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Motivational and academic outcomes in retained middle school students

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Motivational and academic outcomes in retained middle school students

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MOTIVATIONAL AND ACADEMIC OUTCOMES IN RETAINED MIDDLE
SCHOOL STUDENTS

by

Michelle L. Rodriguez

_________________________________________________________________

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

May 2012

Copyright 2012 Michelle L. Rodriguez

ii
ACKNOWLEDGEMENTS
This dissertation would not have been possible without the chair of my
dissertation committee, Dr. Kimberly Hirabayashi, and my dissertation committee
members, Dr. Helena Seli and Dr. Pedro Garcia whose guidance throughout the
research and writing of this dissertation was invaluable. My very deep gratitude is
also due to Dr. Nicolas Gorman and Dr. Holly Ferguson for their assistance with the
statistical analysis, suggestions, insights, and friendly advice and encouragement.
Special thanks go to my colleagues at Rossier School of Education at USC
for their support, collaboration and warm welcome into the Trojan Family. This
study would also not have been possible without the collaboration and support of the
school district and the contribution of students, parents, teachers and school
administration. I am grateful to them for their interest and participation.
In addition, I would like to thank those closest to me, whose presence helped
make the completion of my graduate work possible. My mother for her weekly
assistance in revising and editing my papers and dissertation. My father for inspiring
me to pursue my dream to become a superintendent and to join him as a member of
the Trojan Family. My parents have always encouraged me and shown absolute
confidence in me. I am grateful to them and amazed at their generosity. Thank you
for celebrating with me along the journey. I am also grateful to my sister and her
family for their love and support.
Finally, to my son, Daniel and husband, Juan, I am blessed to have your
unconditional support and love. I know that because of my educational pursuits you

iii
both have made some major sacrifices along the way. I love you both and cherish
the unbreakable bond that we share.

iv
TABLE OF CONTENTS
Acknowledgements ii
List of Tables v
Abstract viii
Chapter One: Introduction 1
Chapter Two: Literature Review 12
Chapter Three: Research Methodology 54
Chapter Four: Results 72
Chapter Five: Discussion 131
References 152
Appendices 158
Appendix A: Informed Consent for Non-Medical Research: 158
Parental Permission
Appendix B: Assent for Non-Medical Research: For Youth 162
(Ages 12-17)
Appendix C: Consentimento Informado Para Estudio No-Médico: 165
Permiso Parental
Appendix D: Self-Efficacy and Goal Orientation Survey 169
Appendix E: Self-Efficacy and Goal Orientation Survey (Spanish) 173

v
LIST OF TABLES
Table 3.1: Intermediate Schools Demographic Data 58
Table 3.2: Primary Data Sources 69
Table 4.1: Gender of Students, Student Sample of Motivational 74
Survey n=134
Table 4.2: Grade Retained, Student Sample of Motivational 74
Survey n=134
Table 4.3: Age of Students, Student Sample of Motivational 75
Survey n=134
Table 4.4: Language Proficiency of Students, Student Sample of 75
Motivational Survey n=134
Table 4.5: Gender of Students, Student Sample of Academic 76
Performance n=6397
Table 4.6: Grade Retained, Student Sample of Academic 76
Performance n=6397
Table 4.7: Language Proficiency of Students, Student Sample of 77
Academic Performance n=6397
Table 4.8: Significant Findings 78
Table 4.9: Summary of Hierarchical Linear Regression of Retention 80
Status on Goal Orientation (N = 117)
Table 4.10: Summary of Hierarchical Linear Regression of Retention 82
Status on Goal Orientation - Mastery Goal Subscale
Scores (N = 118)
Table 4.11: Summary of Hierarchical Linear Regression of Retention 84
Status on Goal Orientation—Skepticism About the Relevance
of School for Future Success (N = 117)
Table 4.12: Summary of Hierarchical Linear Regression of Grade of 87
Retention on Overall Goal Orientation (N = 28)

vi
Table 4.13: Summary of Hierarchical Linear Regression of Grade of 89
Retention on Academic Efficacy (N = 28)
Table 4.14: Summary of Hierarchical Linear Regression of Grade of 94
Retention on 7th Grade CST (N = 1455)
Table 4.15: Summary of Hierarchical Linear Regression of Grade of 96
Retention on CST 8th Scores (N = 1380)
Table 4.16: Summary of Hierarchical Linear Regression of Grade of 99
Retention on 8th Grade CMA Scores (N = 163)
Table 4.17: Summary of Hierarchical Linear Regression of Grade of 101
Retention on 7th Grade ELA Benchmark Scores (N = 1405)
Table 4.18: Summary of Hierarchical Linear Regression of Grade of 103
Retention on 8th Grade ELA Benchmark Scores (N = 1486)
Table 4.19: Summary of Hierarchical Linear Regression of Grade of 105
Retention on 7th Grade District Writing Prompt (N = 1491)
Table 4.20: Summary of Hierarchical Linear Regression of Grade of 107
Retention on 8th Grade District Writing Prompt (N = 1464)
Table 4.21: Summary of Hierarchical Linear Regression of Grade of 108
Retention on Cumulative GPA (N = 957)
Table 4.22: Summary of Hierarchical Linear Regression of Retention 111
Status on 7th Grade CST (N = 5740)
Table 4.23: Summary of Hierarchical Linear Regression of Retention 113
Status on 8th Grade CST (N = 5642)
Table 4.24: Summary of Hierarchical Linear Regression of Retention 115
Status on 8th Grade CMA (N = 317)
Table 4.25: Summary of Hierarchical Linear Regression of Retention 117
Status on 8th Grade CAPA (N = 66)
Table 4.26: Summary of Hierarchical Linear Regression of Retention 118
Status on 7th Grade CELDT (N = 2948)

vii
Table 4.27: Summary of Hierarchical Linear Regression of Retention 119
Status on 8th Grade CELDT (N = 2712)
Table 4.28: Summary of Hierarchical Linear Regression of Retention 121
Status on 7th Grade ELA Benchmark (N = 5640)
Table 4.29: Summary of Hierarchical Linear Regression of Retention 123
Status on 8th Grade ELA Benchmark (N = 5824)
Table 4.30: Summary of Hierarchical Linear Regression of Retention 125
Status on 7th Grade District Writing Prompt (N = 5766)
Table 4.31: Summary of Hierarchical Linear Regression of Retention 127
Status on 8th Grade District Writing Prompt (N = 5739)
Table 4.32: Summary of Hierarchical Linear Regression of Retention 129
Status on GPA (N = 3615)
Table 5.1: IV and DV with Proposed Assessments 150

viii
ABSTRACT
There is a relationship between self-efficacy, goal orientation, and academic
performance, which is based on the social cognitive theoretical framework and
substantiated by a large body of research. This study investigated the intersection
between retention and academic performance specifically with English Language
Learners and low socioeconomic populations. The purpose of this study was to
contribute to the small volume of existing literature that highlights the academic and
motivational affects of retention on middle school students from ethnic and low
socioeconomic backgrounds. Specifically, this study examined three key areas: (a)
to examine whether there is a relationship between the motivation of retained versus
nonretained students; (b) to examine whether retention timing is related to
motivation and academic performance; and (c) to examine whether retention has
differential effects on English Learner Language students.
A stratified purposeful sampling of over 125 seventh and eighth grade
students was drawn from four low-achieving intermediate schools in an urban district
in Southern California. The school district consists of a primary disadvantaged
population with 95% Hispanic, 85% Free and Reduced Lunch, 83% English Learners
and 58% of the parents not graduating high school. The four intermediate schools
were selected due to their homogeneity in relation to their minority, low
socioeconomic, English Language Learner, and Gifted and Talented populations.
The study used the hierarchical linear regression model with block entry of the
variables in Step 1. The variables of grade level, EL status and gender were entered

ix
as a group of variables to estimate the effect of the category of variables on the
outcome. The block entry of the variables also allowed the researcher to determine
whether particular variables explained statistically significantly more variance than
other variables. Within the Step 2, the variable of retention status or grade of
retention was entered last in the regression equation to isolate the unique variance for
that particular variable.
According to expectation, the hierarchical linear regression modeling
demonstrated that retention has a significant negative impact on both overall goal
orientation and academic performance with strong predictors of grade level and EL
status—RFEP. Contrary to expectations, retention was not linked to self-efficacy
and several subscales of goal orientation.
The study contributed to current research by highlighting the significance of
language proficiency and the grade of retention. It provided evidence that school
districts should change policies and instructional practices to more effectively serve
low socioeconomic, language learners and reduce the over use of retention as an
intervention measure. The incorporation of these key recommendations will
transform classrooms and the lives of students so they may reach their ultimate
potential.

1
CHAPTER ONE
INTRODUCTION
There is a relationship between self-efficacy, goal orientation, and academic
performance, which is based on the social cognitive theoretical framework and
substantiated by a large body of research (Bandura, 2006; Chin & Kameoka, 2002;
Eccles, 2009; Glienke & Burg, 2006; Rueda & Dembo, 1995; Usher & Pajares,
2008; Wigfield & Cambria, 2010; Zimmerman, 2000). This study investigated the
intersection between retention and academic performance specifically with English
Language Learners and low socioeconomic populations.
The historical background of retention began in the early 20
th
Century when
the school system within the United States retained nearly 50% of all students and
20% of all students left school by eighth grade (Frey, 2005). In 1992, 18% of African
American and American Indian students and 13% of Hispanic students in Grades K-
12 repeated a grade compared to 9% of Caucasian students (Bowman-Perrott,
Herrera, & Murry, 2010). Kaushal and Nepomnyaschy (2009) made similar findings
noting only 7% of White children repeated a grade while children in Black families
were twice as likely to repeat a grade 13% of the time and Hispanic children 10%.
The practice of requiring students to repeat a grade if they have not met academic
standards affects more than 2.4 million students of all ethnic and language
backgrounds in the United States each year resulting in additional educational
expenses exceeding $14 billion a year (Jimerson, 1999). There have been many
negative effects related to retention. Rumberger’s multi-level analysis found grade

2
retention to be the single most powerful predictor to influence a child’s decision to
leave school (Rumberger, 1995).
California has experienced a rising percentage of English Language Learners
with one out of four students in public schools in California being identified as an
English Language Learner and one out of three students in the elementary school
grades lacking proficiency in English (Gandara, Rumberger, Maxwell-Jolly, &
Callahan, 2003). By 2007, the state of California student population included 6.3
million English Language Learner students (EdSource, 2008). Although the
achievement scores of all American ethnic groups have risen in the last several years,
76% of all third grade English Language Learners still perform below grade level or
well below grade level in reading and 53% in mathematics (Bowman-Perrott et al.,
2010). In addition, Ford and Grantham (2003) found English Language Learners
were unrepresented in gifted education programs and highly overrepresented in low-
performing categories.
Furthermore, substantial research has shown that boys, minorities, and low
socioeconomic status students are significantly overrepresented among low-
achieving students that have been retained (Mantizocopulos & Neuharth-Pritchett,
1998). Today’s national overall rate of retention still hovers around 20%, which is an
increase of 40% in the last 20 years. Due to the increase in grade retentions, decline
in motivation during middle school, and the limited academic success of our
minority students, there is a call for new research (Frey, 2005).

3
Background of the Problem
The early part of the 20
th
Century created an educational system where nearly
50% of all students were retained and 20% of all students left school by eighth grade
(Frey, 2005). Due to the use of homogenous grouping in classrooms and the rise of
social promotion, retention rates declined from the 1930s through 1960s (Valencia,
2002). However, with the start of the standards-based reform, social promotion
received much scrutiny and was even outlawed in some states. By the mid 1980s,
many states were noting that social promotion caused the devaluing of education,
guaranteed that the students would always be behind, and caused a tremendous strain
on both teachers and students (King, 1999). During the 1990s, many states began to
establish statewide policies to end social promotion. Two states to pass such policies
were Ohio with Senate Bill 55 of 1992 and Colorado with the Basic Literacy Act of
1996. California followed suit with the passage of Assembly Bill 1626 and 1639 of
1998, which required districts to retain students who did not meet certain
performance criteria. Each California school board was required to establish
promotion standards for students in Grades 2, 3, and 4 as well as for promotion to
both middle school and high school (United States Department of Education, 1999).
Instead of social promotion or retention, the United States federal
government mandated all states to develop three key areas: (a) establish preschool
programs and early childhood literacy programs, (b) strengthen learning
opportunities through Response to Intervention, and (c) provide extended learning
time with after-school and summer school programs. In the recent years, Response to

4
Intervention (RtI) has received much attention and has been implemented to assist
with minimizing both social promotion and retention. RtI has been established as a
process that emphasizes the early identification of struggling students through an
objective and universal screening of all students in both the academic and the
emotional domains (Reynolds & Shaywitz, 2009). The key component of RtI, after
early identification, is the consistent progress monitoring of a student’s response to
the evidence-based interventions to determine if the intervention should be modified
or continued (Fletcher & Vaughn, 2009). With Response to Intervention programs
and strong core curriculum implementation, students should be provided with
systematic and targeted instruction that may decrease their achievement gap, thus
reducing retention.
Of concern, is the fact that White and middle-class students have served as
the majority in research on self-efficacy (Usher & Pajares, 2008). Alexander,
Entwisle, and Dauber (1994), Meisels and Liaw (1993), and Roderick (1995) studies
included only middle-class children from a variety of ethnic backgrounds.
Therefore, patterns related to low socio-economic and specific ethnic groups have
been minimized and in some cases intentionally excluded (Chin & Kameoka, 2002).
For example, all English Language Learners were excluded in Unrau and
Schlackman’s study 2006.
Given the widespread impact of retention on low socioeconomic and
minority students, it is important to address the issues of retention as it is linked to
possible effects on students’ motivation and academic success. The research

5
reviewed in Chapter Two highlighted five main findings: (a) Retention is an
intervention used throughout the United States since the early 20
th
Century with
sociocultural, racial, and educational implications; (b) positive and negative effects
of retention; (c) the decline in middle school students’ level of motivation, which
may cause the negative signs of retention to appear after the age of 14; (d) the
relationship between self-efficacy, goal orientation and academic performance; and
(e) the lack of research exploring the relationship of retention, motivation, and
academic performance with special populations.
Statement of the Problem
There is little research on how retention affects motivation and academic
success of middle school students, specifically English Language Learners and low
socio-economic students. Furthermore, there is even less research on the effects
regarding the time during which retention occurred and the subsequent motivational
and academic outcomes. The vast majority of schools continue to rely on historical
precedence and colloquial wisdom instead of making scientifically based decisions
(Frey, 2005). According to Schnurr, Kundert, and Nickerson (2009), part of this
reluctance to change is due to the lack of knowledge of the people in authority to
make a retention decision. The classroom teacher generally initiates the retention
process and is central to the retention decision (Tomchin & Impara, 1992).
Therefore, it is important to identify what teachers use to base their decisions to
retain. According to Witmer, Hoffman, and Nottis (2004), 44% of the teachers
reported they use personal experiences when forming their decision to retain a

6
student; and 22% of the teachers attributed their knowledge base to talking with
colleagues. The majority of the teachers use their short-term personal experience
with retained students that provide limited information and does not show long-term
effects of retention (Powell, 2010). In addition, the teachers generally
underestimated the feelings of failure, teasing by peers, and boredom from having to
repeat the same grade-level material the parents see their children experience (Smith
& Shepard, 1988). Due to this lack of understanding of retention and motivation, it is
difficult to minimize the use of retention as an effective intervention.
Purpose of the Study
The purpose of this study was three-fold: (a) to examine whether there is a
relationship between the motivation of retained versus non-retained students; (b) to
examine whether retention timing is related to motivation and academic
performance; and (c) to examine whether retention has differential effects on English
Learner Language students.
Research Questions and Hypotheses
This study aimed to answer four research questions:
1. What effects does retention status have on overall goal orientation,
mastery goal orientation, and self-efficacy?
2. What effect does the grade of retention have on goal orientation, mastery
goal orientation and self-efficacy?
3. What effect does the timing of retention have on student performance in
reading and writing?

7
4. What effects does retention status have on student performance in reading
and writing?
Significance of the Study
This study extended the research on the effects of retention and its
relationship to motivational issues, specifically with low socioeconomic and Latino
middle school students. To date, few studies have examined these issues with special
populations such as English Learner, ethnic, and low socioeconomic status students.
There has been a migration of families moving from suburban to urban setting,
which has had a significant impact on large urban districts (Santrock, 2009). As
documented by Gandara et al. (2003), one out of four students in public schools in
California have been identified as an English Learner with one out of three students
in the elementary school grades considered lacking proficiency in English. New
research is needed to address the increase in grade retentions, decline in motivation
during middle school, and the limited academic success of our minority students
(Frey, 2005). Such research should include the use of consistent methodological
practices, the use of valid and multifaceted surveys and research tools, and pay
special attention to less studied populations (Meece et al., 2006).
Methodology
The goal of this research was to examine the relationship of retention,
motivation, and academic performance with more diverse samplings. These research
questions required primarily numerical answers to make a comparison and perform a
statistical aggregation of data. The statistical analysis included previously collected

8
data from the district AEIRES student information system and Data Director, their
primary data management system. In addition, data was collected specifically for this
study through motivational surveys. In recognition of the purpose, context, and
intended audience of this study, the primary method to gather data was through the
quantitative method.
Assumptions
For the purposes of this study, it was assumed that subjects personally took
all of the state and local assessments fairly and without cheating, the student data
was correctly linked to the correct student identification numbers, and the students
responded honestly to the self-efficacy surveys. The researcher only used the
assessment data for the students who have both assessment and survey data. It was
assumed and ensured that the internal consistency of the set of items with a minority
and low socioeconomic population with a Cronbach’s Alpha between .7 and .9.
Lastly, the survey was unidimensional in that the first half of the survey matches the
second half of the survey.
Definition of Terms
Grade Retention
Grade retention refers to the conscious decision to have a student repeat a
grade upon completion of the first year when the student has not met specific
academic criteria or requirements.

9
Social Promotion
Social promotion is the practice of passing students along from grade to
grade with their peers even if the students have not satisfied academic requirements
or met key performance standards. The term social promotion is used because it is
generally carried out in the perceived interest of a student's social and psychological
well being.
English Learner in California
English Learners are those students whose parents report on the Home
Language Survey a primary language other than English and who have shown on the
California English Language Development Test (CELDT) to lack English language
skills of listening comprehension, speaking, reading, and writing necessary to
succeed in the school's regular instructional programs (California Department of
Education, 2011).
Ethnicity
Ethnicity frequently originates in the assertions of group members as they see
themselves as distinct. The ethnic group lays claims to their common history, certain
symbols that capture the core of the group’s identity, and shared culture (Cornell &
Hartman, 1998).
Self-Efficacy
Self-efficacy is a multifaceted, multidimensional construct, which is an
individual’s judgment of his capability that varies across distinct domains. Self-
efficacy is a person’s explicit judgment of his ability to complete domain-specific

10
tasks at a predetermined level. A person’s level of self-efficacy affects his choice of
activities, effort, and persistence (Bandura, 2006).
Goal Orientation
Goal Orientation is a preeminent approach to motivation that was developed
within the social-cognitive framework. It emphasizes the importance of individuals
think about themselves, the assigned tasks and their performance. The goal
orientation of a person can be predominately identified as mastery, performance
approach or performance avoid oriented.
Organization of the Study
Chapter One presented a brief introduction of the study including national
and state data on the issue of retention. It addressed the background of the study
through a historic timeline and cited some of the alternatives used instead of
retention. It included a concise review of the five main findings from the literature
review. The identified findings led to a discussion of the purpose of the study, the
research questions and hypotheses, and the significance of the study. In order to
fully disclose possible challenges of the study, any assumptions, limitations, and
delimitations were documented. Lastly, to ensure that all readers share a common
language, a list of definition of terms was provided of all operational and technical
terms.
Chapter Two was a review of the literature related to the research study. The
review provided a comprehensive overview of the literature in the following areas:
(a) Sociocultural, racial, and educational implications of retention; (b) positive and

11
negative effects of retention; (c) self-efficacy, goal orientation, and academic
performance; (d) decline of motivation during middle school; and (e) lack of
research on retention, motivation, and academic performance for special populations
such as English Learners and ethnic groups. These topics were summarized to
connect with the specific research questions addressed in this study.
As a result of the purpose of the study, research questions, literature review
and in recognition of the purpose, context, and intended audience of the study, the
appropriate quantitative methodology was chosen and delineated in Chapter Three.
In addition, the chapter spoke to the research design, population and sample,
instrumentation, proposal for data collection, and statistical techniques to be used to
assess each statistical hypothesis.
Chapter Four presented the results of the study. Chapter Five discussed and
analyzed the results in an effort to present conclusions and recommendations.

12
CHAPTER TWO
LITERATURE REVIEW
The purpose of this chapter was to provide a comprehensive overview of the
literature in the following areas: (a) sociocultural, racial, and educational influences
on retention; (b) positive and negative effects of retention; (c) self-efficacy, goal
orientation and academic performance; and (d) decline of motivation during middle
school. Lastly, this review spoke to the lack of research on retention, motivation,
and academic performance for special populations such as English Learners and
ethnic groups.
Despite the research on the negative and costly effects of retention, retention
continues to be a widely used form of intervention (Jimerson, 1999). Today’s
national overall rate of retention hovers around 20%, which reflects an increase of
40% in the last 20 years (Frey, 2005). Adding to the complexity of the issue, there is
a documented decline in middle school students’ level of motivation which may
accentuate the negative signs of retention that appear after the age of 14 (Frey, 2005;
Hughes, Kwok, & Gleason, 2007; Schnurr, Kundert, & Nickerson, 2009; Wu, West,
& Hughes, 2010). A student’s level of motivation can be quantified through multiple
motivational constructs. A valid and reliable measure of motivation is Albert
Bandura’s self-efficacy theory (Wigfield & Cambria, 2009). Self-efficacy is a
multifaceted, multidimensional construct, which is an individual’s judgment of his
capability to complete domain-specific tasks at a predetermined level. A person’s
level of self-efficacy affects his choice of activities, effort, and persistence, which, in

13
turn, affects academic achievement (Bandura, 2006). Further research is warranted to
help us understand the relationship between the motivational and academic
differences between retained and nonretained middle school students.
Sociocultural, Racial, and Educational Influences on Retention
Student retention is a remediative intervention that has been employed in
schools throughout America since the early 20th Century. Historically, retention has
carried multiple sociocultural, racial, and educational implications (Frey, 2005). The
narrative of the historical timeline shows the progression of the practice of retention
from its beginnings in one-room schoolhouses to the current developing trends of
“Red Shirting” and voluntary retention. The unique history of retention has
sociocultural roots and implications, which affects the educational experience
provided to our youth (Mantzicopoulos & Neuharth-Pritchett, 1998).
Historical Roots
It is important to look at the historical roots of retention as it highlights the
political and social implications on which rests the current implications of retention.
Historically, racial division and feelings of superiority have existed in America as far
back as the European discovery of North America. This racial divide led to the
displacement of its indigenous population, which was compounded by the first
importation of Blacks in 1619, and the subsequent institution of slavery (Stephan &
Feagin, 1980). The racial environment became even more complex when Mexicans
lost their land as the United States expanded and years later they became a needed
source of cheap labor (Valencia, 2002).

14
The roots of retention can be traced back to one-room schoolhouses, the
passage of compulsory education, and racial undertones. Originally, compulsory
education did not include Black children, girls, or children older than 10 years of age
(Stephan & Feagin, 1980). With the expansion of compulsory education laws and
the new era of pluralism, however, the concept of retention became even more
complicated as these unintended recipients were incorporated into the schools (Ogbu
& Simons, 1998). The question of how to teach disenfranchised students brought
about much turmoil, which led to numerous court rulings (Ford & Grantham, 2003).
By the middle of the 19
th
Century, the dominant White, English-speaking
group clearly demonstrated a sense of entitlement as observed through their status
ideologies such as the cultural capital theory (Valencia, 2002). These deficit models
contend children of parents with low levels of education are prone to lack the normal
abilities expected upon entering school (Blossfeld & Shavit, 2007). This mindset
created the segregation of schools, which was inherently unequal and provided poor
instruction to minority students. These inequalities were evident at all levels--
between states, school districts, schools within school districts, and classroom-to-
classroom.
In particular, the segregated schools of the early 20
th
Century created a
system where nearly 50% of all students were retained and 20% of all students left
school by eighth grade (Frey, 2005). During the mid 1900’s, schools began to form
classrooms based on homogeneous ability groupings to meet the instructional needs
of students. In addition to the use of homogenous grouping in classrooms, there was

15
the rise of social promotion, which caused the decline of retention rates from the
1930s through 1960s (Valencia, 2002). Nevertheless, with the start of the standards-
based reform, social promotion received much scrutiny and was even outlawed in
some states. By mid 1980s, public opinion polls indicated 72% of the general public
felt strongly that students should only be promoted to the next grade when they had
mastered the current year standards (Frey, 2005). With the focus on standards and
accountability as well as political pressures, retention rates have significantly grown
over the past two decades. These rates are difficult to measure in California as the
California Department of Education never has collected student retention data in a
systematic way (California Department of Education, 2011).
As demonstrated today in the courses offered to diverse student groups,
frequently there is a narrowing of the curriculum where advanced and college
preparatory classes are not offered to minorities. Differences in coursework can
specifically be found in the areas of mathematics, science, and foreign language
(Darling-Hammond, 2007). The inability of the schools to effectively accelerate the
academic progress of minorities was not considered undesirable as it played a role in
the continual marginalization of minority students (Valencia, 2002).
Developing Educational Trends
Over the last decade, a new trend called “Red Shirting” has developed among
many parents, particularly from middle- to upper class homes. More affluent parents
have decided to enroll their child a year or more after their fifth birthday to give
them more time in preschool and further development in early literacy behaviors

16
(Frey, 2005). This is an opportunity available mostly to middle- and upper class
children whose parents can afford the preschool and childcare expenses.
Another trend is the reluctance of schools to change their policies on
retention. The vast majority of schools continue to rely on historical precedence and
colloquial wisdom instead of making scientifically based decisions (Frey, 2005).
Part of this reluctance to change is due to the lack of knowledge of the people in
authority to make a retention decision. According to Witmer et al. (2004), 44% of
the teachers reported they use personal experiences when forming their decision to
retain a student; and 22% of the teachers attributed their knowledge base to talking
with colleagues. The majority of the teachers use their short-term personal
experience with retained students, which provide limited information and do not
show long-term effects of retention (Powell, 2010). In addition, the teachers
generally underestimated the feelings of failure, teasing by peers, and boredom from
having to repeat the same grade-level material that the parents see their children
experience (Smith & Shepard, 1988).
There are numerous reasons why school personnel choose to use retention as
a form of intervention. The informal decision-making process used to determine if a
student should be retained usually includes teacher recommendation, classroom
performance, social and/or emotional functioning, and performance on assessments
(Schnurr, Kundent, & Nickerson, 2009). The primary rationale is that it offers
children the “gift of time” which is opportunity to mature and develop the skills
necessary for a successful first grade experience (Mantizocopulos & Neuharth-

17
Pritchett, 1998). Linked to this rationale is social immaturity, which includes lack of
impulse control, inability to focus attention, and inability to conform to classroom
rules as a reason for retaining a child (Wu et al., 2010). For these reasons,
historically, the majority of students were retained in the primary grades of
kindergarten through third grade (Witmer et al., 2004). Recently, studies indicate
that due to high stakes measures, ninth grade is now the grade when a large number
of retentions occur (Frey, 2005).
Not only do student differences determine if they will be retained, but also
there are multiple teacher variables that influence their decision to retain frequently.
Some of the teacher variables include their underlying assumptions about learning,
understanding of the nonpromotion process, educational philosophy, and their ability
to provide appropriate instruction (Mantizocopulos & Neuharth-Pritchett, 1998).
Tomchin and Impara (1992) found 82.3% of the teachers examined deemed
retention an acceptable school practice, and 69.7% of the teachers believed retention
prevents student failure and motivates students to work harder. A similar study by
Witmer et al. (2004) found 94% of the teachers believed that retention was an
acceptable practice, and 77% of the teachers believed retention prevented failure in
later grades.
The primary factor that leads to retention is lack of academic performance.
Academic performance was considered twice as important as the second most
important factors of effort, ability, and social-emotional maturity (Tomchin &
Impara, 1992). Witmer et al. (2004) found there was a difference between K-2 and

18
3-4 grade teachers. The K-2 teachers placed the most weight on ability as the second
most important factor while 3-4 grade teachers identified effort as the next most
important factor. Both groups placed relative unimportance on gender and physical
size.
The probability of a child being retained is greatly influenced by the teachers’
attitude toward retention. The Tomchin and Impara (1992) study found that the K-2
teachers’ core beliefs were categorized into three areas: (a) Retention is necessary
for future success in school; (b) retention is mandated by the curriculum; and (c)
retention reflects teachers’ adherence to standards. The 4-7 grade teachers’ beliefs
were placed into four areas labeled (a) antiretentionists, (b) remediationist, (c)
standard-bearer, and (d) work-ethnic moralist. The antiretentionists were opposed to
retention in upper grades regardless of the student. The remediationist believed
retention should be avoided if possible and used alternative placements and flexible
students to assist the students. The standards-bearers believed students should be
retained if they did not meet the standards regardless of other circumstances and
factors. The work-ethnic moralists would retain students who did not put forth the
required effort. The category in which a teacher falls is important for this study as it
allows us to understand policies and interventions needed to reduce the practice of
retention.
Another indicator of the likelihood to use retention as an intervention is the
extent to which teachers view the development of school readiness. In Smith and
Shepard’s 1988 study, they placed teachers in four broad categories, which included

19
nativists, diagnostic prescriptives, interventionists, and remediationists. The nativists
believed development is an evolutionary process they cannot influence as a teacher
or parent. Teachers with a nativist point of view retained students to the highest
degree. Diagnostic-prescriptive teachers believed deficits could be diagnosed and
corrected by specialist personnel. They frequently retained if the students did not
receive the needed additional services. Interventionists believed children go through
natural stages that can be influenced by parents and teachers. Remediationists
believed that teachers and parents could make a difference in the children’s readiness
as they see development as a function of their experience, instructional program, and
environment. Remediationists and interventionists retained the least number of
students, as they understood not all children would be at the same level at any
particular point in time and feel that it is the responsibility of the teacher to
accommodate for academic diversity. According to Schnurr et al. (2009), in addition
to the lack of knowledge of the teachers, almost half (48%) of the school
psychologists who assisted with retention decisions and were referred to by teachers
indicated that they only had some-to-moderate knowledge on current research on
retention.
Socio-Cultural Roots
Beliefs are a range of emotional attitudes that are created through our socio-
cultural roots (Santrock, 2009). These beliefs, stereotypes and perceptions lead a
person to believe a proposition and act on those beliefs sometimes without realizing
it (Smith & Shepard, 1988). These beliefs create policies, structural barriers and

20
discrimination in society and schools, which are important determinants of low
school achievement among minorities. Lack of achievement, in turn, triggers
retention. There are two key sociocultural factors involved in retention: (a) low
expectations for minority students and (b) misunderstanding about language
development.
Many teachers still today maintain, subconsciously or consciously, low
expectations for Hispanic and Black students held for decades (Frey, 2005).
Whether their belief is based on the rationale that an extra year provides children the
time to mature and develop needed skills (Mantzicopoulos & Neuharth-Pritchett,
1998) or on racial beliefs of low genetics of minority students, both result in lower
expectations (Valencia, 2002). These minimal expectations translate into the use of
low-level instructional strategies and development of systems and processes such as
the use of retention as an intervention (Gallimore & Goldenberg, 2001). As stated by
Darling-Hammond (2007), the education provided to many minority students is not a
curriculum that fosters thinking but a curriculum geared towards lower level “rote”
skill such as memorization and formulaic reasoning.
In addition, many teachers do not have a good grasp on the language
developmental process or recognize the dual challenge of English Learners to
acquire a new language while simultaneously performing well in content areas
(Gandara, Rumberger, Maxwell-Jolly, & Callahan, 2003). There is a large
discrepancy between everyday conversational English and the academic English
needed for high levels of achievement in multiple content areas (Gandara et al.,

21
2003). At times, English Learners may appear to have acquired English due to their
ability to carry on informal conversations. Misled by these perceptions of their
students’ fluency and unequipped with sound knowledge on language acquisition,
many teachers do not provide English Learners with continual instruction in the
various forms and functions of language throughout their educational experience.
Therefore, many English Learners do not become truly fluent in their second
language and do not develop the academic English necessary to fully access the core
curriculum. Consistent with Bowman-Perrott et al. (2010), cognitive academic
language proficiency can take as long as seven to 10 years to fully develop.
According to Ogbu and Simons (1998), the rate of language acquisition is also
influenced by students’ perception of English acquisition as being additive and
important for their success in society. This acknowledgement of the need to learn a
second language has been the rationale for some educators to promote retention of
English Learners in the primary grades. Many Mexican American students have
been required to spend two years in the first grade without regard to their ability to
do the work (Valencia, 2002).
Additional teacher education on scaffolding techniques, sheltered language
techniques, and second language acquisition will improve the educational experience
of the English Learners. Although all American ethnic groups have risen in both
absolute and relative terms, 76% of third grade English Learners still perform below
grade level or well below grade level in reading and 53% in mathematics (Bowman-
Perrott et al., 2010). In addition, Ford and Grantham (2003) found that English

22
Learners were unrepresented in gifted education programs ranging from 50 to70%
and highly overrepresented in low-performing categories.
Gender and Racial Differences
The retention practice affects more than 2.4 million students of all ethnic and
language backgrounds in the United States each year resulting in additional
educational expenses exceeding $14 billion a year (Jimerson, 1999). However,
substantial research has shown that boys, minorities, and low socioeconomic status
students are significantly overrepresented among low-achieving students that have
been retained (Mantizocopulos & Neuharth-Pritchett, 1998).
Boys are retained substantially more than girls (Mantizocopulos & Neuharth-
Pritchett, 1998). This may be due to the early neurological advantages of girls, the
higher activity level, and slower development of impulse control of boys (Kindlon &
Thompson, 2002). Due to this mismatch between expectations of school behavior
and typical development, boys are twice as likely to be retained than girls and four
times more likely to be referred to a school psychologist than a girl (Frey, 2005). In
addition, boys are more inclined to be miscategorized as learning disabled in the
early grades. The negatively charged learning environment may cause some boys to
disengage from their learning, reduce motivation, and establish a negative pattern of
learning which causes further academic delays and a greater probability of retention
(Kindlon & Thompson, 2002).
There is a disproportionate use of retention with boys, minorities, and low
socioeconomic students. In 1992, 18% of African American and American Indian

23
students and 13% of Hispanic students in Grades K-12 repeated a grade compared to
9% of Caucasian students (Bowman-Perrott et al., 2010). Kaushal and
Nepomnyaschy (2009) made similar findings, noting only 7% of White children
repeated a grade while children in Black families were twice as likely to repeat a
grade 13% of the time and Hispanic children 10%. However, Kaushal and
Nepomnyaschy (2009) further contended that once socio-demographic
characteristics are controlled the differences between the probability of Hispanic and
White children repeating a grade is eliminated. Nevertheless, Black children remain
approximately 2% more likely to repeat a grade than White children even after
adjusting for sociodemographic characteristics.
In summary, student grade retention is a remediative intervention that has a
long history of inequitable use among diverse and underrepresented groups
specifically boys, minorities, and low socioeconomic status students. The historical
foundation provided us with the educational and cultural landscape, which produced
significant educational trends based on sociocultural and educational roots. The
deeply entrenched roots and beliefs have allowed sociocultural implications to
persist in the form of new developing trends of “Red Shirting” and continued
increases in grade retention despite opposing empirical research on the benefits of
retention.
Effects of Retention
There are both positive and negative effects of retention. Some recent
research has found positive short-term effects on the children’s perceived sense of

24
belonging, an increase in their feeling of academic efficacy, and a decrease in
teacher-rated hyperactivity, peer-rated sadness, and withdrawal (Gleason, Kwok, &
Hughes, 2007; Wu et al., 2010). However, there are also many noted long-term
negative effects of retention. Some of the deleterious outcomes of retention include
increased dropout rate, long-term low academic achievement, increased behavior
problems, and disengagement from school (Frey, 2005; Schnurr et al., 2009).
Positive Effects of Retention
The positive effects found by Wu et al. (2010) were short-term effects on a
child’s perceived sense of belonging, an increase in a feeling of academic efficacy,
and a decrease in teacher-rated hyperactivity, peer-rated sadness, and withdrawal.
When a student is first retained, the student experiences an increased sense of
academic efficacy. Especially in the early grades, due to the repeated exposure and
additional experience with classroom activities, the student may feel more advanced
or be better equipped to take on the curriculum than the students who surround him
(Witmer et al., 2004). The academic gains students initially experience diminish
rapidly after a few years as the students encounter new curriculum and routines and
their learning gap begins to reappear. These positive effects of academic efficacy
remain until fourth grade but then disappear by age 14 (Wu et al., 2010). Due to the
initial positive boost in self-confidence, the students frequently appear happier and
more engaged in the curriculum for the first few years after retention. The retained
students are frequently taller than the other children, which provide them with a
social advantage. Particularly with non-academic tasks, retained students are seen as

25
socially superior by their classmates (Hughes et al., 2007). With the added year of
maturity, the retained student will frequently exhibit improved impulse control and
demonstrate a better ability to attend to tasks. Nevertheless, the initial positive
effects unfold over time and create vulnerabilities that surface during middle school
(Wu et al., 2010).
The conclusions of Hughes et al. (2007) and Wu et al. (2010) are at odds with
the majority of research, which have focused on the negative effects of retention.
They specifically speak to Jimerson’s seminal work (1999, 2007), which found
inconsistencies in grade retention literature. They note an absence of a randomized
experimental design and lack of adequate comparison groups and statistical controls
needed to make the causal inferences in regard to retention valid. They believe that
these outstanding factors leave open the possibility that preexisting vulnerabilities
rather than retention may be the cause of the diminishing positive effects of retention
(Wu et al., 2010). They suggested that retention studies must be conducted that
includes extensive durations and comparison groups. Jimerson shared the same
sentiment and believes that further investigation is warranted to disentangle the
initial positive effects of retention from the long-term negative outcomes (Jimerson,
1999).
Negative Effects of Retention
The majority of the literature on retention speaks to the negative effects of
grade retention. The negative effects of retention have been well documented in

26
three main areas: (a) educational outcomes, (b) social/emotional outcomes, and (c)
job status/adult outcomes.
Educational outcomes. Retained students have lower educational outcomes
than socially promoted students. After middle school, they display lower cognitive
competence, lower self-expectations, and poorer school attendance (Jimerson, 1999).
These characteristics are compounded with their tendency to be less engaged in
instruction and reluctant to seek teacher support (Bowman-Perrott et al., 2010). The
retained students’ lower educational expectations for themselves are cemented in
their belief that their academic success or failure is largely out of their control (Frey,
2005). Jimerson (1999) and Jimerson and Ferguson (2007) showed through a 21-
year, prospective, longitudinal study that students who were retained displayed
significantly lower academic adjustment in 11
th
grade than both the low-achieving
but promoted group and the control group. To draw this conclusion they used
multiple scales, which changed during the longitudinal study according to the age of
the child. The measures included the Child Behavior Checklist, Home Observation
for Measurement of the Environment (HOME) inventory, Weschsler Preschool and
Primary Scales of Intelligence (WPPSI) at kindergarten, Peabody Individual
Achievement Test (PIAT) at kindergarten, first, second, and third grade, Wechsler
Intelligence Scale for Children—Revised (WISC—R) at third grade, grade point
average and credits obtained at the high school level, identification of behavioral and
attendance patterns throughout the grades, individual reports of completion of a high

27
school diploma or GED, postsecondary enrollment, and education/employment
status.
Grade retention greatly increases the likelihood of the student dropping out of
school with retained students 11 times more likely to drop out (Rumberger, 1995).
Rush and Vitale (1994) identified retention as one of the eight factors that increased
the risk of a student dropping out of school. The other cited reasons were (a)
academically at risk, (b) behavior and coping skills, (c) socially withdrawn, (d)
family income, (e) parenting, (f) language development, (g) retention, and (h) school
attendance (Rush & Vitale, 1994).
Retained children were less likely than nonretained children to have positive
views of their cognitive competence (Mantizocopulos & Neuharth-Pritchett, 1998).
Retention may trigger younger students to ruminate about their academic
shortcomings and convince themselves through self-talk that they will not succeed in
school (Usher & Pajares, 2008). Academically unstable students begin to question
their ability and make normative comparisons with their peers. These comparisons
are highlighted with the shift to competitive grading procedures, increased
homework, decreased teacher-pupil interaction, and an increase in social
comparison, which occurs in middle school (Usher & Pajares, 2008).
Jimerson’s (1999) study followed three groups: the retained group; the low-
achieving, promoted group, which he identified as the comparison group; and the
control group. The students in the retained group consisted of children in the sample
that was retained once in either kindergarten, first, second or third grade. The

28
students in the low achieving, promoted group were similarly identified to be
retained but were randomly selected to be socially promoted. The control group
consisted of randomly selected students who were not identified to be retained and
generally displayed higher academic achievement. Jimerson found the retained
students had a significantly higher dropout rate: 69% of the retained students
dropped out of high school versus 46% of the comparison group and 29% of the
control group. Similarly, the U.S. Department of Education (1997) reported that
students retained two years or more were four times more likely to drop out as those
never retained. The 1992 Federal High School and Beyond Study found fewer
numbers of students dropping out with an overall rate of 12.4%; however, there were
still a much larger percentage (27.2%) of students dropping out who had been
retained. The same study showed that if students entered into ninth grade at age 15.5
or above, they were three times more likely to drop out (Frey, 2005). While there are
at least eight identified factors that contribute to a student’s tendency to drop out,
Rumberger’s multi-level analysis found grade retention to be the single most
powerful predictor to influence a child’s decision to leave school (Rumberger, 1995).
Social and emotional outcomes. Retention has also proven to have a
negative effect on the student’s emotional health. Retained students display
problematic behaviors, exhibit low emotional health, and have a lower social
acceptance compared to non-retained students (Frey, 2005). Retention is damaging
to the social and emotional development of children especially as it relates to
personal adjustment (Jimerson, 1999). Retained students show a higher level of

29
aggression towards adults and peers than nonretained students (Hudley, Graham, &
Taylor, 2007). Aggression is a powerful predictor of future educational difficulties
including low achievement, low motivation, and poor adjustment (Mantizocopulos &
Neuharth-Pritchett, 1998).
Job status/adult outcomes. The trajectory of adverse outcomes appears to
continue into young adulthood (Ford & Grantham, 2003). Students that have been
retained are ill equipped for the modern workforce, pay fewer taxes, and receive a
greater proportion of welfare services than non-retained students (Jimerson &
Ferguson, 2007). Frey (2005) found that retainees averaged $6.59 an hour wage
versus $8.42 and $8.57 for low-achieving socially promoted students and control
groups. The retained group of students displayed lower employment status and lower
employment competence, which can lead to less opportunity for job promotions and
less stable work environment (Jimerson, 1999). In addition, retained children were
more likely to be incarcerated and abuse drugs and alcohol than those never retained.
Lastly, retained students were three times less likely to pursue secondary education
than socially promote students (Jimerson, 1999; Jimerson & Ferguson, 2007).
In summary, there are both positive and negative effects of retention. There
are some inconsistencies in grade retention literature with the note of the absence of
a randomized experimental design, lack of adequate comparison groups, and
statistical controls needed to make causal inferences. There are outstanding factors
that leave open the possibility that preexisting vulnerabilities rather than retention
may be the cause of the diminishing positive effects of retention (Wu et al., 2010).

30
Some researchers focus on the positive short-term effects on the children’s perceived
sense of belonging, an increase in their feeling of academic efficacy, and a decrease
in teacher-rated hyperactivity, peer-rated sadness, and withdrawal (Hughes et al.,
2007; Wu et al., 2010). The majority of the researchers focus on the long-term
negative effects of retention of increased dropout rate, long-term low academic
achievement, increased behavior problems, and disengagement from school (Hudley
et al., 2007; Jimerson, 1999; Jimerson & Ferguson, 2007; Mantizocopulos &
Neuharth-Pritchett, 1998).
Self-Efficacy and Academic Performance
There is a relationship between self-efficacy and academic performance,
which has been substantiated by a large body of research. Within the research, there
are specific findings that motivation relates to the theoretical tenets of the social
cognitive theory (Bandura, 2006; Usher & Pajares, 2008; Wigfield & Cambria,
2010); sociocultural influences (Chin & Kameoka, 2002; Eccles, 2009; Meece et al.,
2006; Rueda & Dembo, 1995; Zimmerman, 2000); differences among group
membership, ability levels, and academic domains (Meece et al., 2006; Pajares,
Johnson, & Usher, 2007; Unrau & Schlackman, 2006); parental influences (Chin &
Kameoka, 2002; Eccles, 2009; Meece et al., 2005, 2006); and teacher influences
(Meece et al., 2006; Wentzel, 1997).
Foundation of Social Cognitive Theory
In 1977, Albert Bandura introduced self-efficacy theory as a multi-faceted,
multi-dimensional construct, which is an individual’s judgment of his capability that

31
varies across distinct domains. Self-efficacy is a person’s explicit judgment of his
ability to complete domain-specific tasks at a predetermined level. A person’s level
of self-efficacy affects his choice of activities, effort, and persistence (Bandura,
2006). These self-efficacy beliefs increase students’ use of self-regulatory skills such
as diagnosing task demands, constructing and evaluating alternative solutions, setting
proximal goals, self-monitoring, and strategy use that increase the likelihood to
successfully perform the chosen activity (Bandura, 2006; Zimmerman, 2000).
Self-efficacy beliefs differ in generality, strength, and level. The generality
aspect of the construct notes the transferability of the self-efficacy beliefs across
various activities. The strength of self-efficacy is measured by a person’s confidence
in performing the task (Zimmerman, 2000). The level of self-efficacy depends on
the difficulty of the particular task (Meece, Glienke, & Burg, 2006). The judgment of
capability influences the course of action taken, the complexity of the established
goal, the level of commitment to the task, the level of perseverance in face of
obstacles, and the level of resilience after difficulty of an individual (Bandura, 2006).
Four Sources of Self-Efficacy
Self-efficacy beliefs can change over time. There are four hypothesized
sources of self-efficacy beliefs: mastery experience, vicarious experience, social
persuasions, and physiological states (Bandura, 2006; Usher & Pajares, 2006;
Zimmerman, 2000). Students’ perceived mastery experience accounts for the greatest
proportion of variance in self-efficacy and is the most influential source (Pajares et
al., 2007; Wigfield & Cambria, 2010).

32
Mastery experiences are powerful because they allow the student to take
ownership of his learning and demonstrate autonomy (Renninger, Bachrach, &
Posey, 2008). However, due to various personal and situational contributions, the
perceptions of mastery are better predictors of self-efficacy than are the objective
results. Two students receiving the same objective result of a letter grade of B+ who
perceive the accomplishment in a very different light can illustrate this point. For a
student that put in substantial effort and normally obtains a lower grade, the mastery
experience may increase his level of self-efficacy. Whereas, if the student is
accustomed to receiving letter grades of As and puts in substantial effort, the
experience may diminish his level of self-efficacy (Usher & Pajares, 2006). The
ultimate impact of these experienced outcomes depends on what the student makes
of them.
Vicarious experiences occur when someone views another person attempting
a task with success or with failure. Vicarious information is most influential when
students are uncertain about their own abilities or have limited experience with the
academic task (Usher & Pajares, 2006). Especially in the case of younger children,
observing a similar peer successfully performing a task well can promote a sense of
efficacy in them. Students frequently gauge their capabilities in relation to the
performance of others they believe are similar to them (Usher & Pajares, 2006).
Social persuasions are information and feedback provided to individuals from
significant others. Social persuasions are particularly powerful for those not yet
skilled at making accurate self-appraisals. It is easier to weaken self-efficacy beliefs

33
through negative appraisals than to strengthen such beliefs through positive
encouragement (Pajares, Johnson, & Usher, 2007; Usher & Pajares, 2006). In
addition, children increasingly lose faith in social persuasions from others when the
feedback does not correspond with their perceived competency (Usher & Pajares,
2006).
The physiological state of the individual can impact their academic
performance and self-efficacy. Students’ anxiety and stress are related to a
diminished sense of efficacy (Zimmerman, 2000). In all of the studies, mastery
experience proved to be the strongest predictor of academic and self-regulatory self-
efficacy (Bandura, 2006; Usher & Pajares, 2006; Zimmerman, 2000). With the
notable exception of mastery experiences, previous studies of the other three sources
yielded inconsistent results. These inconsistencies may be due to the context-
sensitivity of self-efficacy beliefs, methodological choices, the use of a hierarchical
regression model, differences among group membership, varying ability level, and
sociocultural factors (Pajares et al., 2007; Usher & Pajares, 2006).
Sociocultural Influences
Mental processes do not operate in isolation as they are strongly and
interactively influenced by motivation (Rueda & Dembo, 1995). The motivation of
individuals is shaped by the culture and sociocultural influences in which they are
raised. Initially, there was little attention given to the role of culture and
environmental influences within the study of self-efficacy beliefs (Zimmerman,
2000). Subsequently, there has been ample attention to the key role that social

34
interactions, cultural knowledge, and practices play in learning (Rueda & Dembo,
1995).
As children and adults are exposed to different contexts and cultural
expectations, they acquire different competencies, patterns of success, values, and
long-term goals (Eccles, 2009). The gender socialization patterns are quite different
for Hispanic, Asian, and African American youth (Meece et al., 2006). The different
socialization patterns provide children with different experiences and perceived
norms that shape how they think, feel, and react in specific contexts (Rueda &
Dembo, 1995). In a few studies, there has been a connection drawn to how culture
can play a corrosive effect on a child’s development of a high sense of self-efficacy.
Such is the case with Chin and Kameoka’s (2002) study of middle school children in
inner-city environments. They found that the lack of sense of security, low social
capital, and limited educational resources had a negative impact on the students’
level of self-efficacy. In addition, Meece et al. (2006) found that gender effects are
moderated by students’ ethnicity and socioeconomic status.
Gender Differences in Self-Efficacy
Gender differences in motivation are evident through the differential power
of influence of the four sources of self-efficacy. Girls and women tend to report
stronger vicarious experiences and social persuasions than do boys and men (Pajares
et al., 2007). Whereas, mastery and vicarious experiences predicted these self-beliefs
for boys and men (Usher & Pajares, 2006). Socialization and achievement
experiences play an important role in the development of gender differences in

35
motivation. Such differences in motivation are apparent in early elementary school
years. Boys generally begin school with higher perceptions of their mathematics
abilities; whereas, girls report higher perceptions of their language arts abilities.
(Meece et al., 2006).
Reading and Writing Self-Efficacy
As a result of reading difficulties, a student’s self-efficacy can be impacted in
a negative way (Ferrara, 2005). Schunk and Rice (1993) examined reading self-
efficacy and found that young students who received training to help with their
reading self-efficacy and strategy use were better readers. McGrudden, Perkins, and
Putney (2005) found similar findings, which indicate that explicit strategy instruction
in reading strategy and practice, affect students’ reading self-efficacy. They found
that observation and practice of the modeled skill increased student motivation and
task persistence.
Self-efficacy can have a equally important impact on writing. Pajares et al.
(2007) investigated the sources of self-efficacy in the area of writing. They found
that mastery experience accounted for the greatest proportion of variance in writing
self-efficacy. The results concluded that vicarious experience did not predict writing
self-efficacy. Their effect sizes between self-efficacy and writing outcomes in
multiple regression and path analyses ranged from .19 to .40. In addition, the
established correlations between self-efficacy and writing performance ranged from
.30 to .50.

36
Parental Influences
There are several important pathways by which parents shape their children’s
achievement motivation, which has enduring influence on their children’s career
choice and beliefs regarding their academic ability (Meece et al., 2006). Eccles
(2009) found that parents often underestimate their daughter’s talents and
overestimate their son’s talent. Apart from the different perceptions of their son’s
and daughter’s academic abilities, they frequently have different attributions for their
successes (Eccles, 2009). Many times parents will provide unsolicited, and many
times unnecessary, help to their daughters, which sends an underlining message that
the daughter cannot complete the task without assistance. This unsolicited help can
undermine the daughter’s self-perceptions and sense of self-efficacy (Meece et al.,
2006).
Apart from the influence of explicit expectations of their parents, children
have varying degrees of academically based opportunities according to the socio-
economic level of the parent. By the time that children go to preschool, there already
considerable differences in the vocabulary levels of children linked to their
socioeconomic levels. A low socio-economic parent communicates approximately
400 utterances less per hour than a professional high socio-economic parent
(Santrock, 2009). Fewell and Deutscher (2003) found that language development at
30 months of age predicted reading at eight years of age. This shows that parents
have multiple ways that they influence their children’s pathway to academic
motivation and success.

37
Teacher Influences
Teachers can have an equally impactful influence on their students’ level of
self-efficacy. Perceived support from teachers is a significant predictor of young
adolescents’ motivation and academic achievement (Wentzel, 1997). This support
can be especially meaningful when it is considered jointly with parent support.
Meece et al. (2006) found that teachers generally have higher achievement
expectations for boys than for girls, especially in male-sex-typed activities such as
mathematics and science. These higher expectations result in more frequent teacher-
student interactions with the boys. In addition to a higher number of opportunities to
demonstrate mastery and to receive positive feedback, the boys answered more
process, abstract, and complex questions than the girls (Meece et al., 2006). As with
the parents, the teachers tend to overestimate girls’ effort in mathematics, which may
lead girls to attribute their successes to more effort than ability (Wentzel, 1997).
In summary, social cognitive models emphasize the influence of the
achievement context on individual’s motivation and achievement (Wigfield &
Cambria, 2010). The research has shown that contextual factors such as gender,
ethnicity, academic ability, and academic domain have a significant impact on
motivation. Motivation, specifically the construct of self-efficacy, is a powerful
influence on learning as it is associated with the ability of the student to monitor their
work time more effectively, be more efficient problem solvers, show more
persistence, work harder, and engage in more self-regulatory strategies (Usher &
Pajares, 2008).

38
Goal Orientation and Academic Performance
The Goal Orientation Theory has been a preeminent approach to motivation
over the past two decades (Midgley, Kaplan, & Middleton, 2001). As with self-
efficacy, the theory was developed within the social-cognitive framework and has
strong correlations to academic achievement (Midgely, Kaplan, Middleton, Maehr,
Urdan, Anderman, Anderman, & Roeser, 1998). The goal orientation of the student
influences many of the same aspects as the self-efficacy construct such as the level
of persistence they exhibit when confronted with failure or difficulty, feeling
efficacious despite failures, and use of more deep-level cognitive processing
strategies (Urdan, 1997). Thus, research on Goal Orientation Theory serves to
deepen the understanding of the relationship between motivation and academic
performance, specifically as it relates to the affects of retention on middle school
students.
Goal Orientation Theory seeks to explain the beliefs that students hold about
the purpose of pursuing achievement as well as the standards and criteria the students
use to evaluate their success (Urdan, 1997). The theory focuses on why the
individuals are motivated to achieve through the intended meaning and purpose of
achievement (Midgley & Urdan, 2001). Goal orientation theorists have typically
described two orientations: mastery goal orientation and performance goal
orientation. However, Elliot and Harachiewicz (1996) pointed out the discrepancy
between theory and research and made the conceptual change to divide performance
goal orientation into performance-approach goal orientation and performance-avoid

39
goal orientation. In general, mastery orientation has been seen as a more adaptive
orientation leading to greater beneficial learning outcomes. However, the individual
student’s characteristics, desired outcomes, and context may highlight the possibility
of performance-approach goal orientation being an adaptive orientation as well.
These findings will be discussed in the following sections. Regardless of which
orientation is most influential for the student, each of the orientations is associated
with different patterns of cognition, affect, and behavior (Dweck & Leggett, 1988).
Mastery Goal Orientation
Students with a high level of mastery goal orientation generally pursue the
task because it enables them to learn something new or challenging even though
there is a chance of failure (Dweck & Leggett, 1988). They are willing to risk a
display of incompetence because of the deeper value they place on developing
competency, gaining understanding or sight, or enjoying completion of the task.
There is remarkable consistency between the relationship between mastery goal
orientation and adaptive patterns of learning (Midgley et al., 2001).
For mastery-oriented students, success is achieved when they experience and
display improvement, progress, or mastery (Maehr & Meyer, 1997). They perceive
intelligence and ability as being malleable and dynamic throughout their lifetime
(Dweck & Elliott, 1983). Therefore, they generally exert more effort and use higher
cognitive strategies.

40
Performance Goal Orientation
Students with the performance goal orientation are concerned with how their
ability will be judged and how they perform relative to others (Midgley et al., 2001).
They are concerned with appearing intelligent, impressing others, and receiving
positive feedback and evaluations from others (Dweck & Elliott, 1983). They
generally choose tasks that are easy for them and guarantee success.
For performance-oriented students, success is perceived when they achieve
high grades, high performance in comparison with their peers, and relative
achievement on standardized tests (Maehr & Meyer, 1997). There is significant
evidence that students with a performance-avoid orientation are more inclined to
participate in maladaptive behaviors (Midgely et al., 2001). For example, Midgley
and Urdan (2001) found that performance-avoid goals positively predicted the
reluctance to seek help when they needed it, cheat on assessments, and use avoidance
techniques. However, there is additional evidence that performance-approach
orientation leads to adaptive outcomes such as a positive self-concept, high levels of
effort, optimistic attitudes, positive affect, and appreciation for academic work
(Urdan, 1997).
The goal orientation of the student has an impact on their academic
performance. Students with lower grades, who have a greater chance of being
previously retained, are more likely to have a performance-avoid orientation and use
self-handicapping strategies than higher performing students (Midgley & Urdan,

41
2001). These maladaptive strategies in turn perpetuate the lower performance, which
may cause the performance-avoid orientation to persist (Urdan, 1997).
Gender Differences in Goal Orientation
In certain cases, students may not view high academic achievement as
compatible with popularity and approval of peers. Both positive and negative peers
can influence middle school students’ academic aspirations and achievement.
According to Urdan (1997), students who associated with positively oriented friends
were strongly correlated to holding a mastery goal orientation and maintaining a high
grade point average. However, he did note that girls might be more affected by these
peer relationships than boy. Girls generally see themselves as more cooperative and
interconnected to their in-group. Early adolescent girls tend to place a higher level
of importance on equality and will even sacrifice academic achievement to assist
friends (Phelan, Davidson, & Cao, 1991). Boys, on the other hand, tend to be more
individualistic and competitive. Regardless of the gender, negatively oriented
friends were a strong predictor of performance-avoid goals (Urdan, 1997).
Goal Orientation in Middle School
Achievement goals are thought to be fairly stable, but research has shown
that students adjust their goals according to the demands of the learning environment
(Urdan, 1997). Therefore, the goal structure of the learning environment becomes
integral to the goal orientation of the student (Midgley & Urdan, 2001). The
environments of middle schools generally promote competition between students,
compare students to each other, recognize high levels of achievement, and place a

42
great importance on grades and test scores (Urdan, 1997). This structure encourages
students to refocus on their goal orientation towards a performance orientation.
Those who cannot met the desired standard set by their school may form a
performance-avoid orientation to buffer their academic deficits and level of self-
esteem (Urdan, 1997).
Goal Orientation and Reading
Unrau and Schlackman (2006) examined the effects of intrinsic and extrinsic
motivation on reading achievement in an urban middle school setting. They found
that for all of the participants’ intrinsic and extrinsic motivation declined
significantly as students moved from Grade 6 to Grade 7. In addition, they found the
connection between intrinsic motivation and reading achievement was only
significant for Asian students and not significant for Hispanic students. Specifically,
reading achievement was positively correlated with two dimensions of intrinsic
motivation of involvement and challenge for Asian students. Extrinsic motivation
had a negative effect on Asian students (-.47) and did not have a significant effect on
Hispanic students (-.12) (Unrau & Schlackman, 2006). For female students of both
ethnic groups, there was a positive relationship correlated with the intrinsic
dimension of involvement and two extrinsic dimensions of recognition and social
while there was a negative relationship with the extrinsic dimension of competition
and reading achievement.
In summary, mastery-oriented students are intrinsically motivated, seek to
increase their competence, challenge themselves, and rebound quicker from failure

43
(Dweck, 1986). The performance-oriented students may depend on extrinsic
motivation and are concerned with impressing others and receiving positive
feedback. Students’ goal orientation is influenced not only by their peers but also by
the goal structure of the educational environment. The research on goal orientation
has noted the substantial need for research involving more diverse samples including
ethnic groups and English Language Learners (Midgley et al., 2001; Urdan, 1997).
Decline of Motivation During Middle School
There is strong evidence that a student’s level of self-efficacy affects their
academic success (Bandera, 1999). There is further evidence that a students’ level of
motivation declines in middle school, which may accentuate the negative signs of
retention that appear after the age of 14. The research on the effects of retention
clearly demonstrates that the positive effects of retention diminish after the age of 14
(Frey, 2005; Hughes et al., 2007; Schnurr et al., 2009; Wu et al., 2010). In addition,
the research on motivation, specifically the construct of self-efficacy, shows that a
high level of motivation is instrumental in improving academic performance
(Bandura, 2006; Chin & Kameoka, 2002; Eccles, 2009; Meece et al., 2006; Rueda &
Dembo, 1995; Usher & Pajares, 2008; Wigfield & Cambria, 2010; Zimmerman,
2000). The current research has also identified a decline in middle school students’
level of motivation due to four key areas: change in learning environments (Meece et
al., 2006; Renninger, Bachrach, & Posey, 2008; Usher & Pajares, 2006; Zanobini &
Usai, 2002), differences in teacher interaction and social relationships (Meece et al.,
2006; Wentzel, 1997; Zanobini & Usai, 2002), individual development (Chin &

44
Kameoka, 2002; Eccles, 2009; Pajares, Johnson, & Usher, 2007; Ricco, Pierce, &
Medinilla, 2010; Zanobini & Usai, 2002; Zimmerman, 2000), and gender differences
(Eccles, 2009; Meece et al., 2006; Pajares et al., 2007).
Change in Learning Environment
Some change in motivation can be attributed to the change in the learning
environment from elementary school to middle school. Numerous studies have
shown a decline in students’ grade point average at the beginning of the middle
school transition. (Meece et al., 2006; Zanobini & Usai, 2002). The grade point
average can be significant as it illustrates a decline in key curricular areas such as
reading and writing. There is a critical place for reading and writing in the overall
academic curriculum of a middle school and often a connection between a student
being weak in reading as well as weak in most academic areas (Usher & Pajares,
2006). This decline has been linked to the impersonal, structured, and teacher-
controlled environment of middle school that contrasts with the personalized
environment of elementary school (Usher & Pajares, 2006). Due to the increase of
teacher control, the students have fewer opportunities to make decisions, choose
activities, and manage their own learning process (Zanobini & Usai, 2002). The loss
of choice and decision-making may be attributed to the disengagement of the
students as they may have curiosity questions that are never answered due to the
activity provided or not recognized due to the inflexible learning environment
(Renninger et al., 2008). It is only in the domains for which the students have
developed interest that encourage them to articulate challenging goals which when

45
meet will increase their level of self-efficacy. Dealing with motivational problems
requires personalization and keen knowledge of each student’s zone of proximal
development, which does not occur in the middle school setting (Rueda & Dembo,
2008). In addition, there is a performance orientation focused on competition and
ability differences, which highlights deficiencies and serves to further disengage
struggling students (Meece et al., 2006).
Differences in Teacher Interaction and Social Relationships
Teachers can have an equally impactful influence on their students’ level of
self-efficacy. There is a linked interpersonal relationship between teachers and
students to motivational outcomes (Wentzel, 1997). These relationships can be
compromised as secondary teachers use more whole-class lecture and discussion and
less small-group time with allows for one-on-one interaction (Meece et al., 2006).
This change in dynamics causes a heightened level of mistrust to grow between the
teachers and students. Due to the limited opportunities to establish meaningful
relationships with their teachers, students may perceive that their teachers no longer
care for them (Wentzel, 1997). The change in social relationships and environment
cause a decline in middle school students’ level of motivation (Zanobini & Usai,
2002).
Individual Development
Aspects of self-development change over the course of a lifetime and are
quite malleable over situations at any given point in time. The constant development
occurs as individuals are exposed to and interpret more experiences (Eccles, 2009).

46
The students change the ways in which they judge their own competence. Age
contributes significantly to students’ prediction of educational expectations with
younger children reporting higher expectations (Chin & Kameoka, 2002). Middle
school seems to be a critical juncture at which academic motivation and self-efficacy
decreases (Pajares et al., 2007). Younger children generally overestimate their
competence while early adolescents appear to be more realistic about their
capabilities (Zanobini & Usai, 2002). Self-efficacy beliefs are most likely to change
during skill development activities when faced with novel tasks; or when their new,
lower judgment of competence corresponds with poor performance on more severe
assessments; or when they feel they cannot meet their teachers’ higher expectations
(Usher & Pajares, 2006). External and internal comparisons are key as people assess
their own abilities by comparing their performance with those of other people and
with their own amount of effort (Eccles, 2009).
As the students’ self-perceptions change, they will work to bring their ability
self-concepts and the task value they place on particular schooling experiences and
subjects in alignment (Eccles, 2009). The devaluing of tasks will help them save
their level of self-efficacy but will decrease the value they place on particular
schooling experiences (Graham, Bellimore, Nishina, & Juvoueu, 2009). From
elementary to middle school, students generally become more negative about school
and about themselves, feel more anxious about their performance, place greater
significance on evaluation feedback, and are less intrinsically motivated (Zanaobini
& Usai, 2002). The trajectory of self-development is different for each person as

47
there are significant individual differences in adults’ and adolescents’ beliefs about
their ability to learn. Some individuals see their ability as relatively fixed while
others believe that their ability to learn can be changed through effort and persistence
(Ricco et al., 2010). Their beliefs about learning, which are clearly established in late
adolescence, are molded during their middle school experience (Ricco et al., 2010).
Gender Differences in Middle School
Gender differences in motivation are evident early in school and increase for
reading and language arts over the course of school. Middle school girls have higher
writing self-efficacy than boys even when there are no gender differences in actual
writing performance (Usher & Pajares, 2008). For boys, the value of language arts
declines most rapidly in elementary school; and the value of mathematics declines
most rapidly in high school. Over the last several years, the larger gender differences
in mathematics and science performance have decreased (Meece et al., 2006). In
addition, the learning environment of elementary schools, which focuses on
collaborative and predominantly intrinsic motivation, may favor girls more than boys
(Zanobini & Usai, 2002). This may be one of the causes for the drop that girls
experience in their academic motivation in general and in their perceptions of
competence as they pass through the extrinsically motivated and performance-based
curriculum of middle school (Pajares et al., 2007). However, when gender-role
orientations are taken into account, gender differences in self-efficacy beliefs are no
longer significant (Meece et al., 2006). This may be attributed to the increasing
concerns about conforming to gender-role stereotypes during their individual

48
development. These gender roles are particularly salient during the preschool years
and during early and middle adolescence (Eccles, 2009).
In summary, the decline in motivation and self-efficacy beliefs and a shift to
performance oriented goals of middle school students varies according to their
gender; individual development and beliefs; social relationships; and ability to
assimilate to the changing learning environment, set of expectations, and roles
(Meece et al., 2006; Pajares et al., 2007). This decline in motivation may contribute
to the diminishing positive effects of retention, which occur during middle school.
Lack of Research on Retention, Motivation, and Academic Performance
There is a lack of research regarding the relationship of retention, motivation,
and academic performance. With the focus on standards and accountability as well
as political pressures, retention rates have significantly grown over the past two
decades. Today, the overall rate of retention hovers around 20% and has increased by
40% in the last 20 years (Frey, 2005). At a time when there are increasing calls for
improving student achievement and student apathy is a societal concern, improving
student motivation and decreasing grade retention are important considerations for
both the public and educators (Middleton & Midgley, 2002).
Past research has identified three key areas that require future research: use of
consistent methodological practices (Cleary & Chen, 2009; Pintrich, 2003; Ricco et
al., 2010; Usher & Pajares, 2008; Wu et al., 2010), use of valid and multifaceted
surveys and research tools (Cleary & Chen, 2009; Usher & Pajares, 2006; Usher &
Pajares, 2008), and special attention to less studied populations (Chin & Kameoka,

49
2002; Cleary & Chen, 2009; Frey, 2005; Unrau & Schlackman, 2006; Usher &
Pajares, 2008). Findings from this line of inquiry will make substantial contributions
to educational research and policies and will hopefully result in better student
retention practices that are based on empirical data and documented student
outcomes (Frey, 2005; Usher & Pajares, 2008).
This study highlighted the specific paths of motivation in the middle school
years that is a key transitional period within the developmental spectrum (Cleary &
Chen, 2009). This study examined whether grade retention has contributed to the
high proportion of ethnic minority and low-income students of both genders that lose
confidence in their academic abilities and devalue the importance of education for
their futures (Wiggan, 2007).
Use of Consistent Methodological Practices
Due to the sensitive and ethical nature of studying the effects of retention on
children, there are no experimentally designed studies including random assignment
of students to be retained or promoted (Jimerson & Ferguson, 2007). This
challenging design issue has resulted in studies that can only make causal inferences
about grade retention in the absence of a randomized experimental design.
According to Wu, West, and Hughes (2010), after a thorough literary review of all
grade retention research, only four studies had both adequate comparison groups and
statistical controls. Most studies have resulted in correlational findings and have
been conducted at only one point in time (Usher & Pajares, 2008). Even with
optimal prospective longitudinal studies, there was a restricted sample size, lack of

50
utility of multidisciplinary perspective, and small effect size that limited
generalizability (Ricco et al., 2010; Pintrich, 2003).
Use of Valid and Multifaceted Survey and Research Tools
Within the world of educational research, there is recognition that a statistical
test must measure the operational definitions of the self-efficacy construct in order to
accurately reflect the theoretical tenets of Bandura (Usher & Pajares, 2008).
However, researchers have yet to develop more thorough measures that assess the
multidimensionality of the four hypothesized sources of self-efficacy (Cleary &
Chen, 2009). In some cases, the studies have used an aggregate score from two or
more of these sources which prevents us from understanding each of the individual
sources of self-efficacy and its influence on overall motivation (Usher & Pajares,
2008). The measures of self-efficacy need to provide us with insights into how
parents, teachers, and educators can help middle school children develop and
maintain strong motivation. These multifaceted surveys will include students’
interpretation and evaluation of their academic experiences, identify the importance
they give to the feedback they receive, and assess the influence of same-age peers
and adults (Usher & Pajares, 2006). These measures of self-efficacy will help us
understand how a broader range of motivational beliefs impacts students’ regulatory
behaviors and academic achievement (Cleary & Chen, 2009).
Less Studied Populations
The majority of research on self-efficacy has involved participants from
White and middle class backgrounds (Usher & Pajares, 2008). Studies such as

51
Alexander, Entwisle, and Dauber (1994), Meisels and Liaw (1993), or Roderick
(1995) have included only middle-class children of varying ethnic backgrounds.
Thus, patterns associated with children from low socioeconomic backgrounds or
children of a particular ethnic group have been minimized (Chin & Kameoka, 2002).
In some cases, the diverse students were intentionally excluded. Such an example
was Unrau and Schlackman’s study (2006) that intentionally excluded all English
Learners due to the fact that the English Learners would have had trouble
comprehending the questions because of their limited reading skills. As the cultural
landscape of American schools continues to change and the achievement gap
continues to be large between ethnic groups and White students, there is a need to
pay special attention to less studied populations.
In summary, there is a lack of research examining the relationship of
retention, motivation, and academic performance. Due to the increase in grade
retentions, decline in motivation during middle school, and the limited academic
success of our minority students, there is a call for new research (Frey, 2005). Such
research should include the use of consistent methodological practices, the use of
valid and multifaceted surveys and research tools, and pay special attention to less
studied populations (Meece et al., 2006).
Conclusion
The literature reviewed demonstrated that since the middle of the 19
th

Century grade retention has been used as a form of intervention, which is laden with
sociocultural, racial, and educational implications. Due to these implications, there

52
is a disproportionate use of grade retention for boys, minorities, and low
socioeconomic status students (Mantizocopulos & Neuharth-Pritchett, 1998).
Some research has highlighted the positive short-term effects on the
children’s perceived sense of belonging, an increase in their feeling of academic
efficacy, and a decrease in teacher-rated hyperactivity, peer-rated sadness, and
withdrawal (Gleason et al., 2007; Wu et al., 2010). However, the majority of the
research points to the long-term negative outcomes of retention which include
increased dropout rate, long-term low academic achievement, increased behavior
problems, and disengagement from school (Frey, 2005; Schnurr, Kundert, &
Nickerson, 2009).
A large body of research has substantiated the relationship between the
construct of self-efficacy and academic performance with specific attention to the
hypothesized source of mastery experience (Bandura, 2006; Usher & Pajares, 2008;
Wigfield & Cambria, 2010). The research on motivation, specifically the construct of
self-efficacy, shows that a high level of motivation is instrumental in improving
academic performance (Chin & Kameoka, 2002; Eccles, 2009; Meece et al., 2006;
Rueda & Dembo, 1995; Zimmerman, 2000). The current research has also identified
a decline in middle school students’ level of motivation due to four key areas:
change in learning environments, differences in teacher interaction and social
relationships, individual development, and gender differences (Eccles, 2009; Meece
et al., 2006; Pajares et al., 2007; Renninger, Bachrach, & Posey, 2008; Usher &
Pajares, 2006; Wentzel, 1997; Zanobini & Usai, 2002).

53
To date, few studies have examined these issues with special populations
such as English Learner, ethnic, and low socioeconomic status students. The
majority of the studies have not included diverse populations nor examined the long-
term relationship between retention and motivation. We need more recent studies
that address the changing demographics of the students we serve, specifically in
large urban districts. Due to the noted importance of motivation to academic
achievement, the established decline of motivation in middle school, and the
negative effects of retention after age 14, further research is warranted with more
diverse samplings in the field of motivation and retention.

54
CHAPTER THREE
RESEARCH METHODOLOGY
Introduction
The purpose of this study was threefold: (a) to examine whether there was a
relationship between the motivation of retained versus non-retained students; (b) to
examine whether retention timing was related to motivation and academic
performance; and (c) to examine whether retention had differential effects on English
Learner Language students.
The goal of this research was to examine the relationship of retention,
motivation, and academic performance with more diverse populations. Due to the
increase in grade retentions, decline in motivation during middle school, and the
limited academic success of our minority students, there is a call for new research
(Frey, 2005). This research used consistent methodological practices, administer
valid and multifaceted surveys and research tools, and paid special attention to less
studied populations (Meece et al., 2006) in an effort to contribute to the field of
motivation and retention.
This chapter included the research questions, the hypotheses, and a
description of the research methodology. The latter included the sampling procedure
and population, instrumentation, and procedures for data collections and analysis.

55
Research Questions
This study aimed to answer four research questions:
1. What effects does retention status have on overall goal orientation,
mastery goal orientation, and self-efficacy?
2. What effect does the grade of retention have on goal orientation, mastery
goal orientation and self-efficacy?
3. What effect does the timing of retention have on student performance in
reading and writing?
4. What effects does retention status have on student performance in reading
and writing?
Research Design
In this study, a hierarchical linear regression was used to assess the
motivational and academic differences between retained and nonretained students.
There was an assessment of the differences between students who were retained in
early primary grades versus intermediate grades. In addition, the researcher
examined gender and language development variables. The independent variables
for this study were (a) retention status, (b) grade of retention, (c) gender, (d) grade,
and (f) language proficiency. The dependent variables for this study are (a) level of
self-efficacy, (b) goal orientation, (c) academic performance in reading, and (d)
academic performance in writing.

56
Population and Sample
Stratified purposeful sampling used during the selection of the students. The
sample was drawn from four low-achieving intermediate schools in a large urban
district in Southern California for the motivational survey. The school district
consists of a primary disadvantaged population with 95% Hispanic, 85% Free and
Reduced Lunch, 83% English Learners and 58% of the parents not graduating high
school. All students were either in the sixth, seventh or eighth grade. The units of
analysis were both individual students and groups of students including language
proficiency, grade, and gender. The expectation was that there would be a combined
total of over 125 students from four intermediate schools. This was an accurate
figure since each intermediate school has a student population of approximately
1,600 students with approximately 40% of the students retained some time during
their kindergarten through eighth grade educational experience. This number of
students provided the researcher with a large enough sample size to detect
statistically significant results. All students who returned the parent permission slips
along with the student permission slips and had three years of academic data were
included in the study. To encourage participation and reach the desired 125 students,
both the participating and nonparticipating students had a chance to enter a drawing
for gift certificates when they returned the parent and student permission slips. There
was a separate drawing at each site to encourage participation and maintain equity of
incentives for each school site. The researcher attended the Back to School Night

57
and family night meetings for parents to further explain the study and answer
questions in person.
The sample was limited to participants at these four intermediate schools due
to the homogeneity of the school sites in relation to their minority, low
socioeconomic, English Learner, and Gifted and Talented populations. All of the
school sites had a large percentage of Hispanic students ranging from 92% to 99%.
The schools had a similar percentage of free and reduced lunch students with 84% to
95% of the students participating in the federal program. Another similar
demographic characteristic was the percentage of English Language Learners
ranging from 62% to 67% at all of the schools except School B, which has only 47%
of English Learners. In addition, there was comparability in the schools parent
education level and 2010 and 2011Academic Performance Index (API). All of the
schools had a low percentage of parents who have higher education than high school
with the majority of their parents not reaching high school graduate status. All of the
schools were well below the API state expectation of 800 with all of the schools
except School B with API ranging from 630 to 652. Many of the schools had been
named a Persisting Low Achieving School (PLAS) this past spring or were in danger
of being named a PLAS if they do not make substantial progress during the
forthcoming school year. School B appeared to have the least similar characteristics
from the other three schools. When the data analysis was being compiled, it was
decided that School B should not excluded and remained in the study. Table 3.1

58
provides a summary of the demographic information of the four intermediate schools
used in the study.

Table 3.1
Intermediate Schools Demographic Data
Coding
Label
% of
Hispanic
Students
% of
Free and
Reduced
Lunch
% of
English
Language
Learners
% of
Gifted and
Talented
Students Parent Education Level
2010
API
2011
API
School
A
98% 92% 65% 7%
72% Non High School Graduate
19% High School Graduate
630 648
School
B
92% 84% 47% 12%
48% Non High School Graduate
29% High School Graduate
713 711
School
C
96% 92% 67% 7%
73% Non High School Graduate
16% High School Graduate
652 692
School
D
97% 90% 62% 7%
75% Non High School Graduate
17% High School Graduate
641 656

The motivational survey sample of 134 was limited to participants who were
in either the sixth, seventh or eighth grade at one of these intermediate schools. The
researcher used purposeful sampling to ensure equal representation of male and
female students as well as retained and nonretained students. These students
represent an ideal population for the research questions for three reasons: (a) Range
of students throughout middle school to see the effects of the transition from
elementary school; (b) middle school is the time period when motivation notably
decreases; and (c) the benefits of retention begin to disappear after the age of 14.

59
For the academic performance measures, all ninth and tenth graders currently
enrolled in any of the 8 high schools in the school district with performance data
from their sixth, seventh and eighth grade school years were included in the sample.
Unlike the motivational survey, the large sample of 6,397 students for the academic
performance measures allowed the researcher to have high statistical power.
Instrumentation
The students were asked to complete a self-efficacy and goal orientation
survey (Appendix D and E) with one section being a five-point Likert scale ranging
from not at all true to very true and another section 0 to 100 ranging from cannot do
it at all to highly certain can do. Due to the need for careful instrument selection, the
researcher administered a survey adapted from previously established surveys on
self-efficacy that had all been validated with low socioeconomic and middle school
children. Both of these surveys are available on the public domain.
Patterns of Adaptive Learning Scales (PALS)
The researcher used three parts of Carol Midgley’s 2000 Manual for Patterns
of Adaptive Learning Scales including the sections on Mastery Goal Orientation
(Revised), Academic Efficacy, and Skepticism About the Relevance of School for
Future Success. The students were asked to answer a Likert scale of one to five. One
was strongly disagree to five, which meant strongly agree. The mastery goal
orientation section included five items that had a Cronbach’s alpha of .85, mean of
4.15, standard deviation of 0.88, and skewness of -1.13 in previous studies
completed by Usher and Pajares. The mastery goal survey included responses such

60
as “It’s important to me that I learn a lot of new concepts this year” and “One of my
goals in class is to learn as much as I can.” The academic efficacy section included
five items that had a Cronbach’s alpha of .78, mean of 4.20, standard deviation of
0.71, and skewness of -1.02 in previous studies. Representative questions from the
academic efficacy section were “I’m certain I can master the skills taught in class
this year” and “Even if the work is hard, I can learn it.” The Skepticism About the
Relevance of School for Future Success section contained six items that had a
Cronbach’s alpha of .83, mean of 1.95, standard deviation of 0.92, and skewness of
1.00 in previous studies. Two of the questions from the Skepticism Regarding the
Relevance of School for Future Success survey were “Even if I do well in school, it
will not help me have the kind of life I want when I grow up” and “Getting good
grades in school will guarantee that I will get a good job when I grow up.” Due to
the high percentage of population who are English Learners and the need for access
of the Spanish-speaking parents to the survey, the survey was translated by a state
certified translator and reviewed by a second translator. All students took the survey
in English. Within this study the following Cronbach’s alpha were obtained:
Overall Goal Orientation.
In this study, the internal consistency of the overall 16-item Goal Orientation
scale was found to be adequate (! = .79) with single-item deletions making
negligible improvements to the scale’s alpha. As a result, all 16-items were retained
in a single scale comprised of the average of respondents’ scores.

61
Goal Orientation – Mastery Subscale.
The internal consistency of the five-item Goal Orientation Mastery subscale
was found to be adequate (! = .71) with single-item deletions making minimal
improvements to the scale’s alpha in this study. As a result, all five items were
retained in a single scale comprised of the average of respondents’ scores.
Goal Orientation – Academic Efficacy.
In this study, the internal consistency of the five-item Goal Orientation
Academic Efficacy subscale was found to be adequate (! = .79) with single-item
deletions making negligible improvements to the scale’s alpha. As a result, all five
items were retained in a single scale comprised of the average of respondents’
scores.
Goal Orientation – Skepticism About the Relevance of School for Future
Success.
In this study, the internal consistency of the six-item Goal Orientation
Skepticism About the Relevance of School for Future Success subscale was found to
be lower than anticipated (! = .60). The removal of two items — Question 13
“Doing well in school improves my chances of having a good life when I grow up”
and Question 14 “Getting good grades in school will guarantee that I will get a good
job when I grow up” — yielded a substantially higher overall alpha (! = .69); thus,
only a four-item scale was retained for analysis.

62
Children’s Multidimensional Self-Efficacy Scales
In addition, the survey contained 10 items from Bandura’s Children’s
Multidimensional Self-Efficacy Scale with a reported Cronbach’s !s ranging from
.80 to .87. Usher and Pajares used the same scale items in 2006 with middle school
students, and they obtained a ! coefficient of .84. In this study, the internal
consistency of the 10-item Self-efficacy Scale was found to be adequate (a = .87),
with single-item deletions failing to make any improvements to the scale’s alpha. As
a result all 10-items were retained in a single scale comprised of the average of
respondents’ scores.
The students were asked to rate their degree of confidence by recording a
number from 0 to 100 using the scale of 0 meaning cannot do it at all to 100 which
meant highly certain can do. Five questions were taken from the Self-Efficacy for
Academic Achievement, which included questions asking about their degree of
confidence to “learn reading, writing and language skills” or “learn English
grammar.” Five additional questions were taken from the Self-Efficacy for Self-
Regulated Learning. Two of these questions inquired about their confidence to
“finish my homework assignments by deadlines” and “remember well information
presented in class and textbooks.”
Due to the high percentage of population who are English Learners and the
need for access of the Spanish-speaking parents to the survey, the survey was
translated by a state certified translator and reviewed by a second translator. All
students took the survey in English.

63
To further ensure the internal consistency of the set of items with a minority
and low socioeconomic population, the researcher administered the survey to 30
randomly selected seventh and eighth grade students to measure the Cronbach’s
Alpha. The researcher ensured that the survey was unidimensional in that the first
half of the survey matches the second half of the survey and there was a Cronbach’s
Alpha between .7 to .9. Since one of the subscales had a Cronbach’s Alpha is under
.7, the researcher ran a factor analysis and used the rotated component matrix to
identify items that should be removed from the survey to improve the alpha score on
the Goal Orientation Skepticism About the Relevance of School for Future Success
subscale. No subscales had a Cronbach’s alpha over .9, no items were removed for
redundancy.
Each one of the surveys included items that required reverse coding to ensure
participants were paying attention to the survey and to ask the questions from
multiple viewpoints.
California English Language Development Test (CELDT)
CELDT is a statewide English language proficiency test that must be
administered to student in kindergarten through grade twelve whose primary
language is not English and to students previously identified as English Learners
who have not be reclassified as fluent English proficient (RFEP). CELDT assesses
four domains of listening, speaking, reading and writing in English and is aligned to
the English language development (ELD) standards. The results of the assessment

64
are broken down into five proficiency strands including Beginning, Early
Intermediate, Intermediate, Early Advanced and Advanced.
California Standards Test (CST)
CST measures student’s progress toward achieving California state-adopted
academic content standards in language arts, math, science and social studies. The
content standards describe what students should be able to do in each grade and
subject tested. For this study, only the English Language Arts assessment was
analyzed. The students take a multiple choice test which results are broken down
into five proficiency bands including Far Below Basic, Below Basic, Basic,
Proficient and Advanced.
California Modified Assessment (CMA)
CMA is an assessment for students who have an individualized educational
program (IEP). The purpose of the CMA is to allow students with disabilities greater
access to an assessment that helps measure how well they are achieving. Special
Education students may take the assessment if the accommodation is noted in their
IEP and the student scored below basic on far below basic on the CST the previous
year. The students take a multiple choice test which results are broken down into
five proficiency bands including Far Below Basic, Below Basic, Basic, Proficient
and Advanced.
California Alternate Performance Assessment
CAPA is designed to assess special education students with significant
disabilities who cannot participate in the CST or the CMA even with

65
accommodations. CAPA links directly to the California academic content standards
at each grade level and reflects the portions of the content standards from
kindergarten through high school that are accessible to students with significant
cognitive abilities. The students take a multiple choice test which results are broken
down into five proficiency bands including Far Below Basic, Below Basic, Basic,
Proficient and Advanced.
English Language Arts (ELA) Benchmark
The ELA Benchmark is a district managed benchmark, which is created by
Intel Assess. The benchmark’s purpose is to mirror the standards assessed on the
CST to determine if students are effectively acquiring grade level standards. The
assessment is administered in April six weeks prior to CST administration. Pearson
Learning compared he ELA benchmark to the CST with a correlation of .75. As with
the CST, the students take a multiple choice test which results are broken down into
five proficiency bands including Far Below Basic, Below Basic, Basic, Proficient
and Advanced.
District Writing Prompt
The district writing prompt is writing assessment that assess the writing of
students on six key areas of writing task, thesis and support, organization, sentence
variety/structure, vocabulary and conventions. The students are scored on a five
point rubric including Far Below Basic (1), Below Basic (2), Basic (3), Proficient
(4), and Advanced (5). The students’ writing prompts are scored by a trained group
of 50 teachers. To ensure inter-rater reliability, all teachers that score the writing

66
assessment are trained for 90 minutes on the utilization of the rubric and are
provided anchor papers exemplifying papers at each level in the rubric. Teachers are
provided randomly selected writing assessments. Each paper is scored by two
different teachers. Any paper that has a score difference of more than one rubric
level is read by a third lead teacher.
Data Collection
Upon approval from the University of Southern California’s IRB Office and
the Research and Evaluation Department of the school district, the researcher
initiated data collection. The primary method of recruitment of participants for the
study was personalized letters providing the parents and students an overview of the
research study to be sent to the parents of each sixth, seventh, and eighth grade
student at the four intermediate schools. Attached to the overview letter was the
parental consent form and child assent form (see Appendix A and B). The consent
forms outlined the purpose of the study, defined confidentiality guidelines, and stated
the participants’ ability to exit the study at anytime. Participants received the chance
to enter into a drawing at each school site if they returned the permission slip. They
could enter the drawing regardless of a positive or negative response to be in the
study. The parents and participants were told that the research was interested in
studying students’ level of self-efficacy as well as examining the factors, which lead
to academic success.
The extensive review of their longitudinal achievement data and the
completion of the self-efficacy survey only occurred for students who returned both

67
the parental consent and child assent forms to be part of the study. To maintain
anonymity, each school site was coded with the identification of “School A, School
B, School C, or School D.” A separate list was formed for each school site with
students identified only by their student identification number and birth date. Their
name was not included on the data list. The achievement data was obtained through
the data management system, Data Director included the last four years of statewide
measures such as CST and CELDT as well as local measures including district-wide
language arts benchmarks, writing prompts, and grades. The scale score for each
assessment was used so that each score is maintained as a continuous variable. For
the CST scores for years 2007-2011, the student received their scale score ranging
from the possible score of 200-600. On the 2007-2011 CELDT, the student received
an overall scale score within the possible range of 248-741. For the language arts
benchmark, the students received a percentage score of 0-100%. On the district-
wide writing proficiency, the student was judged by the district-wide criteria and
received a score of 1-5. For schools that used a standards-based grading scale, the
students received their corresponding language arts grade of 1to 5. For the schools
that still used letter grades, the students received a 1 for an F, 2 for D, 3 for C, 4 for
B, and 5 for A. The demographic data such as gender, ethnicity, retention status, and
grade of retention was obtained through the student information system Aeries. This
information was updated on a monthly basis by the school sites and by the parents on
a bi-annual basis to ensure that it is accurate. All boys were coded a “0” and “1” for
all girls. Ethnicity was be coded “1” for Hispanic and “0” for non-Hispanic. The

68
retention status will be coded “0” for retained, “1” for not retained, and “2” if unable
to determine retention status. Any student with an unidentified retention status was
excluded from the study.
The timing of data collection occurred during the fall semester after the
receipt of the permission slips. The permission slips were dispersed in October
2011. The survey pilot occurred at the end of October 2011. The validated survey
was administered one time during the month of November during their first period
class. Any student not present that day was omitted from the study. Due to the high
percentage of population who are English Learners and the need for access of the
Spanish-speaking parents to the survey, the survey was translated by a state certified
translator and reviewed by a second translator. All students took the survey in
English.
Table 3.2 identifies which primary data sources used to obtain the data for
each of the research questions.

69
Table 3.2
Primary Data Sources
Research Questions Data Variable Primary Data Sources
Secondary Data
Sources
Research Question 1 —
What effects does retention
status have on overall goal
orientation, mastery goal
orientation, and self-
efficacy?
Self-Efficacy and Goal
Orientation Survey
Dependent Survey Results If conflicting
data, review of
student on-line
cum files Retention Status Independent Aeries Student
Information System to
identify gender,
retained or nonretained
status
Gender Independent
Language Proficiency Independent
Research Question 2 —
What effect does the grade
of retention have on goal
orientation, mastery goal
orientation and self-efficacy?
Self-Efficacy and Goal
Orientation Survey
Dependent Survey Results If conflicting
data, review of
student on-line
cum files Grade of Retention Independent Aeries Student
Information System to
identify gender and
retention grade if
retained
Language Proficiency Independent
Gender Independent
Research Question 3 —
What effect does the timing
of retention have on student
performance in reading and
writing?
2007-2011 ELA CST Dependent Data Director to
identify all assessment
scores
If conflicting
data, review of
student on-line
cum files
2007-2011 CELDT Dependent
2011 ELA Benchmark Dependent
2011 district writing
prompt #1
Dependent
2011 Final grades Dependent
Grade of Retention Independent Aeries Student
Information System to
identify gender and
retention grade if
retained
Gender Independent
Language Proficiency Independent
Research Question 4 —
What effects does retention
status have on student
performance in reading and
writing?
2007-2011 ELA CST Dependent Data Director to
identify all assessment
scores
If conflicting
data, review of
student on-line
cum files
2007-2011 CELDT Dependent
2011 ELA Benchmark Dependent
2011 district writing
prompt #1
Dependent
2011 Final grades Dependent
Retention Status Independent Aeries Student
Information System to
identify gender,
economic status and
ethnicity
Gender Independent
Language Proficiency Independent

70
Data Analysis
All of the data from the motivational survey was combined onto the Excel
sheet of the information from Aeries and Data Director. The responses to the
motivational survey were hand entered for the participating students. After data
entry and coding, the data was cleaned to check for data entry errors or missing data.
For the variable “Grade of Retention” it was necessary to modify the variable prior
to analyses in the high school dataset. Specifically, for students who were indicated
had been retained twice (example response: 1 & 6) only the earliest year of retention
was reserved for analysis. Once the data was cleaned, the data was examined to
ensure that School B or other schools do not have significantly different scores than
the other schools with no inconsistencies found. All of the data was imported into the
Statistical Package for Social Sciences (SPSS) program and analyzed using SPSS.
Before the data is analyzed through hierarchalinear regressions, the researcher
determined the Cronbach’s alpha of the four different sections of the motivational
survey. No issues were found during the pilot or study.
All four research questions were answered with hierarchical linear regression
model with block entry of the variables in Step 1. The variables of grade level, EL
status and gender were entered as a group of variables to estimate the effect of the
category of variables on the outcome. The block entry of the variables also allowed
the researcher to determine whether particular variables explained statistically
significantly more variance than other variables. Within the Step 2, the variable of

71
retention status or grade of retention was entered last in the regression equation to
isolate the unique variance for that particular variable.
The significant results of this study are reported in Chapter Four. As noted in
Field (2009), “a bad model will have regression coefficients of 0 for the predictors.”
As a result, models determined to be ‘bad’ predictors of the outcomes under
investigation, as demonstrated by a lack of overall statistical significance, will not be
investigated further, as all individual predictors can be assumed to be non-significant
as well. Further investigation of the beta values of individual predictors would be
analogous to conducting post hoc tests following an ANOVA that failed to reach
statistical significance. In either situation, there would be no evidence to justify
treating significant post hoc analyses (or significant beta values) as anything other
than spurious findings (i.e. a Type I error). Chapter Five includes a discussion of the
main findings, implications for the use of retention as an intervention practice, and
possible areas of future research.

72
CHAPTER FOUR
RESULTS
This chapter presents the statistical outcomes for the previously presented
research questions:
1. What effects does retention status have on overall goal orientation,
mastery goal orientation and self-efficacy?
2. What effect does the grade of retention have on goal orientation, mastery
goal orientation and self-efficacy?
3. What effect does the timing of retention have on student performance in
reading and writing?
4. What effects does retention status have on student performance in reading
and writing?
Preliminary Analysis
The study used the hierarchical linear regression model with block entry of
the variables in Step 1. The variables of grade level, EL status and gender were
entered as a group of variables to estimate the effect of the category of variables on
the outcome. The block entry of the variables also allowed the researcher to
determine whether particular variables explained statistically significantly more
variance than other variables. Within the Step 2, the variable of retention status or
grade of retention was entered last in the regression equation to isolate the unique
variance for that particular variable.

73
Goal Orientation
In the area of goal orientation, the students completed three parts of the
Midgley’s Patterns of Adaptive Learning Scales (PALS). As utilized historically
with this scale, subscales to represent the three distinct differences of Mastery Goal
Orientation, Academic Efficacy, and Skepticism about the Relevance of School for
Future Success disaggregated the data from PALS. Prior to combining the scale
items under study, Cronbach's alpha was first computed to determine internal
consistency. After running the initial assessment for internal consistency, each
subscale’s internal consistency was assessed. The Overall Goal Orientation scale
and the subscales had Cronbach’s alpha between .69 and .79.
Self-Efficacy
In the area of self-efficacy, the students completed 10 items from the
Bandura’s Children’s Multidimensional Self-Efficacy Scale which resulted in a
Cronbach’s alpha of .86.
Tables 4.1, 4.2 and 4.3 speak to student demographics including gender,
grade level retained, and age of students at time of motivational survey
administration.

74
Table 4.1
Gender of Students, Student Sample of Motivational Survey n=134
Gender Total Number Retained % Retained
Male 53 (40%) 8 15%
Female 81 (60%) 19 23%

Table 4.2
Grade Retained, Student Sample of Motivational Survey n=134
Grade Level
Number Retained Within
Grade Level
Kinder 5
First 13
Second 12
Third 3
Fourth 0
Fifth 0
Sixth 0
Seventh 0
Eighth 0

75
Table 4.3
Age of Students, Student Sample of Motivational Survey n=134
Age % of Students
12 24%
13 43%
14 29%

Table 4.4
Language Proficiency of Students, Student Sample of Motivational Survey n=134
Language Proficiency % of Students
English Learner 53%
IFEP 1%
RFEP 32%
EO 8%

76
Tables 4.5, 4.6 and 4.7 speak to student demographics, including gender,
grade retained and language proficiency of the students currently in 9th and 10th
grade that were included in the academic performance study.

Table 4.5
Gender of Students, Student Sample of Academic Performance n=6397
Gender Total Number Retained % Retained
Male 3200 880 28%
Female 3197 844 26%

Table 4.6
Grade Retained, Student Sample of Academic Performance n=6397
Grade Level
Number Retained Within
Grade Level
Kinder 189
First 639
Second 343
Third 225
Fourth 96
Fifth 40
Sixth 89
Seventh 34
Eighth 40
Ninth 10
Tenth 2

77
Table 4.7
Language Proficiency of Students, Student Sample of Academic Performance
n=6397
Language Proficiency % of Students
English Learner 45%
IFEP 5%
RFEP 45%
EO 9%

The following information provides an overview of all of the statically
significant findings. Table 4.8 reflects the significant findings found in relation to
the motivational construct of goal orientation, mastery goal orientation and self-
efficacy and the effects of retention status and grade of retention. The covariates of
gender, grade, and language proficiency were assessed for variance. The subsequent
table speaks to the significant interaction between academic performance and
retention status and grade of retention.

78
Table 4.8
Significant Findings
Affected by
Retention
Status
Affected by
Grade of
Retention
Affected by
Language
Proficiency
Affected
by
Gender
Affected
by Grade
Level
Overall Goal Orientation X X X X
Mastery Goal Orientation X X
Academic Efficacy Goal
Orientation

Skepticism About the
Relevance of School for
Future Success
X X
Self-Efficacy
7
th
Grade CELDT X
8
th
Grade CELDT X
7
th
Grade CST X X X X X
8
th
Grade CST X X X X X
7
th
Grade CMA X
8
th
Grade CMA X X X
7
th
Grade CAPA
8
th
Grade CAPA X X
7
th
Grade ELA Benchmarks X X X X
8
th
Grade ELA Benchmarks X X X X
7
th
Grade District Writing
Prompt
X X X X
8
th
Grade District Writing
Prompt
X X X X
Cumulative GPA X X X X X
X= significant finding, Blank= no significant finding. CELDT= California English Language
Development Test, CST=California Standards Test, CMA= California Modified Assessment, CAPA=
California Alternate Performance Assessment, ELA=English Language Arts, GPA= Grade Point
Average

79
Research Question One
Research Question One: What effect does retention status have on overall goal
orientation, mastery goal orientation and self-efficacy?
Overall Goal Orientation
In order to determine whether middle school students’ retention status
predicts their goal orientations after controlling for relevant covariates, hierarchical
linear regression modeling was conducted. Due to strong theoretical plausibility, a
total of three covariates of gender, EL status, and grade level were force-entered into
the model in the first block. Both EL status and grade level were dummy coded, with
EL and sixth grade serving as reference groups. Retention status was then
investigated in the second block as shown in Table 4.9.
The final model revealed that retention status did predict overall goal
orientation with those who were retained showing lower overall goal orientation
scores. Retention status explained about 3% of the variance in students’ goal
orientations after controlling for gender, EL status, and grade level. The covariates of
gender, EL status, and grade level together explained about 19% of the variability
observed in students’ goal orientation scores. Specifically, seventh graders showed
higher goal orientation scores than the sixth grade reference group, and RFEP
students showed higher goal orientation scores than EL students. In the second step
of the model, females were found to have higher goal orientation scores than males
although this was not evident in the first step of the model. When comparing the
relative power of each statistically significant variable through each variable’s

80
standardized beta (!), it is evident that seventh grade status was the single strongest
predictor of overall goal orientation scores.

Table 4.9
Summary of Hierarchical Linear Regression of Retention Status on Goal Orientation
(N = 117)
Variable B SE B "
Step 1
Grade – 7
th
.35 .11 .36**
Grade – 8
th
.18 .12 .16
EL Status – IFEP .38 .20 .17
EL Status – RFEP .26 .10 .24**
EL Status – EO .22 .15 .13
Gender .14 .09 .14
Step 2
Grade – 7
th
.38 .11 .38***
Grade – 8
th
.19 .12 .18
EL Status – IFEP .32 .20 .14
EL Status – RFEP .21 .10 .20*
EL Status – EO .16 .15 .09
Gender .15 .09 .15*
Retention Status .22 .11 .18*
Note. R
2
= .19 for Step 1 (p = .001); #R
2
= .03 (p = 0.05). EL=English Learner, IFEP=Initial Fluent
English Proficient, RFEP=Redesignated Fluent English Proficient, EO=English Only
* p $ 0.05. ** p $ 0.01. *** p $ .001.

81
Mastery Goal Orientation
In order to determine whether middle school students’ retention status
predicted their mastery goal orientations after controlling for relevant covariates,
hierarchical linear regression modeling was conducted as shown in Table 4.10. Due
to strong theoretical plausibility, a total of three covariates of gender, EL status, and
grade level were force-entered into the model in the first block. Both EL status and
grade level were dummy coded with EL and sixth grade serving as reference groups.
Retention status was then investigated in the second block.
The final model revealed that retention status did not predict Mastery Goal
Orientation. However, covariates did predict Mastery Goal Orientations. Gender, EL
status, and grade level together explained about 16% of the variability observed in
students’ Mastery Goal Orientation scores. This means that students who were in
seventh grade were significantly more likely to have higher Mastery Goal
Orientation than the sixth grade reference group, and RFEP students and EO students
were more likely to have higher Mastery Goal Orientation than EL students.

82
Table 4.10
Summary of Hierarchical Linear Regression of Retention Status on Goal Orientation
- Mastery Goal Subscale Scores (N = 118)
Variable B SE B "
Step 1
Grade – 7
th
.28 .12 .25*
Grade – 8
th
.15 .14 .13
EL Status – IFEP .37 .22 .15
EL Status – RFEP .31 .11 .26**
EL Status – EO .44 .17 .23**
Gender .13 .10 .12
Step 2
Grade – 7
th
.30 .12 .27*
Grade – 8
th
.17 .13 .14
EL Status – IFEP .31 .22 .12
EL Status – RFEP .27 .11 .23*
EL Status – EO .38 .17 .20*
Gender .15 .10 .14
Retention Status .21 .13 .15
Note. R
2
= .16 for Step 1 (p = .002); #R
2
= .02 (p = 0.10). EL=English Learner, IFEP=Initial Fluent
English Proficient, RFEP=Redesignated Fluent English Proficient, EO=English Only
* p $ 0.05. ** p $ 0.01.

83
Academic Efficacy Goal Orientation
In order to determine whether middle school students’ retention status
predicted their scores on the Academic Efficacy Goal Orientation subscale after
controlling for relevant covariates, hierarchical linear regression modeling was
conducted. Due to strong theoretical plausibility, a total of three covariates of gender,
EL status, and grade level were force-entered into the model in the first block. Both
EL status and grade level were dummy coded, with EL and sixth grade serving as
reference groups. Retention status was then investigated in the second block.
Hierarchical linear regression modeling revealed that the covariates together
failed to serve as a statistically significant predictor of students’ academic efficacy
goal orientation subscale scores (F
(6,111)
= 1.24, p = .29). Inclusion of students’
retention status failed to result in a statistically significant final model (F
(7,110)
= 1.51,
p = .17).
Skepticism About the Relevance of School for Future Success Goal Orientation
In order to determine whether middle school students’ retention status
predicted their scores on the Skepticism About the Relevance of School for Future
Success subscale after controlling for relevant covariates, hierarchical linear
regression modeling was conducted as shown in Table 4.11. Due to strong
theoretical plausibility, a total of three covariates of gender, EL status, and grade
level were force-entered into the model in the first block. Both EL status and grade
level were dummy coded, with EL and sixth grade serving as reference groups.
Retention status was then investigated in the second block.

84
Table 4.11
Summary of Hierarchical Linear Regression of Retention Status on Goal
Orientation—Skepticism About the Relevance of School for Future Success (N =
117)
Variable B SE B "
Step 1
Grade – 7
th
.54 .22 .28*
Grade – 8
th
.20 .24 .09
EL Status – IFEP .88 .40 .20*
EL Status – RFEP .46 .20 .22*
EL Status – EO .30 .31 .09
Gender .09 .18 .05
Step 2
Grade – 7
th
.56 .22 .29*
Grade – 8
th
.21 .24 .10
EL Status – IFEP .82 .40 .19*
EL Status – RFEP .41 .20 .20*
EL Status – EO .24 .31 .07
Gender .11 .18 .05
Retention Status .22 .23 .09
Note. R
2
= .14 for Step 1 (p = .01); #R
2
= .01 (p = 0.34). EL=English Learner, IFEP=Initial Fluent
English Proficient, RFEP=Redesignated Fluent English Proficient, EO=English Only
* p $ 0.05.

85
The final model revealed that retention status did not predict Relevance of
School for Future Success subscale scores. However, the covariates of gender, EL
status, and grade level together explained about 14% of the variability observed in
students’ Relevance of School for Future Success subscale scores. This means that
students who were in the seventh grade were significantly more likely to have higher
Relevance of School for Future Success than the sixth grade reference group, and
RFEP students and IFEP students were significantly more likely to have higher
Relevance of School for Future Success than EL students.
Self-Efficacy
In order to determine whether middle school students’ retention status
predicted their self-efficacy scores after controlling for relevant covariates,
hierarchical linear regression modeling was conducted. Due to strong theoretical
plausibility, a total of three covariates of gender, EL status, and grade level were
force-entered into the model in the first block. Both EL status and grade level were
dummy coded with EL and sixth grade serving as reference groups. Retention status
was then investigated in the second block.
Hierarchical linear regression modeling revealed that the covariates together
failed to serve as a statistically significant predictor of students’ academic efficacy
goal orientation subscale scores (F
(6,110)
= 1.45, p = .20). Inclusion of students’
retention status failed to result in a statistically significant final model (F
(7,109)
= 1.56,
p = .15)

86
Research Question Two
Research Question Two: What effects does the grade of retention have on overall
goal orientation, mastery goal orientation and self-efficacy?
Overall Goal Orientation
In order to determine whether middle school students’ retention status
predicted their goal orientations after controlling for relevant covariates, hierarchical
linear regression modeling was conducted as shown in Table 4.12. The grade of
retention automatically discarded any student who was not retained from the
analysis. In this analysis, EL status of IFEP was excluded as no IFEP students were
included in the final model. Due to strong theoretical plausibility, a total of three
covariates of gender, EL status, and grade level were force-entered into the model in
the first block. Both EL status and grade level were dummy coded, with EL and sixth
grade serving as reference groups. Retention status was then investigated in the
second block.
The final model revealed that grade of retention did not predict overall goal
orientation. However, the covariates of gender, EL status, and grade level together
did predict overall goal orientation and explained 38% of the variability observed in
students’ overall goal orientation scores. This means that students who were in
seventh grade were significantly more likely to have higher goal orientation scores
than sixth graders, the reference group. EO students were significantly more likely to
have higher overall goal orientation scores than EL students only before grade of
retention was added to the model.

87

Table 4.12
Summary of Hierarchical Linear Regression of Grade of Retention on Overall Goal
Orientation (N = 28)
Variable B SE B "
Step 1
Grade – 7
th
.47 .22 .46*
Grade – 8
th
-.08 .27 -.07
EL Status – RFEP .33 .23 .25
EL Status – EO 1.05 .51 .38*
Gender .16 .20 .14
Step 2
Grade – 7
th
.48 .23 .46*
Grade – 8
th
-.08 .28 -.07
EL Status – RFEP .33 .23 .25
EL Status – EO 1.05 .52 .38
Gender .16 .21 .15
Grade of Retention .01 .10 .02
Note. R
2
= .38 for Step 1 (p = .05); #R
2
< .01 (p = 0.92). EL=English Learner, IFEP=Initial Fluent
English Proficient, RFEP=Redesignated Fluent English Proficient, EO=English Only
* p $ 0.05.

88
Mastery Goal Orientation
In order to determine whether middle school students’ grade of retention
predicted their scores on the Mastery Goal Orientation subscale after controlling for
relevant covariates, hierarchical linear regression modeling was conducted. Due to
strong theoretical plausibility, a total of three covariates of gender, EL status, and
grade level were force-entered into the model in the first block. Both EL status and
grade level were dummy coded, with EL and sixth grade serving as reference groups.
Retention status was then investigated in the second block.
Hierarchical linear regression modeling revealed that the covariates together
failed to serve as a statistically significant predictor of students’ academic efficacy
goal orientation subscale scores (F
(5,22)
= 1.45, p = .25). Inclusion of students’ grade
of retention failed to result in a statistically significant final model (F
(6,21)
= 1.18, p =
.36)
Academic Efficacy
In order to determine whether middle school students’ grade of retention
predicted their scores on the Academic Efficacy subscale after controlling for all
three covariates, hierarchical linear regression modeling was conducted as
demonstrated in Table 4.13. Due to strong theoretical plausibility, a total of three
covariates of gender, EL status, and grade level were force-entered into the model in
the first block. Both EL status and grade level were dummy coded with EL and sixth
grade serving as reference groups. Retention status was then investigated in the
second block.

89

Table 4.13
Summary of Hierarchical Linear Regression of Grade of Retention on Academic
Efficacy (N = 28)
Variable B SE B "
Step 1
Grade – 7
th
.69 .31 .48*
Grade – 8
th
-.04 .38 -.02
EL Status – RFEP .09 .31 .05
EL Status – EO 1.84 .70 .48*
Gender .39 .28 .25
Step 2
Grade – 7
th
.72 .32 .50*
Grade – 8
th
-.01 .38 -.01
EL Status – RFEP .10 .32 .05
EL Status – EO 1.79 .71 .46*
Gender .39 .28 .25
Grade of Retention .08 ..14 .10
Note. R
2
= .40 for Step 1 (p = .04); #R
2
= .01 (p = 0.56). EL=English Learner, IFEP=Initial Fluent
English Proficient, RFEP=Redesignated Fluent English Proficient, EO=English Only
* p $ 0.05.

90
Hierarchical linear regression modeling revealed that the covariates together
served as a statistically significant predictor of students’ Academic Efficacy goal
orientation subscale scores (F
(5,22)
= 1.15, p = .04). Inclusion of students’ grade of
retention failed to make a statistically significant contribution to the model, however
(F
(1,21)
= 0.35, p = .56).
The final model revealed that grade of retention did not predict Academic
Efficacy. However, the covariates did predict Academic Efficacy. Gender, EL status,
and grade level together explained about 40% of the variability observed in students’
overall goal orientation scores. Grade level and language proficiency were shown to
be statistically significant with Academic Efficacy. This means that students who
were in seventh grade were significantly more likely to have higher goal orientation
scores than the sixth grader reference group, and EO students were significantly
more likely to have higher goal orientation scores than EL students.
Skepticism About the Relevance of School for Future Success
In order to determine whether middle school students’ grade of retention
predicted their scores on the Skepticism About the Relevance of School for Future
Success subscale after controlling for relevant covariates, hierarchical linear
regression modeling was conducted. Due to strong theoretical plausibility, a total of
three covariates of gender, EL status, and grade level were force-entered into the
model in the first block. Both EL status and grade level were dummy coded, with EL
and sixth grade serving as reference groups. Retention status was then investigated in
the second block.

91
Hierarchical linear regression modeling revealed that the covariates together
failed to serve as a statistically significant predictor of students’ Skepticism About
the Relevance of School for Future Success goal orientation subscale scores (F
(5,22)
=
0.83, p = .54). Inclusion of students’ grade of retention failed to result in a
statistically significant final model (F
(6,21)
= 0.67, p = .67).
Self-Efficacy
In order to determine whether middle school students’ grade of retention
predicted their self-efficacy scores after controlling for relevant covariates,
hierarchical linear regression modeling was conducted. Due to strong theoretical
plausibility, a total of three covariates of gender, EL status, and grade level were
force-entered into the model in the first block. Both EL status and grade level were
dummy coded with EL and sixth grade serving as reference groups. Retention status
was then investigated in the second block.
Hierarchical linear regression modeling revealed that the covariates together
failed to serve as a statistically significant predictor of students’ self-efficacy scores
(F
(5,22)
= 0.83, p = .55). Inclusion of students’ grade of retention failed to result in a
statistically significant final model (F
(6,21)
= 0.72, p = .64).
Research Question Three
Research Question Three: What effect does the timing of retention have on student
performance in reading and writing?
In order to determine the impact of grade of retention on student performance
in reading and writing, a number of outcome variables were examined including

92
California Exam Language Development Test (CELDT), California Standards Test
(CST), California Modified Assessment (CMA), California Alternative Performance
Assessment (CAPA), English Language Arts (ELA) Benchmark, District Writing
Prompt and Cumulative Grade Point Average (GPA). Each assessment addressed a
different aspect of a student’s literacy abilities. CELDT assessed a student’s
language ability in four domains of listening, speaking, reading, and writing. The
CST, CMA, and CAPA assessments were all state required assessments that were
administered once a year to assess students’ ability to master grade level standards.
Only special education students were allowed to take the CMA in lieu of the CST if
it was included in the Individual Educational Plan (IEP) and they performed Below
Basic or Far Below Basic on the CST the previous year. Only 1% of a school
district’s population can take the CAPA assessment. In addition, they must be special
education students with high needs, and the assessment must be noted in their IEP.
The ELA Benchmark served as a formative assessment used three times a year to
gauge the likelihood that a student will perform well on the CST or CMA. The
District Writing Prompt was administered three times a year and assessed a student’s
ability to demonstrate writing traits at an appropriate grade level. The cumulative
GPA was a weighted GPA that gave more weight to Honors and Advanced
Placement classes.
For each outcome variable, hierarchical linear regression modeling was
examined to investigate the impact of grade of retention after controlling for relevant
covariates. Due to strong theoretical plausibility, a total of three covariates of gender,

93
EL status, and grade level were force-entered into the model in the first block. Both
EL status and grade level were dummy coded, with EL and ninth grade serving as
reference groups. Grade of retention status was then investigated in the second block.
Seventh Grade CELDT
Hierarchical linear regression modeling revealed that the covariates together
failed to serve as a statistically significant predictor of students’ seventh grade
CELDT scores (F
(3,1107)
= 1.33, p = .26). Inclusion of students’ grade of retention
failed to result in a statistically significant final model (F
(4, 1106)
= 1.09, p = .36).
Eighth Grade CELDT
Hierarchical linear regression modeling revealed that the covariates together
failed to serve as a statistically significant predictor of students’ eighth grade
CELDT (F
(3,1038)
= 1.49, p = .22). Inclusion of students’ grade of retention failed to
result in a statistically significant final model (F
(4, 1037)
= 1.28, p = .28).
Seventh Grade CST
In order to determine whether middle school students’ grade of retention
predicted their scores on the Seventh Grade CST after controlling for all three
covariates, hierarchical linear regression modeling was conducted as demonstrated in
Table 4.14. Due to strong theoretical plausibility, a total of three covariates of
gender, EL status, and grade level were force-entered into the model in the first
block. Both EL status and grade level were dummy coded with EL and sixth grade
serving as reference groups. Retention status was then investigated in the second
block.

94
Table 4.14
Summary of Hierarchical Linear Regression of Grade of Retention on 7
th
Grade CST
(N = 1455)
Variable B SE B "
Step 1
Gender 6.03 1.76 .07***
Grade 2.87 1.77 .03
EL Status – IFEP 45.41 5.78 .16***
EL Status – RFEP 62.04 1.96 .65***
EL Status – EO 25.19 3.76 .14***
Step 2
Gender 5.82 1.75 .07***
Grade 4.23 1.79 .05*
EL Status – IFEP 46.53 5.76 .16***
EL Status – RFEP 61.74 1.96 .64***
EL Status – EO 24.27 3.75 .13***
Grade of Retention -1.82 .48 -.08***
Note. R
2
= .42 for Step 1 (p < .001); #R
2
= .01 (p < 0.001). EL=English Learner, IFEP=Initial Fluent
English Proficient, RFEP=Redesignated Fluent English Proficient, EO=English Only
* p $ 0.05. *** p $ .001.

The final model revealed that grade of retention did predict seventh grade
CST scores. However, it predicted less than 1% of the variability in students’ scores.
Therefore, although this finding was statistically significant, it was not likely

95
clinically significant. Due to the large sample size, the analyses had high statistical
power, allowing for even very small effects to be found statistically significant.
Grade of Retention was shown to be statistically significant with seventh grade CST
scores. This means that the older the students were when they were retained, the
lower their seventh grade CST score was found to be.
The covariates of gender, grade, and EL status together did predict CST
seventh grade scores and explained about 42% of the variability observed in
students’ CST seventh grade scores. Gender was shown to be statistically significant
with seventh grade CST scores. This means that female students were significantly
more likely to have higher seventh grade CST scores. Females had, on average,
scores that were 6 points higher than males. In addition, IFEP, RFEP, and EO
students were significantly more like to have higher scores than the EL reference
group. Finally, grade level was not a statistically significant predictor in the first
block but became marginally significant after grade of retention was added to the
model.
Eighth Grade CST
In order to determine whether middle school students’ grade of retention
predicted their scores on the Eighth Grade CST after controlling for all three
covariates, hierarchical linear regression modeling was conducted as demonstrated in
Table 4.15. Due to strong theoretical plausibility, a total of three covariates of
gender, EL status, and grade level were force-entered into the model in the first
block. Both EL status and grade level were dummy coded with EL and sixth grade

96
serving as reference groups. Retention status was then investigated in the second
block.

Table 4.15
Summary of Hierarchical Linear Regression of Grade of Retention on CST 8
th
Scores
(N = 1380)
Variable B SE B "
Step 1
Gender 8.59 1.89 .10***
Grade -3.57 1.90 -.04
EL Status – IFEP 46.06 6.05 .16***
EL Status – RFEP 60.81 2.07 .63***
EL Status – EO 35.07 4.15 .18***
Step 2
Gender 8.44 1.88 .09***
Grade -1.87 1.93 -.02
EL Status – IFEP 47.28 6.02 .17***
EL Status – RFEP 60.21 2.07 .62***
EL Status – EO 33.54 4.12 .17***
Grade of Retention -2.28 0.52 -.09***
Note. R
2
= .40 for Step 1 (p < .001); #R
2
= .008 (p < 0.001). EL=English Learner, IFEP=Initial Fluent
English Proficient, RFEP=Redesignated Fluent English Proficient, EO=English Only
* p $ 0.05. *** p $ .001.

97
The final model revealed that grade of retention did predict eighth grade CST
scores. However, it predicts less than 1% of the variability in students’ scores.
Therefore, although this finding was statistically significant, it was not clinically
significant. Due to the large sample size, the analyses had high statistical power,
allowing for even very small effects to be found statistically significant. The effect
was that the older the students are when they were retained, the lower their eighth
grade CST score was found to be. This was consistent with what was observed with
the seventh grade CST scores.
The covariates of gender, grade, and EL status together did predict CST
eighth grade scores and explained about 40% of the variability observed in students’
eighth grade CST scores. Gender was shown to be statistically significant with eighth
grade CST scores. This means that female students were significantly more likely to
have higher eighth grade CST scores than males. Females had, on average, scores
that were 8.5 points higher than males. In addition, IFEP, RFEP, and EO students
were significantly more likely to have higher scores than the EL reference group.
Seventh Grade CMA
In order to determine whether middle school students’ grade of retention
predicted their scores on the Seventh Grade CMA after controlling for all three
covariates, hierarchical linear regression modeling was conducted. Due to strong
theoretical plausibility, a total of three covariates of gender, EL status, and grade
level were force-entered into the model in the first block. Both EL status and grade

98
level were dummy coded with EL and sixth grade serving as reference groups.
Retention status was then investigated in the second block.
Hierarchical linear regression modeling revealed that the covariates together
failed to serve as a statistically significant predictor of students’ seventh grade CMA
scores (F
(2,70)
= 0.93, p = .40). Inclusion of students’ grade of retention failed to
result in a statistically significant final model (F
(3, 69)
= 0.67, p = .58).
Eighth Grade CMA
In order to determine whether middle school students’ grade of retention
predicted their scores on the Eighth Grade CST after controlling for all three
covariates, hierarchical linear regression modeling was conducted as demonstrated in
Table 4.16. Due to strong theoretical plausibility, a total of three covariates of
gender, EL status, and grade level were force-entered into the model in the first
block. Both EL status and grade level were dummy coded with EL and sixth grade
serving as reference groups. Retention status was then investigated in the second
block.
Hierarchical linear regression modeling revealed that the covariates together
served as a statistically significant predictor of students’ CMA 8
th
scores (F
(4,158)
=
2.47, p = .05). Inclusion of students’ grade of retention failed to make a statistically
significant contribution to the model, however (F
(1,157)
= 2.87, p = .09).

99
Table 4.16
Summary of Hierarchical Linear Regression of Grade of Retention on 8
th
Grade
CMA Scores (N = 163)
Variable B SE B "
Step 1
Gender 21.07 10.60 .16*
Grade 5.11 12.60 .03
EL Status – IFEP 112.19 64.35 .14
EL Status – EO 36.66 19.29 .15
Note. R
2
= .06 for Step 1 (p = .05) IFEP=Initial Fluent English Proficient, EO=English Only
* p <= .05.

The final model revealed that grade of retention did not predict eighth grade
CMA scores (F
(1, 157)
= 2.87, p = .09). Table 4.16 shows the impact of the covariates.
Gender was shown to be statistically significant with eighth grade CMA scores. This
means that female students were significantly more likely to have higher CMA
scores than males. Females scored, on average, 21.07 points higher on their eighth
grade CMA scores after controlling for the other variables.
Seventh Grade CAPA
In order to determine whether middle school students’ grade of retention
predicted their scores on the Seventh Grade CAPA after controlling for all three
covariates, hierarchical linear regression modeling was conducted. Due to strong
theoretical plausibility, a total of three covariates of gender, EL status, and grade

100
level were force-entered into the model in the first block. Both EL status and grade
level were dummy coded with EL and sixth grade serving as reference groups.
Retention status was then investigated in the second block.
Hierarchical linear regression modeling revealed that the covariates together
failed to serve as a statistically significant predictor of students’ seventh grade
CAPA scores (F
(4,32)
= 1.17, p = .34). Inclusion of students’ grade of retention failed
to result in a statistically significant final model (F
(5, 31)
= 1.03, p = .42).
Eighth Grade CAPA
In order to determine whether middle school students’ grade of retention
predicted their scores on the Eighth Grade CAPA after controlling for all three
covariates, hierarchical linear regression modeling was conducted. Due to strong
theoretical plausibility, a total of three covariates of gender, EL status, and grade
level were force-entered into the model in the first block. Both EL status and grade
level were dummy coded with EL and sixth grade serving as reference groups.
Retention status was then investigated in the second block.
Hierarchical linear regression modeling revealed that the covariates together
failed to serve as a statistically significant predictor of students’ eighth grade CAPA
scores (F
(4,32)
= 2.25, p = .09). Inclusion of students’ grade of retention failed to
result in a statistically significant final model (F
(5, 31)
= 1.75, p = .15).
Seventh Grade ELA Benchmark
In order to determine whether middle school students’ grade of retention
predicted their scores on the Seventh Grade ELA Benchmark after controlling for all

101
three covariates, hierarchical linear regression modeling was conducted as
demonstrated in Table 4.17. Due to strong theoretical plausibility, a total of three
covariates of gender, EL status, and grade level were force-entered into the model in
the first block. Both EL status and grade level were dummy coded with EL and sixth
grade serving as reference groups. Grade of Retention status was then investigated in
the second block.

Table 4.17
Summary of Hierarchical Linear Regression of Grade of Retention on 7
th
Grade ELA
Benchmark Scores (N = 1405)
Variable B SE B "
Step 1
Gender 3.82 .68 .12***
Grade -5.77 .68 -.18***
EL Status – IFEP 17.41 2.24 .17***
EL Status – RFEP 20.88 .76 .60***
EL Status – EO 7.11 1.44 .11***
Note. R
2
= .38 for Step 1 (p < .001); #R
2
< .001 (p = .69). IFEP=Initial Fluent English Proficient,
RFEP=Redesignated Fluent English Proficient, EO=English Only
*** p $ .001.

102
The final model revealed that grade of retention did not predict seventh grade
ELA Benchmark scores (F
(1 1398, )
= 0.16, p = .69). Table 17 shows the impact of all
covariates. All variables were found to predict students’ seventh grade ELA
Benchmark scores. Gender was shown to be statistically significant with seventh
grade ELA benchmarks. This means that female students were significantly more
likely to have higher seventh grade ELA benchmarks. Females scored, on average,
3.82 points higher on their seventh grade ELA Benchmark scores after controlling
for the other variables. In addition, IFEP, RFEP, and EO students were significantly
more likely to have higher seventh grade ELA Benchmark scores than the EL
reference group.
Eighth Grade ELA Benchmark
In order to determine whether middle school students’ grade of retention
predicted their scores on the Eighth Grade ELA Benchmark after controlling for all
three covariates, hierarchical linear regression modeling was conducted as
demonstrated in Table 4.18. Due to strong theoretical plausibility, a total of three
covariates of gender, EL status, and grade level were force-entered into the model in
the first block. Both EL status and grade level were dummy coded with EL and sixth
grade serving as reference groups. Retention status was then investigated in the
second block.

103
Table 4.18
Summary of Hierarchical Linear Regression of Grade of Retention on 8
th
Grade ELA
Benchmark Scores (N = 1486)
Variable B SE B "
Step 1
Gender 3.55 .72 .11***
Grade .14 .72 < .01
EL Status – IFEP 14.73 2.47 .13***
EL Status – RFEP 19.01 .81 .53***
EL Status – EO 7.93 1.55 .11***
Step 2
Gender 3.53 .71 .11***
Grade .52 .74 .02
EL Status – IFEP 15.00 2.47 .13***
EL Status – RFEP 18.97 .80 .53***
EL Status – EO 7.71 1.55 .11***
Grade of Retention -.44 .21 -.05*
Note. R
2
= .30 for Step 1 (p < .001); #R
2
= .002 (p = 0.03). EL=English Learner, IFEP=Initial Fluent
English Proficient, RFEP=Redesignated Fluent English Proficient, EO=English Only
* p $ 0.05. *** p $ .001.

The final model revealed that grade of retention did predict eighth grade ELA
Benchmark scores. However, it predicted less than 1% of the variability in students’
scores. Grade of Retention was shown to be statistically significant with eighth grade

104
ELA scores. This means that students who were retained later in their educational
career were significantly more likely to have lower eighth grade ELA scores.
Although this finding was statistically significant, it was likely not clinically
significant.
The covariates of gender, grade, and EL status together did predict eighth
grade CST scores and explained about 30% of the variability observed in students’
eighth grade ELA Benchmark. Gender was shown to be statistically significant with
eighth grade ELA Benchmarks. This means that female students were significantly
more likely to have higher eighth grade ELA Benchmarks. Females had, on average,
scores that were about 3.53 points higher than males. In addition IFEP, RFEP, and
EO students were significantly more likely to have higher scores than the EL
reference group.
Seventh Grade District Writing Prompt
In order to determine whether middle school students’ grade of retention
predicted their scores on the Seventh Grade District Writing Prompt after controlling
for all three covariates, hierarchical linear regression modeling was conducted as
demonstrated in Table 4.19. Due to strong theoretical plausibility, a total of three
covariates of gender, EL status, and grade level were force-entered into the model in
the first block. Both EL status and grade level were dummy coded with EL and sixth
grade serving as reference groups. Retention status was then investigated in the
second block.

105
Table 4.19
Summary of Hierarchical Linear Regression of Grade of Retention on 7
th
Grade
District Writing Prompt (N = 1491)
Variable B SE B "
Step 1
Gender .48 .08 .14***
Grade -.71 .08 -.21***
EL Status – IFEP 1.19 .27 .11***
EL Status – RFEP 1.38 .09 .36***
EL Status – EO .52 .17 .07**
Note. R
2
= .18 for Step 1 (p < .001); #R
2
= .001 (p = 0.11). EL=English Learner, IFEP=Initial Fluent
English Proficient, RFEP=Redesignated Fluent English Proficient, EO=English Only
** p $ 0.01. *** p $ .001.

The final model revealed that grade of retention did not predict seventh grade
District Writing Prompt scores (F
(1, 1484)
= 2.63, p = .11). Table 19 shows the impact
of the covariates. All of the variables were found to predict students’ seventh grade
District Writing Scores. Gender was shown to be statistically significant with
Seventh Grade Writing Scores. This means that female students were significantly
more likely to have higher scores on the Seventh Grade District Writing Prompt.
Females scored, on average, .48 points higher after controlling for the other
variables. In addition IFEP, RFEP, and EO students were significantly more likely to

106
have higher scores on the Seventh Grade District Writing Prompt than the EL
reference group.
Eighth Grade District Writing Prompt
In order to determine whether middle school students’ grade of retention
predicted their scores on the Eighth Grade District Writing Prompt after controlling
for all three covariates, hierarchical linear regression modeling was conducted as
demonstrated in Table 4.20. Due to strong theoretical plausibility, a total of three
covariates of gender, EL status, and grade level were force-entered into the model in
the first block. Both EL status and grade level were dummy coded with EL and sixth
grade serving as reference groups. Retention status was then investigated in the
second block.
The final model revealed that the grade of retention did not predict eighth
grade District Writing Prompt scores (F
(1, 1457)
= 0.15, p = .70). Table 20 shows the
impact of the covariates. All of the variables were found to predict students’ eighth
grade District Writing Prompt Scores. Gender was shown to be statistically
significant with Eighth Grade Writing Scores. This means that female students were
significantly more likely to have higher scores on the Eighth Grade District Writing
Prompt. Females scored, on average, .52 points higher after controlling for the other
variables. In addition, IFEP, RFEP, and EO students were significantly more likely
to have higher scores than the EL reference group.

107
Table 4.20
Summary of Hierarchical Linear Regression of Grade of Retention on 8
th
Grade
District Writing Prompt (N = 1464)
Variable B SE B "
Step 1
Gender .52 .08 .14***
Grade .72 .08 .20***
EL Status – IFEP 1.33 .27 .11***
EL Status – RFEP 1.80 .09 .45***
EL Status – EO 1.14 .17 .15***
Note. R
2
= .30 for Step 1 (p < .001); #R
2
< .001 (p = 0.70). EL=English Learner, IFEP=Initial Fluent
English Proficient, RFEP=Redesignated Fluent English Proficient, EO=English Only
*** p $ .001.

Cumulative GPA
In order to determine whether middle school students’ grade of retention
predicted their scores on Cumulative GPA after controlling for all three covariates,
hierarchical linear regression modeling was conducted as demonstrated in Table
4.21. Due to strong theoretical plausibility, a total of three covariates of gender, EL
status, and grade level were force-entered into the model in the first block. Both EL
status and grade level were dummy coded with EL and sixth grade serving as
reference groups. Retention status was then investigated in the second block.

108

Table 4.21
Summary of Hierarchical Linear Regression of Grade of Retention on Cumulative
GPA (N = 957)
Variable B SE B "
Step 1
Gender .22 .06 .10***
Grade -1.09 .09 -.37***
EL Status – IFEP .27 .19 .04
EL Status – RFEP .62 .07 .27***
EL Status – EO .16 .12 .04
Step 2
Gender .21 .06 .10***
Grade -1.01 .09 -.34***
EL Status – IFEP .30 .19 .05
EL Status – RFEP .61 .07 .26***
EL Status – EO .14 .12 .03
Grade of Retention -.07 .02 -.13***
Note. R
2
= .19 for Step 1 (p < .001); #R
2
= .02 (p < 0.001). EL=English Learner, IFEP=Initial Fluent
English Proficient, RFEP=Redesignated Fluent English Proficient, EO=English Only. *** p $ .001.

109
The final model revealed that grade of retention did predict cumulative GPA.
However, it predicted approximately 2% of the variability in students’ GPAs. Grade
of Retention as shown to be statistically significant with cumulative GPA. This
means that students who were retained later in their educational career were
significantly more likely to have lower cumulative GPAs. The covariates of gender,
grade, and EL status together predicted cumulative GPA and explained about 19% of
the observed variability. Gender was shown to be statistically significant with
cumulative GPAs. This means that female students were significantly more likely to
have higher GPAs than males. Females had, on average, GPAs that were about .21
points higher than males. Grade level was shown to be statistically significant with
cumulative GPAs. This means that older students were significantly more likely to
have lower cumulative GPAs. The sophomores had, on average, cumulative GPAs
that were 1.01 points lower than freshman. In addition, RFEP students were
significantly more likely to have higher scores than the EL reference group. No
differences were detected between IFEP and EO students compared to EL students.
Research Question Four
Research Question Four: What effect does retention status have on student
performance in reading and writing?
In order to determine whether high school students who reported having been
retained experienced different academic outcomes during middle school than high
school students who were not retained, a series of hierarchical linear regressions
were examined. Due to strong theoretical plausibility, a total of three covariates of

110
gender, EL status, and grade level were force-entered into the model in the first
block. Both EL status and grade level were dummy coded, with EL and ninth grade
serving as reference groups. Retention status was then investigated in the second
block.
Seventh Grade CST
The overall model was significant (F
(5, 5734)
= 1105.91, p < .001), and the
addition of grade of retention improved the model (F
(1, 5733)
= 187.61, p < .001).
Examination of R
2
showed that retention status explained 2% of the variability in
CST scores after controlling for gender, grade, and language status. Retention Status
was shown to be statistically significant with Seventh Grade CST scores. This means
that students who were retained were significantly more likely to have lower Seventh
Grade CST scores. All of the covariates except for grade level were significant.
IFEP, RFEP, and EO students were significantly more likely to have higher scores
than the EL reference group with RFEP status having the most impact.

111

Table 22
Summary of Hierarchical Linear Regression of Retention Status on 7
th
Grade CST
(N = 5740)
Variable B SE B "
Step 1
Gender 5.21 .98 .05***
Grade -1.53 .98 -.02
EL Status – IFEP 82.44 2.16 .37***
EL Status – RFEP 73.98 1.06 .71***
EL Status – EO 61.62 1.96 .31***
Step 2
Gender 5.11 0.97 .05***
Grade -1.28 0.97 -.01
EL Status – IFEP 77.95 2.15 .35***
EL Status – RFEP 70.41 1.07 .68***
EL Status – EO 58.70 1.94 .30***
Retention Status 15.69 1.15 .13***
Note. R
2
= .49 for Step 1 (p < .001); #R
2
= .02 (p < 0.001). EL=English Learner, IFEP=Initial Fluent
English Proficient, RFEP=Redesignated Fluent English Proficient, EO=English Only
*** p $ .001.

112
Eighth Grade CST
In order to determine whether high school students’ retention status predicted
their eighth grade CST scores, a hierarchical linear regression was examined. Due to
strong theoretical plausibility, a total of three covariates of gender, EL status, and
grade level were force-entered into the model in the first block. Both EL status and
grade level were dummy coded, with EL and ninth grade serving as reference
groups. Retention Status was then investigated in the second block.
The overall model was significant (F
(5, 5636)
= 897.14, p < .001), and the
addition of retention status improved the model (F
(1, 5635)
= 169.67, p < .001).
Examination of R
2
showed that retention status explained only 2% of the variability
in CST scores after controlling for gender, grade, and language status. Retention
Status was shown to be statistically significant with Eighth Grade CST scores. This
means that students who were retained were significantly more likely to have lower
Eighth Grade CST scores. IFEP, RFEP, and EO students were significantly more
likely to have higher scores than the EL reference group with RFEP status having the
most impact.

113

Table 23
Summary of Hierarchical Linear Regression of Retention Status on 8
th
Grade CST
(N = 5642)
Variable B SE B "
Step 1
Gender 5.99 1.10 .05***
Grade -4.17 1.10 -.04***
EL Status – IFEP 81.64 2.40 .35***
EL Status – RFEP 75.05 1.29 .68***
EL Status – EO 67.28 2.22 .32***
Step 2
Gender 5.85 1.09 .05***
Grade -3.93 1.09 -.04***
EL Status – IFEP 77.00 2.40 .33***
EL Status – RFEP 71.43 1.21 .65***
EL Status – EO 64.10 2.20 .30***
Retention Status 16.94 1.30 .13***
Note. R
2
= .44 for Step 1 (p < .001); #R
2
= .02 (p < 0.001). EL=English Learner, IFEP=Initial Fluent
English Proficient, RFEP=Redesignated Fluent English Proficient, EO=English Only
*** p $ .001.

114
Seventh Grade CMA
In order to determine whether high school students’ retention status predicted
their Seventh Grade CMA scores, a hierarchical linear regression was examined. Due
to strong theoretical plausibility, a total of three covariates of gender, EL status, and
grade level were force-entered into the model in the first block. Both EL status and
grade level were dummy coded, with EL and ninth grade serving as reference
groups. Retention status was then investigated in the second block.
Hierarchical linear regression modeling revealed that the covariates together
failed to serve as a statistically significant predictor of students’ seventh grade CMA
scores (F
(2,121)
= 0.23, p = .80). Inclusion of students’ retention status failed to result
in a statistically significant final model (F
(1, 120)
= 0.41, p = .53).
Eighth Grade CMA
In order to determine whether high school students’ retention status predicted
their eighth grade CMA scores, a hierarchical linear regression was examined. Due
to strong theoretical plausibility, a total of three covariates of gender, EL status, and
grade level were force-entered into the model in the first block. Both EL status and
grade level were dummy coded, with EL and ninth grade serving as reference
groups. Retention status was then investigated in the second block.
The overall model was significant (F
(4, 312)
= 5.39, p < .001), but the addition
of retention status failed to improve the model (F
(1, 311)
= 0.56, p = .46). Examination
of R
2
shows that the covariates explained 7% of the variability in eighth grade CMA
scores. EL Status of IFEP was shown to be statistically significant with eighth grade

115
CMA scores. This means that students who were classified at Fluent English
Proficient at the beginning of their educational career are significantly more likely to
have higher eighth grade CMA scores.

Table 24
Summary of Hierarchical Linear Regression of Retention Status on 8
th
Grade CMA
(N = 317)
Variable B SE B "
Step 1
Gender 15.17 7.82 .11
Grade -22.48 8.19 -.15**
EL Status – IFEP 116.66 38.62 .17**
EL Status – EO 11.25 12.79 .05
Note. R
2
= .07 for Step 1 (p < .001). EL=English Learner, IFEP=Initial Fluent English Proficient,
RFEP=Redesignated Fluent English Proficient, EO=English Only
** p $ .01.

Seventh Grade CAPA
In order to determine whether high school students’ retention status predicted
their Seventh Grade CAPA scores, a hierarchical linear regression was examined.
Due to strong theoretical plausibility, a total of three covariates of gender, EL status,
and grade level were force-entered into the model in the first block. Both EL status

116
and grade level were dummy coded, with EL and ninth grade serving as reference
groups. Retention status was then investigated in the second block.
Hierarchical linear regression modeling revealed that the covariates together
failed to serve as a statistically significant predictor of students’ CAPA seventh
grade scores (F
(4,57)
= 0.13, p = .97). Inclusion of students’ retention status failed to
result in a statistically significant final model (F
(1, 56)
= 1.30, p = .26).
Eighth Grade CAPA
In order to determine whether high school students’ retention status predicted
their eighth grade CAPA scores, a hierarchical linear regression was examined. Due
to strong theoretical plausibility, a total of three covariates of gender, EL status, and
grade level were force-entered into the model in the first block. Both EL status and
grade level were dummy coded, with EL and ninth grade serving as reference
groups. Retention status was then investigated in the second block.
Hierarchical linear regression modeling revealed that the covariates together
failed to serve as a statistically significant predictor of students’ eighth grade CAPA
scores (F
(4,61)
= 0.90, p = .47). Inclusion of students’ retention status resulted in a
statistically significant model and explained an additional 13% of the variability in
students’ eighth grade CAPA scores (F
(1, 60)
= 9.68, p = .003). Retention status was
shown to be statistically significant with eighth grade CAPA scores. This means that
students who were retained were significantly more likely to have lower eighth grade
CAPA scores than non-retained students.

117
Table 25
Summary of Hierarchical Linear Regression of Retention Status on 8
th
Grade CAPA
(N = 66)
Variable B SE B "
Step 2
Gender 2.25 1.81 .15
Grade -4.92 1.87 -.33*
EL Status – RFEP 0.98 2.32 .05
EL Status – EO 1.23 2.62 .06
Retention 5.80 1.87 .39**
Note. R
2
= .19 for Step 2 (p < .001). EL=English Learner, IFEP=Initial Fluent English Proficient,
RFEP=Redesignated Fluent English Proficient, EO=English Only
* p $ 0.05. ** p $ .01.

Seventh Grade CELDT
In order to determine whether high school students’ retention status predicted
their Seventh Grade CELDT scores, a hierarchical linear regression was examined.
Due to strong theoretical plausibility, a total of three covariates of gender, EL status,
and grade level were force-entered into the model in the first block. Both EL status
and grade level were dummy coded, with EL and ninth grade serving as reference
groups. Retention status was then investigated in the second block.

118
Table 26
Summary of Hierarchical Linear Regression of Retention Status on 7
th
Grade
CELDT (N = 2948)
Variable B SE B "
Step 2
Gender -3.96 7.43 -.01
Grade 7.98 7.49 .02
EL Status – RFEP 17.20 10.28 .03
EL Status – EO 87.83 200.99 .01
Retention 25.34 7.68 .06***
Note. R
2
= .006 for Step 2 (p < .001). EL=English Learner, IFEP=Initial Fluent English Proficient,
RFEP=Redesignated Fluent English Proficient, EO=English Only
*** p $ .001.

Hierarchical linear regression modeling revealed that the covariates together
failed to serve as a statistically significant predictor of students’ seventh grade
CELDT scores (F
(4, 2943)
= 1.65, p = .16). Inclusion of students’ retention status
resulted in a statistically significant model and explained an additional 0.4% of the
variability in students CELDT seventh grade scores (F
(1, 2942)
= 9.68, p = .001).
Retention status was shown to be statistically significant with seventh grade CELDT
scores. This means that students who were retained were significantly more likely to
have lower seventh grade CELDT scores.

119
Eighth Grade CELDT
In order to determine whether high school students’ retention status predicted
their eighth grade CELDT scores, a hierarchical linear regression was examined. Due
to strong theoretical plausibility, a total of three covariates of gender, EL status, and
grade level were force-entered into the model in the first block. Both EL status and
grade level were dummy coded, with EL and ninth grade serving as reference
groups. Retention status was then investigated in the second block.

Table 27
Summary of Hierarchical Linear Regression of Retention Status on 8
th
Grade
CELDT (N = 2712)
Variable B SE B "
Step 1
Gender -4.74 8.05 -.01
Grade 8.58 8.10 .02
EL Status – RFEP 50.82 15.46 .06***
EL Status – EO 71.94 208.85 .01
Note. R
2
= .005 for Step 1 (p < .001). EL=English Learner, IFEP=Initial Fluent English Proficient,
RFEP=Redesignated Fluent English Proficient, EO=English Only
*** p $ .001.

120
The overall model was significant (F
(4, 2707)
= 3.37, p < .01), and the addition
retention status failed to improve the model (F
(1, 2706)
= 1.45, p = .23). Examination of
R
2
shows that the covariates explain 0.5% of the variability in eighth grade CELDT
scores with only RFEP status significant. Language proficiency of RFEP was shown
to be statistically significant with eighth grade CELDT. This means that students
who were redesignated as Fluent English Proficient were more likely to have higher
eighth grade CELDT scores.
Seventh Grade ELA Benchmark
In order to determine whether high school students’ retention status predicted
their Seventh Grade ELA Benchmark scores, a hierarchical linear regression was
examined. Due to strong theoretical plausibility, a total of three covariates of gender,
EL status, and grade level were force-entered into the model in the first block. Both
EL status and grade level were dummy coded, with EL and ninth grade serving as
reference groups. Retention status was then investigated in the second block.
The covariates overall served as a statistically significant predictor in Block 1
(F
(5, 5634)
= 918.04, p < .001), and the addition of retention status predicted an
additional 1.7% (F
(1, 5633)
= 183.94, p < .001). All variables were significant with
emphasis on RFEP status. Retention status was shown to be statistically significant
with seventh grade ELA Benchmark scores. This means that students who were
retained were significantly more likely to have lower seventh grade ELA Benchmark
scores than non-retained students.

121

Table 28
Summary of Hierarchical Linear Regression of Retention Status on 7
th
Grade ELA
Benchmark (N = 5640)
Variable B SE B "
Step 1
Gender 2.48 .36 .07***
Grade -7.73 .36 -.21***
EL Status – IFEP 25.97 .80 .33***
EL Status – RFEP 24.11 .39 .66***
EL Status – EO 17.69 .71 .26***
Step 2
Gender 2.38 .35 .07***
Grade -7.86 .35 -.22***
EL Status – IFEP 24.36 .79 .31***
EL Status – RFEP 22.83 .39 .63***
EL Status – EO 16.64 .71 .24***
Retention Status 5.73 .42 .14***
Note. R
2
= .45 for Step 1 (p < .001); #R
2
= .02 (p < 0.001). EL=English Learner, IFEP=Initial Fluent
English Proficient, RFEP=Redesignated Fluent English Proficient, EO=English Only
*** p $ .001.

122
Eighth Grade ELA Benchmark
In order to determine whether high school students’ retention status predicted
their eighth grade ELA Benchmark scores, a hierarchical linear regression was
examined. Due to strong theoretical plausibility, a total of three covariates of gender,
EL status, and grade level were force-entered into the model in the first block. Both
EL status and grade level were dummy coded, with EL and ninth grade serving as
reference groups. Retention status was then investigated in the second block.
The covariates overall served as a statistically significant predictor in Block 1
(F
(5, 5818)
= 766.82, p < .001) predicting 40% of the variability in eighth grade ELA
Benchmark scores, and the addition of retention status predicted an additional 1.5%
(F
(1, 5817)
= 145.76, p < .001). All variables were significant with particular emphasis
on RFEP status. Retention status was shown to be statistically significant with eighth
grade ELA Benchmark scores. This means that students who were retained were
significantly more likely to have lower eighth grade ELA Benchmark scores.

123

Table 29
Summary of Hierarchical Linear Regression of Retention Status on 8
th
Grade ELA
Benchmark (N = 5824)
Variable B SE B "
Step 1
Gender 2.88 .38 .08***
Grade -0.90 .38 -.02*
EL Status – IFEP 25.41 .84 .32***
EL Status – RFEP 23.71 .84 .63***
EL Status – EO 19.34 .41 .27***
Step 2
Gender 2.82 .38 .08***
Grade -0.91 .38 -.02*
EL Status – IFEP 23.83 .84 .30***
EL Status – RFEP 22.49 .42 .60***
EL Status – EO 18.33 .76 .26***
Retention Status 5.37 .45 .13***
Note. R
2
= .40 for Step 1 (p < .001); #R
2
= .02 (p < 0.001). EL=English Learner, IFEP=Initial Fluent
English Proficient, RFEP=Redesignated Fluent English Proficient, EO=English Only
* p $ 0.05. *** p $ .001.

124
Seventh Grade District Writing Prompt
In order to determine whether high school students’ retention status predicted
their Seventh Grade District Writing Prompt scores, a hierarchical linear regression
was examined. Due to strong theoretical plausibility, a total of three covariates of
gender, EL status, and grade level were force-entered into the model in the first
block. Both EL status and grade level were dummy coded, with EL and ninth grade
serving as reference groups. Retention status was then investigated in the second
block.
The covariates overall served as a statistically significant predictor in Block 1
(F
(5, 5760)
= 493.27, p < .001) predicting 30% of the variability in seventh grade
District Writing scores, and the addition of retention status predicted an additional
1.3% (F
(1, 5759)
= 105.67, p < .001). All variables were significant with considerable
emphasis on RFEP status and grade. Retention status was shown to be statistically
significant with seventh grade District Writing Prompt scores. This means that
students who were retained were significantly more likely to have lower seventh
grade District Writing Prompt scores than non-retained students.

125

Table 30
Summary of Hierarchical Linear Regression of Retention Status on 7
th
Grade
District Writing Prompt (N = 5766)
Variable B SE B "
Step 1
Gender .46 .04 .12***
Grade -1.00 .04 -.26***
EL Status – IFEP 2.20 .09 .27***
EL Status – RFEP 1.81 .05 .48***
EL Status – EO 1.55 .08 .21***
Step 2
Gender .46 .04 .12***
Grade -1.00 .04 -.26***
EL Status – IFEP 2.05 .09 .25***
EL Status – RFEP 1.69 .05 .44***
EL Status – EO 1.45 .08 .20***
Retention Status .51 .05 .12***
Note. R
2
= .30 for Step 1 (p < .001); #R
2
= .01 (p < 0.001). EL=English Learner, IFEP=Initial Fluent
English Proficient, RFEP=Redesignated Fluent English Proficient, EO=English Only
*** p $ .001.

126
Eighth Grade District Writing Prompt
In order to determine whether high school students’ retention status predicted
their eighth grade District Writing Prompt scores, a hierarchical linear regression
was examined. Due to strong theoretical plausibility, a total of three covariates of
gender, EL status, and grade level were force-entered into the model in the first
block. Both EL status and grade level were dummy coded, with EL and ninth grade
serving as reference groups. Retention status was then investigated in the second
block.
The covariates overall served as a statistically significant predictor in Block 1
(F
(5, 5733)
= 558.22, p < .001) predicting 33% of the variability in District Writing 8
th

scores, and the addition of retention status predicted an additional 1.2% (F
(1, 5732)
=
105.70, p < .001). All variables were significant including EL Status of IFEP, EO,
and RFEP. Retention status was shown to be statistically significant with eighth
grade District Writing Prompt scores. This means that students who were retained
were significantly more likely to have lower eighth grade District Writing Prompt
scores than non-retained students.

127

Table 31
Summary of Hierarchical Linear Regression of Retention Status on 8
th
Grade
District Writing Prompt (N = 5739)
Variable B SE B "
Step 1
Gender .38 .04 .10***
Grade .57 .04 .15***
EL Status – IFEP 2.17 .09 .27***
EL Status – RFEP 2.01 .04 .53***
EL Status – EO 1.72 .08 .24***
Step 2
Gender .38 .04 .10***
Grade .57 .04 .15***
EL Status – IFEP 2.03 .09 .25***
EL Status – RFEP 1.90 .05 .50***
EL Status – EO 1.63 .08 .23***
Retention Status .49 .05 .11***
Note. R
2
= .33 for Step 1 (p < .001); #R
2
= .01 (p < 0.001). EL=English Learner, IFEP=Initial Fluent
English Proficient, RFEP=Redesignated Fluent English Proficient, EO=English Only
*** p $ .001.

128
Cumulative GPA
In order to determine whether high school students’ retention status predicted
their cumulative GPA scores, a hierarchical linear regression was examined. Due to
strong theoretical plausibility, a total of three covariates of gender, EL status, and
grade level were force-entered into the model in the first block. Both EL status and
grade level were dummy coded, with EL and ninth grade serving as reference
groups. Retention status was then investigated in the second block.
The covariates overall served as a statistically significant predictor in Block 1
(F
(5, 3609)
= 118.70, p < .001) predicting 14% of the variability in cumulative GPA
scores, and the addition of retention status predicted an additional 1.3% (F
(1, 3608)
=
105.70, p < .001).
All variables were significant. Retention status was shown to be statistically
significant with cumulative GPA. This means that students who were retained were
significantly more likely to have lower cumulative GPA.

129

Table 32
Summary of Hierarchical Linear Regression of Retention Status on GPA (N = 3615)
Variable B SE B "
Step 1
Gender .24 .03 .11***
Grade -.68 .05 -.20***
EL Status – IFEP .88 .08 .18***
EL Status – RFEP .69 .04 .32***
EL Status – EO .50 .06 .13***
Step 2
Gender .24 .03 .11***
Grade -.69 .05 -.21***
EL Status – IFEP .81 .08 .17***
EL Status – RFEP .62 .04 .29***
EL Status – EO .46 .06 .12***
Retention Status .29 .04 .12***
Note. R
2
= .14 for Step 1 (p < .001); #R
2
= .01 (p < 0.001). EL=English Learner, IFEP=Initial Fluent
English Proficient, RFEP=Redesignated Fluent English Proficient, EO=English Only
*** p $ .001.

130
Summary
According to expectation, the hierarchical linear regression modeling
demonstrated that retention has a negative impact on both overall goal orientation
and academic performance with strong predictors of grade level and EL status—
RFEP. Contrary to expectations, retention was not linked to self-efficacy and several
subscales of goal orientation.

131
CHAPTER FIVE
DISCUSSION
This chapter provides a summary of the study and a discussion of the main
findings. Implications for research and practitioners, limitations, and
recommendations for future research are also explored, finally ending with
conclusions. At a time when there are increasing calls for improving student
achievement and student apathy is a societal concern, improving student motivation
and decreasing grade retention are important considerations for both the public and
educators (Middleton & Midgley, 2002). There is a gap in the current literature
relating to the motivational and academic effects of retention on low socioeconomic,
English Learners, White, and middle-class students (Usher & Pajares, 2008).
Patterns related to low socioeconomic and specific ethnic groups have been
minimized and in some cases intentionally excluded from retention studies (Chin &
Kameoka, 2002). Furthermore, with the focus on standards and accountability as
well as political pressures, retention rates have significantly grown over the past two
decades. Today, the overall rate of retention hovers around 20% and has increased by
40% in the last 20 years (Frey, 2005). Past research has identified three key areas
that require future research: use of consistent methodological practices (Cleary &
Chen, 2009; Pintrich, 2003; Ricco et al., 2010; Usher & Pajares, 2008; Wu et al.,
2010), use of valid and multifaceted surveys and research tools (Cleary & Chen,
2009; Usher & Pajares, 2006; Usher & Pajares, 2008), and special attention to less
studied populations (Chin & Kameoka, 2002; Cleary & Chen, 2009; Frey, 2005;

132
Unrau & Schlackman, 2006; Usher & Pajares, 2008). The purpose of this study was
threefold: (a) to examine whether there was a relationship between the motivation of
retained versus nonretained students; (b) to examine whether retention timing was
related to motivation and academic performance; and (c) to examine whether
retention had differential effects on English Language Learner students. Findings
from this line of inquiry will make substantial contributions to educational research
and policies regarding English Language Learners and low socio-economic students.
It will hopefully result in better student retention practices that are based on
empirical data and documented student outcomes (Frey, 2005; Usher & Pajares,
2008).
Summary of the Study’s Findings
The following is a summary of main findings in this study. The summary
will focus on the significant findings supported by research as well as findings
inconsistent with prior research in the areas of the disproportionate use of retention,
the impact of goal orientation and self-efficacy, the impact of grade of retention and
retention status, and the relationship between language proficiency, gender, and
grade level with academic performance.
Disproportionate Use of Retention
This study found there was a disproportionate use of retention with boys,
minorities, and low socioeconomic students compared to their White, middle-class
counterparts throughout the United States. In this study, low socioeconomic Hispanic
students were retained an average of 27% compared to the average 7% of White,

133
middle- class students found to be retained in previous studies (Nepomnyaschy,
2009). The retention rate within this homogeneous, low socioeconomic population
was substantially higher than the reported national average of 10% for Hispanic
children (Kaushal & Nepomnyaschy, 2009). These findings are possible bi-products
of the rising pressures to prepare students for college and career with 76% of third
grade English Learners still performing below grade level or well below grade level
in reading and 53% in mathematics (Bowman-Perrott et al., 2010). In addition, this
study found there was a difference in the proportion of retention by gender. Males
were retained 28% percent of the time compared to females who were retained 26%
of the time compared to the norm of 10% (Kaushal & Nepomnyaschy, 2009).
Goal Orientation
This study found that the grade level of the student had significant related on
the student’s overall goal orientation. The goal orientation of the student influences
many aspects such as the level of persistence exhibited when confronted with failure
or difficulty, resilience despite failures, and use of more deep-level cognitive
processing strategies (Urdan, 1997). The learning environment becomes integral to
goal orientation, which is shifted with the transition to middle school (Midgley &
Urdan, 2001). The transition to middle school can initially affect the goal orientation
of a student due to changes in four key areas: change in learning environments,
differences in teacher interaction and social relationships, individual development,
and gender differences (Eccles, 2009; Meece et al., 2006; Pajares et al., 2007). This
may explain why seventh grade students had higher overall goal orientation and

134
mastery goal orientation than the sixth grade reference group. The seventh grade
status was significant on all of the goal orientation findings including Mastery Goal
Orientation and Skepticism About the Relevance of School for Future Success. The
sixth grade students may need time to adjust to the new middle school learning
environment, which is impersonal, structured, and teacher-controlled in contrast to
the personalized environment of elementary school, which is related to lower goal
orientation. The environments of middle schools generally promote competition
between students, compare students to each other, recognize high levels of
achievement, and place a greater importance on grades and test scores (Urdan, 1997).
This structure encourages students to refocus on their goal orientation towards a
performance orientation. Those who cannot meet the desired standard set by their
school may form a performance-avoid orientation to buffer their academic deficits
and level of self-esteem (Urdan, 1997). This study’s findings on goal orientation are
consistent with prior research, which notes the decline of motivation in the middle
school (Meece, 2006).
Retention status negatively impacted the overall goal orientation of students.
Students who were retained had lower overall goal orientation. The goal orientation
of the student has an impact on academic performance. Students with lower grades,
who have a greater chance of being previously retained, are more likely to have a
performance-avoid orientation and use self-handicapping strategies than higher
performing students (Midgley & Urdan, 2001). These maladaptive strategies, in
turn, perpetuate the lower performance, which may cause the performance-avoid

135
orientation to persist (Urdan, 1997). The grade of retention did not affect either the
overall goal orientation or the mastery goal orientation of the student.
Self-Efficacy
It was expected that there would be a negative relationship between self-
efficacy and retention. This did not occur. This may be due to the fact that self-
efficacy changes over time and these beliefs differ throughout one’s life in
generality, strength, and level. The generality aspect of the construct notes the
transferability of the self-efficacy beliefs across various activities. The strength of
self-efficacy is measured by a person’s confidence in performing the task
(Zimmerman, 2000). The level of self-efficacy depends on the difficulty of the
particular task (Meece, Glienke, & Burg, 2006). The judgment of capability
influences the course of action taken, the complexity of the established goal, the
level of commitment to the task, the level of perseverance in the face of obstacles,
and the level of resilience after difficulty of an individual (Bandura, 2006).
Therefore, self-efficacy can be affected by the short-term effects of retention on a
child’s perceived sense of belonging and an increase in a feeling of academic
efficacy, which largely disappear by age 14 (Wu, 2010). A large portion of the
students within this study was under the age of 13. The sample included 24% of
students at age 12, 43% at age 13, and 29% age at 14, which means that the students
may still be experiencing positive effects of the retention.

136
Impact of Grade of Retention
This study found that the grade of retention had an effect on both overall goal
orientation and on the academic performance of the students. If students are to be
retained, they should be retained earlier rather than later in their educational career.
Students who were retained earlier in their educational career had higher academic
performance on the CST, benchmark scores, and cumulative GPA. To date, there is
little research on the impact of the grade in which retention occurred for low
socioeconomic, Hispanic students. However, retention research does point to the
diminishing benefits of retention at age 14 which would indicate that the early grades
provide the students with less instructional time being unable to access core
instruction and more time to receive the benefits of the retention (Wu, 2010). The
practice of retaining students early in their educational career is evidenced by
research on teacher perceptions. Prior studies have found that the primary rationale
teachers gave was it offered children the “gift of time” which was an opportunity to
mature and develop the skills necessary for a successful first grade experience
(Mantizocopulos & Neuharth-Pritchett, 1998). Linked to this rationale is social
immaturity, which includes lack of impulse control, inability to focus attention, and
inability to conform to classroom rules as a reason for retaining a child (Wu et al.,
2010). For these reasons, historically, the majority of students were retained in the
primary grades of kindergarten through third grade (Witmer et al., 2004). Such was
the case with this study with 81% of the students being retained between the grades
of kindergarten to third grade.

137
Impact of Retention Status
This study found that retention status had a negative impact on academic
performance on CST, CAPA, CELDT, ELA Benchmarks, District Writing Prompt,
and cumulative GPA. Nonretained students consistently did better on local, district,
and state assessments during seventh and eighth grade than their retained
counterparts. These findings are consistent with previous research, which found
retained students had lower educational outcomes than socially promoted and
promoted students. Fellow researchers have noted that after middle school the
students display lower cognitive competence, lower self-expectations, and poorer
school attendance coupled with the tendency to be less engaged in instruction and
reluctant to seek teacher support (Jimerson, 1999; Bowman-Perrott et al., 2010).
Retention may trigger younger students to ruminate about their academic
shortcomings and convince themselves through self-talk that they will not succeed in
school (Usher & Pajares, 2008). Academically unstable students begin to question
their ability and make normative comparisons with their peers. These comparisons
are highlighted with the shift to competitive grading procedures, increased
homework, decreased teacher-pupil interaction, and an increase in social
comparison, which occurs in middle school (Usher & Pajares, 2008).
Language Proficiency, Retention, and Academic Performance
This study indicated that the language proficiency of the student had the
largest variance of any covariate in the study. This finding was consistent with prior
research that believes outstanding factors may cause pre-existing vulnerabilities,

138
which both increase the possibility of retention and cause the diminishing benefits of
retention (Wu, 2010). By the time a low socio-economic, English Learner goes to
preschool, there are already considerable differences in the vocabulary levels from
their English speaking, middle class peers. A low socio-economic parent
communicates approximately 400 utterances less per hour than a professional high
socio-economic parent (Santrock, 2009). Fewell and Deutscher (2003) found that
language development at 30 months of age predicted reading at eight years of age.
Prior research speaks to importance of providing systematic language instruction for
English Learners from the first day of kindergarten. The opportunity gap will not
close and allow them to enhance their vocabulary development in either their
primary language or target language unless the educational system provides them
with daily, systematic language instruction. This study found that students who
gained sufficient social and academic language abilities to be redesignated on
CELDT were more successful on all academic performance measures including
CST, ELA Benchmark, and District Writing Prompt. In this study, 45% of all 9
th

and 10
th
grade non-native English speaking students were still concerned English
Learners. If a student has not been able to reclassified on the CELDT that means
that their academic language abilities are an overall score lower than Early
Advanced. With limited number of newcomers in the secondary schools, these
students have been in the educational system for years and have still not acquired
academic English. The English Learners have less success with the academic
performance measures. These findings were in line with the research that there is a

139
large discrepancy between everyday conversational English and the academic
English needed for high levels of achievement in multiple content areas. At times,
English Learners may appear to have acquired English due to their ability to carry on
informal conversations (Gandara, Rumberger, Maxwell-Jolly, & Callahan, 2003).
Misled by these perceptions of their students’ fluency and unequipped with sound
knowledge on language acquisition, many teachers do not provide English Learners
with continual instruction in the various forms and functions of language throughout
their educational experience. Therefore, many English Learners do not become truly
fluent in their second language and do not develop the academic English necessary to
fully access the core curriculum. Therefore, the students who were able to acquire
social and academic English were more successful, accounting for up to 60% of the
variance in scores. The study found that, in fact, the redesignated students (RFEP)
outperformed both the initially fluent proficient students (IFEP) who came to school
with English and the English Only students. All three of these language proficiency
groups outperformed the English Learners in all academic areas. This finding speaks
to the research on the benefits of bilingualism. The language status of the student
was significant when the data was analyzed from both the lens of grade of retention
and retention status.
Gender Differences, Retention, and Academic Performance
This study found gender had a significant impact on academic performance
depending on both the grade in which they were retained and their retention status.
The females, in general, outperformed the boys in all areas of academic performance

140
measures with more significant influence on writing and cumulative GPA. The
females scored an average of .48 points higher on a five-point writing rubric. This is
a significant difference as these results represent half of a proficiency band. These
differences were influenced by multiple variables. As noted in previous research,
middle-school girls have higher writing self-efficacy than boys even when there are
no gender differences in actual writing performance (Usher & Pajares, 2008). For
boys, the value of language arts declines most rapidly in elementary school. Meece et
al. (2006) also found that teachers generally have higher achievement expectations
for females in language arts and writing and higher expectations for males in male-
sex-typed activities such as mathematics and science.
Grade Level Differences, Retention, and Academics Performance
This study found that the age of the student had significant impact on
academic achievement on multiple assessments including CST, ELA Benchmarks,
District Writing Prompts, and cumulative GPA. As students grew older, they
obtained poor results on local, district, and state assessments. These differences
were highlighted in the area of cumulative GPA where the older students, on
average, had cumulative GPAs 1.01 points lower than their younger counterparts.
This is significant because it shows a whole grade lower performance. This finding
reinforces the previous finding that the long-term negative effects of retention may
be related to long-term low academic achievement, increased behavior problems, and
disengagement from school (Hudley et al., 2007; Jimerson, 1999; Jimerson &
Ferguson, 2007; Mantizocopulos & Neuharth-Pritchett, 1998).

141
Implications for Researchers and Practitioners
The findings from this study have implications for research on the effects of
retention on the motivation and academic performance of low socioeconomic
students. This study emphasized the long history of inequitable use of retention with
English Language Learners. School districts with low socioeconomics traditionally
retain more students, which were noted in the study with 27% of the students being
retained (Mantizocopulos & Neuharth-Pritchett, 1998). Results from the study
provided additional evidence of the negative impact retention has on overall goal
orientation of students (Eccles, 2009; Meece et al., 2006; Pajares et al., 2007). This
study provided additional support that retention has a negative impact on academic
performance on widely used and current assessments like CST, CAPA, CELDT,
ELA Benchmarks, and District Writing Prompt (Jimerson, 1999; Bowman-Perrott et
al., 2010). This would provide reasoning for school districts to use caution in
retaining English Language Learners. The pre-existing vulnerabilities of the English
Learner may cause additional diminishing benefits of retention which may make
retention more ineffective intervention. These initially positive effects may
encourage elementary schools to believe that retention is an effective intervention.
School districts may want to study cohort data to see long term effects. Furthermore,
this study provided additional evidence that gender has an effect on the academic
performance in the areas of reading and writing (Usher & Pajares, 2008).
Further, the study extends the current literature on the importance of
examining covariates, specifically language proficiency when discussing the effects

142
of retention. The study supports the importance of language by identifying the fact
that the redesignated (RFEP) students outperformed both the initially fluent
proficient students (IFEP) students who came to school with English and the English
Only students. The study extends the research by including low socioeconomic,
Hispanic students within the study sample. This study allows researchers to make
statements regarding the broader EL, low socioeconomic populations.
Results from this study also have implications for education and policy
makers working to ensure schools are launching pads preparing students to college
and career. This discussion will highlight three key implications: (a) the need for
monitoring and implementing retention policies, (b) the need for district-wide
initiatives focusing on 21
st
Century Learning, and (c) the need for full
implementation of Response to Intervention.
In light of the evidence that retention has a negative impact on both
motivation and academic performance of English Learners, school districts should
establish strict policies to ensure students are not retained prior to formal
interventions and parent support. Today’s national overall rate of retention hovers
around 20%, which reflects an increase of 40% in the last 20 years (Frey, 2005).
Currently, 27% of the students within this study are being retained. This will require
the system to established structures and procedures, which safeguard students from
unnecessary retentions. After establishing strict policies, the district office
administration along with site administration should monitor the implementation and
ask difficult questions when schools are over identifying students for retention.

143
In an effort to reduce the number of students not performing at grade level,
the teachers should provide a broad curriculum, which focuses on 21
st
Century
learning. This change of paradigm will require teachers to hold high expectations for
all students and include science, social studies, and high-level content beginning in
elementary school. As stated by Darling-Hammond (2007), the education provided
to many minority students is not a curriculum that fosters thinking but a curriculum
geared towards lower level “rote” skill such as memorization and formulaic
reasoning. Frequently, there is a narrowing of the curriculum where advanced and
college preparatory classes are not offered to diverse student groups. Differences in
coursework can specifically be found in the areas of mathematics, science, and
foreign language (Darling-Hammond, 2007). In addition, the focus on content
knowledge will not be enough to prepare students for future professions. The
curriculum will have to ensure students are critical thinkers who can problem solve
and analyze information in creative, flexible, and initiative ways (Wagner, 2010).
The students will have to be able to effectively communicate both orally and in
writing which can be a challenge with English Learners.
Lastly, all schools should consider full implementation of Response to
Intervention. In the study, 49% of the population was retained during their
kindergarten and first grade year, which supports the evidence that Response to
Intervention was not being fully implemented. Teachers must provide early
interventions and support to reduce the number of students being retained. Response
to Intervention is a multi-tiered instructional approach that should support student

144
success prior to significant gaps in knowledge. The intervention support should be
based on objective data from both universal screenings and progress monitoring.
The universal screenings should include all students within the school regardless of
proficiency level. The universal screening results would allow the school sites to
capture students who are not keeping pace with instruction and are in need to
additional or targeted instructional time. Once the child has been identified in need
of support, the progress of the child should be monitored every two to three weeks.
The intervention should target specific skills and strategies the students need to
successfully demonstrate proficiency. The support should vary with intensity and
duration according to the needs of the student. The more intensive the needs of the
student, the more support the student should receive. Within the intervention, the
student should receive corrective, frequent, and on-going feedback so they may
monitor, reflect upon their learning, and set proximal goals. The effectiveness of the
intervention should be monitored and, if needed, refined to ensure the student makes
sufficient progress and to drive instruction. Once the child reaches benchmark
levels, the child should receive higher levels of instruction to enrich and accelerate
further progress.
Recommendation for Future Research
The study looked at the impact that the covariates had on both motivation and
academic performance. On multiple models, the covariates were statistically
significant and in some cases accounted for a large portion of the variance.
Examples of the predictability of the covariates could be found in both the

145
motivational scales and the academic performance measures. For motivational
scales, in Table 4.4, it showed that the covariates of grade level, gender, and EL
status accounted for 38% of the variability observed in students’ overall goal
orientation. For academic performance, as seen in Table 4.18, the covariates
together predicted 49% of the variability of academic performance. These results
underscore the importance of examining other covariates. There may be other
relationships that were not examined within this study due to the homogeneous
sample of primarily low socioeconomic students. Two important variables for future
research would be the impact of the socioeconomic level of the student and the
educational level of the mother.
Another variable that warrants further research is in the area of multiple
retentions. Due to the limited number of students retained more than once in this
study, the effects were not able to be calculated. However, since retention has shown
to be significantly related to negative academic achievement, future studies may
investigate double retentions and its effects.
For this study, the grade level of retention of the student was viewed in a
linear fashion as a continuous variable with an assumption that each grade level held
the same value. It is plausible that particular grade levels have greater influence on
motivation and academic performance than others. Future research may wish to run
the grade levels as categorical variables and look at grade spans of primary years (K-
2), early intermediate (3-5), and late intermediate (6-8).

146
Due to the previously stated limitation of a small sample size for the
motivational survey and the disproportionally high achieving and low number of
retained students, more research is warranted on the effect of retention on motivation
on English Learner students. As in the case of the research of Alexander, Entwisle,
and Dauber (1994), Meisels and Liaw (1993), and Roderick (1995), the studies
included only middle-class children from a variety of ethnic backgrounds. In some
cases, the low socioeconomic and specific ethnic groups were minimized and in
other cases intentionally excluded (Chin & Kameoka, 2002).
With the current emphasis on college and career readiness, a new
longitudinal study tracking cohort of students is warranted. As the educational
expectations change to reach 21
st
Century skills, the impact of those changes could
have an effect on the number of students retained each year. As the pressures for
schools to produce critical-thinking and articulate students augment and the number
of English Learners increase, educators may feel compelled to retain students in an
effort to increase their performance (EdSource, 2008). It will become important to
highlight the possible negative effects of retention and to inform teachers and
administrators of the long-term effects.
Lastly, further studies may investigate if similar patterns and results are
found in similar school districts with comparable demographics. Additional studies
will validate the results captured in this study.

147
Limitations
The study was performed in a large, urban school district in Southern
California. The unique feature of the district is the largely homogeneous population
of English Learners and low socioeconomic students. The hierarchical linear
regression modeling allowed the researcher to predict and make conclusions about
the broader EL population. The large EL population allowed the researcher to answer
various important questions about motivation and retention. However, the
homogeneous population also limited the ability to look at the differences between
English Learners and English Only students and high versus low socioeconomic
students.
There was a significantly large sample size for the academic performance
with a sample size of 5,740 seventh grade and 5,642 eighth grade scores. Despite the
efforts of the researcher to ethically encourage students and parents to give
permission to take the motivational survey and subsequently take the survey, it
resulted in a small sample size of 134. In addition, the sample included students from
the same classes many of whom were in the honors classes within the schools. This
resulted in a larger population of high performing students and lower ratio of
retained students. The motivational sample included approximately 21% of retained
students (n=29) compared to the academic performance sample, which included
approximately 29% of retained students (n=1727). This limitation may have caused
the self-efficacy construct to not show statistical significance.

148
The mobility rate of the large, urban district in this study was 95%, which
meant the educational experience including standardized test scores, and retention
could not be tracked (Aeries, 2011). This resulted in 24% of the students (n=1530)
were excluded from the academic performance sample due to being unable to verify
their retention status.
The scope of the study was not focused on special education students. The
data did capture some information regarding the academic performance and the
effects of retention for students with special needs. The data set of 163 students
taking the CMA and 66 students taking the CAPA was small relative to the number
of covariates included for study.
Conclusion
This study attempted to examine the motivational and academic effects of
retention on special populations such as English Learner, ethnic, and low
socioeconomic status students. The researcher wanted to address the changing
demographics of the students we serve, specifically in large urban districts. The
importance of motivation to academic achievement, the established decline of
motivation in middle school, and the negative effects of retention after age 14,
warranted this study with a more diverse population. The study contributed to
current research by highlighting the significance of language proficiency and the
grade of retention. It provided evidence that school districts should change policies
and instructional practices to more effectively serve low socioeconomic, language
learners and reduce the over use of retention as an intervention measure. The

149
incorporation of these key recommendations will transform classrooms and the lives
of students so they may reach their ultimate potential.

150
Table 5.1
IV and DV with Proposed Assessments
Research
Question Variable
Type of
Variable
Level of
Measurement
Proposed
Test Variables
#1 — What
effects does
retention status
have on overall
goal orientation,
mastery goal
orientation and
self-efficacy?
Goal
Orientation
Dependent Interval Hierarchical
linear
regression
modeling
*Student ID #
*Gender (0/1)
*EL Status (EL, IFEP, RFEP,
EO)
*Student Grade
*Retention (Y/N)
*Score on Self-Efficacy
*Score on Goal Orientation
Self-Efficacy Dependent Interval
Retention
Status
Independent Nominal
Gender Independent Nominal
#2 — What
effect does the
grade of
retention have
on overall goal
orientation,
mastery goal
orientation and
self-efficacy?
Goal
Orientation
Dependent Interval Hierarchical
linear
regression
modeling
*Student ID #
*Gender (0/1)
*EL Status (EL, IFEP, RFEP,
EO)
*Student Grade
*Retention (Y/N)
*Grade of Retention (0-8)
*Score on Self-Efficacy
*Score on Goal Orientation
Self-Efficacy Dependent Interval
Grade of
Retention
Independent (Interval — 0-8,
Interval — K and
on, 1
st
and on, 2
nd

and on, 3
rd
and on,
4
th
and on, 5
th
and
on, 6
th
and on, 7
th

and on, 8
th
and on)
Gender Independent Nominal
Language
Proficiency
Independent Nominal
#3 —What
effect does the
retention status
have on student
performance in
reading and
writing?
Academic
Success on
2007-2011
ELA CST
Dependent Interval Hierarchical
linear
regression
modeling
*Student ID #
*Gender (0/1)
*EL Status (EL, IFEP, RFEP,
EO)
*Student Grade
*Retention (Y/N)
*Grade of Retention (0-8)
*Scale score on 7
th
grade CST
(200-600)
*Scale score on 8
th
grade CST
(200-600)
*Scale score on 7
th
grade
CELDT (100-600)
*Scale score on 8
th
grade
CELDT
*% correct on 7
th
grade ELA
Benchmark (0-100%)
*% correct on 8
th
grade ELA
Benchmark (0-100%)
*7
th
grade District Writing
Prompt (1-5)
*8
th
grade District Writing
Prompt (1-5)
*7
th
grade Final GPA (1-4)
*8
th
grade Final GPA (1-4)

151
Table 5.1, continued
Research
Question Variable
Type of
Variable
Level of
Measurement
Proposed
Test Variables
#4 — What
effect does the
timing of
retention have
on student
performance in
reading and
writing?
Academic
Success on
2007-2011
ELA CST
Dependent Interval Hierarchical
linear
regression
modeling
*Student ID #
*Gender (0/1)
*EL Status (EL, IFEP, RFEP,
EO)
*Student Grade
*Retention (Y/N)
*Grade of Retention (0-8)
*Scale score on 7
th
grade CST
(200-600)
*Scale score on 8
th
grade CST
(200-600)
*Scale score on 7
th
grade
CELDT (100-600)
*Scale score on 8
th
grade
CELDT
*% correct on 7
th
grade ELA
Benchmark (0-100%)
*% correct on 8
th
grade ELA
Benchmark (0-100%)
*7
th
grade District Writing
Prompt (1-5)
*8
th
grade District Writing
Prompt (1-5)
*7
th
grade Final GPA (1-4)
*8
th
grade Final GPA (1-4)
Academic
Success on
2007-2011
CELDT
Dependent Interval
Academic
Success on
ELA
Benchmark
Dependent Interval
Academic
Success on
District
Writing
Prompt
Dependent Interval
Academic
Success on
2011 Final
Grades
Dependent Interval
Grade Level
of Retention
(early or late)
Independent Nominal
Gender Independent Nominal
Language
Proficiency
Independent Nominal

152
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APPENDIX A
INFORMED CONSENT FOR NON-MEDICAL RESEARCH: PARENTAL
PERMISSION

University of Southern California
Rossier School of Education
Waite Phillips Hall
3470 Trousdale Parkway
Los Angeles, CA 90089

INFORMED CONSENT FOR NON-MEDICAL RESEARCH
PARENTAL PERMISSION

Motivational and Academic Outcomes in Retained Middle School Students

Your child is invited to participate in a research study conducted by Michelle
Rodriguez, doctoral student and Dr. Kimberly Hirabayashi from the University of
Southern California. Your child’s participation is voluntary. You should read the
information below, and ask questions about anything you do not understand before
deciding whether to participate and/or allow your child to participate. Please take as
much time as you need to read the consent form. Your child will also be asked
his/her permission and given a form to read, which is called an assent form. Your
child can decline to participate, even if you agree to allow him/her. You and/or your
child may also decide to discuss it with your family or friends. If you and/or your
child decide to participate, you will be asked to sign this form, and your child be
asked to sign the assent form. You will be given a copy of this form.

Purpose of the Study

To identify if there is a relationship between the level of motivation of your child and
his/her success at have at school.

Study Procedures

If you agree to allow your child to participate your child will be asked to fill out a 26
question survey one time. Your child should be able complete in 15 minutes within

159
his/her homeroom. They will be asked questions such as “One of my goals in class
is to learn as much as I can” which your child will have to circle one of the three
answers “Not at all true, Somewhat true or Very true”.

Potential Risks and Discomforts

There is no anticipated risk.

Potential Benefits to Participants and/or to Society

There are no anticipated direct benefits to the participants. The schools will be able
to use this information to improve your program and services to students and parents.

Payment/Compensation for Participation

There will be no payment or form of compensation for participation.

Confidentiality

Any identifiable information obtained in connection with this study will be disclosed
only with your permission or as required by law.

The members of the research team and the University of Southern California’s
Human Subjects Protection Program (HSPP) may access the data.

The HSPP reviews and monitors research studies to protect the rights and welfare of
research subjects.

The data will be stored without your name or any form of identification. The data
will be kept for three years. When the results of the research are published or
discussed in conferences, no identifiable information will be used.

When the results of the research are published or discussed in conferences, no
identifiable information will be included.

Participation and Withdrawal

You and/or your child’s participation is/are voluntary. You and/or your child’s
refusal to participate will involve no penalty or loss of benefits to which you or your
child are otherwise entitled. You may withdraw your consent, and your child may
draw his/her assent, at any time and discontinue participation without penalty. You,
or your child, are not waiving any legal claims, rights or remedies because of
your/your child’s participation in this research study.

160
Alternatives to Participation

You will continue with normal class activities during homeroom if you choose not to
participate.

Emergency Care and Compensation For Injury

If you are injured as a direct result of research procedures not done primarily for
your own benefit, you will receive medical treatment; however, you or your
insurance will be responsible for the cost. The University of Southern California
does not provide any other form of compensation for injury.

Investigators Contact Information

If you have any questions or concerns about the research, please feel free to contact
the following people either by phone, mail or e-mail: Michelle Rodriguez at (714)
558-5656, 1601 E. Chestnut Avenue, Santa Ana, CA, 92701 or rodrigml@usc.edu or
Dr. Kimberly Hirabayashi at (213) 740-3470, Rossier School of Education, Waite
Phillips Hall 3470 Trousdale Parkway Los Angeles, CA 90089 or hirabaya@usc.edu.

Rights of Research Participant – IRB Contact Information

If you have questions, concerns, or complaints about your rights as a research
participant you may contact the IRB directly at the information provided below. If
you have questions, concerns, complaints about the research and are unable to
contact the research team, or if you want to talk to someone independent of the
research team, please contact the University Park IRB (UPIRB), Office of the Vice
Provost for Research Advancement, Stonier Hall, Room 224a, Los Angeles, CA
90089-1146, (213) 821-5272 or upirb@usc.edu.

SIGNATURE OF PARENT(S)

I have read the information provided above. I have been given a chance to ask
questions. My questions have been answered to my/our satisfaction, and I agree to
participate in this study and/or have my child participate in this study. I have been
given a copy of this form.

Name of Participant

Name of Parent (1)

161

Signature of Parent (1) Date

SIGNATURE OF INVESTIGATOR

I have explained the research to the participant and his/her parent(s), and answered
all of their questions. I believe that the parent(s) understand the information
described in this document and freely consents to participate.

Name of Person Obtaining Consent

Signature of Person Obtaining Consent Date

162
APPENDIX B
ASSENT FOR NON-MEDICAL RESEARCH: FOR YOUTH (AGES 12-17)

University of Southern California
Rossier School of Education
Waite Phillips Hall
3470 Trousdale Parkway
Los Angeles, CA 90089

ASSENT FOR NON-MEDICAL RESEARCH
FOR YOUTH (AGES 12-17)

Motivational and Academic Outcomes in Retained Middle School Students

You are invited to participate in a research study conducted by Michelle Rodriguez,
doctoral student and Dr. Kimberly Hirabayashi at the University of Southern
California, because you are a seventh or eighth grade student. This study is funded
by does not require funding. Your participation is voluntary. You should read the
information below, and ask questions about anything you do not understand, before
deciding whether to participate. Your parent’s permission will be sought; however,
the final decision is yours. Even if your parents agree to your participation by
signing a separate consent document, you don’t have to participate if you don’t want
to. Please take as much time as you need to read this form. You may also decide to
discuss it with your family or friends. If you agree to participate, you will be asked to
sign this form. You will be given a copy of this form.

Purpose of the Study

To find out if there is a relationship between how motivated you are and the success
at have at school.

Study Procedures

If you volunteer to participate in this study, you will be asked to fill out a 26 question
survey one time. You should be able complete in 15 minutes within your homeroom.

163
Potential Risks and Discomforts

There are no potential risks.

Potential Benefits to Participants and/or to Society

There are no potential direct benefits to the participants. The schools will be able to
use this information to improve your program and services to students and parents.

Payment/Compensation for Participation

There will be no payment or form of compensation for participation.

Confidentiality

Any identifiable information obtained in connection with this study will remain
confidential and will be disclosed only with your permission or as required by law.
The members of the research team and the University of Southern California’s
Human Subjects Protection Program (HSPP) may access the data. The HSPP reviews
and monitors research studies to protect the rights and welfare of research subjects.

The data will be stored without your name or any form of identification. The data
will be kept for three years. When the results of the research are published or
discussed in conferences, no identifiable information will be used.

Participation and Withdrawal

You can choose to be in this study or not. If you volunteer to be in the study, you
may withdraw at any time without any consequences. You may also refuse to answer
any questions you don’t want to answer and still remain in the study.

Alternatives to Participation

You will continue with normal class activities during homeroom if you choose not to
participate.

Emergency Care and Compensation for Injury

If you are injured as a direct result of research procedures not done primarily for
your own benefit, you will receive medical treatment; however, you or your
insurance will be responsible for the cost. The University of Southern California
does not provide any other form of compensation for injury.

164
Investigator’s Contact Information

If you have any questions or concerns about the research, please feel free to contact
the following people either by phone, mail or e-mail: Michelle Rodriguez at (714)
558-5656, 1601 E. Chestnut Avenue, Santa Ana, CA, 92701 or rodrigml@usc.edu or
Dr. Kimberly Hirabayashi at (213) 740-3470, Rossier School of Education, Waite
Phillips Hall 3470 Trousdale Parkway Los Angeles, CA 90089 or hirabaya@usc.edu.

Rights Of Research Participant – IRB Contact Information

If you have questions, concerns, or complaints about your rights as a research
participant you may contact the IRB directly at the information provided below. If
you have questions about the research and are unable to contact the research team, or
if you want to talk to someone independent of the research team, please contact the
University Park IRB (UPIRB), Office of the Vice Provost for Research
Advancement, Stonier Hall, Room 224a, Los Angeles, CA 90089-1146, (213) 821-
5272 or upirb@usc.edu.

SIGNATURE OF RESEARCH PARTICIPANT

I have read the information provided above. I have been given a chance to ask
questions. My questions have been answered to my satisfaction, and I agree to
participate in this study. I have been given a copy of this form.

Name of Participant

Signature of Participant Date

SIGNATURE OF INVESTIGATOR

I have explained the research to the participant and answered all of his/her questions.
I believe that he/she understands the information described in this document and
freely consents to participate.

Name of Person Obtaining Consent

Signature of Person Obtaining Consent Date

165
APPENDIX C
INFORMED CONSENT FOR NON-MEDICAL RESEARCH: PARENTAL
PERMISSION (SPANISH)

Universidad del Sur de California
Escuela de Educación de Rossier
Waite Phillips Hall
3470 Trousdale Parkway
Los Angeles, CA 90089

CONSENTIMENTO INFORMADO PARA ESTUDIO NO-MÉDICO
PERMISO PARENTAL

Resultados Académicos y de Motivación en Estudiantes Reprobados en Escuelas
Intermedias

Su hijo está invitado a participar en un estudio organizado por Michelle Rodriguez,
estudiante en doctorado y la Dra. Kimberly Hirabayashi de la Universidad del Sur de
California. La participación de su hijo/a es voluntaria. Usted debe leer la
información debajo, y hacer preguntas de cualquier cosa que usted no entienda antes
de decidir si deja que su hijo/a participe. Favor de tomar tiempo para leer el
consentimiento informado. Su hijo/a también tendrá que firmar un permiso, el cual
se llama Forma de Conocimiento. Su hijo/a puede decidir de no participar aún si
usted está de acuerdo. Usted y/o su hijo/a pueden decidir si hablan con su familia o
amigos antes de firmar. Si usted y su hijo/a deciden participar, usted tendrá que
llenar la forma, y su hijo/a tendrá que llenar su forma. Usted puede recibir una copia
de esta forma.

Propósito de Este Estudio

Para identificar la relación entre el nivel de motivación de su hijo y su éxito en la
escuela.

166
Procedimientos del Estudio

Si usted está de acuerdo que su hijo/a pueda participar, su hijo/a llenará un
cuestionario de 26 preguntas solamente una vez. Su hijo/a debe poder completar el
cuestionario en su salón principal. Le harán preguntas como “Una de mis metas en la
clase es aprender lo más que pueda” en el cual su hijo/a tendrá que circular una de
las tres respuestas “No es cierto, más o menos cierto o muy cierto”.

Riesgos e Incomodidades Potenciales

No hay ningún riesgo o incomodidad anticipados.

Beneficos Potenciales para Participantes y/o para La Sociedad

No hay ningunos beneficios directos anticipados a los participantes. Las escuelas
usarán esta información para mejorar sus programas y los servicios para los
estudiantes y sus familias.

Pago/Compensación por Participar

No hay ningún pago o forma de compensación por participar.

Confidencialidad

Cualquier información identificable obtenida en conexión con este estudio solamente
será revelada con su permiso o como requiere la ley.

Los miembros de este equipo de estudio y el Programa de Protección de Sujetos
Humanos (HSPP) de la Universidad del Sur de California tendrán acceso a este dato.

El HSPP repasa y monitorea los estudios para proteger los derechos y el bienestar de
los sujetos de estudios.

Los datos serán mantenidos sin su nombre o cualquier forma de identificación. Los
datos serán mantenidos por tres años. Cuando los resultados del estudio sean
publicados ó discutidos en unas conferencias, no información identificable será
usada.

Participación y Cambio de Parecer

La participación de usted y/o su hijo/a es voluntaria. La negación de participar no
resultará en castigo alguno ó pérdida de benéficos a los cuales su hijo/a tiene
derecho. Usted puede retirar su consentimiento y su hijo/a puede retirar su

167
consentimiento en cualquier momento y dejar de participar sin castigo alguno. Usted,
ó su hijo/a, no están renunciando a ninguna reclamación, derecho o remedio para
participar en este estudio.

Alternativas de Participación

Su hijo/a continuará con las actividades de su clase normal durante el salón principal
si no desea participar.

Cuidado de Emergencia y Compensación de Herida

Si usted resulta herido como resultado directo de los procedimientos del estudio no
hecho primeramente para su beneficio, usted recibirá tratamiento médico; sin
embargo, usted o su seguro médico serán responsables por el costo. La Universidad
del Sur de California no provea cualquier forma de compensación de herida.

Información de Contacto de Las Investiagadoras

Si tiene una pregunta ó preocupación sobre el estudio, favor de contactar a la gente
siguiente por teléfono, correo ó correo electrónico: Michelle Rodriguez a (714) 558-
5656, 1601 E. Chestnut Avenue, Santa Ana, CA, 92701 o rodrigml@usc.edu o Dra.
Kimberly Hirabayashi a (213) 740-3470, Escuela de Educación de Rossier, Waite
Phillips Hall 3470 Trousdale Parkway Los Angeles, CA 90089 o hirabaya@usc.edu.

Derechos de Los Participantes del Estudio—Información de Contacto de IRB

Si usted tiene preguntas, preocupaciones ó quejas sobre sus derechos como
participante del estudio, puede contactar el IRB directamente a la información
debajo. Si tiene preguntas, preocupaciones ó quejas y no puede contactar el equipo
del estudio, ó si usted quiere hablar con alguien independiente del equipo del estudio,
favor de contactar a University Park IRB (UPIRB), Office of the Vice Provost for
Research Advancement, Stonier Hall, Room 224a, Los Angeles, CA 90089-1146,
(213) 821-5272 o upirb@usc.edu.

FIRMA DEL PADRE O TUTOR

Yo he leído la información arriba. He tenido la oportunidad de hacer preguntas. Mis
preguntas han sido contestadas a mi satisfacción y estoy de acuerdo en participar en
este estudio y/o tener mi hijo/a participar en este estudio. Yo he recibido una copia
de esta forma.

Nombre del Participante

168

Nombre del Padre de familia (1)

Firma del Padre o Tutor (1) Fecha

FIRMA DE INVESTIGADORA

Yo he explicado el estudio al participante y sus padres y he contestado a sus
preguntas. Yo creo que los padres de familia entienden la información descrita en
este documento y dan permiso libremente.

Nombre de la Persona Obteniendo Consentimiento

Firma de la Persona Obteniendo Consentimiento Fecha

169
APPENDIX D
SELF-EFFICACY AND GOAL ORIENTATION SURVEY
Label for Student ID#, Birth date & School Code
Here are some questions about you as a student. Please circle the number that best
describes what you think. All information will be kept confidential. There is no
correct answer.

1. It’s important to me that I learn a lot of new concepts this year.

1 2 3 4 5
Not at all true Somewhat true Very true

2. One of my goals in class is to learn as much as I can.

1 2 3 4 5
Not at all true Somewhat true Very true

3. One of my goals is to master a lot of new skills this year.

1 2 3 4 5
Not at all true Somewhat true Very true

4. It’s important to me that I thoroughly understand my class work.

1 2 3 4 5
Not at all true Somewhat true Very true

5. It’s important to me that I improve my skills this year.

1 2 3 4 5
Not at all true Somewhat true Very true

6. I’m certain I can master the skills taught in class this year.

1 2 3 4 5
Not at all true Somewhat true Very true

170

7. I’m certain I can figure out how to do the most difficult class work.

1 2 3 4 5
Not at all true Somewhat true Very true

8. I can do almost all the work in class if I don’t give up.

1 2 3 4 5
Not at all true Somewhat true Very true

9. Even if the work is hard, I can learn it.

1 2 3 4 5
Not at all true Somewhat true Very true

10. I can do even the hardest work in this class if I try.

1 2 3 4 5
Not at all true Somewhat true Very true

11. Even if I do well in school, it will not help me have the kind of life I want when I
grow up.

1 2 3 4 5
Not at all true Somewhat true Very true

12. My chances of succeeding later in life don’t depend on doing well in school.

1 2 3 4 5
Not at all true Somewhat true Very true

13. Doing well in school improves my chances of having a good life when I grow up.

1 2 3 4 5
Not at all true Somewhat true Very true

14. Getting good grades in school will guarantee that I will get a good job when I
grow up.

1 2 3 4 5
Not at all true Somewhat true Very true

171
15. Even if I am successful in school, it won’t help me fulfill my dreams.

1 2 3 4 5
Not at all true Somewhat true Very true

16. Doing well in school won’t help me have a satisfying career when I grow up.

1 2 3 4 5
Not at all true Somewhat true Very true

172
Label for Student ID#, Birth date & School Code
Rate your degree of confidence by recording a number from 0 to 100 using the scale
given below:

0 10 20 30 40 50 60 70 80 90 100
Cannot Moderately Highly certain
do at all can do can do

I am confident that I can…
Confidence (0-100)

Learn reading, writing, and language skills _____

Learn to use computers _____

Learn a foreign language _____

Learn social studies _____

Learn English grammar _____

Finish my homework assignments by deadlines _____

Get myself to study when there are other interesting things to do _____

Take good notes during classroom instruction _____

Plan my schoolwork for the day _____

Remember well information presented in class and textbooks _____

173
APPENDIX E
SELF-EFFICACY AND GOAL ORIENTATION SURVEY (SPANISH)
Label for Student ID#, Birth date & School Code
Aquí están unas preguntas sobre como eres como un estudiante. Favor de encerrar
con un circulo el numero que mejor describe como piensas. Toda la información
estará mantenido confidencial. No hay una respuesta correcta.

1. Es importante para mí que yo aprendo muchos conceptos nuevos durante este
año.

1 2 3 4 5
No es cierto Más o menos cierto Muy cierto

2. Una de mis metas en la clase es aprender el más que puedo.

1 2 3 4 5
No es cierto Más o menos cierto Muy cierto

3. Una de mis metas es aprender con destreza muchas habilidades este año.

1 2 3 4 5
No es cierto Más o menos cierto Muy cierto

4. Es importante para mí que entiendo mi trabajo de la clase completamente.

1 2 3 4 5
No es cierto Más o menos cierto Muy cierto

5. Es importante para mí que mejoro mis habilidades este año.

1 2 3 4 5
No es cierto Más o menos cierto Muy cierto

6. Estoy seguro/a que puedo aprender con destreza las habilidades enseñado en la
clase este año.

1 2 3 4 5
No es cierto Más o menos cierto Muy cierto

174

7. Estoy seguro/a que puedo entender como hacer el trabajo de la clase más difícil.

1 2 3 4 5
No es cierto Más o menos cierto Muy cierto

8. Yo puedo hacer casi todo el trabajo de la clase si no me doy por vencido.

1 2 3 4 5
No es cierto Más o menos cierto Muy cierto

9. Aún si el trabajo es difícil, yo puedo aprenderlo.

1 2 3 4 5
No es cierto Más o menos cierto Muy cierto

10. Yo puedo hacer aún el trabajo más difícil de esta clase si intento.

1 2 3 4 5
No es cierto Más o menos cierto Muy cierto

11. Aún si hago bien en la escuela, no me ayudaría a tener el tipo de vida que deseo
cuando yo sea grande.

1 2 3 4 5
No es cierto Más o menos cierto Muy cierto

12. Las posibilidades de tener éxito más tarde en mi vida no dependen en como hago
en la escuela.

1 2 3 4 5
No es cierto Más o menos cierto Muy cierto

13. Haciendo bien en la escuela mejora las posibilidades de tener una vida buena
cuando yo sea grande.

1 2 3 4 5
No es cierto Más o menos cierto Muy cierto

175

14. Recibiendo buenas calificaciones en la escuela garantiza obtener un buen trabajo
cuando yo sea grande.

1 2 3 4 5
No es cierto Más o menos cierto Muy cierto

15. Aún si tengo éxito en la escuela, no me ayudaría a cumplir mis sueños.

1 2 3 4 5
No es cierto Más o menos cierto Muy cierto

16. Haciendo bien en la escuela no me ayudaría a tener una carera satisfactoria
cuando yo sea grande.

1 2 3 4 5
No es cierto Más o menos cierto Muy cierto

176
Label for Student ID#, Birth date & School Code
Evalúe su nivel de seguridad en si mismo escogiendo un numero del 0 al 100 usando
la siguiente escala:

0 10 20 30 40 50 60 70 80 90 100
No puedo Puedo hacer Altamente seguro
hacerlo moderadamente que puedo hacerlo

Tengo confianza que puedo…
Confianza (0-100)

Aprender lectura, escritura y habilidades de artes de lenguaje _____

Aprender a usar computadoras _____

Aprender un idioma extranjero _____

Aprender estudios sociales _____

Aprender la gramática de Ingles _____

Terminar mis tareas antes de la fecha limite _____

Estudiar aún cuando hay otras cosas interesantes que hacer _____

Tomar buenos apuntes durante la instrucción de la clase _____

Planear mi trabajo de la escuela para el día _____

Recordar bien la información presentada en la clase y los libros de textos _____

Abstract (if available)

Abstract There is a relationship between self-efficacy, goal orientation, and academic performance, which is based on the social cognitive theoretical framework and substantiated by a large body of research. This study investigated the intersection between retention and academic performance specifically with English Language Learners and low socioeconomic populations. The purpose of this study was to contribute to the small volume of existing literature that highlights the academic and motivational affects of retention on middle school students from ethnic and low socioeconomic backgrounds. Specifically, this study examined three key areas: (a) to examine whether there is a relationship between the motivation of retained versus nonretained students

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The practice and effects of a school district's retention policies

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The relationship of students' self-regulation and self-efficacy in an online learning environment

Asset Metadata

Creator Rodriguez, Michelle L. (author)

Core Title Motivational and academic outcomes in retained middle school students

School Rossier School of Education

Degree Doctor of Education

Degree Program Education

Publication Date 04/09/2012

Defense Date 04/06/2012

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

Tag English language learners,goal orientation,grade retention,OAI-PMH Harvest,self efficacy

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Hirabayashi, Kimberly (committee chair), García, Pedro Enrique (committee member), Seli, Helena (committee member)

Creator Email michelle.rodriguez@sausd.us

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c3-3811

Unique identifier UC11288295

Identifier usctheses-c3-3811 (legacy record id)

Legacy Identifier etd-RodriguezM-581.pdf

Dmrecord 3811

Document Type Dissertation

Rights Rodriguez, Michelle L.

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