University of Southern California Dissertations and Theses

Evaluating college readiness through a mathematical lens: a quantitative study of predominately African American high schools in the Los Angeles Unified School District from 2003 – 2012

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Evaluating college readiness through a mathematical lens: a quantitative study of predominately African American high schools in the Los Angeles Unified School District from 2003 – 2012

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Content Running head: EVALUATING COLLEGE READINESS 1
EVALUATING COLLEGE READINESS THROUGH A MATHEMATICAL LENS:
A QUANTITATIVE STUDY OF PREDOMINATELY AFRICAN AMERICAN HIGH
SCHOOLS IN THE LOS ANGELES UNIFIED SCHOOL DISTRICT FROM 2003 – 2012
by
Angelique S. Sims
A Dissertation Presented to the
FACULTY OF THE USC ROSSIER SCHOOL OF EDUCATION
UNIVERSITY SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
Doctor of Education
May 2019
Copyright 2019 Angelique S. Sims
EVALUATING COLLEGE READINESS 2
DEDICATION
In Loving Memory
of
Ivory Godbolt, William Godbolt, Sr., James D. Murray, Adre Sims, and Brister Sims, Sr.
First giving all glory and praises to my heavenly Father who which none of this would
have been possible. My dissertation journey would not have been possible without the love and
support of my family, my crew, friends, students, sorority sisters, and my 2013 Thursday Night
Cohort. To my daddy and mommy, Brister Jr.& Elsie Sims thank giving a spiritual foundation
and understanding to know that all things are possible and loving me unconditionally. To my
brother and sisters Cassandra Todd, Dana Howard, De Marlo Sims (Tricia), Monique Hogan
(Clyde), for always supporting me. To my nieces and nephews Demond Todd (Christina), Myles
Sims (Rayana), Jasmine Sims, Jasmeén Sims, Nicole Sims, Ashia Souder, Alexa Hogan, Erin
Hogan, Isabella Todd and Preston Todd for making me an auntie and I hope I have been a role
model that makes you proud. To my crew thank you for always providing me with laughter and
learning to always take time out to appreciate life. To my church family, I know without your
prayers I would not be where I am today. Thank you to my colleagues who have been my
inspiration and support to keep growing professionally. To my many sons and daughters I have
had the pleasure of teaching, counseling, coaching, and mentoring thank you for the opportunity
but, more importantly thank you for teaching me lessons along the way. Thank to my sorority
sisters of Delta Sigma Theta Sorority, Inc. all over the world (a special OO-OOP to Ra’Kenna
Luckey for proofreading and editing many of my assignments). Finally, to the 2013 Thursday
Night Cohort (and a special thank you Scott “Scotty Pooh” Mc Nutt and Michelle Merchain) I
FINALLY FINISHED! FIGHT ON!
EVALUATING COLLEGE READINESS 3
ACKNOWLEDGEMENTS
I wish to express my deepest and most sincere gratitude to Dr. Julie Marsh, and Dr.
Laurie Love I thank you for being patience as I have had to fight through my many health
issues (known and unknown), your kind words and support during my writing process is
valued and appreciated. You both exemplify true academia examples of strong women who
have demonstrated dedication to students and to the profession. Your integrity and kindness
helped make this journey possible and perfect.
Similarly, Dr. Lawrence Picus, thank you for stepping in as my dissertation chair. Your
continue support and patience has helped me during this process. There were times when I
wanted to throw in the towel, but your kind words exemplified the meaning of “Fight On.”
The words of those emails may have been few in text, but meant more than you know, thank
you. Words cannot express what they really meant during me fighting my mental subtlety.
In addition, to Dr. Dennis Hocevar I would like to convey my sincere gratitude and
upmost appreciation to you for your unwavering dedication to assuring my journey would be
perfect and completed. The perseverance and tenacity you have demonstrated has helped me
fight through my own personal and health obstacles to see my dissertation experience through.
You will never understand how much your guidance has meant to me.
Finally, a special thank you to Dr. Antoinette Linton I am blessed by your mentorship
and friendship. Your words, remarks, and vast knowledge of academic pedagogy have helped
mold me into a stronger educator for my community. Lastly, if not for your financial support
and encouragement in the beginning, I could not stand here at this moment of accomplishment,
THANK YOU!
EVALUATING COLLEGE READINESS 4
TABLE OF CONTENTS
Dedication 2
Acknowledgements 3
List of Tables 6
List of Figures 8
Abstract 9
Chapter One: Background of the Problem 10
Importance of Study 11
Purpose of the Study 12
Research Questions 13
Significance of the Study 13
Deficiencies in the Literature 14
Definitions 15
Organization of the Study 16
Chapter Two: Review of the Literature 18
History of NCLB 19
Elementary And Secondary Education Act 20
A Nation At Risk 21
Improving America’s Schools Act (Iasa) 23
Components of NCLB 25
Implications of NCLB 27
Perceptions and Challenges of African American Students 30
Opportunity to Learn 31
African American Students’ Achievement Gap 32
Summary 35
Chapter Three: Methodology 37
Participants 38
Setting 39
George Washington Preparatory High School 39
Susan Miller Dorsey High School 40
Crenshaw High School 41
Los Angeles Unified School District 41
California Department Of Education 42
Instrumentation 43
Procedure 44
Analytic Framework 46
Limitations 46
Threats to Internal Validity 46
Threats to External Validity 46
Threats to Statistical Conclusion Validity 47
Summary 47
Chapter Four: Results and Discussion 48
Findings 49
Analysis Results for Research Question 1 49
Analysis Results for Research Question 2 52
EVALUATING COLLEGE READINESS 5
Analysis Results for Research Question 3 56
Analysis Results for Research Question 4 59
76 Discussion
Chapter Five: Summary, Discussions and Recommendations 79
Summary of Methodology 80
Discussion of Results 82
Target Schools 82
Target Schools and Opportunity-to-Learn 83
Target Schools and Proficiency Success Rates 84
Target Schools Versus LAUSD African American Students Opportunity-to-Learn Rates 84
Target Schools Versus LAUSD African American Students Proficiency Success Rates 85
Target Schools Versus LAUSD White Students Opportunity-to-Learn Rates 85
Target Schools Versus LAUSD White Students Proficiency Success Rates 86
Increasing African American Students Proficiency Rates in College Readiness Courses 87
Implications for General Practice 88
Limitations 90
Recommendation For Further Research 90
Conclusion 91
References 92
Appendix A: 2003-2012 CST Target Schools and LAUSD AA Algebra II 99
Appendix B: 2003-2012 CST Target Schools and LAUSD AA Algebra II 100
Appendix C: 2003-2012 CST Target Schools and LAUSD White Algebra II 101
Appendix D: 2003-2012 CST Target Schools HS Summative 102
Appendix E: 2003-2012 CST Target Schools and LAUSD AA Hs Summative 103
Appendix F: 2003-2012 CST Target Schools and LAUSD W Hs Summative 104
Appendix G: 2003-2012 CST Target School Proficiency Success Rates Algebra II 105
Appendix H: 2003-2012 CST Target School Proficiency Success Rates Algebra II 106
Appendix I: 2003-2012 CST Target School and LAUSD W Proficiency Success Rates
Algebra II 107
Appendix J: 2003-2012 CST Target School and LAUSD W Proficiency Success Rates HS
Summative 108
Appendix K: 2003-2012 Cst Target School and LAUSD W Proficiency Success Rates HS
Summative 109
Appendix L: 2003-2012 Cst Target School and LAUSD W Proficiency Success Rates HS
Summative 110
EVALUATING COLLEGE READINESS 6
LIST OF TABLES
Table 1: Descriptive Statistics of Opportunity-to-Learn for Algebra II and HS Summative 50
Table 2: Descriptive Statistics of Proficiency for Algebra II and HS Summative 50
Table 3: Effect Size Analysis for Opportunity-to-learn 51
Table 4: Effect Size Analysis for Proficiency Success Rates 51
Table 5: Descriptive statistics of Opportunity-To-Learn for Algebra II and HS Summative 53
Table 6: Descriptive statistics of Proficiency Success Rates for Algebra II and HS Summative 53
Table 7: Effect Size Analysis for Opportunity-To-Learn 54
Table 8: Effect Size Analysis for Proficiency Success Rates 55
Table 9: Descriptive statistics of Opportunity-To-Learn for Algebra II and HS Summative 56
Table 10: Descriptive statistics of Proficiency Success Rates for Algebra II and HS
Summative 56
Table 11: Effect Size Analysis for Opportunity-To-Learn 57
Table 12: Effect Size Analysis for Proficiency Success Rates 58
Table 13: Opportunity-To-Learn for Algebra II Growth Over Time 60
Table 14: Opportunity-To-Learn for Algebra II Growth Over Time 61
Table 15: Opportunity-To-Learn for Algebra II Growth Over Time 62
Table 16: Opportunity-To-Learn for HS Summative Growth Over Time 64
Table 17: Opportunity-To-Learn for HS Summative Growth Over Time 65
Table 18: Opportunity-To-Learn for HS Summative Growth Over Time 66
Table 19: Proficiency Success Rate for Algebra II Growth Over Time 68
Table 20: Proficiency Success Rate for Algebra II Growth Over Time 69
Table 21: Proficiency Success Rate for Algebra II Growth Over Time 71
Table 22: Proficiency Success Rate for HS Summative Growth Over Time 72
EVALUATING COLLEGE READINESS 7
Table 23: Proficiency Success Rate for HS Summative Growth Over Time 74
Table 24: Proficiency Success Rate for HS Summative Growth Over Time 75
EVALUATING COLLEGE READINESS 8
LIST OF FIGURES
Figure 1: Opportunity-To-Learn for Algebra II from 2003 to 2012 for African American
students at the three target schools (Crenshaw HS, Dorsey HS, and Washington Prep HS) 59
Figure 2: Opportunity-To-Learn for Algebra II from 2003 to 2012 for African American
students at the three target schools (Crenshaw HS, Dorsey HS, and Washington Prep HS)
and LAUSD AA. 61
Figure 3: Opportunity-To-Learn for Algebra II from 2003 to 2012 for African American
students at the three target schools (Crenshaw HS, Dorsey HS, and Washington Prep HS) and
LAUSD Whites. 62
Figure 4: Opportunity-To-Learn for HS Summative from 2003 to 2012 for African American
students at the three target schools (Crenshaw HS, Dorsey HS, and Washington Prep HS). 63
Figure 5: Opportunity-To-Learn for HS Summative from 2003 to 2012 for African American
students at the three target schools (Crenshaw HS, Dorsey HS, and Washington Prep HS) and
LAUSD AA. 65
Figure 6: Opportunity-To-Learn for HS Summative from 2003 to 2012 for African American
students at the three target schools (Crenshaw HS, Dorsey HS, and Washington Prep HS) and
LAUSD Whites. 66
Figure 7: Proficiency Success Rate for Algebra II from 2003 to 2012 for African American
students at the three target schools (Crenshaw HS, Dorsey HS, and Washington Prep HS) 67
Figure 8: Proficiency Success Rate for Algebra II from 2003 to 2012 for African American
students at the three target schools (Crenshaw HS, Dorsey HS, and Washington Prep HS) and
LAUSD AA. 69
Figure 9: Proficiency Success Rate for Algebra II from 2003 to 2012 for African American
students at the three target schools (Crenshaw HS, Dorsey HS, and Washington Prep HS) and
LAUSD Whites. 70
Figure 10: Proficiency Success Rate for HS Summative from 2003 to 2012 for African
American students at the three target schools (Crenshaw HS, Dorsey HS, and Washington
Prep HS). 72
Figure 11: Proficiency Success Rate for HS Summative from 2003 to 2012 for African
American students at the three target schools (Crenshaw HS, Dorsey HS, and Washington
Prep) and LAUSD AA. 73
Figure 12: Proficiency Success Rate for HS Summative from 2003 to 2012 for African
American students at the three target schools (Crenshaw HS, Dorsey HS, and Washington
Prep) and LAUSD Whites. 75
EVALUATING COLLEGE READINESS 9
ABSTRACT
African American students’ college readiness performance levels are decreasing all
across the United States. In addition, there has been a decline in African American students’
preparation for college level classes, especially mathematics (Curry, 2015). The study will
evaluate mathematics performance data using results from the California Standards Test in the
target schools of Washington Preparatory High School, Susan Miller Dorsey High School, and
Crenshaw High School. The schools selected have the largest enrollment of African American
students in Los Angeles Unified School District. The study will give background information
that defines success in obtaining college readiness. In addition, statistical experiments,
descriptive statistics and linear regression for comparisons among high schools and with the
district’s overall data. Finally, the research will discuss the implications of supporting African
American students in increasing their college readiness performance levels to meet or exceed
those of the district.
EVALUATING COLLEGE READINESS 10
CHAPTER ONE: BACKGROUND OF THE PROBLEM
Mathematics is a critical component of the curriculum at all grade levels. Over 30 years
ago, the report A Nation at Risk by the National Commission on Excellence in Education
(Gardner, 1983) brought attention to the mediocrity of schools. The nation recognized school
systems’ lack of focus on rigorous academic standards and its effects on academic achievement.
There was a desire to improve students’ academic performance through a more comprehensive
vision of consistency throughout the nation. Subsequently, current high school requirements in
most states need at least four years of English, three years of mathematics, two years of science,
and two years of social science to receive a high school diploma.
In 1989, the National Council of Teachers of Mathematics (NCTM) created its own
curriculum and evaluation standards for the teaching of mathematics (NCTM, 1991). The newly
developed standards assisted in aligning mathematical frameworks nationwide. In 1992, NCTM
revised the standards due to the fact that students were still performing poorly in mathematics.
The basic tenets of NCTM are that (1) all students need to learn more (and often different)
mathematical content contained in current programs, and (2) the currently prevalent methods of
instruction in mathematics must be significantly revised (NCTM, 1992). Therefore, NCTM
provides support in multi intelligence curriculum lessons plans that are accessible and equitable
to all students. In 2012, the board of directors incorporated technology in their tenets (NCTM,
2012).
In an effort to develop rigorous academic strands that included the ability to reason,
communicate, and solve problems, in 1992, the state of California implemented the Mathematics
Framework for California Public Schools (Becker & Jacob, 2000). Consequently, in 1995, a
statewide Mathematics Tasks Force was established to address the need to improve students’
EVALUATING COLLEGE READINESS 11
academic performance in mathematics. The task force recommended that the standards
statewide Mathematics Tasks Force was established to address the need to improve students’
academic performance in mathematics. The task force recommended that the standards
emphasize basic skills and technology and focus on mathematic content balanced with the eight
strands already established in the Mathematics Framework. Therefore, in keeping with the
national objectives of the Mathematics Education Framework and NCTM, standards were
incorporated into students’ outcomes and into teaching methods to support mathematical
curriculum from kindergarten through twelfth grade. During this time, secondary education had
a very problematic task of identifying effective mathematic teaching methods and even more so
with high-level subjects (Becker & Jacob, 2000; Department of Education, 2012; NCTM, 1992).
In 2010, a number of states (including California) adopted common standards for English
and mathematics. The standards are termed Common Core State Standards (CCSS). Politicians
and administrators felt sharing the same standards would assist all students in receiving a more
rigorous education even if they changed schools or moved to a different state. Teachers, parents,
and education experts designed the standards to prepare students for success in college and the
workplace in the 21
st
Century (California Department of Education, 2014). Although the CCSS
addressed the need to implement similar standards nationwide, in the case of mathematics, these
standards only address the lower-level subjects of algebra 1, geometry, and algebra 2. There is no
evidence that suggests CCSS will address the higher level-subjects that are directly aligned to
college level mathematics and provide access to post-secondary education (Linn, 2000).
Importance of Study
In every field, including education, there are common problems of practice. These
problems are related to, but extend beyond, specific organizational or contextual problems.
EVALUATING COLLEGE READINESS 12
Since 1981, the nation has recognized the connection between school systems’ lack of rigorous
academic standards and students’ academic performance. Since 2000, at Washington
Preparatory High School (WPHS) less than 10% of students enrolled have participated in the
higher level mathematic courses (Western Association of Schools and Colleges [WASC], 2011).
Susan Miller Dorsey High School (DHS) has less than 20% of students enrolled have
participated in the higher level mathematic courses (Los Angeles Unified School District [Public
School Choice 2.0], 2012). Finally, although Crenshaw High School (CHS) has the largest
African American enrollment of students less than 30% of students are enrolled in high level
mathematic courses (Los Angeles Unified School District, 2013). All three schools’ mission
statements focuses on students possessing the academic and social skills needed to think
critically, function in a diverse society, and be college ready. Therefore, the purpose of this
study will give background to evaluate college readiness through mathematics for African
American students at WPHS, DHS, and CHS. This lack of college readiness negatively impacts
the school’s enrollment, staffing and retaining highly qualified teachers, student learning.
Purpose of the Study
The purpose of this study is to examine the role mathematics courses play in college
readiness. However, deficiencies in the literature on the correlation between college readiness
and achievement in mathematics courses exist (Ewing, 2006). Data suggests that students are
taking college prep courses at a higher rate than in previous years, but fail to link post-secondary
achievement for African American students to success in post-secondary education (Ewing, 2006
& Sarnoff, 2006). In addition, the literature does not give a definitive explanation of what
constitutes success in being college ready (Ewing, 2006; Moore & Slate, 2008, Curry, 2015).
EVALUATING COLLEGE READINESS 13
According to the research, college professors and secondary teachers differ on whether students
are mathematically ready (Sanoff, 2006, Curry, 2015, & Tierney, 2015).
Research Questions
The following four research questions guide this study:
1. To what extent do the three target schools (Washington, Dorsey and Crenshaw) differ
on African American opportunity-to-learn and proficiency in Algebra II and Summative High
School Mathematics for the years 2003 – 2013?
2. To what extent do the three target schools (Washington, Dorsey and Crenshaw) differ
on African American opportunity-to-learn and proficiency in Algebra II and Summative High
School Mathematics when compared to African Americans attending other schools in LAUSD
for the years 2003-2013?
3. To what extent do the three target schools (Washington, Dorsey and Crenshaw) differ
on African American opportunity-to-learn and proficiency in Algebra II and Summative High
School Mathematics when compared to Whites attending other schools in LAUSD for the years
2003-2013?
4. To what extent if any, has African-American opportunity-to-learn and proficiency
changed from 2003 to 2013 at the three target schools (Washington, Dorsey and Crenshaw)
compared to the change for Whites and African-Americans attending other schools in LAUSD
over the same time period?
Significance of the Study
The focus of this study observes three high schools’ college readiness curricula through
the subject of mathematics through California Standardized Test (CST). With the transition to
CCSS, many schools found the implementation to be very challenging in preparing students for
EVALUATING COLLEGE READINESS 14
upcoming enrollment in AP classes. In addition, due to the fact that higher level mathematics
such as math analysis, statistics, and calculus are not aligned to CCSS unlike the CST, teachers
find it difficult to prepare students for the mandated newly developed Smarter Balance Testing
concurrently with students preparing for AP examinations.
As a result, this study can be a tool to support decision making in regard to college
readiness curriculum mathematics program. The results will be designed to help the make more
informed decisions in regards to mathematics that will help improve student participation and
performance in post-secondary settings, and with the implementation of CCSS.
Deficiencies in the Literature
There are deficiencies in the literature in regard to college readiness as demonstrated
through achievement in mathematics. Most research discusses the growth of the African
American students in preparatory mathematics courses from the 1980’s to the 2000’s, but there is
no information related to the role mathematics played in students’ outcomes and success in post-
secondary academics (Ewing, 2006; Moore & Slate, 2008). In addition, the research literature
discusses the strengths and weakness of African American students in prep mathematics courses,
but not how successful these students were in high-level mathematic courses after graduating
(Roderick & Stoker, 2010). Another deficiency within the literature is there is no national
dialogue on how the newly developed CCSS will be aligned to serve students who pursue higher
level mathematics (Linn, 2000).
Additionally, post-secondary educators’ perceptions of students’ preparation differ
significantly, and there is no consensus on whether students are adequately prepared for a college
curriculum (Sanoff, 2006). Many high school teachers feel students are prepared when leaving
their educational institutions; however, many college professors tend to feel the converse about
EVALUATING COLLEGE READINESS 15
how prepared students are when entering college (Sanoff, 2006; Curry, 2015). College faculty
members implied that many students are not adequately prepared for high-level course work and
score lower than a C in many classes (Sarnoff, 2006; Curry, 2015; Tierney & Duncheon, 2015).
In addition, Curry (2015) and Tierney and Duncheon (2015) students from low economic status
communities tend to perform even lower.
Furthermore, there is no literature presently on what type of impact the newly developed
CCSS will have in higher mathematics courses. Also, there is no data with the newly adopted
assessment tool Smarter Balance to measure students’ academic performance, many states have
not determined what role the assessment will have on students who are enrolled in math classes
beyond algebra II. At this time, Smarter Balance tests assess only algebra 1, algebra 2, and
geometry.
Definitions
For the purpose of this study, the following definitions are utilized to assist in clarifying
terminology.
Access Rates: Defined as every student having the equal opportunity to enroll in honors
or college-prep level courses.
California Standards Test (CST): The assessment formerly used to measure students’
achievement and progression in subject areas of English, math, science, and social science in the
state of California.
Curriculum frameworks: Frameworks discuss instructional approaches to assist teachers
in implementing standards.
EVALUATING COLLEGE READINESS 16
Common Core State Standards (CCSS): A set of high-quality academic standards in
mathematics and English language arts/literacy (ELA). These learning goals outline what a
student should know and be able to do at the end of each grade.
EO: English Only: Students who are native English speakers
Smarter Balanced Assessment: A state-led consortium developed to assess accurately
student progress toward college- and career-readiness.
.Reclassified Fluent English Proficient (RFEP): Students whose first language is not
English and are reclassified as being fluent in English.
Resources and support: To assure all schools successfully implement a standard-based
instruction based on an accountability measure
Socio-Economic Status: The eligibility for a free lunch as a measure of a student’s
socioeconomic status.
Success Rate: The description of various results to better understand how students can
succeed in post-secondary education.
Organization of the Study
This dissertation is divided into five chapters. Chapter One introduces the research,
which includes the problem of the study. In addition, Chapter One includes the purpose of the
study, research questions, importance of the study, and the specific terminology used
throughout the dissertation. Chapter Two offers an inclusive review of the literature relevant to
African American students being college ready. Additionally, Chapter Two will discuss the
gaps in the literature. The methodology used to conduct the research will be explained in
Chapter Three. This chapter will discuss the instruments, variables, setting, instrumentation,
procedure, data analysis, and limitations of the study. Chapter Four and Chapter Five present
EVALUATING COLLEGE READINESS 17
the findings of the study, discuss and examine the results, and, finally, present the implications
and limitations of the study.
EVALUATING COLLEGE READINESS 18
CHAPTER TWO: REVIEW OF THE LITERATURE
The purpose of this literature review is to examine the history, advancement, and
evaluation of the No Child Left Behind Act of 2001(NCLB) as it pertains to the challenges of
African American students from 9
th
through 11
th
grade, particularly in college readiness as
demonstrated through achievement in mathematics courses through formative assessments.
There is significant data that demonstrates there is still an achievement gap, even with significant
gains among African American students (Walters, 2001). The study will investigate African
American students’ academic performance geometry, algebra 2, trigonometry/math analysis, and
statistics.
The study will include data collected from the California Department of Education (CDE)
pertaining to students in the 9
th
grade and concluding with students in the 11
th
grade from the
years 2003 to 2013. For practical purposes, this study focuses on students from Crenshaw High
School (CHS), Susan Miller Dorsey High School (DHC), and Washington Preparatory High
School (WPHS). Finally, the data analysis compares African American students’ academic
success in the three targeted schools to all African American students in Los Angeles Unified
School District (LAUSD) and White students in LAUSD.
The literature review is organized into four areas to present key findings related to the
research questions. The first section discusses the history and importance of NCLB. The second
section focuses on the various perceptions and challenges of African American students. The
third section discusses the perceptions and implications of the achievement gap among African
American students. The final section discusses a theoretical framework through the literature.
EVALUATING COLLEGE READINESS 19
History of NCLB
In the middle of the 18
th
century, America established formal education. Until then,
education was provided at religious or private school settings. With the arrival of immigrants at
a consistent and rapid pace, there was a need to establish a formal educational system. The free
and public education of today started with establishment of free elementary school. In American
history, there has always been an achievement gap among citizens (Coulson, 1990). Since the
country was established in 1776, there has been an upper class and a lower class caste system.
Therefore, those of the upper class had the opportunity to receive an education. However, the
majority lower class citizens had to choose between receiving an education and helping to
support their families.
In 1867, after the civil war, African Americans received the opportunity for a free and
public education (Moses & Cobb, 2001; Walters, 2001). Even so, blacks would not receive free
and public education under the Plessy v. Ferguson decision of 1896 which upheld the
constitutionality of state laws requiring racial segregation in public facilities under the doctrine
of “separate but equal” (McGuinn & Hess, 2005; Moses & Cobb, 2001). It was not until 1954
that the landmark decision in Brown v. Board of Education declared “separate but equal” was
unconstitutional and blacks should be given equal access to public education (McGuinn & Hess,
2005; Moses & Cobb, 2001). Following the Brown v. Board of Education decision, the civil
rights movement began. This movement also exposed the lack of opportunities African
American and other minorities were afforded in terms of receiving an education. Before and
during the civil rights movement many states were not compiling with the Supreme Court’s
decision that “separate but equal” was unconstitutional.
EVALUATING COLLEGE READINESS 20
Elementary and Secondary Education Act
In the 1960s many laws were passed to support segregating schools nationwide and
giving equal educational access to all citizens. In 1965, the Elementary and Secondary
Education Act (ESEA) passed. Under President Lyndon B. Johnson, the ESEA marked the first
time that the federal government addressed K-12 educational policy. The Johnson
administration began to address inequities within schools. The ESEA was initially intended to
afford additional resources to underrepresented and disenfranchised students in the country’s
poorest communities. The act meant the federal government was to have little involvement in
how local state governments allocated funding. Although the federal government’s initial
intentions were to let state governments decide how to apply the funds from ESEA, over the past
40 years, the federal government’s involvement has grown significantly, through the enactment
of laws, political bureaucracy, and numerous court decisions.
Congress approved a $1.3 billion appropriation for ESEA. The act consisted of five
separate objectives. Title I was allocated the majority of funds ($1.06 billion). Title II
established a five year program to support school libraries, instructional materials, and textbooks.
Title III provided a five-year allocation for educational service centers. Title IV provided $100
million in funding and gave the United States Commission of Education the authority to partner
with universities and other state agencies to complete educational research, surveys, and
demonstrations. Lastly, Title V provided $25 million over a five year period to give additional
support to state departments of education (McGuinn & Hess, 2005).
Policymakers and educational researchers agree that the ESEA was created to address the
educational needs of poor children. There was an ideological debate between conservatives and
liberals regarding methods related to disadvantaged students. Politicians could not agree on
EVALUATING COLLEGE READINESS 21
whether the approach should be that of a deficit perspective, structural perspective, or a
something entirely new (McGuinn & Hess, 2005). Many conservatives thought students from a
poverty background could ultimately succeed if taught middle class values. Liberals suggested
that, due to political, economic, cultural and structural inequalities, America’s poorer schools
were well equipped for teaching. Although the ESEA’s budget continue to grow and expand to
cover various underrepresented students, the promise to increase educational opportunity was not
kept.
A Nation at Risk
During President Regan’s administration, the National Commission on Excellence in
Education (Commission) was established on August 26, 1981. The Commission was designed to
evaluate and examine the quality of education in the United States. Its main objective was the
perception of the public educational system, and its charge was to monitor six specific areas: (1)
assessing the quality of teaching in all sectors of education which included K-12 public and
private schools, colleges, and universities, (2) studying the relationship between college
admissions and high school achievement, (3) studying the relationship between college
admission requirements and high school student achievement, (4) identifying educational
programs which correlated to student success in college, (5)evaluating the degree to which major
social and educational changes in the last quarter century had a positive effect in student
achievement, and (6) outline specific challenges and determine if measures serve to develop
educational excellence (Gardner, 1983; Gardner, Larsen, & Baker, 1983).
The Commission took particular interest in adolescence as it pertains to high school
secondary education. In doing so, it focused on five major sources to gather data to assess the
progression of secondary education: (1) educational papers, (2) administrators, teachers,
EVALUATING COLLEGE READINESS 22
students, professional representatives, community groups, and parent organizations, (3)
preexisting educational challenges schools faced, (4)information from concerned citizens,
teachers, and administrators who volunteered information on the decline of America’s education,
and (5) programs and unique approaches to education (Gardner, 1983; Gardner et al., 1983). In
all, the Commission did demonstrate that concerned individuals from various diverse
backgrounds can and do agree on common goals to support the advancement of secondary
education.
In 1983, the Commission reported four specific indicators of risk prohibiting student
achievement. First, school content was diluted, as many students were not participating in
college prep programs and were opting to take general track courses. Secondly, there was a
deficiency of student expectations. It was found that the average time spent on homework had
declined despite the fact that students’ grades were improving. In addition, other countries began
incorporating mathematics into their curriculum starting at the 6
th
grade, while only 70% of the
states required one year of mathematics in order to receive a high school diploma. Thirdly, the
Commission found three trends that supported a lack of student development both in and out of
the classroom. For one, students in other industrialized countries spent more time completing
schoolwork than American students. Secondly, the usage of time in and out of the classroom
proved to be ineffective, and, third, there was a lack of support in assuring students developed
study skills to assist in dedicating more time to homework. Finally, the fourth finding saw a
need for improved teacher development programs. The Commission noticed teacher
credentialing and preparation did not attract more students to the profession, which was
demonstrated in teacher shortages across the nation. The teacher shortage was most severe in
mathematics and science (Gardner, 1983; Gardner et al., 1983; Jorgensen & Hoffman, 2003).
EVALUATING COLLEGE READINESS 23
Consequentially the recommendations were as follow. Regarding content, the
recommendation was to strengthen requirements for all students seeking a high school diploma.
Therefore, the Five New Basics were created. The new curriculum would include 4 years of
English, 3 years of mathematics, 3 years of science, 3 years of social sciences, and 1 semester of
computer science. Also, students who participated in college prep programs were strongly
advised to complete 2 years of a foreign language. In addition to the Five New Basics, there
were specific references related to mathematics. To reinforce the importance of competing with
other nations, the mathematics curriculum needed to equip students in understanding geometric
and algebraic concepts, elementary probability and statistics, real life mathematics, and in
estimating, approximating, and measuring calculations.
Recommendations related to expectations were to endorse schools, colleges, and
universities in adopting more rigorous expectations of students’ academic performance.
Suggestions included increasing the requirements for college and university admission. In
addition, increasing the school day and calendar days per school year was suggested to remedy
the lack of time students had in an out of the classroom. Finally, a suggestion pertaining to
teaching was to have districts move to an 11-month contract to support time for preparation and
increase professional in-service time. In addition, to help with the shortage of math and science
teachers, it was recommended that districts recruit from the non-educator arenas who were
familiar with what challenges students would embark, with limited science and math skills
(Gardner et al., 1983).
Improving America’s Schools Act (IASA)
On February 16, 1994, the House Committee on Education and Labor passed the
Improving America’s Schools Act (IASA) to be implemented from the fiscal year of 1995
EVALUATING COLLEGE READINESS 24
through the fiscal year of 1999. IASA was a reauthorization of the ESEA of 1965, and the
authorized amount of grant money was approximately $12.5 billion. IASA was organized into
five titles: Title I reauthorization of ESEA, Title II amended the General Education Provision
Act, Title III amended various educational statues, Title IV reauthorized the National Center of
Education Statistics, and Title V contained miscellaneous provisions (United States Congress,
1994). Additionally, IASA established new programs such as technology, educational
assistance, library media, and 21
st
century community learning centers which were added to Title
II. Title III would not include public charter schools. Title X would coordinate service projects.
Title IX gave approval for improvement to school facilities, and, under Title XII, urban and rural
would receive additional educational assistance support (United States, 1994).
Additionally, IASA focused on improving education for disadvantaged students by
reinforcing Title I to include “system reform” of K-12 public education. In order to receive
federal and state funds, states and districts would need to develop plans that included more
rigorous curriculum content related to states’ assessments and student achievement and
“opportunity-to-learn” standards to outline conditions ensuring all students meet state assessment
standards. Furthermore, IASA gave specific attention to improving teaching and learning by
establishing the Dwight D. Eisenhower Professional Development Program. The program would
approve providing teacher’s professional development activities in the core academic areas of
English, mathematics, science, social science, geography, foreign language, government, and
economics.
In 1994, a progressive movement toward standards-based education and assessment
began under IASA (Jorgensen & Hoffmann, 2003). Under IASA, The Goals 2000: Educate
America Act (ESEA) was established and was the first law that focused on the needs of all
EVALUATING COLLEGE READINESS 25
students, which included gifted and talented enrichment, honors, advanced, second-language
learners, students with disabilities, and students of socio-economic status (Jorgensen, 2003). The
act required all states to include content and performance levels, align assessments to newly
developed standards, and introduced an accountability system. The new accountability system
would be charged with identifying low performing schools within each state. With ESEA, states
had more flexibility to execute their programs with Federal funds.
From the origin of IASA, came a new educational reform measure in 2001 with the
signing of the newly created No Child Left Behind (NCLB) and the introduction of state
standards. States had to demonstrate a level of school performance through what was called
annual yearly progress (AYP). The newly developed standards were meant to increase students’
comprehension through a sequential order of standards-based concepts. States gave teachers set
standards in which students would have to demonstrate academic performance through grade
level testing and newly revised state exit exams (Jorgensen & Hoffmann, 2003).
Components of NCLB
In 2002 President George Bush signed the NCLB into law. This was to ensure all
students would receive an inclusive, responsive, and fair education (U.S. Department of
Education, 2003). This act was also designed to balance the achievement of students of
different ethnicities, second-language learners, students with disabilities, and students of low
socio-economic status. The problem in the with NCLB is the lack of consistency amongst all
states, particularly as it relates to high school exit exam requirements (Shaul & Ganson, 2005;
and US Department of Education, 2003).
One major component of NCLB was that each state was demonstrate accountability and
student achievement through assessment of students before they graduate. According to 2011-
EVALUATING COLLEGE READINESS 26
2012 data collected from the Center of Education Policy, only 30 states implemented a state exit
exam or end-of-course exam and, out of the 30, only 25 made it a graduation requirement. This
means that only 69% of the nation’s students are in states with exit exams (McIntosh, 2012;
Shaul & Ganson, 2005; US Department of Education, 2003). Since the signing of NCLB, most
states received multiple waivers to extend implementation of any type of assessment. Therefore,
there is a disparity within the nation in terms of adherence to NCLB (McIntosh, 2012). This
problem is important to address because it challenges the effectiveness of NCLB in in ensuring
all students receive an inclusive, responsive, and fair education. The major problem with NCLB
in the state of California is that it increased the achievement gap between African American
students and non-African American students.
Additionally, NCLB was to close the achievement gap by holding states, districts, and
schools accountable for improving the academic performance of all students. Key requirements
of NCLB are the annual proficiency assessments in grades 3 through 11, hiring highly-qualified
teachers, developing research-based curriculum, increasing parental involvement, establishing
public school choice as an option for parents and students, and annual report cards to help
support said goals. In addition, the goals of NCLB were to implement additional interventions to
meet the needs of all children. NCLB provisions were created for all states, districts, and schools
that received federal Title I funding.
Obama’s administration concerns for the implementation of NCLB are that it is “hurting
our children instead of helping them,” as President Obama noted in a speech announcing the
waivers (Riddle, 2012; The White House, 2011). There has been much emphasis on how to
implement NCLB with accountability to close the achievement gap. However, to date, most
EVALUATING COLLEGE READINESS 27
states have not implemented an accountability system nor lessened the achievement gap before
students graduate from the 12
th
grade (U.S. Department of Education, 2004).
Attempts are aimed at implementing national guidelines to improve educational access,
equity, and equality for all students. However, the effectiveness of NCLB has come under
question due to measures of accountability that from state to state. Beginning in 2012, many
states opted for the newest educational reform, CCSS, and for end-of-course exams as qualifiers
for graduation and adequate yearly performance measures (McIntosh, 2012).
Despite the lack of closing the academic achievement gap, NCLB has created an
accountability structure and produced significant data that provides insight to how states and
school districts support African American students in increasing their progress through their
performance on high stake testing (McIntosh, 2012, Nichols, Glass, & Berliner, 2005).
Implications of NCLB
NCLB has been widely criticized, particularly for the accountability policies. Although
there is a basic outline of accountability for NCLB, determining its effectiveness is challenging
because the statute does allow for variation (Riddle, 2012). Each state has decision-making
power in regards to state content standards, assessments, and defining proficiency levels. As a
result, rigor of curriculum and standards varies from state to state (Riddle, 2012). Additionally,
each state has separate educational policy, such as types of subgroups and sizes of testing
subgroups, which defines adequately yearly progress for federal funding. Therefore, NCLB has
exhibited significant gains in closing the achievement gap in regards to state policy. However,
the following differences have made it difficult to determine the impact of NCLB on student
academic performance and achievement at a national level, due to the lack of continuity as it
EVALUATING COLLEGE READINESS 28
pertains to state versus federal educational policy (Anonymous, 2007, Lader & Frankfort, 2011,
& Linn, 2000).
NCLB expressed President Bush’s promise to end the “soft racism of low expectations”
by closing achievement gaps and bringing all students to proficiency by 2014 (Riddle, 2012).
NCLB created unprecedented measurement of academic progress in English and mathematics.
The reauthorization of NCLB in 2008 added measurement of academic progress in science and
social science. Mandated yearly tests in elementary and middle school and were meant to ensure
all children attain 100% proficiency. Additionally, schools were required, under threat of strict
sanctions, to raise achievement each year in math and reading and to eliminate the achievement
gap in terms of race, ethnicity, language, and special education status (Riddle, 2012; Nichols,
Glass, & Berliner, 2005). The new requirement would encourage reviewing data in terms of
personal growth and not how the progression of whole groups. With the new requirement many
states including California, were able to implement accountability measures, such as Safe Harbor
(Linn, 2000, Linn & at el, 2002, Nichols, Glass, & Berliner, 2005). Safe Harbor was an
additional accountability strategy that would support many school districts with populated urban
students containing African American students. The new measures have helped to close the
achievement gap by using various calculations that gave consideration to the what the actual
academic goal was versus lowering the percent of academic progress to a more realistic goal
(Linn, 2000, Linn & at el, 2002, Nichols, Glass, & Berliner, 2005). Achievement gaps establish
important barometers in educational and social progress. The National Assessment of
Educational Progress (NAEP), the professed nation’s report card of student achievement,
provides information on the achievement gaps among different racial and socioeconomic groups
in core academic subjects. In the 1990s, there were significant setbacks in the national progress
EVALUATING COLLEGE READINESS 29
toward narrowing the achievement gaps. Few states were able to improve the average
achievement and narrow the gaps simultaneously. With the creation of NCLB 2001intentions
were to ensure academic excellence and equity by providing new opportunities and challenges for
states to advance the goal of closing the achievement gap (Walters, 2001, and Wenglinsky,
2004).
In the 1970s and 1980s showed the achievement gap narrowing sustainably in
socioeconomic and racial categories in core academic subjects. During the 1970s education
and social policies strived to narrow the achievement gaps by warranting a low adequate level
of achievement for African Americans through Title I, minimum competency testing,
mandatory segregation (including mandatory busing), equalization of school funding, raging a
war on poverty, and the introduction of affirmative action within the school setting (Walters,
2001, and Wenglinsky, 2004). Now during the last two decades the focus of education has
moved from equality and equity to excellence and proficiency, which can cause tension
between academic excellence and equity (Walters, 2001, and Wenglinsky, 2004). The Na
National Assessment of Educational Progress (NAEP) unofficial known as the nation’s report
card of student academic achievement, offers information the achievement gap between races
and various socioeconomic groups in English, mathematics, social science, and science (Ford,
Grantham, & Whiting, 2008l; Ladner & Burke, 2010, and Lips & Marshall, 2008).
There has been mixed findings in the research that pertains to high-stakes testing on
improving student’s academic performance, creating controversy over the usefulness of
educational policy (Walters, 2001, and Wenglinsky, 2004).
Although NCLB builds on unproven success of states who adopted accountability
systems during the establishment of NCLB, evaluating the effectiveness has required more
EVALUATING COLLEGE READINESS 30
demanding scrutiny of the new evidence from the NAEP and state reports. While NCLB
established baseline state assessments for determining accountability, NAEP provides
independent assessments to support and validate state results regarding the achievement gap
(Walters, 2001, and Wenglinsky, 2004).
Perceptions and Challenges of African American Students
Researchers have identified a variety of perceptions and challenges African American
students encounter in their academic achievement (Lips & Marshall, 2008; Rodenick, Nagaok,
Coca, 2009; Tierney & Duncheon, 2015; Wenglinsky, 2004). Scholars suggest African
Americans do not value their education or African American students lack self-discipline and
motivation (Balduf, 2009 & Colkey, 2003). Although studies explore the argument that African
American students do not value their education or lack self-discipline and motivation, other
practitioners suggest negative attributes of African American students contribute to African
American history, educational setting, demographics, and lack of access to rigorous courses
(Cokley, 2003; Conley, 2013; Currry, 2015; Ladner & Burke, 2010; Nikolakakos, Reeve, &
Shuch, 2012; Roderick & Stoker, 2010). Further empirical evidence suggest there is a disparity
in affording African American student equitable educational settings to white students, which
increases lack of self-discipline and lack of motivation (Mitchell, 2007; Tierney & Duncheon,
2015). Other challenges are large populations of African American students tend to lack highly
qualified teachers and attrition from faculty in their educational institutions (Walters, 2001).
Additional to lack of experienced teaching and high turnover in schools, many school urban
communities to do offer a variety of rigorous course selection to students (Anonymous, 2008;
Conley, Drummond, De Gonzalez, Rooseboom, Stout, 2011; & Curry, 2015). Despite the varies
EVALUATING COLLEGE READINESS 31
factors obstacles in which African students have been challenged with evidence display there has
been growth in closing the achievement gap through standardized assessments ( CDE, 2015).
Opportunity-To-Learn
Studies have considered opportunity to learn (OTL) to be relevant for two specific
reasons. First, standardized testing are dominated in public education in the United States, due to
legislation such as NCLB. There is an assumption that all students have been afforded the same
opportunity to learn the curriculum on which they will be assessed (Barnard-Brak & Yang,
2018). Second, the achievement gaps in socioeconomic populations continue to persist within
the United States context for two reasons. On the contrary, the achievement gap is still evident
and many students do not receive the same opportunity to learn similar curriculum before or after
being tested. Observing opportunity to learn would appear to clarify the why there remains
achievement gaps (Barnard-Brak & Yang, 2018).
Opportunity to learn (OTL) was first defined in 1963 by John Carroll. Carroll’s define
OTL as the amount of time students are engaged in learning specific curriculum in comparison to
how much time students need to learn the curriculum in a school setting. In addition to time,
variables such as content and quality of instruction given also are considered to equating OTL.
Overtime independent variables such as teacher questionnaires and appraising approved
textbooks have been included in the definition of OTL (Wijaya, van den Heuvel-Panhuizen, &
Doorman, 2015).
Research has demonstrated that a combination of student and teacher information that is
based in student-center learning can properly assess OTL. However, OTL can be considered
undependable due to every student does not retain the same level of information due a variety of
EVALUATING COLLEGE READINESS 32
circumstances. In addition, schools and districts can over exaggerate their claims of predicting
students OTL.
Nevertheless, the many reasons on determining factors on OTL is measured, it apparent
student’s academic performance has increased and there is a correlation of consistent academic
performance in urban communities (Barnard-Brak & Yang, 2018).
African American Students’ Achievement Gap
There is current and academic achievement disproportion amongst African Americans
(AA) students in California and their White students. The achievement gap can be defined by a
social-economic status (SES) and instructional practice disparities (Ford, Grantham, & Whiting,
2008l; Ladner & Burke, 2010, and Lips & Marshall, 2008). Researchers visible demonstrated
that the SES of African American students in urban school setting has an effect on African
American student’s academic performance (Hall & Kennedy, 2006 and Johnston & Viadero,
2000). The effects are defined as homelessness, nutrition, and income (Becker and Luthar,
2002). By studying the demographics of African American students and the types of
instructional practices given to them throughout their educational career research shows
standardized assessment be analyzed through opportunity-to-learn (OTL) and proficiency
success rates in mathematics (Johnston & Viadero, 2000; Linn, Baker, & Betebenner, 2002, and
Neter, Wasserman, and Kutner, 1990).
By looking at disaggregated data of the California Standardized Test specifies African
American students are afforded the opportunity to participate in college readiness. Although
students are given the opportunity to enroll in college readiness courses such as, algebra II,
trigonometry, AP Statistics and calculus, participation rates of African American students are
lower than their white peers. Research suggests the low numbers are due to self-confidence, early
EVALUATING COLLEGE READINESS 33
childhood experiences in elementary or middle school, or lack of instructional practices in
previous courses (Becker & Luthar, 2002 and Cokley, 2003). Even so, when AA students do
participate in college readiness courses their proficiency success rate is substantial lower that
White students. Once again research contribute the low academic performance rate to lack of
instructional practice and early childhood education (Becker & Luthar, 2002 and Cokley, 2003).
Historically African Americans students have developed low self-esteem due to
circumstances that surround the Jim Crow Era. Separate but equal played a factor on how
African Americans were viewed by society and themselves. Unfortunately, throughout the
African American history a sigma has been passed down generationally that African Americans
are not better than their white peers. Scholars have also indicate historical the inequities of race
and class continue to persist in American society. History shows that African American students
did not receive formal high schooling education until 1968 (Becker & Luthar, 2002; Cokley,
2003; Mitchell, 2007; Moses & Cobb, 2001, and Sampson & Garrison-Wade, 2011).
Studies point out urban schools with lack of instructional practices can be attributed to
debt and education disparity. Many urban school do not receive similar funding due to low
enrollment. In addition, urban schools are at a greater risk of teacher attrition, due to hiring first
year teachers. Many times first year teachers lack the experience of teaching college readiness
courses and have not been give adequate time in participating in professional developments that
would better prepare them for such a task.
Even so, when AA students do participate in college readiness courses their proficiency
success rate is substantial lower that White students. Once again research contribute the low
academic performance rate to lack of instructional practice and early childhood education
EVALUATING COLLEGE READINESS 34
(Becker & Luthar, 2002; Cokley, 2003; Mitchell, 2007; Moses & Cobb, 2001, and Sampson &
Garrison-Wade, 2011).
Therefore, the AA achievement gap is distinct to their social-economic status (SES) and
instructional practice disparities. Hence, pursing to close the achievement gap for AA students
and their classmates educational institutions increase professional development to support
teachers to increase their instructional practices. Increasing professional development in support
of teachers will help to decrease high rates of teacher attrition in urban school settings.
However, more research is required to support decreasing the SES through an academic quality
for the African American community (Becker & Luthar, 2002; Cokley, 2003; Mitchell, 2007;
Moses & Cobb, 2001, Sampson & Garrison-Wade, 2011, and Walters, 2001).
The gap between African American students versus White and Latino students’
educational progression actualizations is becoming increasingly problematic for the United
States and its African American citizens. Projections by the U. S. Bureau of the Census (2010)
estimate that the White students will expand slowly until 2020 and then stabilize, where African
American students rise, largely due to a substantial increase in the number of other minorities
(Walters, 2001 and Wenglinsky, 2004). Given that racial and ethnic minorities are expected to
increase in both number and percentage in high school populations, the underrepresentation of
low-income, African-American students in the college ready population is likely to have a
substantial effect on American society. Due to their lower rates of participation in mathematics,
African-American students are less likely than White students to be successful in postsecondary
education (Curry, 2015; Hall & Kennedy, 2006; Le & Frankfort, 2011Lotkowski; and Robbins,
& Noeth, 2004).
EVALUATING COLLEGE READINESS 35
Within the Los Angeles Unified School District (LAUSD) high schools that are
predominantly African American there are several trends that effect closing the achievement gap
to White students. Schools with high attrition lacks consistency for students to participant in a
rigorous curriculum. Due to various teaching characteristics, techniques, and personality
evidence show students learn at a slower rate than students who have highly qualified and
experience teachers (Conley, 2013; Masen, 2010; Additionally, students are afforded the
opportunity to have a wider selection of honor and advanced placement courses that are related
to college readiness (Masen, 2010; Moore & Slate, 2008; Riddle, 2012 and Shaul & Ganson,
200; and Roderick & Stoker, 2010).
Similarly, students who have a larger selection of courses and more opportunities to
participate in more college readiness courses tend perform better on standardized testing (Masen,
2010; Moore & Slate, 2008; Riddle, 2012). Studies show students who participate in college
readiness course with consistency as early as the 9
th
grade proficiency success rates are higher
than students who participate in college readiness classes beginning in the 11
th
grade. In
addition, evidence demonstrate students in LAUSD predominantly African American schools
have a low proficient success rates in algebra 1 and geometry prior to college readiness courses,
such as algebra II, advanced placement statistics and calculus (Masen, 2010; Moore & Slate,
2008; Riddle, 2012 and Shaul & Ganson, 200; and Roderick & Stoker, 2010).
Summary
The purpose of this literature review was to define an argument to ensure African
American students have an adequate and equitable opportunity to participate and succeed when
participating in college readiness level mathematics courses based on the research college
readiness mathematical courses in regards to African American students needs to have a
EVALUATING COLLEGE READINESS 36
demanding support and drive from state and federal levels that are consistent, coherent, and
produce significant results over time. To improve and enhance the ability to increase
opportunity-to-learn and proficiency rates of African American students in college readiness
mathematical courses the federal government needs to relinquish the theory of one size fits all
mindset and trust state government deliver what is fair and adequate within their districts (Curry,
2015). Studies also demonstrate that many students (more African Americans) have a difficult
transition from high school to college (Cokley, 2003; Lips & Marshall, 2008, and Roderick &
Stoker, 2010). Consequently the likelihood that African Americans will make a successful
transition to a college environment is more than like a determined by their college readiness in
English and mathematics (Curry, 2015).
In conclusion, there is still a significant achievement gap to close that impends all high
school students nationwide, but more specifically for African American students. In this
advanced technologic age it is unacceptable for large number of any students, regardless of their
ethnicity not to have the essential skills and knowledge that prepares them for a college level
curriculum. “We cannot be satisfied until every child in America- and I mean every child has the
same chance for a good education that we want for our children,” stated by President Obama
(Lips & Marshall, 2008).
EVALUATING COLLEGE READINESS 37
CHAPTER THREE: METHODOLOGY
This chapter defines the research questions discussed in Chapter One and gives a
complete detail of the study, describes the participants, the school setting, what procedures were
used to collect data, instruments used, and the process for data analysis. The purpose of this
study is to examine the effect mathematics achievement has on college readiness by conducting a
longitudinal experiment that focuses on algebra 2, trigonometry/math analysis, statistics, and
achievement of African Americans from 2003 to 20102.
The following four research questions guide this study:
1. To what extent do the three target schools (Washington, Dorsey and Crenshaw) differ
on African American opportunity-to-learn and proficiency in Algebra II and Summative High
School Mathematics for the years 2003 – 2012?
2. To what extent do the three target schools (Washington, Dorsey and Crenshaw) differ
on African American opportunity-to-learn and proficiency in Algebra II and Summative High
School Mathematics when compared to African Americans attending other schools in LAUSD
for the years 2003-2012?
3. To what extent do the three target schools (Washington, Dorsey and Crenshaw) differ
on African American opportunity-to-learn and proficiency in Algebra II and Summative High
School Mathematics when compared to Whites attending other schools in LAUSD for the years
2003-2012?
4. To what extent if any, has African-American opportunity-to-learn and proficiency
changed from 2003 to 2012 at the three target schools (Washington, Dorsey and Crenshaw)
compared to the change for Whites and African-Americans attending other schools in LAUSD
over the same time period?
EVALUATING COLLEGE READINESS 38
The study aimed to evaluate student college readiness at WPHS, DHS, and CHS as it
compared to that among the remaining African Americans students and Whites students of
LAUSD through a quantitative method. This quantitative study used online data from the
California Department of Education and LAUSD covering 10 years. With the permission of the
Institutional Review Board in conjunction with the university’s approval, the study used LAUSD
student information, such as ethnicity as a status variable, gender, and academic performance on
the California Standards Test (CST). Finally, the quantitative study acquired student
performances from the California Department of Education.
In conducting a quasi-experiment, there are certain variables that are defined as status,
accepted causes and effects (Creswell, 2014). In a quasi-experiment, the quasi-independent
variable is the variable whose variation does not depend on that of other variables and are
accepted causes of the study. For this study, WPHS, DHS, CHS, and LAUSD are quasi-
independent variables. Additionally, a quasi-experiment has dependent variables whose
variation depends on causes or effects of a study. The CST data is the dependent variable of this
study. Additional dependent variables are opportunity-to-learn and proficiency success rates
related to the CST. Status variables are variables that cannot be changed or influenced;
therefore, ethnicity is referred to as status variables.
Participants
The participants for this study were all 9
th
through 11
th
grade African American students
at WPHS, DHS, and CHS in LAUSD, from 2003 to 2012. In addition, participants were the
remaining African American and White students in LAUSD. The three schools collectively had
the largest population of African American students. All African American students are English
only students, meaning their first language is English; these include students who are of African
EVALUATING COLLEGE READINESS 39
descent. Additional grouping consists of Gifted and Talented students whose traits consist of
high levels of general abilities, commitment, and creativity; students with learning disabilities,
accommodations, or modifications as identified in their individualized education program (IEP)
or 504 plans; Advanced Placement students, defined as students who participate in college-level
curriculum and national examinations; Honors students, meaning those enrolled in the maximum
number of Honors and/or AP classes; students who are classified as low socio-economic status,
meaning they qualify for free or reduced-price lunch; and transient students, meaning they are
identified as dropouts, homeless, and late enrollees.
Setting
The following participant samples were unique to LAUSD high schools. Washington
Prep, Dorsey, and Crenshaw had the largest populations of African American students in the
district (LAUSD, 2017). According to LAUSD (2017) data, Hispanics are the majority
population within the district, and African Americans, whites and other populations are
underrepresented. For the purpose the study, the data used to demonstrate college readiness
among African American students at these three schools in comparison with that of African
American students throughout the district. In addition, to the quasi-experiment, the study
compared African American students to Whites students in LAUSD.
George Washington Preparatory High School
WPHS is a comprehensive high school in South Los Angeles with approximately 1,336
students. It was established in 1927 as part of the Los Angeles High School District. In 1981,
under the leadership of George McKenna, Washington High School added ninth grade,
established two magnets (Performing Arts and Communication Arts) and created a triad
“preparatory” school model based on the educational perceptions of Effective School Correlates
EVALUATING COLLEGE READINESS 40
written by Ron Edmonds (WPHS, 2013). Today, WPHS is comprised of a music/performing
arts and science, technology, engineering, and mathematics magnet and a small learning
community focused on social justice and law. LAUSD student report data reports WPHS’s 2013-
2014 student population consisted of 695 (52%) African American students, 601 (45%) Hispanic
students, and 53 (4%) White, Asian Pacific, and other students. Of the 1,336 students, 67 (5%)
are considered gifted and talented, 240 (18%) have disabilities, and 1,095(82%) are
economically disadvantaged students.
WPHS is one of 197 high schools within the boundaries of the LAUSD and is located in
an unincorporated area of Los Angeles County adjacent to the city of Los Angeles and near the
cities of Inglewood, Gardena, and Hawthorne. The residents in the neighboring area are
approximately 55% African American and 45% Latino, and the Latino population is steadily
growing (LAUSD, 2013). All of the students are eligible for Title I services, creating a low
socio-economic profile for the student body. In addition, WPHS houses Duke Ellington
Continuation High School and an offsite Maxine Waters Employment Preparation Center.
Susan Miller Dorsey High School
DHS is an urban comprehensive high school in South Los Angeles built in 1937 that
serves a population of approximately 1,180 students. DHS was also part of the Los Angeles
High School District before the creation of LAUSD. DHS is adjacent to numerous churches, the
Crenshaw-Baldwin Hills Mall, single-family residences, and large multi-unit apartment
complexes (WASC, 2001). DHS consists of two magnet schools (law and public service magnet
and mathematics and science) and two academies: digital filmmaking and theatrical arts and
school of business and entrepreneurship. Each magnet and academy serves approximately 500
students (DHS, 2015).
EVALUATING COLLEGE READINESS 41
DHS’s 2013-2014 student population consisted of 614 (52%) African American students,
543 (46%) Hispanics students, and 23 (2%) White, Asian Pacific, and other students. Of the
1,180 students 71 (6%) are considered gifted and talented, and 944 (80%) are economically
disadvantaged students. DHS is identified as a Title I school.
Crenshaw High School
CHS was established in 1968 as part of LAUSD. CHS’s student population stems from
affluent African American neighborhoods of Baldwin Hills and View Park-Windsor Hills. The
current student population is approximately 1,069. In the 2014-2015 school year, CHS was
reconstituted into a comprehensive magnet high school. The school consists of three individual
magnet programs: Science, Technology, Engineering, and Mathematics; Business
Entrepreneurship and Technology; and Visual Arts and Performing Arts. Each program houses
approximately 500 students.
CHS has the largest African American population in LAUSD. Its student population
consists of 770 (72%) African American students, 289 (27%) Hispanic students, and 11(1%)
White, Asian Pacific, and other students. Of the 1,069 students, 53 (5%) are considered gifted
and talented, 171(16%) have disabilities, and 833 (78%) are recognized as economically
disadvantaged. CHS is also a Title I school.
Los Angeles Unified School District
LAUSD was established as Los Angeles High School District in 1853. In 1961, the Los
Angeles High School District was unified and renamed LAUSD. LAUSD is the largest school
district in California and the second largest in the nation. LAUSD’s total K-12 student
population is nearly 600,000. It is separated into six local district centers serving the north,
south, and east, central, southwest, and northwest regions. LAUSD has over 1,300 schools and
EVALUATING COLLEGE READINESS 42
centers. This includes over 457 elementary, 84 middle, 103 senior highs, 250 charters, 56 option
schools, 44 magnets, 23 multi-level schools, and 15 special educational facilities (LAUSD,
2013). Additionally, LAUSD has 138 K-12 magnet centers housed in various elementary,
middle, and senior high schools and has access to 10 community adult schools, Maxine Waters
Occupational Center, 1 regional occupational center, 26 skill centers, and 85 early educational
centers (LAUSD, 2013). LAUSD’s student enrollment is 653,826 students of whom 0.4% is
American Indian/Alaskan Native, 4.1% is Asian, 9.2% is African American, 2.0% is Filipino,
73.5% is Latino, 0.4% is Pacific Islander, 9.3% is White (not Latino), 0.1% is of an ethnicity
other that Latino, and 1.1% is of an reported ethnicity (CDE, 2013). Of the total LAUSD
enrollment 179,322 (27.4%) students are identified as English Learners and 501,125 (76.6%)
students are identified as economically disadvantaged in the free or reduced-price meal plan.
California Department of Education
The California Department of Education’s (CDE) annual data and statistics cover all
California schools. The data is helpful in identifying specific educational needs to increase and
support student’s academic performance (CDE, 2015). The California Basic Educational Data
System compiles information to assist in determining staffing assignments, graduation
requirements, and technology data (CDE, 2015). The California Longitudinal Pupil
Achievement Data System disaggregates the information into sample groups to support
determining student demographics, course data, discipline, assessments, and other state and
federal reporting (CDE, 2015). Information compiled by both systems helps determine various
mandated reports, such the population of English Learners, Title I funding, transient populations,
foster/group home counts, and dropout rates from the previous three years (CDE, 2015).
EVALUATING COLLEGE READINESS 43
Instrumentation
The instrument used for the study will be the algebra 2 and summative high school
mathematics (includes statistics and AP Calculus AB/BC) portions of the CST. From 2003 to
2013, the CST was administered during the spring semester throughout the state to comply with
state and federal mandates in accordance with NCLB (CDE, 2009). The exam was created to
measure student’s academic performance and progression in grades 2 through 11 in four
categories: English, mathematics, science, and social science. Additionally, the 11
th
grade
English, algebra 2 and summative high school math exams identified students who were
perceived as college ready through additional supplemental questions. This additional testing
was in partnership with the California State University (CSU) Mentor program and developed to
help identify students who were college ready. In addition, students who were identified as
college ready were waved from participating in community, CSU, and University of California
placement exams (CDE, 2013). In 2012, California introduced the California Modified
Assessment to support students with IEPs. However, the CMAs did not include the
supplemental question for college readiness. Students with IEPs who wanted to participate in the
CSU Mentor program were required to complete the CST’s English and algebra 2 sections or the
summative high school mathematics exams (CDE, 2013). The data gained from the CST are to
support districts, schools, and teachers in improving student learning.
Subsequently, in order for teachers to improve student learning, students were identified
by performance levels on the CST. The first level, Advanced, indicated students demonstrated
grade-level knowledge at a superior level. The second level, Proficient, meant students were
considered on track according to their grade level. The third level, Basic, meant students
demonstrated knowledge but also displayed gaps, according to their grade level, that limited their
EVALUATING COLLEGE READINESS 44
academic progression. The fourth level, Below Basic, meant students demonstrated major gaps
in their grade level content. Lastly, Far Below Basic meant students performed two or more
grade level below their own (CDE, 2009). Each performance level is identified by a numerical
score. Performance level scores ranged from 150 to 600. Students identified as college ready
were those who scored above Basic on both the CST and supplemental questions considered
(CDE, 2009).
Procedure
Student data acquired through online resources from the CDE and DataQuest website.
This study gauged to what extent, if any, high school mathematics curriculum (algebra 2,
trigonometry/math analysis, statistics, and Advance Placement Calculus AB/BC) provide access
to and success within post-secondary education for African Americans at WPHS, DHS, and
CHS. The data collected allowed for a longitudinal study over a ten year span from 2003 to
2012. This study only used algebra 2 and high school summative mathematics test scores from
the CST. Students who have successfully completed algebra 2 prior to the 12
th
grade and who
are enrolled in either trigonometry/math analysis, statistics, or Advance Placement Calculus
AB/BC automatically are given the high school summative CST exam. The data compared the
WPHS, DHS, and CHS to one another and all three school’s data were compared to that of
district’s African American and White population and state by calculating opportunity-to-learn
and proficiency success rates.
Opportunity-to-learn (OTL) data for algebra 2 students were determined by dividing the
number of students participating in algebra 2 by the number of 11
th
grade English Language
students in the 11
th
grade. English Language totals are used as the denominator, due to the fact
all students in the state of California must take English all four years of high school, therefore
EVALUATING COLLEGE READINESS 45
this number gives the exact amount of students for 11
th
grade. OTL for high school summative
mathematics students were determined by dividing the number of students participating in high
school summative mathematics by the number of 11
th
grade English Language students.
Proficiency success rates data for algebra 2 students were determined by dividing the number of
students proficient in algebra 2 by the number of 11
th
grade English Language students.
Proficiency success rates data for high school (summative) mathematics students were
determined by dividing the number of students proficient in high school (summative)
mathematics by the number of 11
th
grade English Language students.
After completing the OTL analysis for all three high schools, the researcher completed
the same for the remaining African American and White students in LAUSD by taking the
number of students who participated in the algebra 2 district-wide exam and dividing it by the
number of students in 11
th
grade. Then, the researcher calculated the opportunity to learn for high
school summative mathematics by dividing the number of students who participated in high
school summative mathematics district-wide by the total number of students in the 11
th
grade.
Next, proficiency success rates were calculated by dividing the number of students who are
proficient in algebra 2 district-wide by the number of students in the 11
th
grade district-wide.
Finally, the researcher calculated proficiency by taking the number of students who are proficient
in high school summative mathematics district-wide and dividing it by the number of students in
the 11
th
grade district-wide. Correlation significance was determined by applying Cohen’s d
results. The level of significance used to accept or reject the hypothesis will be set at .05 level.
EVALUATING COLLEGE READINESS 46
Analytic Framework
Only descriptive analyses were conducted with an emphasis on means, standard
deviations and Cohen’s d to measure effect size. For Cohen’s d, the conventional standards will
be used: .2 small effect; .5 medium effect; and .8 large effect.
Limitations
There may have been several threats to validity that may arise in a quantitative study. An
experimental study is designed to eliminate probable rationales that can manipulate or change
the effect of a study. There are two types of threats that can invalidate a study: (a) internal
threats, (b) external threats, and (c) statistical conclusion (Creswell, 2014).
Threats to Internal Validity
Internal threats to validity permit the researcher exposed existing concerns as these relate
to the experimental procedures, treatments, and experiments of the participants and data
collected that could affect the outcomes of the study (Creswell, 2014). Selection of participants
for the study were nonrandomized due to the fact that all students were enrolled in 11
th
grade
English, which is a possible internal threat. Therefore, all students were tested on the same
course material regardless of IEP, general education, advanced placement or honors courses.
Hence, to compensate for the threat, the study considered opportunity to learn and proficiency
rates. Since the statistical baseline was established by defining success as scoring at Basic Level
or higher, the study can evaluate the treatment more efficiently (Creswell, 2014).
Threats to External Validity
The researcher created external threats to validity by giving incorrect implications in
terms of participants, settings, or previous or future situations (Creswell, 2014). Due to the
unique history of each high school, external threats to validity did present themselves. For
47 EVALUATING COLLEGE READINESS
example, WPHS did not receive an Academic Performance Index (API) from 2006 to 2008;
therefore, conclusions predicting success is not possible (WPHS. 2013). Also, DHS academic
performance index may have been affected when the school was applying to become a Public
School Choice 3.0 institution. During the application process many veteran faculty members
transferred to other high schools (Public School Choice, 2009). Finally, in 2014, CHS was
reconstituted and reopened as a comprehensive magnet high school, which may have led to
manipulation of its performance data due to the removal of teachers and attrition of students.
Threats to Statistical Conclusion Validity
Statistical conclusion validity occurs when the researcher draws inaccurate inferences due to
comprised statistical information (Creswell, 2014). In this study, inaccuracies may have been
caused by low attendance or participation rates and by students who were not tested in the
correct grade level or course. Also, information coded incorrectly by human error could lead to
discrepancies in statistical results.
Summary
In this study, the statistical implications may have limited generalizations due to each
school’s population and setting in comparison to LAUSD as a whole. The distinctiveness of
WPHS, DHS, and CHS may contribute to a variety of factors such as percentages of students of
different ethnicities who are tested any given year and the policies of both the district and the
individual school. In addition, the threats of validity may include teacher attrition, curriculum,
department assessments, and individual characteristics of teachers.
EVALUATING COLLEGE READINESS 48
CHAPTER FOUR: RESULTS AND DISCUSSION
The purpose of this study is to examine the role mathematics courses play in college
readiness of African American high school students. Specifically, the study examines the
opportunity to learn and proficiency success rates of African American versus white students in
predominately African American urban schools in Los Angeles Unified School District. The
following eight research questions guides this study:
1. To what extent do the three target schools (Washington, Dorsey and Crenshaw) differ
on African American opportunity-to-learn and proficiency in Algebra II and Summative High
School Mathematics for the years 2003 – 2013?
2. To what extent do the three target schools (Washington, Dorsey and Crenshaw) differ
on African American opportunity-to-learn and proficiency in Algebra II and Summative High
School Mathematics when compared to African Americans attending other schools in LAUSD
for the years 2003 – 2013?
3. To what extent do the three target schools (Washington, Dorsey and Crenshaw) differ
on African American opportunity-to-learn and proficiency in Algebra II and Summative High
School Mathematics when compared to Whites attending other schools in LAUSD for the years
2003 – 2013?
4. To what extent if any, has African-American opportunity-to-learn and proficiency
changed from 2003 to 2013 at the three target schools (Washington, Dorsey and Crenshaw)
compared to the change for Whites and African-Americans attending other schools in LAUSD
over the same time period?
EVALUATING COLLEGE READINESS 49
Findings
To answer research questions 1-3, descriptive statistics of opportunity-to-learn and
proficiency success rates were computed. Inferential statistics were not computed because a
population rather than a sample was analyzed. Cohen’s d (mean difference/pooled standard
deviation) were computed for the effect sizes (Cohen, 1988). Note for Cohen’s d = 2*t / ),
where t = t-statistic and df = degrees of freedom (Thalheimer & Cook, 2002). Cohen’s d
standards for small, medium, and large effects are .20, .50, and .80 respectively.
To answer research question 4, four multiple linear regressions (Thalheimer & Cook,
2002) were performed. The four dependent variables, two were opportunity-to-learn and
proficiency for algebra and the other two were opportunity-to-learn and proficiency for
summative high school mathematics (HS). For each regression model, the independent variables
were school and year. The interaction effect of school and year was also included in each model.
For each model, the coefficient of year represented the estimated yearly change of the dependent
variable. The interaction effect of school and year was used to determine if the effect of year
varied by school, i.e., the interaction effect of school and year was used to determine if the yearly
change of the dependent variable for the three target schools was statistically significantly
different from the yearly change of the dependent variable for LAUSD.
All analyses were conducted using SAS 9.4 (Agresti, 2002).
Analysis Results for Research Question 1
Table 1 and Table 2 shows the descriptive statistics of opportunity-to-learn and
proficiency success rates for Algebra II and HS Summative for AA students in Crenshaw,
Susan Miller Dorsey, and Washington Preparatory.
EVALUATING COLLEGE READINESS 50
Research question 1 “To what extent do the three target schools (Washington, Dorsey and
Crenshaw) differ on African American opportunity-to-learn and proficiency in Algebra II and
Summative High School Mathematics for the years 2003 – 2013?”
Table 1
Descriptive Statistics of Opportunity-to-Learn for Algebra II and HS Summative
Mean (SD) Min Max
Opportunity-to-learn, Algebra II Crenshaw 0.45 (0.12) 0.22 0.67
Dorsey 0.42 (0.13) 0.23 0.62
Washington Preparatory 0.46 (0.11) 0.32 0.69
Opportunity-to-learn, HS
Summative
Crenshaw 0.08 (0.02) 0.00 0.12
Dorsey 0.15 (0.05) 0.07 0.23
Washington Preparatory 0.23 (0.10) 0.10 0.39
Note: N = 11 for each school year, SD = standard deviation
Table 2
Descriptive Statistics of Proficiency for Algebra II and HS Summative
Mean (SD) Min Max
Proficiency, Algebra II Crenshaw 0.00 (0.00) 0.03 0.01
Dorsey 0.01 (0.01) 0.00 0.05
Washington Preparatory 0.00 (0.00) 0.00 0.00
Proficiency, HS Summative Crenshaw 0.01 (0.01) 0.00 0.02
Dorsey 0.01 (0.01) 0.00 0.02
Washington Preparatory 0.00 (0.01) 0.00 0.03
Note: N = 11 for each school year, SD = standard deviation
There were no large differences in opportunity-to-learn for Algebra II for AA students in
Crenshaw, Susan Miller Dorsey, and Washington Preparatory (Washington Prep). The range all
student that tested in Algebra 2 was from a low of 0.42 at Susan Miller Dorsey to a high 0.46 at
Washington Preparatory. There were small differences in opportunity-to-learn for HS
Summative for AA students in Crenshaw, Susan Miller Dorsey, and Washington Prep. The
range was from a low 0.08 at Crenshaw to a high 0.23 at Washington Prep.
EVALUATING COLLEGE READINESS 51
The analysis results of RQ1 are shown in Tables 1 and 2. In particular, opportunity-to-
learn HS Summative was highest Washington Prep (M = 0.23) in comparison to Crenshaw (M =
0.08) and Dorsey (M = 0.15). Opportunity-to-learn also was higher for Washington Prep (M =
0.23) in comparison to Crenshaw (M = 0.08).
There were no differences in proficiency success rates for Algebra II AA and HS
Summative students in Crenshaw, Dorsey, and Washington Prep. The range for Algebra II and
HS Summative were from a low .00 at Crenshaw to a high .01 at Dorsey.
Table 3 and Table 4 show the effect size of opportunity-to-learn and proficiency success
rates for Algebra II and HS Summative for AA students in Crenshaw, Dorsey, and Washington
Prep.
Table 3
Effect Size Analysis for Opportunity-to-learn
Cohen’s d
Opportunity-to-learn
Algebra II
Crenshaw(.45) vs. Dorsey(.42) 0.27
Crenshaw(.45) vs. Washington Preparatory(.46) 0.08
Dorsey(.42) vs. Washington Preparatory (.46) 0.36
Opportunity-to-learn,
HS Summative
Crenshaw(.08) vs. Dorsey(.15) 1.81
Crenshaw(.08) vs. Washington Preparatory (.23) 2.05
Dorsey(.15) vs. Washington Preparatory (.23) 0.97
Table 4
Effect Size Analysis for Proficiency Success Rates
Cohen’s d
Proficiency, Algebra II Crenshaw(.00) vs. Dorsey(.01) 0.51
Crenshaw(.00) vs. Washington Preparatory (.00) 0.78
Dorsey(.01) vs. Washington Preparatory (.00) 0.68
Proficiency, HS
Summative
Crenshaw(.01) vs. Dorsey(.01) 0.15
Crenshaw(.01) vs. Washington Preparatory 00) 0.43
Dorsey(.01) vs. Washington Preparatory (.00) 0.27
EVALUATING COLLEGE READINESS 52
For Algebra II opportunity-to-learn in Table 3, one finding was that there were small
effects (.27 and .36) when Dorsey (M = 0.42) was contrasted with Crenshaw (M = 0.45) and
Washington Prep (M = 0.46). Another finding was that all the differences between the three
schools on opportunity-to-learn HS Summative were large according to Cohen’s d from .97 to
2.05. Specifically, students that were tested in HS Summative opportunity-to-learn was highest
in Washington Prep (M = 0.23), second highest in Dorsey (M = 0.15) and lowest in Crenshaw
(M = 0.42). All of the differences were substantial.
As discussed above, proficiency success rates in Algebra II and HS Summative were
extremely low (range equal zero percent to one percent). Because effect sizes are based on the
assumption of normality the data in Table 4 are difficult to interpret and thus no interpretation
will be attempted.
Analysis Results for Research Question 2
Table 5 and Table 6 shows the descriptive statistics of opportunity-to-learn and
proficiency success rates for Algebra II and HS Summative for AA students in Crenshaw,
Dorsey, Washington Preparatory, and all African American students in LAUSD.
Research question 2 “To what extent do the three target schools (Washington, Dorsey and
Crenshaw) differ on African American opportunity-to-learn and proficiency success rates in
Algebra II and Summative High School Mathematics when compared to African Americans
attending other schools in LAUSD for the years 2003-2013.”
EVALUATING COLLEGE READINESS 53
Table 5
Descriptive statistics of Opportunity-To-Learn for Algebra II and HS Summative
Mean (SD) Min Max
Opportunity-to-learn, Algebra II Crenshaw 0.45 (0.12) 0.22 0.67
Dorsey 0.42 (0.13) 0.23 0.62
Washington Preparatory 0.46 (0.11) 0.32 0.69
LAUSD AA 0.32 (0.04) 0.25 0.38
Opportunity-to-learn, HS
Summative
Crenshaw 0.08 (0.02) 0.00 0.12
Dorsey 0.15 (0.05) 0.07 0.23
Washington Preparatory 0.23 (0.10) 0.10 0.39
LAUSD AA 0.15 (0.03) 0.12 0.20
Note: N = 11 for each school year, SD = standard deviation, AA = African-American
Table 6
Descriptive statistics of Proficiency Success Rates for Algebra II and HS Summative
Mean (SD) Min Max
Proficiency, Algebra II Crenshaw 0.00 (0.00) 0.03 0.01
Dorsey 0.01 (0.01) 0.00 0.05
Washington Preparatory 0.00 (0.00) 0.00 0.00
LAUSD AA 0.01 (0.003) 0.003 0.01
Proficiency, HS
Summative
Crenshaw 0.01 (0.01) 0.00 0.02
Dorsey 0.01 (0.01) 0.00 0.02
Washington Preparatory 0.00 (0.01) 0.00 0.03
LAUSD AA 0.02 (0.01) 0.01 0.04
Note: N = 11 for each school year, SD = standard deviation, AA = African-American
There were no large differences in opportunity-to-learn for Algebra II for AA students in
Crenshaw, Susan Miller Dorsey, and Washington Preparatory. However in all students tested in
Algebra 2, there was fairly large difference in opportunity-to-learn for Algebra II for AA
students in LAUSD. The range was from a low.32 at LAUSD to a high .46 at Washington
Preparatory.
The analysis results of RQ2 are shown in Table 5 and Table 6. Particularly, opportunity-
to-learn for Algebra II was lower for LAUSD AA (M = 0.32) in comparison to Crenshaw (M =
EVALUATING COLLEGE READINESS 54
0.45), Susan Miller Dorsey (M = 0.42), and Washington (M = 0.46). Most importantly LAUSD
AA students were exposed to Algebra II are a rate of 1 or more percentage points lower than the
three target schools.
LAUSD AA (M = 0.15) had higher opportunity-to-learn for HS Summative in
comparison to Crenshaw (M = 0.08) and AA LAUSD and Dorsey had equal opportunity-to-learn
scores (M = 0.15). However, LAUSD AA (M = 0.15) has a lower opportunity-to-learn for HS
Summative than Washington Preparatory (M = 0.23).
Similarly to RQ1, there were negligible differences in proficiency success rates for
Algebra II AA and HS Summative students in Crenshaw, Susan Miller Dorsey, Washington
Preparatory, and AA in LAUSD. The range for Algebra II was from a low .00 at Crenshaw
and Washington to a high .01 at LAUSD and Dorsey. Further, HS Summative were from a
low .00 at Washington to a high .02 at LASUD.
Table 7 and Table 8 shows the effect size of opportunity-to-learn and proficiency
success rates for Algebra II and HS Summative for AA students in Crenshaw, Susan Miller
Dorsey, Washington Preparatory, and all AA in LAUSD.
Table 7
Effect Size Analysis for Opportunity-To-Learn
Cohen’s d
Opportunity-to-learn,
Algebra II
LAUSD AA(.32) vs. Crenshaw(.45) 1.61
LAUSD AA(.32) vs. Dorsey(.42) 1.16
LAUSD AA(.32) vs. Washington Preparatory (.46) 1.89
Opportunity-to-learn,
HS Summative
LAUSD AA(.15)vs. Crenshaw(.08) 2.67
LAUSD AA(.15) vs. Dorsey(.15) 0.06
LAUSD AA(.15) vs. Washington Preparatory (.23) 1.08
EVALUATING COLLEGE READINESS 55
Table 8
Effect Size Analysis for Proficiency Success Rates
Cohen’s d
Proficiency, Algebra II LAUSD AA(.01) vs. Crenshaw(.00) 1.91
LAUSD AA(.01) vs. Dorsey(.01) 0.08
LAUSD AA(.01) vs. Washington Preparatory (.00) 2.85
Proficiency,
HS Summative
LAUSD AA(.02) vs. Crenshaw(.01) 1.46
LAUSD AA(.02) vs. Dorsey(.01) 1.53
LAUSD AA(.02)vs. Washington Preparatory (.00) 1.79
For Algebra II opportunity-to-learn in Table 7, one finding was all the differences
between LAUSD and all three high schools were large according to Cohen’s d from 1.16 to
1.89. Particularly, Algebra II was highest in Washington Prep (M = 0.46) and the lowest in
Dorsey (M = 0.42). All of the differences were significant. The second finding for HS
Summative opportunity-to-learn was between LAUSD and Dorsey were small effects .06
when LAUSD (.32) was contrasted with Dorsey (M = 0.15). A third finding was that all the
differences between LAUSD and Crenshaw and Washington Prep schools on opportunity-to-
learn HS Summative were large according to Cohen’s d from 1.08 to 2.67. Specifically, the
HS Summative opportunity-to-learn LAUSD difference was highest in Crenshaw (effect =
2.67) and lowest in Dorsey (effect = .06). All of the differences were substantial.
For Algebra II in Table 8, one finding was a small effect size of .08 between on
proficiency success rates in Algebra II in LAUSD (M = 0.01) and Dorsey (M = 0.01).
Another finding were between LAUSD Crenshaw and Washington Prep schools were large
according to Cohen’s d from 1.91 to 2.85. Particularly, Algebra II was highest in
Washington Prep (M = 0.00) and the lowest in Crenshaw (M = 0. 00). All of the differences
were significant.
EVALUATING COLLEGE READINESS 56
Analysis Results for Research Question 3
Table 9 and Table 10 shows the means and standard deviation of opportunity-to-learn and
proficiency success rates for Algebra II and HS Summative for AA students in Crenshaw,
Dorsey, Washington Preparatory, and all white students in LAUSD.
Research question 3 “To what extent do the three target schools (Washington, Dorsey and
Crenshaw) differ on African American opportunity-to-learn and proficiency in Algebra II and
Summative High School Mathematics when compared to Whites attending other schools in
LAUSD for the years 2003-2012?”
Table 9
Descriptive statistics of Opportunity-To-Learn for Algebra II and HS Summative
Mean (SD) Min Max
Opportunity-to-learn, Algebra II Crenshaw 0.45 (0.12) 0.22 0.67
Dorsey 0.42 (0.13) 0.23 0.62
Washington Preparatory 0.46 (0.11) 0.32 0.69
LAUSD W 0.28 (0.03) 0.24 0.32
Opportunity-to-learn, HS Summative Crenshaw 0.08 (0.02) 0.00 0.12
Dorsey 0.15 (0.05) 0.07 0.23
Washington Preparatory 0.23 (0.10) 0.10 0.39
LAUSD W 0.35 (0.05) 0.30 0.44
Note: N = 11 for each school, SD = standard deviation, W = White
Table 10
Descriptive statistics of Proficiency Success Rates for Algebra II and HS Summative
Mean (SD) Min Max
Proficiency, Algebra II Crenshaw 0.00 (0.00) 0.03 0.01
Dorsey 0.01 (0.01) 0.00 0.05
Washington Preparatory 0.00 (0.00) 0.00 0.00
LAUSD W 0.04 (0.01) 0.02 0.05
Proficiency, HS Summative Crenshaw HS 0.01 (0.01) 0.00 0.02
Dorsey 0.01 (0.01) 0.00 0.02
Washington Preparatory 0.00 (0.01) 0.00 0.03
LAUSD W 0.18 (0.04) 0.13 0.24
Note: N = 11 for each school, SD = standard deviation, W = White
EVALUATING COLLEGE READINESS 57
Opportunity-to-learn for Algebra II was lower for LAUSD White students (M = 0.28) in
comparison to AA students in Crenshaw (M = 0.45), Dorsey (M = 0.42), and Washington Prep
(M = 0.46). Opportunity-to-learn for HS Summative was higher for LAUSD White students (M
= 0.35) than in comparison to AA students in Crenshaw (M = 0.08), Dorsey (M = 0.15), and
Washington Prep (M = 0.23).
Proficiency for Algebra II was higher for LAUSD White students (M = 0.04) than AA
students in relationship to Crenshaw (M = 0.00), Dorsey (M = 0.01), and Washington Prep (M =
0.00). Proficiency for HS Summative was higher for LAUSD White students (M = 0.18) in
contrast to AA students in Crenshaw (M = 0.01), Dorsey (M = 0.01), and Washington Prep (M =
0.00).
Table 11 and Table 12 shows the effect size of opportunity-to-learn and proficiency
success rates for Algebra II and HS Summative for AA students in Crenshaw, Susan Miller
Dorsey, Washington Preparatory, and all White students in LAUSD.
Table 11
Effect Size Analysis for Opportunity-To-Learn
Cohen’s d
Opportunity-to-learn,
Algebra II
LAUSD W(.28) vs. Crenshaw(.45) 2.06
LAUSD W(.28) vs. Dorsey(.42) 1.57
LAUSD W(.28) vs. Washington Preparatory (.46) 1.64
Opportunity-to-learn,
HS Summative
LAUSD W(.35) vs. Crenshaw(.08) 7.62
LAUSD W(.35) vs. Dorsey(.15) 4.23
LAUSD W(.35) vs. Washington Preparatory (.23) 6.66
EVALUATING COLLEGE READINESS 58
Table 12
Effect Size Analysis for Proficiency Success Rates
Cohen’s d
Proficiency, Algebra II LAUSD W(.04) vs. Crenshaw(.00) 5.95
LAUSD W(.04) vs. Dorsey(.01) 2.72
LAUSD W(.04) vs. Washington Preparatory (.00) 2.41
Proficiency, HS
Summative
LAUSD W(.18) vs. Crenshaw(.01) 6.16
LAUSD W(.18) vs. Dorsey(.01) 6.18
LAUSD W(.18) vs. Washington Preparatory (.00) 6.27
For Algebra II opportunity-to-learn in Table 11, all the differences between LAUSD and
all the three high schools were large according to Cohen’s d from 1.57 to 2.06. Specifically,
Algebra II effects size was highest in Crenshaw (M = 0.45), second highest in Washington Prep
(M = 0.46), and lowest in Dorsey (M = 0.42). It bears repeating that opportunity-to-learn for
Algebra II was higher in the three target schools.
Similarly, on opportunity-to-learn HS Summative the effects size were extremely large
according to Cohen’s d from 4.23 to 6.66. HS Summative opportunity-to-learn HS Summative
was more than four standard deviation higher for White students than AA students in LAUSD.
All of the differences were significant. Meaning whites' students still are given more exposure
to learning advance college level mathematics, such as statistics or AP calculus than African
American students in LAUSD.
Correspondingly, For Algebra II proficiency success rates in Table 12, all the differences
between LAUSD whites and all the three target high schools were large according to Cohen’s d
from 2.41 to 5.95. Algebra II was highest in Crenshaw (M = 0.00), second highest in Dorsey (M
= 0.01) and lowest in Washington Prep (M = 0.00). Equally, on opportunity-to-learn HS
Summative were extremely large according to Cohen’s d from 6.16 to 6.27. Specifically, HS
Summative opportunity-to-learn HS Summative was highest in Washington Prep (M = 0.00),
EVALUATING COLLEGE READINESS 59
second highest in Dorsey (M = 0.01), and lowest in Crenshaw (M = 0.01). All of the differences
were substantial.
Analysis Results for Research Question 4
Research question 4 “To what extent if any, has African-American opportunity-to-learn and
proficiency changed from 2003 to 2013 at the three target schools (Washington, Dorsey and
Crenshaw) compared to the change for Whites and African-Americans attending other schools in
LAUSD over the same time period?”
Figure 1. Opportunity-To-Learn for Algebra II from 2003 to 2012 for African American students
at the three target schools (Crenshaw HS, Dorsey HS, and Washington Prep HS).
EVALUATING COLLEGE READINESS 60
Table 13
Opportunity-To-Learn for Algebra II Growth Over Time
Target Schools Post-Score Pre-Score Change
Crenshaw HS 0.5053 0.2203 0.2850
Dorsey HS 0.5346 0.2337 0.3009
Washington Prep HS 0.6894 0.4985 0.1909
Figure 1 shows the opportunity-to-learn (OTL) for Algebra II from 2003 to 2012 for
African American students at the three target schools (Crenshaw, Dorsey, and Washington Prep)
demonstrate constant growth over time. Crenshaw HS had the largest increase between the three
schools in 2006 and 2007. However, 2008 Crenshaw decreased in OTL during an administration
change. Similarly, Washington Prep HS had a constant growth over time with the exception of
2009 the same year there was an administration change. Dorsey HS also had a decrease in OTL
for Algebra II in 2006 during the change of administration. Table 13 shows that during a period
of ten years all three schools OTL for Algebra II increased, Dorsey HS having the highest .3009,
Crenshaw HS at .2850, and Washington Prep HS at 0.1909.
EVALUATING COLLEGE READINESS 61
Figure 2. Opportunity-To-Learn for Algebra II from 2003 to 2012 for African American students
at the three target schools (Crenshaw HS, Dorsey HS, and Washington Prep HS) and LAUSD
AA.
Table 14
Opportunity-To-Learn for Algebra II Growth Over Time
Target Schools Post-Score Pre-Score Change
Crenshaw HS 0.5053 0.2203 0.2850
Dorsey HS 0.5346 0.2337 0.3009
Washington Prep HS 0.6894 0.4985 0.1909
LAUSD AA 0.3846 0.2512 0.1334
Figure 2 shows the opportunity-to-learn (OTL) for Algebra II three target schools had a
greater constant growth over time than all LAUSD AA students overall. LAUSD AA did display
EVALUATING COLLEGE READINESS 62
constant growth over a ten year period. Figure 2 displays that LAUSD AA students from 2006
to 2009 there was no growth. Table 14 shows that during a period of ten years Dorsey HS had a
difference of .1764 higher than LAUSD AA. Crenshaw HS had a difference of .1675 and Washington
Prep HS at .0575 higher than LAUSD AA.
Figure 3. Opportunity-To-Learn for Algebra II from 2003 to 2012 for African American students
at the three target schools (Crenshaw HS, Dorsey HS, and Washington Prep HS) and LAUSD
Whites.
Table 15
Opportunity-To-Learn for Algebra II Growth Over Time
Target Schools Post-Score Pre-Score Change
Crenshaw HS 0.5053 0.2203 0.2850
Dorsey HS 0.5346 0.2337 0.3009
Washington Prep HS 0.6894 0.4985 0.1909
LAUSD W 0.2891 0.2361 0.0530
EVALUATING COLLEGE READINESS 63
Figure 3 shows the opportunity-to-learn (OTL) for Algebra II three target schools had a
greater constant growth over time than all LAUSD White students overall. LAUSD Whites did
display constant growth over times until 2010. Figure 2 displays that LAUSD Whites students
from 2010 to 2012 there displayed a slight decrease. Table 15 shows that during a period of ten
years Dorsey HS had a difference of .2479 higher than LAUSD Whites. Crenshaw HS had a
difference of .2320 and Washington Prep HS at .1379 higher than LAUSD
Whites.dif
Figure 4. Opportunity-To-Learn for HS Summative from 2003 to 2012 for African American
students at the three target schools (Crenshaw HS, Dorsey HS, and Washington Prep HS).
EVALUATING COLLEGE READINESS 64
Table 16
Opportunity-To-Learn for HS Summative Growth Over Time
Figure 4 shows the opportunity-to-learn (OTL) for HS Summative from 2003 to 2012 for
African American students at the three target schools (Crenshaw, Dorsey, and Washington Prep)
demonstrate growth and reduction over a ten-year period. Dorsey HS displayed the most
constant growth minimum drop in 2006 and 2011. Washington Prep HS significant growth from
2008 to 2009 and from 2010 to 2011. Additionally, Washington Prep HS had a major deduction
from 2009 to 2010 and from 2011 to 2012. However, Crenshaw HS had the least amount of
growth over the ten year period. In the year 2011 Crenshaw displayed a major decrease in 2011.
Table 16 shows that during a period of ten years all three schools OTL for HS Summative
increased, Washington Prep HS having the highest .1722, Dorsey HS at .1340, and Crenshaw HS
at .0289.
Target Schools Post-Score Pre-Score Change
Crenshaw HS 0.0930 0.0641 0.0289
Dorsey HS 0.2264 0.0924 0.1340
Washington Prep HS 0.2879 0.1157 0.1722
EVALUATING COLLEGE READINESS 65
Figure 5. Opportunity-To-Learn for HS Summative from 2003 to 2012 for African American
students at the three target schools (Crenshaw HS, Dorsey HS, and Washington Prep HS) and
LAUSD AA.
Table 17
Opportunity-To-Learn for HS Summative Growth Over Time
Target Schools Post-Score Pre-Score Change
Crenshaw HS 0.0930 0.0641 0.0289
Dorsey HS 0.2264 0.0924 0.1340
Washington Prep HS 0.2879 0.1157 0.1722
LAUSD AA 0.1963 0.1228 0.0735
Figure 5 shows the opportunity-to-learn (OTL) for HS Summative from 2003 to 2012 for
African American students at Dorsey HS and Washington Prep HS demonstrate growth higher
than LAUSD AA students. Figure 5 also displays that LAUSD AA students’ demonstrated
constant growth over a ten-year period. LAUSD AA students’ highest growth was in 2011 and
EVALUATING COLLEGE READINESS 66
2012. Table 17 displays Washington Prep HS growth over time difference was higher than
LAUSD AA students’ at.0987 and Dorsey HS difference was higher at .0605. LAUSD AA
students’ growth over time difference was higher than Crenshaw HS at .0446
Figure 6. Opportunity-To-Learn for HS Summative from 2003 to 2012 for African American
students at the three target schools (Crenshaw HS, Dorsey HS, and Washington Prep HS) and
LAUSD Whites.
Table 18
Opportunity-To-Learn for HS Summative Growth Over Time
Target Schools Post-Score Pre-Score Change
Crenshaw HS 0.0930 0.0641 0.0289
Dorsey HS 0.2264 0.0924 0.1340
Washington Prep HS 0.2879 0.1157 0.1722
LAUSD W 0.4237 0.3111 0.1126
EVALUATING COLLEGE READINESS 67
Figure 6 shows the opportunity-to-learn (OTL) for HS Summative from 2003 to 2012 for
LAUSD Whites had a constant growth over all three target schools. However Washington Prep
HS OTL was higher in 2010 and 2012 students at Dorsey HS and Washington Prep HS
demonstrate growth higher than LAUSD AA students. Figure 5 also displays that LAUSD AA
students’ demonstrated constant growth over a ten-year period. LAUSD AA students’ highest
growth was in 2009 and 2011. Although LAUSD Whites demonstrated constant growth Table
18 displays Washington Prep HS growth over time difference was higher than LAUSD Whites
students’ at .0596 and Dorsey HS difference was higher at .0214. LAUSD White students’
growth over time difference was higher than Crenshaw HS at .0837.
Figure 7. Proficiency Success Rate for Algebra II from 2003 to 2012 for African American
students at the three target schools (Crenshaw HS, Dorsey HS, and Washington Prep HS).
EVALUATING COLLEGE READINESS 68
Table 19
Proficiency Success Rate for Algebra II Growth Over Time
Target Schools Post-Score Pre-Score Change
Crenshaw HS 0.0067 0.0000 0.0067
Dorsey HS 0.0481 0.0070 0.0411
Washington Prep HS 0.0000 0.0000 0.0000
Figure 7 displays the proficiency success rate for Algebra II from 2003 to 2012 for
African American students at the three target schools (Crenshaw HS, Dorsey HS, and
Washington Prep HS) did not have significant proficiency success rate over a ten-year period,
with the exception of Dorsey HS in 2012. Crenshaw HS displayed minimum growth, but not
significant, while Washington Prep HS had no growth in ten years. Table 19 shows that within
the ten year period there was no proficiency success rate, Dorsey HS having the highest at .0411,
due to new leadership and permeant staffing, Crenshaw HS at .0067, and Washington Prep HS at
.0000.
EVALUATING COLLEGE READINESS 69
Figure 8. Proficiency Success Rate for Algebra II from 2003 to 2012 for African American
students at the three target schools (Crenshaw HS, Dorsey HS, and Washington Prep HS) and
LAUSD AA.
Table 20
Proficiency Success Rate for Algebra II Growth Over Time
Target Schools Post-Score Pre-Score Change
Crenshaw HS 0.0067 0.0000 0.0067
Dorsey HS 0.0481 0.0070 0.0411
Washington Prep HS 0.0000 0.0000 0.0000
LAUSD AA 0.0115 0.0050 0.0065
Figure 8 displays the proficiency success rate for Algebra II from 2003 to 2012 for
African American students at the three target schools (Crenshaw HS, Dorsey HS, and
Washington Prep HS) and LAUSD African American students were slightly higher than African
EVALUATING COLLEGE READINESS 70
American students in the three targeted schools over a ten-year period, with the exception of
2012. LAUSD highest performance was in 2010. Table 20 shows during a ten year period
Dorsey HS had the highest difference at .0346 and Crenshaw HS difference at .0002 than higher
LAUSD AA. However, LAUSD AA had a difference of .0065 higher than Washington Prep HS
Figure 9. Proficiency Success Rate for Algebra II from 2003 to 2012 for African American
students at the three target schools (Crenshaw HS, Dorsey HS, and Washington Prep HS) and
LAUSD Whites.
EVALUATING COLLEGE READINESS 71
Table 21
Proficiency Success Rate for Algebra II Growth Over Time
Target Schools Post-Score Pre-Score Change
Crenshaw HS 0.0067 0.0000 0.0067
Dorsey HS 0.0481 0.0070 0.0411
Washington Prep HS 0.0000 0.0000 0.0000
LAUSD W 0.0408 0.0378 0.0030
Figure 9 displays the proficiency success rate for Algebra II from 2003 to 2012 for
African American students at the three target schools (Crenshaw HS, Dorsey HS, and
Washington Prep HS) and LAUSD White students were higher than African American students
in the three targeted schools over a ten-year period. LAUSD highest performance was in
2009. Table 21 shows during a ten year period Dorsey HS difference at .0381 and Crenshaw
HS difference at .0037 than higher LAUSD Whites. However, LAUSD Whites had a
difference of .0030 higher than Washington Prep HS.
EVALUATING COLLEGE READINESS 72
Figure 10. Proficiency Success Rate for HS Summative from 2003 to 2012 for African American
students at the three target schools (Crenshaw HS, Dorsey HS, and Washington Prep HS).
Table 22
Proficiency Success Rate for HS Summative Growth Over Time
Figure 10 displays the proficiency success rate for Algebra II from 2003 to 2012 for
African American students at the three target schools (Crenshaw HS, Dorsey HS, and
Washington Prep HS) demonstrated no consistency in increasing growth over time. Crenshaw
HS and Dorsey HS displayed growth for one year but would decline the next year. Crenshaw HS
Target Schools Post-Score Pre-Score Change
Crenshaw HS 0.0059 0.0072 -0.0013
Dorsey HS 0.0249 0.0111 0.0138
Washington Prep HS 0.0058 0.0000 0.0058
EVALUATING COLLEGE READINESS 73
had two major growth in its proficiency success rates in 2007 and 2010. Dorsey HS
demonstrated growth, but the school’s highest growth was in 2012 similar to the school’s
Algebra II proficiency success rates. Washington Prep HS did not make gains from 2005 to
2007, afterwards it showed growth from 2008 to 2009, before a significant drop in 2010.
Table 22 shows that within the ten -year period there was no proficiency success rate, Dorsey
HS having the highest at .0138, Washington Prep HS at .0058, and Crenshaw HS demonstrated
a negative growth at -.0013.
Figure 11. Proficiency Success Rate for HS Summative from 2003 to 2012 for African American
students at the three target schools (Crenshaw HS, Dorsey HS, and Washington Prep) and
LAUSD AA.
EVALUATING COLLEGE READINESS 74
Table 23
Proficiency Success Rate for HS Summative Growth Over Time
Target Schools Post-Score Pre-Score Change
Crenshaw HS 0.0059 0.0072 -0.0013
Dorsey HS 0.0249 0.0111 0.0138
Washington Prep HS 0.0058 0.0000 0.0058
LAUSD AA 0.0334 0.0123 0.0211
Figure 11 displays the proficiency success rate for Algebra II from 2003 to 2012 for
African American students at the three target schools (Crenshaw HS, Dorsey HS, and
Washington Prep HS) and LAUSD AA students were higher than African American students in
the three targeted schools over a ten-year period. LAUSD demonstrated constant growth over
ten years, with the exception of 2011. Table 23 shows during a ten year period LAUSD AA had
the highest change at .0211. LAUSD AA difference at .0224 higher than Crenshaw HS, higher
EVALUATING COLLEGE READINESS 75
than Washington Prep HS at .0153, and Dorsey HS at. 0073.
Figure 12. Proficiency Success Rate for HS Summative from 2003 to 2012 for African American
students at the three target schools (Crenshaw HS, Dorsey HS, and Washington Prep) and
LAUSD Whites.
Table 24
Proficiency Success Rate for HS Summative Growth Over Time
Target Schools Post-Score Pre-Score Change
Crenshaw HS 0.0059 0.0072 -0.0013
Dorsey HS 0.0249 0.0111 0.0138
Washington Prep HS 0.0058 0.0000 0.0058
LAUSD W 0.2373 0.1493 0.0880
EVALUATING COLLEGE READINESS 76
Figure 12 displays the proficiency success rate for Algebra II from 2003 to 2012 for
African American students at the three target schools (Crenshaw HS, Dorsey HS, and
Washington Prep HS) and LAUSD White students were higher than African American students
in the three targeted schools over a ten-year period. LAUSD demonstrated constant growth
over ten years, with the exception of 2011. Table 24 shows during a ten year period LAUSD
AA had the highest change at .0880. LAUSD AA difference at .0893 higher than Crenshaw HS,
higher than Washington Prep HS at .0822 and Dorsey HS at. 0742.
Discussion
The descriptive statistical results indicate there were small differences between the
African American students at the three targeted schools (Crenshaw, Dorsey, and Washington
Prep) in regards to opportunity-to-learn (OTL) and proficiency success rates in Algebra II and
Summative High School Mathematics, but no significant differences. The data displays that
AA in the target schools do take Algebra II and Summative High School Mathematics in the
11
th
, but are not successful in reaching proficiency. In addition, OTL and proficiency success
rates were too low to interpret using Cohen’s d.
Outcomes using descriptive statistics for the African American students of the three
target schools did not differ significantly to Los Angeles Unified School District (LASUD)
African American students with OTL and proficiency success rates in Algebra II and
Summative High School Mathematics. As stated previously LAUSD AA do take Algebra II
and Summative High School Mathematics in the 11
th
, but are not successful in reaching
proficiency, similar to the three target schools. However, using Cohen’s d there was a small
effect size between proficiency success rates among the AA students in LAUSD and Dorsey
HS. Additionally, LAUSD AA students Cohen’s d effect size was significantly larger than
EVALUATING COLLEGE READINESS 77
Dorsey HS and Washington Prep HS AA students. There Cohen’s d results were significant as
the results pertain to effect size.
Similarly, the descriptive statistical results show LAUSD White students were lower
than the African American students of the three target schools in OTL. Due to the NCLB
legislation schools located in urban communities, such as the three targeted schools college
level mathematics offering did increase (Linn, Baker, & Betebenner, 2002). Therefore, the data
indicates whites students are either not taking advantage of participating in Algebra II in the
11
th
grade or have already taken Algebra II prior to the 11
th
grade. Which suggest why LAUSD
Whites students’ success proficiency rates were higher than AA students for the three target
schools. Additionally, the data exhibited through Cohen’s d that OPT was higher in three
targeted schools versus LAUSD White students in Algebra II. HS Summative OPT was higher
for LAUSD White students that AA students in the three target schools. This shows more
LAUSD White students have been afforded the opportunity to complete more college ready
courses than AA in the target schools. However LAUSD White students are still displaying
higher proficiency success rates versus the AA students in the target schools.
However when considering how well AA students in the three target schools performed
over a ten-year period compared to LAUSD AA and whites the data exhibits that there has
been growth. The AA in the target schools shows that students are given the opportunity to
complete college readiness courses in both Algebra II and HS Summative Mathematics. Each
of the target schools did experience lack of growth when faced with administrative transitions.
However each school was able to stabilize a constant growth once personnel changes were
completed. Dorsey experienced the most growth in Algebra II in OTL, while Washington Prep
should growth in OTL in HS Summative Mathematics. Even when compared to LAUSD AA
EVALUATING COLLEGE READINESS 78
and Whites students the three schools demonstrated growth in OTL in Algebra II. But when the
matched to LAUSD Whites in HS Summative Mathematics the target schools were
considerably lower with the exception of Washington Prep HS. Meaning there were more
students completing higher level college readiness courses that LAUSD Whites.
On the other hand the target schools exhibited little or no growth in proficiency success
rates in Algebra II or HS Summative Mathematics. The only significant growth over time was
with Dorsey HS. Similarly, LAUSD AA students did not show substantial growth over a period
of time in proficiency success rates. Conversely, LAUSD White students did show a significant
achievement gap in proficiency success rates in Algebra II and HS Summative Mathematics.
In conclusion, the data did reveal that there has been academic progress made among AA
students in the district. Also, more AA students have increase the enrollment in completing
college readiness courses. This would suggest the target schools are making an assertive effort
to offer and prepare AA students for post-secondary education. Even so, the lack of proficiency
success rates would propose AA students are lacking in understanding, applying, and evaluating
academic performance standardized examinations. Additionally, the quality of instruction
provide in the targeted schools could play a major role on why success rates are still considerable
lower than white students in LAUSD.
EVALUATING COLLEGE READINESS 79
CHAPTER FIVE: SUMMARY, DISCUSSIONS AND RECOMMENDATIONS
The purpose of this study was to examine the longitudinal role mathematics courses play
in college readiness of African American high school students. Specifically, the study was to
examine the Opportunity-to-Learn (OTL) and proficiency success rates of African American
versus white students in predominately and other African American in Los Angeles Unified
School District. The quantitative study compared OTL and proficiency success rates by each
academic year from 2003-2013. There theoretical framework describes aspects of how college
readiness courses prepare students for post-secondary success. In addition, analytical
framework interprets the given data of California Standardized Testing (CST) on how it is used
to determine OTL and proficiency success rates through descriptive statistics and regression
statistics in chapter 4. The conclusions given are in retort to the research questions developed
and asked in Chapter 1. Consequentially, the conclusions have given incite to certain
recommendations concerning the participation, teaching and success of African American
students success in college readiness courses in urban high schools.
For decades the nation has been faced with a growing academic achievement gap
between African Americans and Whites in urban public school systems. This challenge is
evident in test scores, participation in college readiness courses, and completing college.
Although African Americans have been able to make significant strides in academic achievement
the gap between the two ethnicities still remains (Lips & Marshall, 2008). In efforts to close the
academic achievement gap schools have been mandated to follow federal and state
accountability guidelines. In 2002 NCLB was implemented starting with kindergarten through
high school. The overall goal of NCLB was to ensure all students nationwide would receive an
inclusive, responsive, and fair education. NCLB was also designed to balance the achievement
EVALUATING COLLEGE READINESS 80
of students of different ethnicities, second-language learners, students with disabilities, and
students of low socio-economic status. The four components of NCLB (1) stronger
accountability for results, (2) more choices for parents of children from disadvantaged
backgrounds, (3) greater local control and flexibility for states and school districts in the use of
federal funds, and (4) emphasis on research-based teaching methods that have been proven to
work ((US Department of Education, 2003). In addition, NCLB requires all states curriculum be
taught by highly qualified teachers.
The purpose of this study was to examine the role mathematics courses play in college
readiness of African American high school students. Specifically, the study examines the
opportunity to learn and proficiency success of African American versus white students in
predominately African American urban schools in Los Angeles Unified School District.
The study acquired data through online resources from the CDE, DataQuest and from
LAUSD’s website. This study gauges to what extent, if any, high school mathematics
curriculum (algebra 2, trigonometry/math analysis, statistics, and Advance Placement Calculus
AB/BC) provide access to and success within post-secondary education for African Americans at
WPHS, DHS, and CHS. The data collected will allow for a longitudinal study over a ten year
span from 2003 to 2013. The longitudinal data calculated the opportunity-to-learn and
proficiency rates by using EXCEL and SPSS. The data used determined the growth of
opportunity-to-learn and proficiency rates and significant academic achievement.
Summary of Methodology
In order to compare OTL and proficiency success rates a descriptive statistical analysis
was utilized. For each descriptive statistical computation the variables used were number of
participants in each subject and the 11
th
grade. English Language totals are used as the
EVALUATING COLLEGE READINESS 81
denominator, due to the fact all students in the state of California must take English all four years
of high school, therefore this number gives the exact amount of students for 11
th
grade.
Inferential statistics were not computed because a population rather than a sample was analyzed.
Cohen’s d (mean difference/pooled standard deviation) were computed for the effect sizes
(Cohen, 1988). Cohen’s d standards for small, medium, and large effects are .20, .50, and .80
respectively. This quasi-experiment indicated African American students in the targeted schools
opportunity-to-learn had higher rates success than other African American and White student in
the district. Although students participated in college readiness course African American
students’ proficiency success rates were considerably lower than White students in LAUSD, but
comparable to other African American students in the district.
To compare the change for Whites and African-Americans attending other schools in
LAUSD over the same time period a multiple linear regressions (Thalheimer & Cook, 2002)
were performed. For each regression model, the independent variables were school and year. The
interaction effect of school and year were also included in each model. For each model, the
coefficient of year represented the estimated yearly change of the dependent variable. The
interaction effect of school and year was used to determine if the effect of year varied by school,
i.e., the interaction effect of school and year was used to determine if the yearly change of the
dependent variable for the three target schools was statistically significantly different from the
yearly change of the dependent variable for LAUSD.
EVALUATING COLLEGE READINESS 82
Research Questions
Based on the results of this study following was analyzed by the four research questions.
1. To what extent did the three target schools (Washington, Dorsey and Crenshaw) differ
on African American opportunity-to-learn and proficiency success rates in Algebra II and
Summative High School Mathematics for the years 2003 – 2012?
2. To what extent did the three target schools (Washington, Dorsey and Crenshaw) differ
on African American opportunity-to-learn and proficiency success rates in Algebra II and
Summative High School Mathematics when compared to African Americans attending other
schools in LAUSD for the years 2003-2012?
3. To what extent did the three target schools (Washington, Dorsey and Crenshaw) differ
on African American opportunity-to-learn and proficiency success rates in Algebra II and
Summative High School Mathematics when compared to Whites attending other schools in
LAUSD for the years 2003-2012?
4. To what extent if any, has African-American opportunity-to-learn and proficiency
success rates change from 2003 to 2012 at the three target schools (Washington, Dorsey and
Crenshaw) compared to the change for Whites and African-Americans attending other schools in
LAUSD over the same time period?
Discussion of Results
Target Schools
The Los Angeles Unified School District is a predominately Hispanic. The African
American population is less than 10%. However the targeted schools selected for this study all
have an average of 56.4% African American population. Crenshaw High School (CHS) Susan
Miller Dorsey High School (DHS), and George Washington Preparatory High School (WPHS),
EVALUATING COLLEGE READINESS 83
have the largest populations of African American students in LAUSD (Los Angeles Unified
School District, 2015). Although, Hispanics are the majority population within the district, the
African American, white and other populations are underrepresented in LAUSD (Los Angeles
Unified School District, 2015). Therefore, the data used demonstrated college readiness between
African American students in comparison with all other African Americans and white students in
LAUSD.
Target Schools and Opportunity-To-Learn
The descriptive statistics of OTL results for Research Question 1 for Algebra II and HS
Summative for AA students in Crenshaw, Susan Miller Dorsey, and Washington Preparatory
were one of the most interested finding in this study. Similarly, there were small differences in
OTL for HS Summative for AA students in Crenshaw, Susan Miller Dorsey, and Washington
Prep.
In addition, the descriptive statistics for OTL shows there were no large differences
between Crenshaw, Dorsey, Washington Preparatory, and all African American students in
LAUSD in Algebra II and HS Summative. Most importantly LAUSD AA students were exposed
to Algebra II and advanced courses. The rate of 1 or more percentage points lower than the three
target schools.
Therefore, the results display that African American student are given the opportunity to
enroll and participate in college readiness courses (Conley, 2013, Curry, 2015, & Tierney, 2015).
Data demonstrates over a ten year period participation increased. Hence, research based on
NCLB policy has supported and helped to increase participation in all students regardless of
ethnicity and socio-economic status (Johnston & Viadero, 2000; Ladner & Burke, 2010; and
Lotkowski, Robbins, & Noeth, 2004).
EVALUATING COLLEGE READINESS 84
Finally, the findings of (Nichols, Glass, & Berliner, 2005) found that since NCLB was
implemented college readiness opportunities in all ethnicities have increased, therefore, the
achievement gap has not closed, but remained the same. Furthermore, in order states that as long
as all students are afforded the same opportunities individual subgroups data will continue to
show growth (Nichols, Glass, & Berliner, 2005).
Target Schools and Proficiency Success Rates
In contrast to OTL there was no differences in proficiency success rates for Algebra II
AA and HS Summative students in Crenshaw, Dorsey, and Washington Prep. The range for
Algebra II and HS Summative were from a low .00 at Crenshaw to a high .01 at Dorsey. In
addition, the effect size of proficiency success rates for Algebra II and HS Summative for AA
students in Crenshaw, Dorsey, and Washington Prep. For Algebra II.
Findings indicated that although African American students do participate in college
readiness courses proficiency success rates are very low. Majority students scored below basic
or lower. Although research has shown an increase in participation, there has not been
significant gains in becoming proficiency rates (Moore & Slate, 2008 and Mason, 2010).
Target Schools versus LAUSD African American Students Opportunity-To-Learn Rates
Conversely, the target schools versus LAUSD AA students’ opportunity-to-learn rates
did not provide large differences. There were some variation ranging from a low of 0.42 at DHS
and a high .046 at WPHS in the opportunity-to-learn rates for Algebra II. However, the analysis
results of RQ2 are shown in Table 5 and Table 6. Particularly, opportunity-to-learn for Algebra
II was lower for LAUSD AA (M = 0.32) in comparison to Crenshaw (M = 0.45), Susan Miller
Dorsey (M = 0.42), and Washington (M = 0.46). Most importantly LAUSD AA students were
EVALUATING COLLEGE READINESS 85
exposed to Algebra II are a rate of 1 or more percentage points lower than the three target
schools.
Target Schools versus LAUSD African American Students Proficiency Success Rates
Similarly to RQ1, there were negligible differences in proficiency success rates for
Algebra II AA and HS Summative students in Crenshaw, Susan Miller Dorsey, Washington
Preparatory, and AA in LAUSD. The range for Algebra II was from a low .00 at Crenshaw and
Washington to a high .01 at LAUSD and Dorsey. Further, HS Summative were from a low .00
at Washington to a high .02 at LASUD.
The effect size of opportunity-to-learn and proficiency success rates for Algebra II and
HS Summative for AA students in Crenshaw, Susan Miller Dorsey, Washington Preparatory, and
all AA in LAUSD.
For Algebra II opportunity-to-learn in Table 7, one finding was all the differences
between LAUSD and all three high schools were large according to Cohen’s d from 1.16 to 1.89.
Particularly, Algebra II was highest in Washington Prep (M = 0.46) and the lowest in Dorsey (M
= 0.42). All of the differences were significant. The second finding for HS Summative OTL
was between LAUSD and Dorsey were small effects .06 when LAUSD (.32) was contrasted with
Dorsey (M = 0.15). A third finding was that all the differences between LAUSD and Crenshaw
and Washington Prep schools on opportunity-to-learn HS Summative were large according to
Cohen’s d from 1.08 to 2.67. Specifically, the HS Summative opportunity-to-learn LAUSD
difference was highest in Crenshaw (effect = 2.67) and lowest in Dorsey (effect = .06). All of
the differences were substantial.
Target Schools versus LAUSD White Students Opportunity-To-Learn Rates
EVALUATING COLLEGE READINESS 86
Research question 3 shows means and standard deviation of opportunity-to-learn and
proficiency success rates for Algebra II and HS Summative for AA students in Crenshaw,
Dorsey, Washington Preparatory, and all white students in LAUSD.
Opportunity-to-learn for Algebra II was lower for LAUSD White students (M = 0.28) in
comparison to AA students in Crenshaw (M = 0.45), Dorsey (M = 0.42), and Washington Prep
(M = 0.46). Opportunity-to-learn for HS Summative was higher for LAUSD White students (M
= 0.35) than in comparison to AA students in Crenshaw (M = 0.08), Dorsey (M = 0.15), and
Washington Prep (M = 0.23).
Target Schools versus LAUSD White Students Proficiency Success Rates
Proficiency for Algebra II was higher for LAUSD White students (M = 0.04) than AA
students in relationship to Crenshaw (M = 0.00), Dorsey (M = 0.01), and Washington Prep (M =
0.00). Proficiency for HS Summative was higher for LAUSD White students (M = 0.18) in
contrast to AA students in Crenshaw (M = 0.01), Dorsey (M = 0.01), and Washington Prep (M =
0.00).
Correspondingly, all the differences between LAUSD whites and all the three target high
schools were large according to Cohen’s d from 2.41 to 5.95. Algebra II was highest in
Crenshaw (M = 0.00), second highest in Dorsey (M = 0.01) and lowest in Washington Prep (M =
0.00). Equally, on opportunity-to-learn HS Summative were extremely large according to
Cohen’s d from 6.16 to 6.27. Specifically, HS Summative opportunity-to-learn HS Summative
was highest in Washington Prep (M = 0.00), second highest in Dorsey (M = 0.01), and lowest in
Crenshaw (M = 0.01). All of the differences were substantial.
The proficiency success rate for Algebra II from 2003 to 2012 for African American
students at the three target schools (Crenshaw HS, Dorsey HS, and Washington Prep HS) and
EVALUATING COLLEGE READINESS 87
LAUSD White students were higher than African American students in the three targeted
schools over a ten year period. LAUSD demonstrated constant growth over ten years, with the
exception of 2011. Table 24 shows during a ten year period LAUSD AA had the highest change
at .0880. LAUSD AA difference at .0893 higher than Crenshaw HS, higher than Washington
Prep HS at .0822 and Dorsey HS at. 0742.
Increasing African American Students Proficiency Rates in College Readiness Courses
Closing the achievement gap for African American students is by in no means and easy
or small feat, given the history of how society has impeded in the advancement of African
Americans as a whole. Since 1969 the National Assessment of Educational Progress (NAEP)
has recorded data representing the age groups of 9, 13, and 17 olds to detect the progression or
lack of progression in closing the achievement gap (National Center for Education Statistics,
2000). The NAEP also gauges trends in student performance amongst other ethnic subgroups.
NAEP notice a racial achievement gap beginning in the early 1970’s. In the 1980’s the racial
gap began to decrease, but by the 1990’s the racial gap began to increase again (National Center
for Education Statistics, 2000). Therefore, when the Federal government began to take action in
closing the gap in the early 2000’s reversing the ever increasing racial gap had already began to
be an overwhelming mission.
Despite the gallant intent of various educational initiatives to increase all students’
educational achievement, there has been limited progress (Lotkowski, Robbins, & Noeth, 2004).
In an effort, to close the achievement gap of African American students is to consider the quality
of instruction and cultural relevancy within the curriculum with emphasis in the mathematics to
begin to support academic achievement (Sampson & Garrison-Wade, 2011). Implementing
culturally relevant lessons that encourage oral traditions, kinetic rhythms, important historical
EVALUATING COLLEGE READINESS 88
findings, and academic field trips that support students understanding and relevancy in
America’s history encourage students to improve in their academic learning (Sampson and
Garrison-Wade, 2011and Tinto, 2006). Additionally, research proved that African American
students’ progression increased when implementing culturally relevant lessons with teachers that
cared and connected with cultural relevancy (Sampson and Garrison-Wade, 2011and Tinto,
2006).
Likewise in closing the achievement gap strategies such as, reducing the disproportionate
number of African Americans in special education, enrolling more African American students in
more challenging classes, such as math analysis, trigonometry, or AP calculus, providing
teachers with professional developments that are more culturally relevant and diverse to African
American students learning, and giving monetary incentives for educators who or want teach in
urban communities (Lotkowski, Robbins, & Noeth, 2004). Another strategy for supporting
closing the achievement gap for African American students is having it become a part of the
overall accountability in schools The Report Card (Lotkowski, Robbins, & Noeth, 2004).
Some of these strategies are presumably more effective than others.
Hence many of the suggested strategies will support the academic progression of African
American students reducing the achievement gap, however it will also benefit other ethnic
subgroups as well. (Lotkowski, Robbins, & Noeth, 2004; Sanoff, 2006; Tinto, 2005, and 2006)
Implications for General Practice
The findings from this study have implications for increasing college readiness through
mathematics for African Americans. The following are two proposals of practical implications
for a line of research on the professional development of cultural relevancy. The current study
provides evidence of the need for? An alternative form of professional development that
improves
EVALUATING COLLEGE READINESS 89
teachers’ ability to foster mathematics achievement for students attending a low-performing
urban high school. As the country has become more reliant on technology in both mathematics
and science, its demands to fill STEM careers grows, thus placing pressure on American learning
institutions to produce capable, mathematically, and scientifically proficient individuals to fill
positions.
First, to implement more professional development of cultural relevancy contexts,
teachers are charged as being the implementers of curriculum and instructional reform with
accountability (Riddle, 2012; Shaul & Ganson, 2005). This was the case for assessing students
in college readiness mathematics beginning with algebra 2. This perspective of African
Americans students closing the achievement gap was not clearly observed in the study. In
addition, it was detected there was capacity of performing well in algebra 2, but not in higher
level mathematics courses, such as trigonometry, math analysis, or advanced placement
calculus. The perspective reflects analysis here can be interpreted as teachers have a good
context of teaching African Americans students in mathematics to some degree, by some type
of reform is needed to reach closing the achievement gap in higher college readiness math
courses. By taking on a perspective of teachers as inquirers of practice, professional
development can address the complex situation of teacher cognition and practice that reflect
cultural relevancy.
Similarly, there is evidence with the data to suggest instruction strategies within the
mathematics curriculum do not have a strong impact on teacher’s ability to foster mathematics
academic performance in the higher mathematics college readiness courses. The data suggests
teachers need to be allotted more time to plan, collaborate, and implement classroom strategies
that benefit all students in more challenging curriculum (Riddle, 2012 and Shaul & Ganson,
EVALUATING COLLEGE READINESS 90
2005). Teachers need more time to interpret, assess, and transform the instructional reforms
that will support a more rigorous curriculum that will lead to closing the achievement gap.
Limitations
In this study, internal and external threats may have limited generalizations from the
population and setting studied to other populations and settings. There is a uniqueness in the
population, particularly Los Angeles Unified School District. Its uniqueness is contributed by
various factors such as African American students are not the majority, high levels of attrition
from both teachers and students, redistricting by Crenshaw High School, and Susan Miller
Dorsey participating in school choice.
Recommendation for Further Research
This study focused on data from CST ELA from 2003-2013 when NCLB policies were
still being implemented and enforced. Since then, the state of California has adopted the
Common Core standards, assessing 11
th
grade students with the California Assessment of
Student Performance and Progress (CAASPP), also known as Smarter Balanced.
At this time accountability not being reinforced in the educational system educational
system in California. Federal and state funding has been consistently reduced annually. Even
so, the curriculum, standards, and assessments are still as rigorous, if not more. Apart from
the accountability, standards-based curriculum, instruction, and assessments, there are some
issues that stand out in with the new assessment that is, instruction and testing for African
American students are still not connecting on a cultural relevancy, despite research on cross-
curriculum teaching and best practices (Nikolakakos & Shuch, 2012).
The recommendations from this study would be to strengthen how Los Angeles
Unified School District implements cultural relevancy with in the curriculum, not only
EVALUATING COLLEGE READINESS 91
mathematics. It is a model that has been proven to be effective in closing the achievement gap.
This model where students from all ethnicities can participate while learning. Additionally,
ensuring African Americans have access to highly qualified teachers in the urban schools,
updated resources such as technology, and textbooks. Lastly creating an accountability
system that collates to students academic is needed and SMART goals to support academic
success.
A recommendation for future research would be to conduct a compressive comparative
study between U.S. schools and European schools that have parallel issues regarding
achievement gap between ethnicities. Finally, conduct a quantitative study that determines the
cause of the increase or decrease in the achievement gap is due to instruction, curriculum, or
assessments.
Conclusion
The African American student population will continue to decrease within the Los
Angeles Unified School District. However, an academic achievement gap between African
American students and their peers will still be in existence (Gandara, 2009; Hall, 2007; Reardon
& Galindo, 2009; Stanton-Salazar, 1997; and Valencia, 2002). Without including teacher
professional development that implements cross-cultural curriculum, in addition to effective
academic strategies and interventions to reverse ever growing academic achievement gap with
African American students, statistical data will continue to reflect an increasing achievement gap
(Stanton-Salazar, 1997; Valencia, 2002).
EVALUATING COLLEGE READINESS 92
References
Abraham, R. A., Slate, J. R., Saxon, D. P., & Barnes, W. (2014). College-Readiness in Math: A
Conceptual Analysis of the Literature. Research & Teaching in Developmental
Education, 30(2).
Agresti, A. (2002). Categorical data analysis. Hoboken, NJ: John Wiley & Sons, Inc.
Anonymous (2008), No Child Left Behind: Growth Models Ensure Improved Education for All
Students, 3-62.
Anonymous (2007), No Child Left Behind Education Should Clarify Guidance and Address
Potential Compliance Issues for Schools in Corrective Action and Restructuring Status,
1-64.
Balduf, M. (2009). Underachievement among college students. Journal of advanced academics,
20(2), 274-294.
Becker, B. E., & Luthar, S. S. (2002). Social-emotional factors affecting achievement outcomes
among disadvantaged students: Closing the achievement gap. Educational psychologist,
37(4), 197-214.
Becker, J. P., & Jacob, B. (2000). The politics of California school mathematics: The anti-reform
of 1997-99. Phi Delta Kappan, 81(7), 529-537.
Burris, C. C., & Welner, K. G. (2005). Closing the achievement gap by detracking. Phi Delta
Kappan, 86(8), 594-598.
Bush, G. W. (2001). No Child Left Behind.
California of Department of Education (CDE). (2015, September 19). California Department of
Data and Statistics. Retrieved from http://ayp.cde.ca.gov/reports.
EVALUATING COLLEGE READINESS 93
Cohen J. (1988). Statistical Power Analysis for the Behavioral Sciences. Lawrence Erlbaum
Associates.
Cokley, K. (2003). What do we know about the motivation of African American students?
Challenging the" anti-intellectual" myth. Harvard Educational Review, 73(4), 524-558.
College Board. (2015, May 1). AP Central of AP Exams. Retrieved from
http://apcentral.collegeboard.com/apc/public/exam/index.html.
Conley, D. T., Drummond, K. V., de Gonzalez, A., Rooseboom, J., & Stout, O. (2011). Reaching
the Goal: The Applicability and Importance of the Common Core State Standards to
College and Career Readiness. Educational Policy Improvement Center (NJ1).
Conley, D. T. (2013). Getting ready for college, careers, and the Common Core: What every
educator needs to know. John Wiley & Sons. Creswell, J.W. (2014). Research design:
Qualitative, quantitative, and mixed methods approaches. Thousand Oaks, CA: Sage
Publications.
Curry, J. (2015). African Americans and Career and College Readiness. African American
Students’ Career and College Readiness: The Journey Unraveled, 1.
Ewing, M. (2006). The AP program and student outcomes: A summary of research
(College Board Research Report No. 2006-29). New York: The College Board.
Ford, D. Y., Grantham, T. C., & Whiting, G. W. (2008). Culturally and linguistically diverse
students in gifted education: Recruitment and retention issues. Exceptional Children,
74(3), 289-306.
Gardner, D. P., Larsen, Y. W., & Baker, W. (1983). A nation at risk: The imperative for
educational reform. Washington, DC: US Government Printing Office.
EVALUATING COLLEGE READINESS 94
Gardner, D. P. (1983). A nation at risk. Washington, DC: The National Commission on
Excellence in Education. US Department of Education.
Geiser, S., & Santelices, V. (2004). The role of advanced placement and honors courses in
college admissions. Expanding opportunity in higher education: Leveraging promise, 75-
113.
Hall, D., & Kennedy, S. (2006). Primary progress, secondary challenge. Education, 1.
Jobs for the Future. (2012). Retrieved from http://www.jff.org
Johnston, R. C., & Viadero, D. (2000). Unmet Promise: Raising Minority Achievement. The
Achievement Gap. Education Week, 19(27), n27.
Jorgens, M.A & Hoffman, J (2003), History of No Child Left Behind of 2001 (NCLB), Person,
2-7.
Ladner, M., & Burke, L. M. (2010). Closing the Racial Achievement Gap: Learning from
Florida's Reforms. Backgrounder. No. 2468. Heritage Foundation.
Larson, R. and Farber, B. (2003). Elementary Statistics. Upper Saddle River, NJ: Prentice-Hall,
Inc.
Le, C., & Frankfort, J. (2011). Accelerating College Readiness: Lessons from North Carolina's
Innovator Early Colleges. Jobs for the Future.
Los Angeles Unified School District 2013/2014 Local Education Agency Plan (CA Dept. of
Education). (2014). Retrieved from
achieve.lausd.net/cms/lib08…/107/…2013.2014%20plan%20final.pdf
Linn, R. L. (2000). Assessments and accountability. Educational researcher, 29(2), 4-16.
EVALUATING COLLEGE READINESS 95
Linn, R. L., Baker, E. L., & Betebenner, D. W. (2002). Accountability systems: Implications of
requirements of the no child left behind act of 2001. Educational Researcher, 31(6), 3-
16.
Lips, D., & Marshall, J. A. (2008). Transforming and Improving American Education: A Memo
to President-elect Obama. No. 7. Heritage Foundation.
Lotkowski, V. A., Robbins, S. B., & Noeth, R. J. (2004). The Role of Academic and Non-
Academic Factors in Improving College Retention. ACT Policy Report. American
College Testing ACT Inc.
Mason, J. C. (2010). The role of teacher in Advanced Placement (AP) access (Unpublished
doctoral dissertation). California State University, Sacramento, CA.
Mathis, W. J. (2010). The “Common Core” standards initiative: An effective reform tool.
Boulder and Tempe: Education and the Public Interest Center & Education Policy
Research Unit. Retrieved July, 29, 2010.
McGuinn, P., & Hess, F. (2005). Freedom from ignorance? The Great Society and the evolution
of the Elementary and Secondary Education Act of 1965. The great society and the high tide of
liberalism, 289-319.
McIntosh, S. (2012), State High School Exit Exams: A Policy in Transition, Center on Education
Policy, 2-49.
Mitchell, R. (2007). The Journal of Negro Education, 76(3), 519-520. Retrieved from
http://www.jstor.org.libproxy1.usc.edu/stable/40034597
Moore, G. W., & Slate, J. R. (2008). Who's taking the Advanced Placement courses and how are
they doing: A statewide two-year study. The High School Journal, 92(1), 56-67.
EVALUATING COLLEGE READINESS 96
Moses, R. P., & Cobb, C. E. (2001). Radical equations: Math literacy and civil rights. Beacon
Press (MA).
Nikolakakos, E., Reeves, J. L., & Shuch, S. (2012). An examination of the causes of grade
inflation in a teacher education program and implications for practice. College and
University, 87(3), 2-13.
National Center for Education Statistics. (2000). NAEP 1999: Trends in academic progress.

Washington, D.C.: U.S. Department of Education.
National Council of Teachers of Mathematics. Commission on Teaching Standards for School
Mathematics. (1991). Professional standards for teaching mathematics. Nat’l Council of
Teachers of Mathematics.
Nichols, S. L., Glass, G. V., & Berliner, D. C. (2005). High-Stakes Testing and Student
Achievement: Problems for the No Child Left Behind Act. Appendices. Education Policy
Research Unit.
Neter, J., Wasserman, W., and Kutner, M. (1990). Applied linear statistical models. Boston:
Richard D. Irwin, Inc.
Sampson, D., & Garrison-Wade, D. F. (2011). Cultural vibrancy: Exploring the preferences of
African American children toward culturally relevant and non-culturally relevant lessons.
The Urban Review, 43(2), 279-309.
Riddle, W. (2012). What Impact Will NCLB Waivers Have on the Consistency, Complexity and
Transparency of State Accountability Systems? Center on Education Policy.
Roderick, M., & Stoker G. (2010). Bringing Rigor to the Study of Rigor. Handbook of Research
on Schools, Schooling and Human Development, 216.
EVALUATING COLLEGE READINESS 97
Sanoff, A. P. (2006). A perception gap over students’ preparation. Chronicle of Higher
Education, 52(27), B9-B14.
SAS Institute Inc. (2013). SAS/STAT 13.2 User's Guide. Cary, NC: SAS Institute Inc.
Shaul, M. S., & Ganson, H. C. (2005). The No Child Left Behind Act of 2001: The Federal
government's role in strengthening accountability for student performance. Review of
research in education, 151-165.
Thalheimer, W., & Cook, S. (2002). How to calculate effect sizes from published research: A
simplified methodology. Work-Learning Research, 1-9.
Tienken, C. H., & Zhao, Y. (2010). Common core national curriculum standards: More
questions… and answers. AASA Journal of Scholarship and Practice, 6(4), 3-13.
Tierney, W. G., & Duncheon, J. C. (Eds.). (2015). The Problem of College Readiness. SUNY
Press.
Tinto, V. (2005). College student retention: Formula for student success. Greenwood Publishing
Group.
Tinto, V. (2006). Research and practice of student retention: What next?. Journal of College
Student Retention: Research, Theory & Practice, 8(1), 1-19.
United States. Congress. House. (1994). Improving America's schools act: Conference report to
accompany H.R. 6. (No. 103-761). Washington: U.S. G.P.O.
Walters, P. B. (2001). Educational access and the state: Historical continuities and discontinuities
in racial inequality in American education. Sociology of Education, 35-49.
Ward, N. L. (2006). Improving equity and access for low-income and minority youth into
institutions of higher education. Urban Education, 41(1), 50-70.
Washington Preparatory High School (WPHS). (2013, September). Focus on Learning
EVALUATING COLLEGE READINESS 98
Western Association of Schools and Colleges Mid Cycle Report 2013 Western
Accreditation of Schools and Colleges Report. Retrieved from
http://www.washingtonprep.org.
Wenglinsky, H. (2004). Closing the Racial Achievement Gap: The Role of Reforming
Instructional Practices. education policy analysis archives, 12(64), n64
Wijaya, A., van den Heuvel-Panhuizen, M., & Doorman, M. (2015). Opportunity-to-learn
context-based tasks provided by mathematics textbooks. Educational Studies in
Mathematics, 89(1), 41-65.
EVALUATING COLLEGE READINESS 99
APPENDIX A
2003-2012 CST Target Schools and LAUSD AA Algebra II
Year Crenshaw HS Dorsey HS Washington Prep HS
2003 0.2203 0.2337 0.4985
2004 0.3294 0.4052 0.3670
2005 0.3967 0.3125 0.3595
2006 0.5390 0.2678 0.4000
2007 0.5236 0.3571 0.4156
2008 0.3707 0.4286 0.4847
2009 0.4553 0.3850 0.3152
2010 0.4638 0.4842 0.4796
2011 0.5059 0.6000 0.4970
2012 0.5053 0.5346 0.6894

EVALUATING COLLEGE READINESS 100
APPENDIX B
2003-2012 CST Target Schools and LAUSD AA Algebra II
Year Crenshaw HS Dorsey HS
Washington Prep
HS LAUSD AA
2003 0.2203 0.2337 0.4985 0.2512
2004 0.3294 0.4052 0.3670 0.2545
2005 0.3967 0.3125 0.3595 0.2703
2006 0.5390 0.2678 0.4000 0.3159
2007 0.5236 0.3571 0.4156 0.3123
2008 0.3707 0.4286 0.4847 0.3156
2009 0.4553 0.3850 0.3152 0.3126
2010 0.4638 0.4842 0.4796 0.3385
2011 0.5059 0.6000 0.4970 0.3600
2012 0.5053 0.5346 0.6894 0.3846

EVALUATING COLLEGE READINESS 101
APPENDIX C
2003-2012 CST Target Schools and LAUSD White Algebra II
Year Crenshaw HS Dorsey HS
Washington Prep
HS LAUSD W
2003 0.2203 0.2337 0.4985 0.2361
2004 0.3294 0.4052 0.3670 0.2561
2005 0.3967 0.3125 0.3595 0.2361
2006 0.5390 0.2678 0.4000 0.2829
2007 0.5236 0.3571 0.4156 0.2908
2008 0.3707 0.4286 0.4847 0.2945
2009 0.4553 0.3850 0.3152 0.3219
2010 0.4638 0.4842 0.4796 0.3160
2011 0.5059 0.6000 0.4970 0.3024
2012 0.5053 0.5435 0.6894 0.2891

EVALUATING COLLEGE READINESS 102
APPENDIX D
2003-2012 CST Target Schools HS Summative
Year Crenshaw HS Dorsey HS Washington Prep HS
2003 0.0641 0.0924 0.1157
2004 0.0924 0.1634 0.1348
2005 0.0919 0.0982 0.1634
2006 0.1179 0.0711 0.1020
2007 0.1023 0.1333 0.1905
2008 0.0778 0.1316 0.1756
2009 0.1018 0.1690 0.3658
2010 0.0771 0.2105 0.2896
2011 0.0270 0.1850 0.3939
2012 0.0930 0.2264 0.2879

EVALUATING COLLEGE READINESS 103
APPENDIX E
2003-2012 CST Target Schools and LAUSD AA HS Summative
Year Crenshaw HS Dorsey HS Washington Prep HS LAUSD AA
2003 0.0641 0.0924 0.1157 0.1228
2004 0.0924 0.1634 0.1348 0.1294
2005 0.0919 0.0982 0.1634 0.1294
2006 0.1179 0.0711 0.1020 0.1231
2007 0.1023 0.1333 0.1905 0.1441
2008 0.0778 0.1316 0.1756 0.1273
2009 0.1018 0.1690 0.3658 0.1513
2010 0.0771 0.2105 0.2896 0.1532
2011 0.0270 0.1850 0.3939 0.1881
2012 0.0930 0.2264 0.2879 0.1963

EVALUATING COLLEGE READINESS 104
APPENDIX F
2003-2012 CST Target Schools and LAUSD W HS Summative
Year Crenshaw HS Dorsey HS Washington Prep HS LAUSD W
2003 0.0641 0.0924 0.1157 0.3111
2004 0.0924 0.1634 0.1348 0.305
2005 0.0919 0.0982 0.1634 0.3341
2006 0.1179 0.0711 0.1020 0.3371
2007 0.1023 0.1333 0.1905 0.3394
2008 0.0778 0.1316 0.1756 0.324
2009 0.1018 0.1690 0.3658 0.3137
2010 0.0771 0.2105 0.2896 0.3328
2011 0.0270 0.1850 0.3939 0.3688
2012 0.0930 0.2264 0.2879 0.4237

EVALUATING COLLEGE READINESS 105
APPENDIX G
2003-2012 CST Target School Proficiency Success Rates Algebra II
Year Crenshaw HS Dorsey HS Washington Prep HS
2003 0.0000 0.0070 0.0000
2004 0.0000 0.0000 0.0037
2005 0.0000 0.0000 0.0000
2006 0.0052 0.0000 0.0000
2007 0.0037 0.0000 0.0000
2008 0.0000 0.0043 0.0000
2009 0.0046 0.0000 0.0000
2010 0.0000 0.0097 0.0000
2011 0.0000 0.0060 0.0000
2012 0.0067 0.0481 0.0000

EVALUATING COLLEGE READINESS 106
Appendix H
2003-2012 CST Target School Proficiency Success Rates Algebra II
Year Crenshaw HS Dorsey HS Washington Prep HS LAUSD AA
2003 0.0000 0.0070 0.0000 0.0050
2004 0.0000 0.0000 0.0037 0.0051
2005 0.0000 0.0000 0.0000 0.0054
2006 0.0052 0.0000 0.0000 0.0032
2007 0.0037 0.0000 0.0000 0.0031
2008 0.0000 0.0043 0.0000 0.0063
2009 0.0046 0.0000 0.0000 0.0094
2010 0.0000 0.0097 0.0000 0.0135
2011 0.0000 0.0060 0.0000 0.0108
2012 0.0067 0.0481 0.0000 0.0115

EVALUATING COLLEGE READINESS 107
APPENDIX I
2003-2012 CST Target School and LAUSD W Proficiency Success Rates Algebra II
Year Crenshaw HS Dorsey HS Washington Prep HS LAUSD W
2003 0.0000 0.0070 0.0000 0.0378
2004 0.0000 0.0000 0.0037 0.0333
2005 0.0000 0.0000 0.0000 0.0236
2006 0.0052 0.0000 0.0000 0.0255
2007 0.0037 0.0000 0.0000 0.0320
2008 0.0000 0.0043 0.0000 0.0412
2009 0.0046 0.0000 0.0000 0.0515
2010 0.0000 0.0097 0.0000 0.0348
2011 0.0000 0.0060 0.0000 0.0484
2012 0.0067 0.0481 0.0000 0.0408

EVALUATING COLLEGE READINESS 108
APPENDIX J
2003-2012 CST Target School and LAUSD W Proficiency Success Rates HS Summative
Year Crenshaw HS Dorsey HS Washington Prep HS
2003 0.0072 0.0111 0.0000
2004 0.0000 0.0065 0.0040
2005 0.0027 0.0000 0.0000
2006 0.0000 0.0043 0.0000
2007 0.0121 0.0000 0.0000
2008 0.0044 0.0000 0.0035
2009 0.0130 0.0051 0.0073
2010 0.0238 0.0063 0.0058
2011 0.0035 0.0000 0.0000
2012 0.0059 0.0249 0.0058

EVALUATING COLLEGE READINESS 109
APPENDIX K
2003-2012 CST Target School and LAUSD W Proficiency Success Rates HS Summative
Year Crenshaw HS Dorsey HS
Washington Prep
HS LAUSD AA
2003 0.0072 0.0111 0.0000 0.0123
2004 0.0000 0.0065 0.0040 0.0116
2005 0.0027 0.0000 0.0000 0.0091
2006 0.0000 0.0043 0.0000 0.0123
2007 0.0121 0.0000 0.0000 0.0144
2008 0.0044 0.0000 0.0035 0.0178
2009 0.0130 0.0051 0.0073 0.0166
2010 0.0238 0.0063 0.0058 0.0306
2011 0.0035 0.0000 0.0000 0.0263
2012 0.0059 0.0249 0.0058 0.0334

EVALUATING COLLEGE READINESS 110
APPENDIX L
2003-2012 CST Target School and LAUSD W Proficiency Success Rates HS Summative
Year Crenshaw HS Dorsey HS Washington Prep HS LAUSD W
2003 0.0072 0.0111 0.0000 0.1493
2004 0.0000 0.0065 0.0040 0.1250
2005 0.0027 0.0000 0.0000 0.1503
2006 0.0000 0.0043 0.0000 0.1551
2007 0.0121 0.0000 0.0000 0.1561
2008 0.0044 0.0000 0.0035 0.1458
2009 0.0130 0.0051 0.0073 0.1600
2010 0.0238 0.0063 0.0058 0.1897
2011 0.0035 0.0000 0.0000 0.2176
2012 0.0059 0.0249 0.0058 0.2373

Abstract (if available)

Abstract African American students’ college readiness performance levels are decreasing all across the United States. In addition, there has been a decline in African American students’ preparation for college level classes, especially mathematics (Curry, 2015). The study will evaluate mathematics performance data using results from the California Standards Test in the target schools of Washington Preparatory High School, Susan Miller Dorsey High School, and Crenshaw High School. The schools selected have the largest enrollment of African American students in Los Angeles Unified School District. The study will give background information that defines success in obtaining college readiness. In addition, statistical experiments, descriptive statistics and linear regression for comparisons among high schools and with the district’s overall data. Finally, the research will discuss the implications of supporting African American students in increasing their college readiness performance levels to meet or exceed those of the district.

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University of Southern California Dissertations and Theses

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Asset Metadata

Creator Sims, Angeliques Sharee (author)

Core Title Evaluating college readiness through a mathematical lens: a quantitative study of predominately African American high schools in the Los Angeles Unified School District from 2003 – 2012

School Rossier School of Education

Degree Doctor of Education

Degree Program Education (Leadership)

Publication Date 05/13/2019

Defense Date 05/10/2019

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

Tag African American,college,High schools,LAUSD,mathematics,OAI-PMH Harvest

Format application/pdf (imt)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Picus, Lawrence (committee chair)

Creator Email angeliqs@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c89-170092

Unique identifier UC11661510

Identifier etd-SimsAngeli-7445.pdf (filename),usctheses-c89-170092 (legacy record id)

Legacy Identifier etd-SimsAngeli-7445.pdf

Dmrecord 170092

Document Type Dissertation

Format application/pdf (imt)

Rights Sims, Angeliques Sharee

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