance their teaching by using data (Elementary, Middle
School Principal, interviews, September 2, 2010).
Recommendation for Future Research
Best practices used by educators in using data to drive learning continued to
be lacking from the literature. Teachers and school leaders at both Coastal Academy
and Synergy Academies felt that there were always new strategies that could be
learned and shared to improve on student learning that were difficult to develop by
just analyzing data. The principal at Coastal Academy mentioned that it was
important to have research on sharing best practices by charter and public schools to
enhance student learning. The principal acknowledged:
I continue to really seek best practices. The reason why I’m at a charter
school is to be able to develop the best practices that have always been out
there, but district philosophy, the district inertia has really hurt I think,
education as a whole in not allowing us to share ideas or develop studies of
shared practices (Principal, interview, July 9, 2010).

According to a teacher leader at Synergy Academies regarding best practices and
special education students:
It is really hard for teachers and especially students who came from special
day classes, at schools, where they weren’t expected to do anything. We have
all the kids mainstreamed in regular classes and we expect them to live up to
our high standards. It is really hard for both of us. There needs to be more on
strategies to work with special education students. At Synergy we read a lot
on good teaching practices but we do not know if it all works with special
education students. The students meet the challenge, but I always wonder if

138
there are better ways to teach them. As teachers we want to do our best for
each student (Teacher Leader IV, interview, August 25, 2010).

Due to the importance of data-driven decision-making under NCLB driven by
standards based instruction and accountability; additional research is needed to
determine the impact of data-driven decision-making by school leaders on student
achievement; and on closing the achievement gap (Datnow, et al., 2007). Further
research should be conducted on school sites where data-driven decision-making was
successful. It is important to note that although both school networks experienced
high student achievement, teaching strategies and teaching practices were very
different in each network (Personal observations).
In conclusion, the findings from this study provided insight into the
implementation of data-driven decision-making and the effects of this process on
school leaders, teachers, students, parents and the fulfillment of schoolwide goals
and objectives. Both networks focused on using data to drive and improve
instruction with concentration on student learning needs, which ultimately led to
meeting federal and state accountability standards and high student achievement.
Furthermore, the study provided research on how school leaders facilitated the use of
data to improve instructional practices. The schools’ participation in this study
provided new knowledge on school leaders’ use of data-driven decision-making to
improve student achievement through USC’s Compendium of Promising Practices.
Educators and policy makers will have online access to these innovations to

139
encourage the replications and use of best practices in this area of leadership to
improve student learning.

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A Nation at Risk. (1983). National Commission on Excellence in Education.

Alwin, L. (2002). The will and the way of data use. School Administrator 59(11).
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ESjh.

American Association of School Administrators. (2002). Using Data to Improve
Schools: What’s Working. Retrieved from:
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APPENDIX A
CONTENTS OF THE COMPENDIUM: TYPES OF DATA TO BE COLLECTED
Goal of PP
Description of PP
Theory of Action for PP
Implementation Details:
• History
• Time (start-up/planning time; time PP has been in place)
• Lessons learned (benefits, challenges, next steps for sustainability)
• Evidence of impact

Resource Requirements:
• Budget information
• Staffing (level and type of staff expertise needed)
• Facility/space
• Professional development/training
• Other (e.g., technology)

Supporting Documents and Materials (printable in PDF format):
• Varied assessment data (other than State Assessments)
• Parent contracts
• Video to support PP
• Professional development manuals
• Evaluation reports (data demonstrating results of PP)

Recommended Resources for Additional Information:
• Books
• Articles
• Web sites
• Sources of technical assistance
• Potential funding sources

152
APPENDIX B
PRINCIPAL PRE-SITE INTERVIEW PROTOCOL
School Name: ____________________________________ Date: ______________
Researcher: _________________________________________________________
Start Time: ___________ End Time: ___________Total Time (minutes): _____

[Introduction]
I am working with the University of Southern California’s Rossier School of
Education. We are studying promising practices in California charter schools.
Through a nomination process, your school was selected as having success in/with
[Promising Practice: Data-Driven Decision-Making]. The purpose of this interview
is to learn more about [promising practice] at your school and to schedule a site visit
at a time this spring when it is convenient for you.

The information from this research will be incorporated into a Web-based
compendium of promising practices. The Website is hosted by USC’s Center on
Educational Governance. The goal of the compendium is to spread new knowledge
and innovation about promising practices to inspire educators to improve school
performance.

By participating in this study, your school will get recognition at the annual
California Charter Schools Association conference; a certificate to display at your
school; and publicity in the media, including statewide and local press releases.

This preliminary interview should take only around 5-10 minutes. Is now a good
time? (If not – when would a better time be to talk with you?) Do you have any
questions for me before we begin?

A. Background- Laying the Foundation
1. How long have you been the principal at this school?
2. Would you tell me about your background and previous experience in
education?

3. How long has this school been using the [promising practice]?

153
4. Who else on campus is involved with the [promising practice]?
[Probe for other school leaders]

B. Scheduling and Logistics
5. We are planning to visit schools sometime this spring, at the end of May or
June. The visit will last no more than two days and I would like to speak
with you again, along with the other persons you mentioned who are involved
with [promising practice]. If possible, I also would like to observe a
professional development session related to [promising practice].

a. What month and days are best to visit your school?
b. Will it be possible to attend a professional development session
related to [promising practice] during the visit?

c. [Will I be able to speak with other school leaders involved in
implementing the promising practice during my visit?]

6. Who should I speak with about arranging the visit and scheduling interviews?
I can [send, fax or email] a list of persons we discussed to interview during
my visit, along with a scheduling grid.

For future contacts, is it best to communicate with you by phone, or do you prefer
fax or email?

FAX: __________________________
TEL: __________________________
EMAIL: ________________________
[Closing]
Thank you very much for your time. I will send the scheduling grid to [PERSON] in
the next day or two, and if it can be returned to me by [DATE], that would be very
helpful.

I look forward to visiting your school on ___________, and will plan to contact you
the week before to confirm the visit and interview schedule. Again, thank you for
participating in USC’s Compendium.

154
APPENDIX C
ON-SITE PRINCIPAL INTERVIEW PROTOCOL
School Name: __________________________________Date: ________________
Name of Interview Subject:____________________________________________
Researcher: _________________________________________________________
Start Time: ___________End Time: __________Total Time (minutes): _______

[Introduction]
Thank you for agreeing to meet with me. I am working with the University of
Southern California’s Rossier School of Education. We are studying promising
practices in California charter schools. Through a nomination process, your school
was selected as having success in/with [Promising Practice: Data-Driven Decision-
Making]. The purpose of this interview is to learn more about [promising practice]
at your school.

The information from this research will be incorporated into a Web-based
compendium of promising practices. The Website is hosted by USC’s Center on
Educational Governance. The goal of the compendium is to spread new knowledge
and innovation about promising practices to inspire educators to improve school
performance.

By participating in this study, your school will get recognition at the annual
California Charter Schools Association conference; a certificate to display at your
school; and publicity in the media, including statewide and local press releases.

This interview should take approximately 60 minutes. Do you have any questions for
me before we begin?

A. Theory of Action and History
1. Can you briefly describe [promising practice] at your school?
2. What is the goal of [promising practice]

155
3. Please tell me about the history of [promising practice] at your school.
(Probe: How/why did it get started, who were the people initially involved in
developing the practice?

4. Can you tell me a little about your role as principal with respect to [promising
practice]?

5. Who have been the main people involved with the planning and
implementation of [promising practice]?

6. In your opinion, what factors have contributed to the successful
implementation of [promising practice]?

7. How do you think the [promising practice] has led to school improvement
and higher student achievement?

B. Implementation Details
8. How long has [promising practice] been in place?
9. How much start up/planning time was needed to implement [promising
practice]?

10. How much planning or collaboration time on a monthly basis is needed to
maintain implementation of [promising practice]?

11. What do you see as the next steps for ensuring sustainability of the
[promising practice]?

12. How do you know [promising practice] is making a difference? [What is the
evidence of impact?]

13. What are the benefits of implementing [promising practice]?
(Probes: Benefits for students, staff, administrators, parents)

14. What are the challenges of implementing [promising practice]?
(Probes: Challenges for students, staff, administrators, parents)
15. What lessons have you learned by implementing [promising practice]?
C. Resource Requirements
16. How much of your budget is spent on the [promising practice]?

156
17. What is the level of staff expertise required with respect to [promising
practice]?

18. What facilities are needed to carry out [promising practice]?
19. How much professional development time has been devoted to implementing
[promising practice]?

20. Do you think the training/professional development that has been conducted
meets the needs for people to implement [promising practice] effectively?
(Probe: What other types of PD do you think would be helpful to effectively
implement promising practice?)

D. Recommended Resources for Additional Information
21. Are there any books that have been helpful to you in implementing
[promising practice]?

22. Are there any articles that have been helpful to you in implementing
[promising practice]?

23. Are there any Websites that have been helpful to you in learning about
[promising practice]?

24. Are there any sources of technical assistance that have been helpful to you in
implementing [promising practice]?

25. Additional comments:
[Closing]
Thank you very much for your time. Your comments and insights are invaluable for
our research.

157
APPENDIX D
OTHER SCHOOL LEADER - INTERVIEW PROTOCOL
School Name: ________________________________Date:___________________
Name of Interview Subject: ____________________________________________
Position: ____________________________________________________________
Researcher: _________________________________________________________
Start Time: ___________End Time: ___________Total Time (minutes): _______

[Introduction]
Thank you for agreeing to meet with me. I am working with the University of
Southern California’s Rossier School of Education. We are studying promising
practices in California charter schools. Through a nomination process, your school
was selected as having success in/with [promising practice]. The purpose of this
interview is to learn more about [promising practice] at your school.

The information from this research will be incorporated into a Web-based
compendium of promising practices. The Website is hosted by USC’s Center on
Educational Governance. The goal of the compendium is to spread new knowledge
and innovation about promising practices to inspire educators to improve school
performance.

By participating in this study, your school will get recognition at the annual
California Charter Schools Association conference; a certificate to display at your
school; and publicity in the media, including statewide and local press releases.

This interview should take approximately 60 minutes. Do you have any questions
for me before we begin?

158
A. Theory of Action and History
1. Can you briefly describe [promising practice] at your school?
2. What is the goal of [promising practice]?
3. Please tell me about the history of [promising practice] at your school.
(Probe: How/why did it get started, who were the persons initially involved in
developing the practice?)

4. Can you tell me a little about your role as school leader with respect to
[promising practice]?

5. Who have been the main persons involved with the planning and
implementation of [promising practice]?

6. In your opinion, what factors have contributed to the successful
implementation of [promising practice]?

7. How do you think that [promising practice] has led to school improvement
and higher student achievement?

B. Implementation Details
8. How long has [promising practice] been in place?
9. How much start up/planning time was needed to implement [promising
practice]?

10. How much planning or collaboration time on a monthly basis is needed to
maintain implementation of [promising practice]?

11. What do you see as the next steps for ensuring sustainability of the
[promising practice]?

12. How do you know [promising practice] is making a difference? [What is the
evidence of impact?]

13. What are the benefits of implementing [promising practice]?
(Probes: Benefits for students, staff, administrators, parents)

14. What are the challenges of implementing [promising practice]?
(Probes: Challenges for students, staff, administrators, parents)

159
15. What lessons have you learned by implementing [promising practice]?
C. Resource Requirements
16. How much of your budget is spent on [promising practice]?
17. What is the level of staff expertise required with respect to [promising
practice]?

18. What facilities/technology are needed to carry out [promising practice]?
19. How much professional development time has been devoted to implementing
[promising practice]?

20. Do you think the training/professional development that has been conducted
meets the needs for people to implement [promising practice] effectively?
(Probe: What other types of PD do you think would be helpful to implement
promising practice effectively?)

D. Recommended Resources for Additional Information
21. Are there any books that have been helpful to you in implementing
[promising practice]?

22. Are there any articles that have been helpful to you in implementing
[promising practice]?

23. Are there any Websites that have been helpful to you in learning about
[promising practice]?

24. Are there any sources of technical assistance that have been helpful to you in
implementing [promising practice]?

25. Additional comments:
[Closing]
Thank you very much for your time. Your comments and insights are invaluable for
our research.

160
APPENDIX E
PROFESSIONAL DEVELOPMENT OBSERVATION PROTOCOL
School Name: ___________________________Date: ________________________
Professional Development Topic: _______________________________________
Researcher: __________________________Activity Location: _______________
Time Started: _________Time Ended: __________Total Time (minutes): ______
Number of Participants: ______________

A. Professional Development Leadership
Who led training (check all that apply)?
Teacher (from the school site)
Administrator (from the school site)
Teacher from another school
Administrator from another school
University faculty member
Outside consultant (describe)
Other (describe)

1. List the name and position of professional development session leaders

B. Professional Development Session:
2. Describe the intended purpose of the professional development session.
3. List the agenda items for the professional development session.
(include a printed copy of the agenda, if available)

161
C. Structure of Activities during Professional Development Session
Structure
(lecture, small group,
whole group, etc.) Intended Purpose

4. Describe the content of the professional development session in detail:
(Probes: Key terms, theories and implementation issues related to promising
practice)

5. List materials used for the professional development session
[Note: Collect all that are available]

Type of Material Description of Material

6. Additional comments:

Abstract (if available)

Abstract The current interest in using data-driven decision-making in schools has focused on how best to use student achievement data to meet the demands of current accountability requirements. The purpose of this study was to investigate promising practices specific to school leaders' use of data-driven decision-making for school improvement at two California charter schools. ❧ ❧ The following data sources were included in this qualitative case study that applied descriptive research and design: interviews of charter school principals and other administrators, interviews with teacher leaders, review of archival documents, and obsevation of professional development meetings related to the use of data to influence teaching and promote student achievement. The case study answered the following questions: How do charter school leaders use data for decision-making and school improvement? How are resources allocated to effectively implement the use of data for decision-making and school improvement? What challenges have charter schools faced in implementing the use of data for decision-making and school improvement and how were they addressed? What evidence exists that the use of data for decision-making resulted in positive educational outcomes? ❧ ❧ The study found that the greatest impact of using data-driven decision-making was on results of high student achievement and on the improvement of teaching strategies to meet student needs. By establishing a strong data-driven school culture, daily classroom observations, professional development, and providing teachers with ongoing support, school leaders experienced a profound impact on student achievement. ❧ ❧ In order to implement the effective use of data-driven decision-making the findings suggested several practical strategies. First, the total school community (parents, students, teachers, school leaders) had a common understanding of how data was used and analyzed to meet individual student learning needs. Additionally, the principals and other school leaders embraced the data-driven decision-making process, had strong skills in curriculum and instruction, provided ongoing professional development and analyzed data with the intentions to improve teaching strategies and improve student achievement. Classroom visits were conducted on a daily basis allowing principals to provide immediate support or model a lesson if necessary. Finally, a culture of trust and collaborative inquiry was established where teachers were able to learn, question and share the relationship between data and good teaching practices. ❧ ❧ The findings of this study have been incorporated into the Center on Educational Governance Web-Compendium of Promising Practices designed to disseminate innovative best practices beyond the school site and assist other policy makers and educators who wish to gain knowledge on leaders' use of data-driven decision-making for school improvement.

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Asset Metadata

Creator Simpson, Guadalupe H. (author)

Core Title School leaders' use of data-driven decision-making for school improvement: a study of promising practices in two California charter schools

School Rossier School of Education

Degree Doctor of Education

Degree Program Education (Leadership)

Publication Date 06/16/2011

Defense Date 05/11/2011

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

Tag accontablility,charter school leaders'use of data,charter schools,cultures of data-driven decision-making,data and student achievement,data use and professional development,data use in schools,data-driven decision making,data-driven leadership education,OAI-PMH Harvest,principal's use of data,teacher leaders and data use

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Wohlstetter, Priscilla (committee chair), Castruita, Rudy M. (committee member), Rousseau, Sylvia G. (committee member)

Creator Email guadalupe.simpson@csun.edu,keredepul@verizon.net

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c127-617113

Unique identifier UC1368554

Identifier usctheses-c127-617113 (legacy record id)

Legacy Identifier etd-SimpsonGua-28.pdf

Dmrecord 617113

Document Type Dissertation

Rights Simpson, Guadalupe H.

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

Repository Email cisadmin@lib.usc.edu