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Motivational, parental, and cultural influences on achievement and persistence in basic skills mathematics at the community college

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Motivational, parental, and cultural influences on achievement and persistence in basic skills mathematics at the community college

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Content MOTIVATIONAL, PARENTAL, AND CULTURAL INFLUENCES
ON ACHIEVEMENT AND PERSISTENCE
IN BASIC SKILLS MATHEMATICS AT THE COMMUNITY COLLEGE

by

Donna E. Nordstrom

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 Donna E. Nordstrom
ii

DEDICATION
For my mother and father.
iii

ACKNOWLEDGMENTS
Sincere thanks to my dissertation chair, Dr. Ruth Chung, and to my dissertation
committee members, Dr. Kim Hirabayashi and Dr. Brock Klein. Your expertise and
encouragement were invaluable. Thank you for supporting my efforts to complete this
study.
I am also grateful to my friends and family for encouraging me throughout this
process. Without their support evidenced in very practical ways, this study would not
have been completed. Particularly, I thank my Mom and Dad for providing so many days
and nights of excellent child care and delicious meals. Your deep faith, constant
encouragement and unconditional love strengthened me. Thank you for being my biggest
fans and for always believing in me. I am grateful to my brother’s family for often
including my son in their activities so I could study, and I thank my sister for her
encouraging cross-country phone calls.
Lastly, I give a big, big thank you to my precious son who patiently endured
through my doctoral program right alongside me, who graciously adjusted to changes in
our daily routine, and who now probably knows more educational psychology than any
other 11-year-old. Thank you for your patience and kindness. Thank you for making me
laugh. You bring me so much joy. I pray you continue to walk where Christ leads. I
look forward to encouraging and supporting you through your own doctoral program one
day.
iv

TABLE OF CONTENTS
Dedication ii

Acknowledgements iii

List of Tables vii

Abstract viii

Chapter I: Introduction 1
Background of the Problem 3
Theoretical Frameworks Used in this Study 6
Social Cognitive Theory 7
Self-efficacy 8
Self-regulation 9
Importance of the Study 9
Purpose of the Study 10
Research Questions 11
Definitions 11

Chapter II: Literature Review 13
Self-Efficacy 13
Self-efficacy, Academic Achievement and Persistence. 16
Self-efficacy and College Students 17
Mathematics Self-efficacy 17
Summary of Self-efficacy 20
Self-Regulation 20
Self-regulation and College Students 22
Self-regulation and Achievement 25
Summary of Self-regulation 26
Parenting Style 26
Baumrind’s Framework 27
Parenting Style’s Influence on Academic Achievement 28
Parenting Style’s Influence on College Students 28
Parenting Styles, Ethnicity and Academic Achievement. 29
Summary of Parenting Styles 31
Relations Between Self-Efficacy, Self-Regulation and Parenting Style 31
Acculturation 33
Acculturation Theory 33
Acculturation of Hispanic Adolescents and Young Adults 34
Acculturation Influence on Achievement of Hispanic Students 37
Summary of Acculturation 38
Summary 39

v

Purpose of the Study 40
Research Questions 41

Chapter III: Methodology 42
Participants 42
Instruments 44
Demographics 44
Math Self-efficacy 44
Self-regulation 45
Parenting style 47
Acculturation 49
Achievement 50
Persistence 51
Procedure 51
Data Analysis 51

Chapter IV: Results 53
Preliminary Analysis 53
Descriptives 53
Correlations 53
Analysis of Research Questions 57
Results of Research Question 1 57
Results of Research Question 2 59
Group Differences Across Self-efficacy, Math Grade,
and Persistence
59
Group Differences Across Self-regulation 60
Group Differences Across Parenting Styles 60
Results of Research Question 3 61
Results of Research Question 4 62

Chapter V: Discussion 65
Discussion of Results 65
Relationship between Motivational and Parental Variables and
Achievement and Persistence
65
Group Differences 67
Relationship between Self-efficacy, Self-regulation, Parenting
Style, Acculturation and Math Achievement and Persistence
for Hispanic Students
68
Relationship between Acculturation and Self-efficacy, Self-
regulation and Parenting Style
69
Implications for Research and Practice 71
Limitations of the Study 73
Recommendations for Future Research 75
Conclusion 76

vi

References 78

Appendices
Appendix A: Information Sheet for Non-Medical Research 86
Appendix B: Demographic Information 89
Appendix C: Math Self-efficacy and Self-regulation Scale 90
Appendix D: Parental Authority Questionnaire 94
Appendix E: Bidimensional Acculturation Scale for Hispanics 97

vii

LIST OF TABLES
Table 1: Frequency Distribution of Student Participants 43
Table 2: Means, Standard Deviations, and Pearson Product Correlations for
Measured Variables.

55
Table 3: Summary of Simultaneous Regression Analysis for Variables
Predicting Math Achievement

58
Table 4: Summary of Logistic Regression Analysis for Variables Predicting
Persistence in a Math Course

59
Table 5: Summary of Simultaneous Regression Analysis for Variable
Predicting Math Achievement among Hispanics

62
Table 6: Summary of Simultaneous Regression Analysis for Acculturation
Variables Predicting Math Self-efficacy among Hispanics

63
Table 7: Summary of Simultaneous Regression Analysis for Acculturation
Variables Predicting Effort Regulation among Hispanics

64
Table 8: Summary of Simultaneous Regression Analysis for Acculturation
Variables Predicting Authoritative Parenting among Hispanics

64
viii

ABSTRACT
The purpose of this study was to address the gap in the current literature on
community college students in basic math courses by examining motivational, parental
and cultural factors as predictors of achievement and persistence of students enrolled in
basic skills mathematics courses at a community college. More specifically, this study
investigated the degree to which mathematics self-efficacy, self-regulation, and parenting
style predict achievement and persistence of community college students in prealgebra
and elementary algebra. For Hispanics in particular, an additional variable of
acculturation was considered. Participants included 390 community college students
enrolled in a basic skills math course. Participants completed a paper-and-pencil survey
consisting of demographic background information, the self-efficacy and self-regulation
subscales of the Motivated Strategies for Learning Questionnaire, the Parental Authority
Questionnaire, and the Bidimensional Acculturation Scale for Hispanics. Results suggest
that both math self-efficacy and self-regulation are important influences on achievement
and persistence in a basic skills math course. Math self-efficacy and regulation of time
and study environment were found to be the most significant predictor variables for
achievement and persistence of community college students in a basic skills math course.
Caucasian students earned significantly higher grades in their basic skills math courses as
well as reported having higher levels of self-regulation of their time and study
environment than did their Hispanic counterparts. Math self-efficacy and regulation of
time and study environment were found to be the most significant predictor variables for
achievement by Hispanic students in a basic skills math course. Lastly, while
acculturation to the dominant culture for Hispanic students correlated significantly with
ix

math self-efficacy, metacognitive regulation, effort regulation, and authoritative
parenting, it explained a small percentage of the variance in math self-efficacy, effort
regulation and authoritative parenting. Results of this study emphasize the importance of
community college math faculty understanding motivational principles. Specifically,
implications for practice include community college math faculty learning and
implementing strategies to strengthen their students’ math self-efficacy and improve the
students’ regulation of time and study environment.
1

CHAPTER I: INTRODUCTION
The 112 California community colleges served over 2.6 million students in the
2010-2011 academic year (California Community Colleges Chancellor’s Office
[CCCCO], 2012a). This system is the largest higher education organization in the nation
and represents nearly 25% of the nation’s community college student population
(CCCCO, 2012b). In addition, the California Community College system serves more
minority students than any other institution of higher learning (American Association of
Community Colleges, 2009) with minorities making up approximately 65% of the student
population and Hispanics being the largest minority group consisting of almost 34% of
the 2010-2011 student body (CCCCO, 2012a).
Unfortunately, many of these community college students are entering college
unprepared for college level courses. Upon arrival at a community college in California,
72% of students assess at below college-level English (CCCCO, 2009a). In mathematics,
the situation is even worse; 84% of incoming community college students in California
assess at below college-level mathematics (CCCCO, 2009a). These students must enroll
in 1 to 5 semesters, possibly more than 2 academic years, of coursework which will not
transfer to a university.
Furthermore, a large percentage of these students subsequently fail or drop out of
these below college-level courses. In the academic year 2009-2010, the course
completion rate across California for pre-collegiate level math and English courses at
community colleges was 61.4% (CCCCO, 2011a). In mathematics, the course
completion rate is even lower; 52.6% of students successfully completed their pre-
collegiate level math course (CCCCO, 2011b). In addition, the persistence rate from fall
2

2009 to fall 2010 for underprepared students at California community colleges was
68.7% (CCCCO, 2009b). Certainly, these success and persistence rates are troubling,
and factors contributing to these patterns need to be investigated.
California Community Colleges also face the challenge of making a college
education attainable for their large Hispanic student population. At the community
college, Hispanics are overrepresented in courses below college-level while European-
Americans are underrepresented. In the 2010-2011 academic year, 34% of California
community college students identified themselves as Hispanic while 41% of students in
pre-collegiate courses identified as Hispanic (CCCCO, 2012a). On the other hand, 34.4%
of California community college students identified themselves as White, while only
21.8% of students in pre-collegiate courses identified as White (CCCCO, 2012a).
Unfortunately, the achievement gap which exists in K-12 for Hispanics also exists
at the community college level. While 30% of all degree-seeking students have
completed a certificate or degree after six years from starting at a community college,
only 22% of degree-seeking Hispanics have completed a certificate or degree after six
years (Moore & Shulock, 2010). Furthermore, Hispanics were less than half as likely to
transfer as their white counterparts at the community college, with 14% of Hispanics
transferring as opposed to 29% of whites (Moore & Shulock, 2010).
It is critical to understand the factors that influence college students’ ability to
succeed academically, particularly when these students are underprepared for college
level math. Research has long supported the powerful influence of motivation factors on
academic achievement (Chemers, Hu, & Garcia, 2001; Pintrich & De Groot, 1990;
Zimmerman, Bandura, & Martinez-Pons, 1992) especially factors such as self-efficacy
3

(Multon, Brown, & Lent, 1991) and self-regulation (Kitsantas, Winsler, & Huie, 2008;
Schunk & Zimmerman, 1998; Zimmerman, 1990). Furthermore, parental influences have
been shown to play a role in the development of self-efficacy beliefs and self-regulation
strategies. Research also has identified acculturation as an important influence on
educational outcomes of Hispanic students (Carranza, You, Chhuon, & Hudley, 2009;
Martinez, DeGarmo & Eddy, 2004) with some research finding an indirect relationship
between acculturation of Hispanics and academic achievement through parental
educational expectations (Carranza, You, Chhuon, & Hudley, 2009).
This study addresses the problem of low success rates among underprepared
community college math students by examining the relationship between motivational,
parental and cultural factors and academic outcomes. Specifically, this study was
designed to investigate the relationship between math self-efficacy, self-regulation,
parenting styles and achievement in pre-collegiate math courses at the community
college. Acculturation of Hispanics was also examined in conjunction with the above
variables. The following section further explores the current situation regarding
academic achievement in below college-level mathematics at California community
colleges.
Background of the Problem
The community college system plays an important role in the higher education
system within California. In 1960, the California Legislature approved the Master Plan
for Higher Education which developed a coherent, coordinated relationship between three
educational segments: the University of California (UC), the California State University
(CSU), and the California Community College (CCC) system (California Postsecondary
4

Education Commission, 2002). While UC and CSU schools accept the top one-eighth
and one-third of the graduating high school class respectively, the California Community
Colleges are required to accept all applicants (California Postsecondary Education
Commission, 2002). This open enrollment policy has made the California Community
College system into the largest higher education system in the nation, serving nearly 2.6
million students in 2010-211 (CCCCO, 2012a).
While the primary mission of community colleges is to provide instruction in the
first two years of undergraduate work, another aspect of their role is to provide necessary
“remedial instruction” (California Postsecondary Education Commission, 2002). Several
terms such as remediation, pre-collegiate, basic skills, and developmental have been used
to refer to courses below college-level, to skills necessary to succeed in college-level
work, and even to students themselves who are not prepared for college-level work.
Currently, in the community college context, the use of the term “basic skills” is
encouraged. Basic skills are considered those foundation skills in reading, writing and
mathematics that are necessary for students to succeed in college-level work (Academic
Senate for California Community Colleges, 2007).
It is not uncommon for community colleges to offer three, and sometimes even
four, levels of math courses that are below college-level math. These courses may have
titles such as arithmetic, mathematical foundations, prealgebra, elementary algebra, or
intermediate algebra. The majority of students assessing at below college-level math
actually assess at two or three levels below college-level (CCCCO, 2009). In 2004, the
California Legislature introduced a new performance measurement system by means of
the Basic Skills Initiative in which all community colleges were asked to improve in
5

several areas, including student performance in basic skills math courses (CCCCO,
2010b) which have a 52.6% success rate (CCCCO, 2011b). Under the directive of the
Legislature, California community colleges have been mandated to increase the success
rates of students in these basic skills mathematics courses.
The low success and completion rates at the community colleges are putting a
strain on the coherent, coordinated relationship between the three segments of higher
education. According to Moore and Shulock (2010) only 43% of transfer students
actually completed a transfer curriculum before transferring, thus not following the
“intent” of the Master Plan. In addition, the sheer magnitude of basic skills programs
throughout the state depletes a significant amount of community college resources.
Across the state, basic skills math sections totaled 25% of the credit sections offered
(CCCCO, 2009). The California Budget Project (2011) reports that California spends
almost $600 million a year in state and local funding on basic skills education at the
community colleges. Students themselves incur additional costs when they must repeat a
course they previously failed. In this budget crisis era, it is important that community
colleges increase the success and persistence rates of students in basic skills math classes.
Furthermore, while academic achievement is related in general to numerous
positive outcomes such as greater earnings and healthier lifestyles (Baum, Ma, & Payea,
2007; National Center for Education Statistics, 2010), it is specifically related to job
opportunities. According to the Georgetown Center on Education and the Workforce, by
the year 2018 about two-thirds of all jobs will require some college education.
Completion of even some college work requires successfully completing basic skills
math. Hence, prealgebra and elementary algebra specifically are prerequisites for other
6

courses which are needed to obtain almost any level of college education, whether it be to
earn an associate’s degree, to acquire program certification, or to transfer to a four-year
university. Failing these basic skills math courses keeps thousands of students from
continuing on with their future higher education plans. Students are certainly locked out
of any of the STEM (Science, Technology, Engineering and Mathematics) majors and
careers if they are unable to pass a college-level math course. It is clear that failing basic
skills math courses severely limits one’s options for choice of major as well as career
opportunities.
This is especially evident among the Hispanic student population as the
achievement gap leads to an under-representation of Hispanics in both science degree
programs as well as in the scientific workplace. For instance, in 2006, Hispanics made
up only 4% of the science and engineering workforce while comprising roughly 15% of
the US population (U. S. Census Bureau, 2009). Failure to complete basic skills math
programs severely limits job opportunities for Hispanics. Due to the large growth of the
Hispanic population in the United States, in California and in basic skills courses and in
light of their lower performance, it is imperative to study factors that influence Hispanic
students’ academic success, particularly in mathematics.
Theoretical Frameworks Used in this Study
Several major theories provide a framework for this study, particularly Social
Cognitive Theory in considering personal, behavioral and environmental factors which
influence learning. The following section briefly describes this overarching Social
Cognitive Theory as well as two important constructs within this theory: self-efficacy and
self-regulation. More in-depth discussion on theories is provided later in Chapter 2.
7

Social Cognitive Theory. Social Cognitive Theory is based on Bandura’s (1986)
concept of triadic reciprocality. Bandura’s (1986) model of human functioning involves
reciprocal interactions of personal, behavioral and environmental factors. According to
this theory, personal factors such as cognition, affect and biological factors constantly
interact with behavior and environmental influences to produce this threefold reciprocal
relationship. From this perspective, people are both “products and producers of their own
environments and of their social systems” (Pajares, 2008, p. 112). Specifically, personal
factors such as self-efficacy and acculturation, behavioral factors such as self-regulation
and performance, and environmental factors such as culture and parents all interact with
each other to produce a threefold reciprocal relationship.
Bandura (1986) proposed that these reciprocal interactions influence one’s
learning. As its name suggests, Social Cognitive Theory attributes an individual’s
learning and cognitive development to both social and cognitive factors. Specifically,
two types of learning are described: enactive and vicarious. In enactive learning, one
learns by doing and experiencing the consequences of one’s own actions. In addition,
one receives direct feedback (e.g. information, consequences) about one’s own
performance. However, one also can learn vicariously through observing models such as
parents, teachers, or classmates or even symbolic models such as textbooks. Self-
efficacy and self-regulation are key constructs within this theory. According to Social
Cognitive Theory, acculturation and parenting styles are considered both personal and
environmental factors which interact with behavior to influence learning. This study
investigated aspects of triadic reciprocal interactions between some personal factors (i.e.
self-efficacy, self-regulation, acculturation), behavioral factors (i.e. use of self-regulation
8

strategies, achievement, and persistence in a college mathematics course) and
environmental factors (i.e. culture, parents).
Self-efficacy. An important aspect of the Social Cognitive Theory of motivation
is self-efficacy. A person’s self-efficacy to perform a task is that person’s judgment of
his or her capabilities to successfully complete the task. Unlike one’s self-concept or
self-worth, self-efficacy is very task specific. When one has high self-efficacy for a task,
one is more likely to choose to perform this task, put forth effort to complete the task and
persist in the task (Barnyak & McNelly, 2009; Luszczynska, Gutiérrez-Doña, &
Schwarzer, 2005; Schunk, 1995).
Bandura (1997) hypothesized that students interpret information from four
sources to form their self-efficacy beliefs. These sources are mastery experience,
vicarious experience, social persuasion, and physiological states. While all four sources
correlate significantly with self-efficacy, mastery experience has been shown to have the
greatest influence on the formation of self-efficacy (Britner & Pajares, 2006; Klassen,
2004; Pajares, 2008; Usher & Pajares, 2006). Mastery experience is when a student
engages in a task and then interprets the results. Students make judgments about their
abilities based on their interpretation of the task’s outcomes. Such self-efficacy beliefs
influence behaviors which in turn modify self-efficacy beliefs. In the mean time,
environmental influences from teachers and peers are also affecting self-efficacy beliefs
and behaviors. Triadic reciprocality is clearly evident when one considers the construct
of self-efficacy. Closely related to self-efficacy and motivation is self-regulation. This
next section provides a brief description of self-regulation from a social cognitive
perspective.
9

Self-regulation. Self-regulation is the “process by which learners personally
activate and sustain cognition, affects, and behaviors that are systematically oriented
toward the attainment of learning goals” (Schunk & Zimmerman, 2008, p. vii). Social
Cognitive Theory considers self-regulation to consist of three processes: self-observation,
self-judgment, and self-reaction (Bandura, 1986; Zimmerman, 1990). Bandura’s (1997)
triadic reciprocality is manifested again as these processes interact with each other as
well as with the environment. Because personal, behavioral and environmental factors
change during learning, the process of self-regulation is a cyclical process in which
students monitor their learning, implement strategies to attain their goals and reflect on
their progress (Zimmerman, 2008; Schunk, Pintrich, & Meece, 2008). Zimmerman’s
three phase model of self-regulation defines these aspects of self-regulation as the
forethought phase, the performance control phase and the self-reflection phase
(Zimmerman, 2008). Academic self-efficacy beliefs have been shown to be influential
during all three of these self-regulation phases (Pajares, 2008).
Importance of the Study
California community colleges served nearly 2.6 million students last year. While
the primary mission of community colleges is to provide instruction in the first two years
of undergraduate work, these colleges must also provide instruction at the basic skills
level in order to meet the needs of the underprepared student. However, only a little
more than half of basic skills students are successful in their mathematics courses. The
California legislature has urged community colleges to increase the success rate of basic
skills students. Self-efficacy and self-regulation have been found to be significant
predictors of academic achievement at various grade levels as has authoritative parenting
10

for the achievement of Caucasian students. In addition, acculturation is known to be
related to academic outcomes for Hispanics who are an overrepresented population in
community college basic skills courses. However, these motivational, parental, and
cultural factors have yet to be examined collectively among the basic skills math
community college population. To that end, this study provides a deeper understanding of
how these factors relate to the achievement and persistence of community college
students in basic skills mathematics courses.
Administrators, faculty, parents and students can benefit from the findings of this
study. Knowledge of the motivational, parental and cultural factors influencing
achievement will provide community college administrators a better understanding of the
necessary student support services to offer. This knowledge will enable administrators
and faculty to better target intervention programs specifically for the basic skills student.
“First-year College Success” courses or parenting training courses may be improved.
Parents will gain awareness of parenting styles that positively influence their child for
academic success. Given that Hispanics comprise 41% of basic skills students across the
state, community college faculty need to be aware of acculturation factors which their
students may be experiencing. Students themselves will be able to make better use of
their time at college with an increased awareness of their own self-efficacy beliefs and
use of self-regulation strategies.
Purpose of the Study
The purpose of this study was to address the gap in the current literature on
community college students in basic math courses by examining motivational, parental
and cultural factors as predictors of achievement and persistence of students enrolled in
11

basic skills mathematics courses at a community college. More specifically, this study
investigated the degree to which mathematics self-efficacy, self-regulation, and parenting
style predict achievement and persistence of community college students in prealgebra
and elementary algebra. For Hispanics in particular, an additional variable of
acculturation was considered.
Research Questions
This study aims to investigate the following four research questions:
Research Question 1: Do math self-efficacy, self-regulation, and parenting style predict
math achievement and persistence among basic skills math students in California
community colleges?
Research Question 2: Is there is a difference between Hispanics and European-American
students enrolled in a basic skills math course at a community college in math self-
efficacy, self-regulation, parenting style, math achievement and persistence in a math
course?
Research Question 3: Along with math self-efficacy, self-regulation, and parenting style,
does acculturation predict math achievement and persistence among Hispanic basic
skills students in community colleges?
Research Question 4: Does acculturation predict math self-efficacy, self-regulation, and
parenting style among Hispanic basic skills students in community colleges?
Definitions
Basic Skills. Basic skills are considered those foundation skills in reading,
writing and mathematics that are necessary for students to succeed in college-level work.
12

Persistence. For the purposes of this study, persistence is considered persisting
through a math course. Hence, persistence is defined in terms of course completion
which is measured by whether or not the student withdrew from the class.
The remaining chapters have been organized as follows:
Chapter 2 is a review of the recent literature in the areas of self-efficacy, self-
regulation, parenting styles, and acculturation.
Chapter 3 presents the methodology used in this study, including a description of
the participants, the instruments used, the data collection procedures and the methods of
data analysis.
Chapter 4 reviews the results of the study and addresses the research questions.
Chapter 5 provides a discussion of the major results of the research, as well as its
limitations and implications.
13

CHAPTER II: LITERATURE REVIEW
The following section is a review of the literature relating to how self-efficacy,
self-regulation, parenting styles, and acculturation of Hispanics influence academic
achievement and persistence. These factors are first explored in general academic
settings and then specifically within the college population. This chapter begins with a
section on self-efficacy, followed by sections on self-regulation and parenting style. The
subsequent section explores relations between these three variables. This is followed by
a section on acculturation. The chapter then concludes with a summary and a
presentation of the research questions.
Self-efficacy
An important construct of Social Cognitive Theory is self-efficacy. A person’s
self-efficacy to perform a task is that person’s judgment of his or her capabilities to
successfully complete the task (Bandura, 1997). Unlike one’s self-concept or self-worth,
self-efficacy is very task specific. When one has high self-efficacy for a task, one is more
likely to choose to perform this task, put forth effort to complete the task and persist in
the task (Luszczynska et al., 2005; Barnyak & McNelly, 2009). Bandura (1997)
proposed that students make cognitive judgments about their ability to organize and
execute necessary steps to complete a task. At their core, self-efficacy beliefs are beliefs
that one’s actions will produce some change. Thus, Bandura (1997) hypothesized that
students’ self-efficacy contributes to their academic performance. Research has found
that self-efficacy not only relates to academic performance but also to numerous other
positive outcomes (Britner & Pajares, 2006; Multon et al., 1991; Usher & Pajares, 2006).
14

Bandura (1997) hypothesized that students interpret information from four
sources to form their self-efficacy beliefs. These sources are mastery experience,
vicarious experience, social persuasion, and physiological states. While all four sources
correlate significantly with self-efficacy, mastery experience - when a student engages in
a task and then interprets the results - has been shown to have the greatest influence on
the formation of self-efficacy (Britner & Pajares, 2006; Klassen, 2004; Usher & Pajares,
2006). Generally, successful experiences will raise one’s self-efficacy while failures will
lower it. However, an occasional failure among several successes will generally not
significantly change one’s self-efficacy. Vicarious experiences refer to situations in
which one observes the performance of others considered similar to oneself. Social
persuasion includes the phenomenon in which self-efficacy beliefs are formed through
comments or feedback from others. Finally, Bandura (1997) considered physiological
states as a source of self-efficacy beliefs. Physiological reactions such as heart
palpitations or sweaty palms may influence an individual to conclude he or she lacks skill
for a certain task, thus altering his or her self-efficacy beliefs.
Numerous studies have investigated how these sources of self-efficacy beliefs
differ depending on numerous variables such as subject domain, gender, and race.
Britner and Pajares (2006) specifically investigated the sources of science self-efficacy.
Their findings were consistent with studies of self-efficacy of general academic
performance in that science self-efficacy was the most consistent predictor of middle
school students’ science grades (Britner & Pajares, 2006). Usher and Pajares (2006)
found that social persuasion, as well as mastery experience predicted self-efficacy in
middle school females while vicarious experience, along with mastery experience,
15

predicted academic self-efficacy in middle school males. The relationship between self-
efficacy and academic performance is evidenced across various ethnicities including
African American (Long, Monoi, Harper, Knoblauch, & Murphy, 2007; Usher & Pajares,
2006) and Indo-Canadian (Klassen, 2004), as well as Costa Rican, German, Polish, and
Turkish (Luszczynsk et al., 2005). In addition to mastery experience, physiological state
predicted academic self-efficacy for White students while social persuasions predicted it
for African American students (Usher & Pajares, 2006).
Furthermore, because Bandura (1986) suggested that self-efficacy beliefs are
domain and task specific, he warned that measures of self-efficacy also must be equally
task specific. Other researchers (Multon et al., 1991; Pajares & Miller, 1995) agree that
self-efficacy must be specifically rather than globally assessed, that there must be a direct
correspondence between the assessment and the performance task, and that the
assessments of self-efficacy and the corresponding performance be given as close in time
as possible. Because of this, researchers have not only assessed a general academic self-
efficacy which they relate to GPA (Multon et al., 1991) but also self-efficacy for specific
subjects (i.e. math, science, reading) which they relate to performance in the
corresponding class (Pietsch, Walker and Chapman, 2003) as well as self-efficacy for
completing very specific tasks (i.e. solve a stated math problem) which they relate to
one’s performance on that exact same task (Pajares & Miller, 1994; Pajares & Miller,
1995). The following sections consider some of the above literature as self-efficacy is
first discussed in relation to achievement and persistence and then specifically in relation
to college students. This is followed by a discussion of math self-efficacy.
16

Self-efficacy, academic achievement and persistence. Twenty years ago, a
meta-analysis investigation found positive and significant relationships between self-
efficacy and academic performance and persistence (Multon et al., 1991). In the 36
studies used in this meta-analysis, several different measures of academic performance
were used, ranging from standardized tests to classroom related measures to basic skills
tasks. Self-efficacy was found to be significantly related to academic performance.
Furthermore, the meta-analysis (Multon et al., 1991) found this relation of self-efficacy to
performance varied by students’ achievement status. The stronger relationships between
self-efficacy and performance were found among low-achieving students than among
average achieving students. Participants of the current study could be considered “low-
achieving” in math based on both their current level of math ability and their performance
in their particular math course. Thus, the findings of Moulton et al. (1991) suggest that
efforts to increase the self-efficacy of students in basic skills math classes at community
college may be particularly beneficial to their academic achievement. In addition,
persistence, measured in 18 of these studies included in the meta-analysis, was
operationalized as time spent on task, number of items attempted and number of
academic terms completed. Again, self-efficacy was found to be related to persistence.
Moreover, Multon et al. (1991) found some results which lend credence to
Bandura’s (1986) caution that self-efficacy must be assessed specifically and correspond
directly to a performance measurement given close in time. In the meta-analysis, the
strongest effects were produced by studies which compared specific efficacy judgments
with basic skills measure of performances and “used highly concordant self-efficacy
indices that were administered at the same time point” (Multon et al., 1991, p. 35).
17

During the past twenty years, researchers have continued to find that self-efficacy is a
significant predictor of academic performance (Chemer et al., 2001; Pietsch, Walker and
Chapman, 2003; Zimmerman et al., 1992) at all different grade levels including college
as discussed in the following section.
Self-efficacy and college students. Recently, another meta-analysis was
performed involving 109 studies of college and university students (Robbins et al., 2004).
This meta-analysis (Robbins et al., 2004) sought to integrate the literature on educational
persistence and motivational theory by examining the relationship between psychosocial
and study skill factors and college outcomes. Over 20,000 students were included in the
meta-analysis with almost 7,000 college students being included in studies involving
academic self-efficacy. Specifically, Robbins et al. (2004) explored whether academic
self-efficacy, achievement motivation, academic goals and six other psychosocial factors
predicted achievement as measured by GPA and persistence as measured be retention.
The meta-analysis indicated that academic self-efficacy positively correlated with both
achievement and persistence. In fact, academic self-efficacy and achievement motivation
were the best predictors of achievement in college (i.e. cumulative GPA) (Robbins et al.,
2004). Further analysis revealed that academic self-efficacy had a positive relationship to
achievement and persistence even after controlling for socioeconomic status, high school
GPA, and standardized test scores (Robbins et al., 2004). Considering that self-efficacy
beliefs are domain specific (Bandura, 1986), the following section explores mathematics
self-efficacy specifically.
Mathematics self-efficacy. Self-efficacy in the area of mathematics has
consistently been found to predict math-related performance (Hackett, 1985; Pajares &
18

Miller, 1994; Pajares & Miller, 1995; Pietsch, Walker and Chapman, 2003). Pajares and
Miller (1995) stressed the importance of heeding Bandura’s (1986) caution that self-
efficacy should be assessed specifically, not globally, and must correspond directly to the
performance task. Consequently, they assessed students’ math self-efficacy three
different ways: confidence to solve math problems, confidence to succeed in math-related
courses, and confidence to perform math-related tasks. Furthermore, they included 2
outcomes: solution of the same math problems on which the students’ self-efficacy was
assessed and choice of math-related majors. As expected, each outcome was more
strongly related to the similar type of assessment of self-efficacy than to the other types.
That is, students’ confidence to solve a math problem was a stronger predictor of their
ability to solve the identical problem than was their confidence to succeed in math-related
courses or confidence to perform general math-related tasks (Pajares & Miller, 1995).
Similarly, students’ confidence to succeed in a math course was more predictive of their
choice of major, which may require math-related courses, than was their confidence to
solve specific math problems or general math tasks (Pajares & Miller, 1995). Hence,
Pajares and Miller’s (1995) findings support Bandura’s (1986) theoretical claims as well
as provide evidence for the positive relation between math self-efficacy and math
performance.
Further evidence for this positive relation between math self-efficacy and math
performance is obtained by Pietsch et al. (2003). In their study involving over 400 high
school students, Pietsch et al. (2003) investigated relationships between math self-
efficacy, math self-concept and math performance. While the construct of math self-
concept was also included, the findings only on math self-efficacy and performance are
19

pertinent to this study. Students’ math self-efficacy was assessed by measuring the
students’ self-efficacy for performing well in math generally, for succeeding in their
current math course, and for solving specific math problems. Performance was assessed
using an end of the year exam as well as several specific math items completed at the
same time as the self-efficacy assessment. Similar to previous results (Pajares & Miller,
1995), the math self-efficacy scores related to performance with the stronger relation
being at the corresponding level of specificity. However, while stressing the need for
specificity of assessment, Pietsch et al. (2003) acknowledge that “within more general
domains such as mathematics,…,in which the tasks that constitute the domain cannot be
easily captured by a small number of items, more general measures of efficacy beliefs
represent efficient predictors of future performance” (p. 599). That is, Pietsch et al.
(2003) recognize that assessing self-efficacy for each aspect of a broad subject such as
mathematics is impracticable. Their particular study assessed students’ self-efficacy for
solving particular percentage problems, and this type of math self-efficacy had the
strongest relation with performance on solving these same percentage problems.
However, Pietsch et al. (2003) support assessing a more general form of math self-
efficacy, such as self-efficacy for succeeding in a particular math course, as this can be a
more practical yet still actual predictor of math performance.
Another area of research surrounding math self-efficacy has been in its relation to
choice of major and career. Specifically, many studies have found a relation between
math self-efficacy and interest in a science, technology, engineering, and mathematics
(STEM) field (Rottinghaus, Larson, & Borgen, 2003). Given the need for more STEM
20

majors in the U.S., especially among minorities, understanding the role of self-efficacy in
choice of major as well as achievement is essential.
Summary of self-efficacy. Research continues to find positive and significant
relationships between self-efficacy and academic achievement (Klassen, 2004; Multon et
al., 1991; Usher & Pajares, 2006) across various ethnicities (Long et al., 2007;
Luszczynsk et al., 2005; Usher & Pajares, 2006). Research findings continue to support
Bandura’s (1986) hypothesis that self-efficacy must be specifically rather than globally
assessed, that there must be a direct correspondence between the assessment and the
performance task, and that the assessments of self-efficacy and the corresponding
performance be given as close in time as possible (Multon et al., 1991; Pajares & Miller,
1995). In light of this, math self-efficacy has been found to relate significantly to math
achievement at different grade levels, including college (Hackett, 1985; Pajares & Miller,
1994; Pajares & Miller, 1995; Pietsch, Walker and Chapman, 2003). A construct often
intertwined with self-efficacy is self-regulation. Recently, Berger and Karabenick (2011)
found that math self-efficacy predicted more frequent use of self-regulation strategies.
The following section discusses literature on self-regulation with a particular emphasis on
college students and achievement.
Self-regulation
Schunk (2001) defines self-regulation as the process by which learners activate
and control their cognition, affects, and behaviors in order to achieve their academic
goals. From a social cognitive perspective, self-regulation involves setting specific goals,
utilizing learning strategies, maintaining high levels of self-efficacy and interest as well
as monitoring and reflecting on one’s performance (Schunk, 2001). Self-regulation is
21

often related to higher achievement (Zimmerman, 1990). Within a model of academic
self-regulation, researchers (Zimmerman & Risemberg, 1997; Dembo & Eaton, 2000)
have identified six dimensions of behavior that influence learning: motivation, methods
of learning, use of time, physical environment, social environment, and performance.
This review will examine the literature on self-regulation among college students using
the above six-dimensional model. These six dimensions are briefly discussed next.
The first dimension, motivation, is defined as the “process whereby goal-directed
activity is instigated and sustained” (Schunk, Pintrich, et al., 2008, p. 4). Thus,
motivation involves processes in which an individual intentionally and purposefully
initiates some behavior and puts forth effort to continue the behavior. We can measure
motivation through the 3 indices of choice of task, effort exerted on a task, and
persistence with a task (Schunk, Pintrich, et al., 2008). Dembo and Eaton (2000) suggest
that successful students can motivate themselves to complete a task even when they don’t
feel like it. Thus, according to Dembo and Eaton (2000), successful students must
control and monitor, that is self-regulate, their own motivation for academic tasks.
The second dimension, methods of learning, refers to strategies that students use
to self-regulate their learning. These include strategies such as elaboration, organization,
and rehearsal of material. The third dimension, use of time, refers to one’s ability to
control the use of one’s time in order to meet desired goals. Dembo and Eaton (2000)
suggest that the key factor is prioritizing activities. The fourth dimension, the physical
environment, refers to the self-regulation of one’s physical environment which may
include determining the need for a less distracting study space. The fifth dimension, self-
regulation of one’s social environment, refers to the ability to know when to seek help or
22

when to study alone or with others. Lastly, the performance dimension consists of
planning and monitoring one’s performance. Research on academic self-regulation can
be viewed from the perspective of these six dimensions. The following section explores
literature pertaining to self-regulation and the general college population.
Self-regulation and college students. Utilizing the motivation dimension,
Wolters (1998) explored self-regulation from a different perspective than most
researchers. As self-regulation involves controlling not only one’s cognition and
behavior but also affects, Wolters (1998) investigated college students’ self-regulation of
motivation itself, the first of the six dimensions. Specifically, Wolters (1998) studied
what strategies students use to regulate their motivation and how motivational regulation
is related to other aspects of self-regulation and achievement. Wolters (1998) categorized
responses from 115 college students into 14 categories of strategies used to cope with
three motivational problems: irrelevant material, difficult material and boring material.
The most frequently mentioned strategy, comprising of 22% of all responses, was that of
cognition. In this category, students responded that they used, for example, various
reading, test-taking, or note-taking strategies. In addition, this cognitive strategy was
employed when faced with difficult material significantly more than other means of self-
regulation. Negative attitudes towards mathematics may include beliefs that math is
irrelevant, difficult or boring which were the categories included in Wolters’ (1998)
study. Thus, it may be necessary for basic skills community college students who may
also believe math is irrelevant, difficult and boring to increase the self-regulation of their
own motivation for completing tasks in their mathematics course. Overall, Wolters’
23

(1998) findings support the model that self-regulation includes monitoring and regulating
one’s motivation for a task.
Additionally, as expected, Wolters (1998) found that students who employed
intrinsic regulation strategies (i.e. strategies aimed at increasing one’s self-efficacy, task
value, and interest) reported higher mastery goal orientation, working towards goals
based on a desire to understand material and master tasks. Similarly, the use of extrinsic
regulation strategies (i.e. promising oneself extrinsic rewards, working for performance
goals) was the only significant predictor of performance goal orientation, working
towards goals based on doing better than others or appearing smart to others. In essence,
these findings suggest that students self-regulate their motivation for tasks with strategies
similar to the goals they adopt regarding those same tasks (Wolters, 1998).
Unfortunately, no ethnicity data was given for the population.
Differences in self-regulation have been found among low- and high-achieving
students (Ruban & Reis, 2006; Zimmerman & Martinez-Pons, 1990). In particular, high-
achieving students have been found to use more effective and efficient strategies of self-
regulation than low achieving students (Ruban & Reis, 2006; Zimmerman & Martinez-
Pons, 1990). Using both open- and closed-ended items, Ruban and Reis (2006)
investigated patterns in the self-regulation strategies of 180 undergraduate students.
There were 49 students in the low-achieving group and 131 in the high-achieving group.
The coding of responses to open-ended questions resulted in 8 categories of self-
regulation strategies reported by low- and high-achieving students. While Ruban and
Reis (2006) used different names, these 8 categories included all but one (i.e. motivation)
of Dembo and Eaton’s (2000) dimensions. For instance, Ruban and Reis (2006) used
24

classifications of managing time, utilizing support networks, structuring environment,
and self-evaluating which correspond to Dembo and Eaton’s (2000) use of time, social
environment, physical environment and performance dimensions, respectively.
Similar to other findings, Ruban and Reis’ (2006) findings show that high
achievers reported using more advanced, deep processing strategies (Ruban & Reis,
2006), such as learning for meaning not just memorization, whereas low achievers
reported using simpler surface processing strategies such as memorizing and reviewing
notes. Ruban and Reis (2006) offer a possible reason for this which is particularly
pertinent to the current study of basic skills math college students whom could be
considered “low-achieving” in math based on their current level of math ability as well as
their performance in their particular math course. Ruban and Reis (2006) suggest that
perhaps high-achieving students have had more opportunities earlier in their academic
careers to learn self-regulation strategies. Hence, it may be that the low-achieving
students in community college basic skills math courses have not had sufficient
opportunities to develop self-regulation strategies. Thus, university staff would need to
provide opportunities for low-achieving students to learn, to develop and to practice their
self-regulation skills. Perhaps these occasions could be provided through a first-year
college success course or provided within a content-based class itself. The latter would
require the faculty to explicitly discuss self-regulation strategies and provide
opportunities for students to develop these skills in the context of the course content.
However, it must be noted that Ruban and Reis’ (2006) particular findings were obtained
from a population with a European American majority across both groups, low- and high-
achieving, and with less than 5% of the entire population being Hispanic. More research
25

is needed on the self-regulation strategies of Hispanics, particularly at the community
college level, in order to determine if similar findings hold for that particular population.
The following section explores the relation between self-regulation and academic
achievement.
Self-regulation and achievement. Self-regulation processes have been shown to
particularly influence academic achievement (Kitsantas et al., 2008; Wolters, 1998).
Kitsantas, Winsler, and Huie (2008) investigated two of Dembo and Eaton’s (2000) six
dimensions: use of time and performance. In their study, Kitsantas et al. (2008)
examined the role of self-regulation in predicting the academic performance of 243 first
semester undergraduate students at a large public university. Specifically, Kitsantas et al.
(2008) used subscales of the Motivated Strategies for Learning Questionnaire to
investigate time and study management strategies and metacognitive strategies. Both of
these strategies correlated significantly with first- and third- year college GPA. In fact,
time management strategies contributed unique variance in predicting achievement above
that of even prior ability. This study’s population was 64% White and only 4% Hispanic.
In addition, SAT scores were above the national average, as were household income and
parents’ level of education (Kitsantas et al., 2008). More research is needed to
investigate the relationship between performance of low-achieving students and their
self-regulation as measured by their use of time.
A construct often intertwined with self-regulation is self-efficacy (Pajares, 2008).
One self-regulation process within the forethought phase is goal setting. Zimmerman,
Bandura, and Martinez-Pons (1992) found that the setting of goals by self-efficacious
students predicted greater academic achievement. When goals are proximal, specific, and
26

moderately difficult, self-efficacy and motivation to attain these goals is increased. In
another study among urban 9
th
graders, math self-efficacy was found to predict greater
self-regulation through more frequent use of deep-processing learning strategies (Berger
& Karabenick, 2011).
Summary of self-regulation. Conclusions drawn from these studies suggest that
planning and monitoring one’s performance, use of time, and control of one’s physical
and social environments are dimensions of self-regulation that are significantly related to
academic achievement among high school and college students. Therefore, the specific
cognitive and behavioral processes examined in this study include metacognitive self-
regulation, time and study environment management, and effort regulation. More
research is needed on these self-regulation processes of community college students
unprepared for college level mathematics. Considering that links have been made
between self-efficacy, motivation and parenting styles (Hoang, 2007; Silva et al., 2008;
Turner et al., 2009), the next section reviews literature on parenting styles with particular
emphasis on how they relate to academic achievement as well as to parenting style
variations among ethnicities.
Parenting Style
A parenting style has been defined as “a stable complex of attitudes and beliefs
that form the context in which parenting behaviors occur” (Brenner & Fox, 1999, p. 343).
Aspects of a parenting style include a parent’s view of his or her role, the parent’s beliefs,
as well as engagement and behavior that influence a child (Ginsberg & Bronstein, 1993).
This next section describes a theoretical framework for parenting styles based on Diana
27

Baumrind’s (1968) seminal work. This is followed by a review of the literature linking
parenting styles to academic achievement, college students, and ethnicity.
Baumrind’s framework. Diana Baumrind (1968, 1971,1991) was one of the
first researchers to categorize parenting styles. In her seminal work, Baumrind classified
parenting styles into three categories: authoritative, authoritarian, and permissive. These
categories are based on parents exhibiting varying amounts of warmth or responsiveness
and control or demandingness. Authoritative parenting, which is high in both warmth
and control, is described as democratic, firm and nurturing. While authoritative parents
set and enforce rules, they may explain the rationale behind the rules and are responsive
to their individual child’s needs. Authoritative parents want their children to be “self-
regulated as well as cooperative” (Baumrind, 1991, p. 62). They encourage their
children’s independence.
On the other hand, authoritarian parenting is characterized by a high level of
control but little warmth (Baumrind, 1991). Authoritarian parents demand obedience
from their child without input from the child. They do not engage in open
communication with their child. Authoritarian parenting is described as harsh,
demanding, punitive, and directive (Baumrind, 1971).
The third parenting style in Baumrind’s (1968) framework is the permissive
parenting style. It is characterized as being more responsive than controlling. Permissive
parents demand little from their child and provide few guidelines for them. Permissive
parents are described as indulgent and caring (Baumrind, 1968). The use of punishment
is minimal in permissive parenting.
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Parenting style’s influence on academic achievement. While Baumrind was
one of the first to report a positive relationship between authoritative parenting and
academic achievement, many studies have since found a similar relationship (Silva et al.,
2008; Steinberg, Lamborn, Dornbusch, & Darling, 1992). In her original study,
Baumrind studied primarily Caucasian, middle-class parents of preschool children in
northern California. Children of authoritative parents were found to be more mature and
independent than children of nonauthoritative parents (Baumrind, 1966; Baumrind,
1968). These children also exhibited more prosocial behavior and were more
achievement-oriented. In contrast, children of permissive parents lacked persistence
when faced with a challenge and were more rebellious.
Others have investigated the relationship between authoritative parenting and
academic achievement in adolescents. Steinberg, Lamborn, Dornbusch and Darling
(1992) studied approximately 6400 adolescents from high schools in Wisconsin and
northern California. Compared to Baumrind’s sample, Steinberg’s sample was ethnically
and socioeconomically heterogeneous. However, again, a positive relationship between
an authoritative parenting style and academic achievement was evident. That is, children
who reported that their parents provided them with warmth, autonomy and high
demands--characteristics of authoritative parenting--performed higher academically
(Steinberg, Lamborn, et al., 1992).
Parenting style’s influence on college students. Other studies (Silva et al.,
2008; Turner et al., 2009; Joshi, Ferris, Otto, & Regan, 2003) investigated whether
authoritative parenting predicted academic achievement in college students. These
findings have been somewhat inconclusive. For instance, both mother’s and father’s
29

authoritative parenting style were related to higher grade point averages among 300
college students attending a large southeastern university (Silva et al., 2008). In addition,
Turner et al. (2009) found a significant relationship between authoritative parenting and
grade point average in approximately 260 undergraduate students at a major southwestern
university. However, no significant relationship was found between these same variables
among 200 urban students (Joshi et al., 2003).
In light of these discrepancies, researchers have begun to challenge the
generalizability of the claim that authoritative parenting promotes higher academic
achievement and have searched for other pertinent variables. Baumrind’s (1966) original
study as well as some mentioned above (Silva, et al., 2008; Turner et al., 2009) included
a sample of which the large majority was Caucasian. In addition, in the case of Turner et
al. (2009), more than half of the participants’ parents were college educated. Thus, some
have argued there may be mediating or moderating factors present in the relationship
between authoritative parenting and academic achievement. The next section considers
the role ethnicity may have in the extent to which parenting styles predict achievement.
Parenting styles, ethnicity and academic achievement. Numerous studies
support the benefits of authoritative parenting on Caucasian children and adolescents
(Baumrind, 1968; Silva et al., 2008; Steinberg, Lamborn, et al., 1992). However, in
many studies (Park & Bauer, 2002; Steinberg, Lamborn, et al., 1992; Leung, Lau & Lam,
1998) this relationship was not confirmed for other ethnic groups. Park and Bauer (2002)
found no noticeable differences between authoritative and authoritarian parenting on
academic achievement for a large sample of Asian American and African American high
school students. The difference was only evident among their European American
30

population (Park & Bauer, 2002). Similarly, in another study, authoritative parenting
predicted academic achievement for the Caucasian adolescents but not for the African
American adolescents (Steinberg, Lamborn, et al., 1992). Furthermore, authoritarian
parenting, usually associated with lower academic achievement, was positively
associated to academic achievement among Chinese children in Hong Kong (Leung et al.,
1998).
Hispanic parents have been found to be more authoritarian and less authoritative
than Caucasian parents (Dornbusch et al., 1987; Steinberg, Dornbusch & Brown, 1992)
however authoritarian parenting for Hispanics was not significantly related to grades
(Dornbusch et al., 1987). Considering parenting practices as opposed to parenting styles,
Dumka, Gonzales, Bonds, and Millsap (2009) studied parents and adolescents from 560
Mexican origin families. Of the parenting practices included in their study, only
mother’s harshness, considered authoritarian in Baumrind’s framework, related
significantly to grade point average, and this was only for girls not boys (Dumka, et al.,
2009). Mother’s or father’s parenting practices classified as exhibiting warmth, which
would classify as authoritative in Baumrind’s framework, did not correlate significantly
with grade point average for boys or girls (Dumka et al., 2009). Thus, there is evidence
that the impact of parenting styles on academic achievement varies across ethnicities. In
light of the inconsistencies in findings, there is a need for more studies to investigate
Baumrind’s parenting styles among Hispanics, particularly among Hispanic college
students.
Darling and Steinberg (1993) developed a contextual model of parenting styles to
include the context in which parental goals are developed and manifested. In this model,
31

it is possible “that parents of different ethnicities hold unique educational aspirations,
goals and values for their children and therefore enact unique parenting practices” (Spera,
2005, p. 141). Additionally, research has investigated the possibility that socioeconomic
status moderates the relationship between parental goals and parental practices (Spera,
2005) and that parenting style moderates between parenting practices and adolescent
outcomes (Steinberg, Lamborn, et al., 1992).
Summary of parenting styles. While studies have long supported the influence
of parenting on the behavior of children and adolescents (Baumrind, 1966; Baumrind,
1991; Steinberg, Lamborn, et al., 1992), many studies indicate that parenting style is a
predictor of various outcomes even for college students (Silva et al., 2008; Turner et al.,
2009; Joshi et al., 2003). Differences have been found among Caucasian and Hispanic
families both in the type of parenting style most often employed and in the relation
between parenting style and academic achievement. Hispanic parents have been found
to be more authoritarian and less authoritative than Caucasian parents (Dornbusch et al.,
1987; Steinberg, Dornbusch, et al., 1992) however authoritarian parenting for Hispanics
was not significantly related to grades (Dornbusch et al., 1987) as it has been for
Caucasians (Baumrind, 1968; Silva et al., 2008; Steinberg, Lamborn, et al., 1992). The
following section briefly discusses some relations between self-efficacy, self-regulation
and parenting style.
Relations between Self-efficacy, Self-regulation, and Parenting Style
Social Cognitive Theory asserts that learning occurs through a triadic
reciprocality of personal, behavioral and environmental factors (Bandura, 1986). Thus, it
seems plausible that the personal factors of self-efficacy beliefs, behavioral factors of
32

self-regulation, and environmental factors of parenting all may influence one another.
For instance, since the use of self-regulation strategies predicts academic performance
(Kitsantas et al., 2008; Wolters, 1998), then perhaps aspects of a particular parenting
style may foster specific motivational outcomes which in turn influence achievement.
Based on triadic reciprocality, Social Cognitive Theory strongly supports the necessity of
considering the interactions of personal, behavioral, and environmental factors rather than
considering each in isolation. Thus, it is important to consider the interactions of self-
efficacy, self-regulation, and parenting style with each other, instead of just individually
relating them to achievement. Numerous studies have investigated various interactions of
these particular variables (Berger & Karabenick, 2011; Gonzalez, Greenwood, & Hsu,
2001; Hoang, 2007).
For instance, self-efficacy has been found to relate significantly to self-regulation
(Berger & Karabenick, 2011). Berger and Karabenick (2011) studied 306 ninth grade
students regarding how they learn and felt about mathematics. Math self-efficacy was
found to predict more frequent use of self-regulation strategies including metacognition,
elaboration and time and physical environment management (Berger & Karabenick,
2011).
Further interactions were investigated when, considering Baumrind’s (1967)
conclusions that authoritative parenting promotes responsibility and independence,
researchers studied the relations between parenting styles and motivation as seen through
goal orientation (Gonzalez, Greenwood, & Hsu, 2001; Gonzalez, Holbein, & Quilter,
2002; Gonzalez, Willems, & Holbein, 2005). The mother’s authoritativeness was
significantly related to college students having higher mastery orientation while a father’s
33

authoritarianism was significantly related to college students having higher performance
orientation (Gonzalez, Greenwood, & Hsu, 2001). Within this study, over three-fourths
of the sample was Caucasian, with Hispanics accounting for less than 8% of the sample
(Gonzalez, Greenwood, & Hsu, 2001). Similarly, Hoang (2007) examined motivational
outcomes predicted by parenting styles among high school math students. Students
whose parents were more authoritative or authoritarian had higher mastery goal
orientation (Hoang, 2007). This was not true for students with permissive parents
(Hoang, 2007). While investigating the interactions between self-efficacy and
authoritative parenting, Turner et al. (2009) found no significant relation between these
variables amongst 264 college students. Further investigation into the relationship
between these variables among community college students is necessary. The following
section discusses literature on acculturation with a particular emphasis on college
students and achievement.
Acculturation
Acculturation theory. Acculturation has been defined as the cultural and
psychological changes that occur when two cultures come into continuous contact with
each other (Berry, 1997). This study investigates the variable of acculturation of
Hispanics and how it relates to students’ achievement and persistence in a math course.
Unidimensional models of acculturation describe it as following a linear continuum
ranging from not acculturated to complete acculturation. In this model, individuals only
move along one dimension, either maintaining their culture of origin or adopting the
dominant culture while having to reject their own.
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However, newer models of acculturation include two dimensions, one for an
individual’s culture of origin and another for the dominant culture. This allows for
independent movement along these two continua based on degree of maintenance to the
heritage culture and degree of adoption of the mainstream culture. Thus, four quadrants
are created corresponding to four acculturation strategies: integration, assimilation,
separation and marginalization (Berry, 1997). In the first case of integration, an
individual maintains their own native culture while adopting the new behaviors and
customs of the dominant culture. When an individual does not maintain their native
culture identity but chooses to adopt a new identity within the dominant culture, they are
said to have assimilated. Separation occurs when an individual maintains their native
culture identity while rejecting the dominant culture. Lastly, marginalization occurs for
individuals that both lose their identity within their native culture and fail to adopt a new
identity within the dominant culture. Acknowledging the bidimensional aspect of
acculturation, new measurements of acculturation provide an acculturation score based
on a score from each of the two cultural dimensions: the native culture and the dominant
culture. The following section discusses general factors related to the acculturation of
Hispanics. This is followed by a section which looks specifically at acculturation’s
influence on achievement.
Acculturation of Hispanic adolescents and young adults. Studies have
indicated that higher levels of acculturation are associated with both positive and negative
outcomes among Hispanic adolescents and young adults. A recent and unique study
investigated whether more time in the United States is associated with school
misbehavior (Ewert, 2009). While many have considered academic performance as a
35

dependent variable, Ewert (2009) tested the relationship of immigrant generation and
acculturation on three levels of disciplinary problems (minor, intermediate, serious)
during the senior year of high school. Attending class unprepared was considered a
minor offense, getting in trouble for breaking the school rules an intermediate offense,
and being suspended from school a serious offense. In the sample of over 8300 high
school seniors with minority groups and various generation levels well represented,
Ewert (2009) found that first generation and 1.5 generation Hispanic immigrants attend
class more prepared and are less likely to get in trouble for breaking school rules than
third and fourth generation Hispanic immigrants. In contrast, race and ethnicity, not
immigrant generation, was the key predictor of serious misbehavior: suspension from
school. Hispanics were 1.42 times more likely to get suspended than white students.
Ewert’s (2009) results suggest that “becoming American has some detrimental effects on
the school behavior of immigrant children” (p. 835).
In addition, the high school dropout rate for Hispanics is higher than for their non-
Hispanic peers (National Center for Education Statistics, 2010). Martinez, DeGarmo and
Eddy (2004) investigated the role of acculturation on the high school dropout rate for
Hispanics. In their study, acculturation was based on the use of English at home, English
proficiency, and U.S. nativity. Among 250 Hispanic 6
th
through 12
th
graders, Martinez et
al. (2004) found that greater student acculturation predicted lower likelihood of dropout.
Acculturation of Hispanics may also be related to the attainment of higher
education through one’s academic aspirations and likelihood to simply attend college.
One early study, involving over 400 Mexican American junior and senior high school
students, found no relation between the acculturation level and desire to go to college or
36

engagement in practical actions to get to college (Hurtado & Gauvain, 1997). However,
in a much more recent study of nearly 300 Mexican American high school students,
acculturation was significantly related to and had a direct effect on students’ academic
aspirations (Carranza et al., 2009). Students in this study were asked to select the highest
level of education they would like to attain from a list ranging from obtaining a GED to
obtaining a graduate degree. Students with higher levels of acculturation had higher
academic aspirations. In addition, generational status and parents’ level of education
were significantly related to acculturation level. Hence, Carranza et al. (2009) suggest
that these factors may contribute to the relation between acculturation and achievement
more than the adherence to American values. Furthermore, research has found a relation
between acculturation and simply attending college (Hurtado & Gauvain, 1997; Hurtado-
Ortiz & Gauvain, 2007). Among 116 high school graduates, Hurtado and Gauvain
(1997) found that more acculturated Mexican American students were more likely to
attend college. Similar results were found again in a study of 104 recent high school
graduates of Mexican American descent for whom there was a positive relation between
acculturation and college attendance (Hurtado-Ortiz & Gauvain, 2007).
Thus, these studies suggest that acculturation plays a role in the attainment of
higher education for Hispanic youth. Third and fourth generation Hispanics were more
likely to get in trouble during senior year of high school than first generation Hispanics.
While Hispanics are more likely to drop out of high school than their white peers, those
more acculturated were less likely to dropout. Furthermore, more acculturated students
had higher college aspirations and were more likely to attend college. The next section
37

discusses the research on the relationship of acculturation of Hispanic youth and
academic achievement, as measured by grades.
Acculturation influence on achievement of Hispanic students. Acculturation
has been considered an important factor influencing Hispanic student’s educational
outcomes; however, the research results have been somewhat inconsistent on academic
achievement in terms of grades. Some studies have found that higher acculturation levels
are associated with higher academic achievement (Carranza et al., 2009; Lopez, Ehly, &
Garcia-Vazquez, 2002) while others have found no relationship (Fuligni, Witkow, &
Garcia, 2005; Hurtado-Ortiz & Gauvain, 2007; Martinez et al., 2004).
In their study involving nearly 300 Mexican American high school students,
Carranza et al. (2009) considered the relationship of acculturation, along with perceived
parental involvement and self-esteem, on academic achievement. Finding the difference
of the two scores from a bidimensional measure of acculturation, Carranza et al. created a
linear measure of acculturation with five levels, ranging from very Mexican oriented to
very assimilated or “Anglicized,” with bicultural in the middle of this range. Using
structural equation modeling, Carranza et al. found a direct effect of acculturation on
students’ self-reported grade point average. On the five-level scale of acculturation,
students who were closer to the assimilated level reported higher grade point averages.
While the majority of students in this study were first or second generation immigrants,
all five levels of acculturation were represented in the sample.
Similar findings resulted in a study involving 60 Mexican American ninth
graders. Lopez, Ehly, and Garcia-Vazquez (2002) investigated whether acculturation and
social support are associated with academic achievement. Specifically, they found that
38

the more highly integrated students, that is, students who integrated their native culture
with the new dominant culture, had higher grade point averages. Thus, maintaining one’s
own culture while adopting values and practices of the dominant culture was associated
with greater academic achievement (Lopez et al., 2002). However, these results must be
evaluated cautiously as the sample size was small and very few participants were first
generation immigrants, thus limiting variability.
On the other hand, some studies have found no relationship between the
acculturation level of Hispanic students and academic achievement as measured by grade
point average. While greater acculturation predicted a lower likelihood of dropping out
of high school, it was not significantly related to self-reported grade point average
(Martinez et al., 2004). Among 104 recent high school graduates of Mexican American
descent, Hurtado-Ortiz and Gauvain (2007) also found no relationship between
acculturation and high school or college GPA.
Summary of acculturation. Acculturation, the change that occurs when two
cultures come into continuous contact with each other (Berry, 1997), is an important
factor among Hispanic immigrants. While research shows that acculturation plays an
important role in Hispanics attaining higher education through one’s academic aspirations
and likelihood to simply attend college, the results are somewhat mixed as to exactly how
it relates specifically to academic achievement. Furthermore, a limited number of studies
have looked at how acculturation relates to achievement in college mathematic courses.
Thus, this study aims to contribute to the knowledge of how acculturation relates to the
academic achievement, specifically in basic skills mathematics, of Hispanic college
students.
39

Summary
In conclusion, research continues to find positive and significant relationships
across various grade levels and ethnicities between self-efficacy, self-regulation,
parenting style, acculturation of Hispanics and academic achievement. These findings
confirm that self-efficacy is task specific and must be assessed specifically rather than
globally. In light of this, self-efficacy for mathematics has been found to relate
significantly to math achievement at different grade levels, including college (Hackett,
1985; Pajares & Miller, 1994; Pajares & Miller, 1995; Pietsch, Walker and Chapman,
2003). A construct closely intertwined with self-efficacy is self-regulation. Math self-
efficacy, particularly, has been shown to predict more frequent use of self-regulation
strategies (Berger and Karabenick, 2011).
Several dimensions of self-regulation, including planning and monitoring one’s
performance, use of time, and control of one’s physical and social environments, are
significantly related to academic achievement among high school and college students
(Kitsantas et al., 2008; Wolters, 1998; Zimmerman, 1990). In fact, studies have found
that time management strategies contributed unique variance in predicting achievement
even above that of prior ability (Kitsantas et al., 2008). Thus, it is critical that community
colleges understand the relation between not only self-efficacy and achievement but also
between self-regulation and achievement.
Parenting styles, as identified by Baumrind (1971), have been shown to be related
to academic achievement. However, research has also suggested that parenting style may
be a predictor of student motivation (Hoang, 2007) as well with authoritative and
authoritarian parenting style being related to mastery goal orientation. In addition, while
40

it is clear that the authoritative parenting style is related to the best possible academic
outcomes for Caucasians, research is inconsistent on which parenting style results in the
best academic outcomes for Hispanics.
Acculturation is a major factor among Hispanic immigrants. Research shows that
acculturation plays an important role in Hispanics attaining higher education through
one’s academic aspirations and likelihood to attend college. However, the results are
somewhat mixed as to exactly how acculturation relates specifically to academic
achievement. With Hispanics comprising over 40% of California community college
basic skills mathematics students (CCCCO, 2012a), it is imperative to study the relation
between acculturation and academic performance. In summary, there is a complex
relation between self-efficacy, self-regulation, parenting styles, acculturation and
achievement and these relations have not been studied thoroughly among college students
underprepared in math.
Purpose of the Study
Therefore, the purpose of this study is to address the gap in the current literature
on community college students in basic math courses by examining motivational,
parental and cultural factors as predictors of achievement and persistence of students
enrolled in basic skills mathematics courses at a community college. More specifically,
the primary goal of this study is to investigate the degree to which mathematics self-
efficacy, self-regulation, and parenting style predict achievement and persistence of
community college students in prealgebra and elementary algebra. A secondary goal is to
examine Hispanics in particular, and include an additional variable of acculturation in
conjunction with the above variables.
41

Research Questions
This study aims to investigate the following four research questions:
Research Question 1:
Do math self-efficacy, self-regulation, and parenting style predict math achievement and
persistence among basic skills math students in California community colleges?
Hypothesis 1a: Math self-efficacy and self-regulation will positively predict math
achievement and persistence.
Hypothesis 1b: Authoritative parenting will predict math achievement and
persistence.
Research Question 2:
Is there is a difference between Hispanics and European-American students enrolled in a
basic skills math course at a community college in math self-efficacy, self-regulation,
parenting style, math achievement and persistence in a math course?
Hypothesis 2: There is a difference between Hispanics and European-American
community college basic skills math students in math self-efficacy, self-
regulation, parenting style, math achievement and persistence.
Research Question 3:
Along with math self-efficacy, self-regulation, and parenting style, does acculturation
predict math achievement and persistence among Hispanic basic skills students in
community colleges?
Research Question 4:
Does acculturation predict math self-efficacy, self-regulation, and parenting style among
Hispanic basic skills students in community colleges?
42

CHAPTER III: METHODOLOGY
This study examined the relationship of motivational, parental, and cultural
variables to the achievement and persistence of community college students.
Specifically, this non-experimental, quantitative study investigated the relationship of
math self-efficacy, self-regulation, parenting style and acculturation of Hispanics to
student math grades in and completion of a basic skills math course at a California
community college. This chapter presents the participants, the instruments, the
procedures and the design for data analysis used in this study.
Participants
A total of 390 basic skills math students participated in the study. Subjects for
this study were enrolled in one of fifteen sections of 2 different basic skills math courses:
prealgebra and elementary algebra. All students in the study were attending a large,
urban Southern California community college during the spring semester of 2011. All
390 participants completed the survey; however, 33 of these did not give their consent to
release their math grade for the study and thus, these participants’ responses were not
used in the analysis involving achievement or persistence. Of the 390 respondents, 194
were prealgebra students and 196 were elementary algebra students. As shown in Table
1, the percentage of students that were Hispanic, Caucasian, Asian, African-American,
and Other were 60.8%, 14.1%, 12.8%, 7.7%, and 1.8% respectively. Females comprised
56.4% of the sample, while males comprised 42.8%. The mean age was 22.37 years (SD
= 6.086) with 44.6% of the sample being 18 or 19 years old and 30.8% being between 20
and 24 years old. First year college students comprised 44.4% of the participants.
Participants were born in 24 different countries with 15.9% being first generation
43

Americans and 46.4% being second generation. The sample was appropriate because it is
similar to the population of interest, namely, basic skills math college students at this
particular community college.

Table 1
Frequency Distribution of Student Participants
N Percentage*
Gender
Male 167 42.8
Female 220 56.4

Race/Ethnicity
Hispanic 237 60.8
Caucasian 55 14.1
Asian 50 12.8
African-American 30 7.7
Other 14 3.6

Current Math Course
Prealgebra 194 49.7
Elementary Algebra 196 50.3

Age
Under 20 174 44.6
20-24 120 30.8
25-34 71 18.2
35 and over 20 5.1

Generational Status
First 62 15.9
Second 181 46.4
Third 41 10.5
Fourth 24 6.2
Above Fourth 50 12.8
Note: Numbers of missing cases for gender = 3, for race = 4, for
age = 5, and for generational status = 32.
*Percentage does not add up to 100 due to missing data.
44

Instruments
The survey instrument consisted of five sections: demographic information
(Appendix B), math self-efficacy (Appendix C), self-regulation (Appendix D), parenting
style (Appendix E) and acculturation level (Appendix F). Participants were instructed to
complete the acculturation section if they identified as Hispanic or Latino. Math self-
efficacy and self-regulation were measured using subscales of the Motivated Strategies
for Learning Questionnaire (MSLQ) (Pintrich, Smith, Garcia & McKeachie, 1991).
Parenting styles were measured using the Parental Authority Questionnaire (Buri, 1991)
with three parenting styles identified as authoritarian, authoritative and permissive.
Acculturation was measured using the Bidimensional Acculturation Scale for Hispanics
(Marin & Gamba, 1996) in which students were given scores in two domains: Hispanic
and non-Hispanic. The following sections describe these specific measures in more
detail.
Demographics. Students were asked to provide demographic information (see
Appendix B). This section included questions on their age, gender, years of education
after high school, ethnic background, country of birth, years in the U.S., generation
status, family structure, socioeconomic status, and current math course.
Math self-efficacy. The variable of math self-efficacy was measured using a
subscale of the MSLQ (Pintrich et al., 1991). The MSLQ was developed by the National
Center for Research on Improving Postsecondary Teaching and Learning at the
University of Michigan in 1986 (Pintrich et al., 1991). In its entirety, the MSLQ consists
of 2 sections comprised of a total 15 subscales and 81 items designed to measure
students’ motivational beliefs and self-regulated learning strategies. The motivational
45

subscales are based on a social cognitive theoretical framework (Pintrich, et al., 1991).
One of the motivational subscales, the self-efficacy subscale, was used in this study to
measure students’ math self-efficacy.
The self-efficacy subscale consists of 8 items scored on a 7-point Likert-type
scale ranging from 1-not at all true of me to 7 - very true about me. Participants were
asked to respond to each item in relation to a specified class. This makes each item
domain specific. Thus, this study was measuring the student’s math self-efficacy in the
students’ current math class. Sample items include, “I’m certain I can master the skills
being taught in this class,” and “I’m confident I can understand the most complex
material presented by the instructor in this course.” With each of the 8-questions being
scored on a 7-point scale, possible total scores ranged from 8 to 56. A mean score was
calculated for each participant by dividing their total score by 8.
Originally, the MSLQ’s reliability and validity were established on a sample of
380 college students from the Midwest. The internal consistency reliability of scores for
the self-efficacy subscale was .93 and there was a .41 correlation with students’ final
grade (Pintrich, Smith, Garcia, & McKeachie, 1993). In the current study, the Cronbach
alpha coefficient was .94.
Self-regulation. The variable of self-regulation was measured using three
subscales of the Motivated Strategies for Learning Questionnaire (MSLQ) (Pintrich et al.,
1991). As indicated above, the MSLQ in its entirety consists of 2 sections comprised of a
total 15 subscales and 81 items designed to measure students’ motivational beliefs and
self-regulated learning strategies. This study used the metacognitive self-regulation
subscale, the time and study environmental management subscale and the effort
46

regulation subscale. All three of these subscales are scored on a 7-point Likert-type scale
ranging from 1-not at all true of me to 7 - very true about me.
The metacognitive self-regulation subscale consists of 12 items. Sample items
include, “I ask myself questions to make sure I understand the material I have been
studying in this class,” and “I try to think through a topic and decide what I am supposed
to learn from it rather than just reading it over when studying for this course.” A few
items were modified and adapted to a math course. For example, the item “If course
readings are difficult to understand, I change the way I read the material” was modified to
the following: “If course assignments are difficult to understand, I change the way I
approach the assignment.” The internal consistency reliability of scores for the self-
regulation subscale was .79 and there was a .30 correlation with students’ final grade
(Pintrich et al., 1993). In the current study, the Cronbach alpha coefficient was .82 for
the metacognitive self-regulation subscale.
The time and study environment management subscale consists of 8 items.
Sample items include, “I make good use of my study time for this course” and “I find it
hard to stick to a study schedule” (reverse coded). The internal consistency reliability of
scores for the time and study environment management subscale was .76 and there was a
.28 correlation with students’ final grade (Pintrich et al., 1993). In the current study, the
Cronbach alpha coefficient was .80 for the time and study environment management
subscale.
The effort regulation subscale consists of 4 items. Sample items include, “I work
hard to do well in this class even if I don’t like what we are doing” and “When course
work is difficult, I either give up or only study the easy parts” (reverse coded). The
47

internal consistency reliability of scores for the effort regulation subscale was .69 and
there was a .32 correlation with students’ final grade (Pintrich et al., 1993). In the current
study, the Cronbach alpha coefficient was .71 for the effort regulation subscale.
Mean scores for each of the three subscales were calculated by dividing the total
score for each subscale by the respective number of items. Thus, each participant
received a score for each of the three subscales: metacognitive self-regulation, time and
study environmental regulation, and effort regulation.
Parenting style. The Parental Authority Questionnaire (PAQ) (Buri, 1991) was
used to measure the independent variable of parenting style. Buri (1991) developed the
PAQ to specifically measure Baumrind’s (1968, 1971) permissive, authoritarian, and
authoritative parental authority prototypes. Buri (1991) acknowledged that parental
behavior is highly correlated to one’s perception of that behavior. Thus, the PAQ
measures parenting style not by asking parents directly about their behavior but rather by
asking the respondent about their recollections of their parents’ behavior.
The scale consists of 30-items with 10 questions measuring each of the three
parental prototypes. The original measure consists of separate measures for both fathers
and mothers resulting in a 60-item questionnaire. The current study adapted the original
measure to assess overall parenting style rather than fathers’ and mothers’ style
separately. Participants were instructed to think of their father and mother as a unit when
answering the questions. Participants from single-parent homes were instructed to
answer the questions with this one parent in mind.
Each of the 30 items was scored on a 5-point Likert-type scale ranging from 1 -
strongly disagree to 5 - strongly agree. Sample items included, “As I was growing up,
48

my parents seldom gave me expectations and guidelines for my behavior” and
“Whenever my parents told me to do something as I was growing up, they expected me
to do it immediately without asking any questions.” With each of the 10-questions being
scored on a 5-point scale, possible total scores ranged from 10 to 50 for each parenting
style. Thus, each student received a score for each of the three parenting styles:
permissive, authoritarian, and authoritative. Mean scores for each parenting style were
calculated by dividing the total scores by 10.
The PAQ has strong reliability and validity as seen through a variety of tests
(Buri, 1991). In Buri’s (1991) original study, test-retest reliability ranged from .77 to .92.
When testing for internal consistency reliability, Cronbach’s alpha ranged from .74 to
.87. With only 10 items per scale, these reliability coefficients are considered quite good
(Buri, 1991). Buri (1991) also found the PAQ had discriminant-related validity,
indicated by each style being inversely related to the other two styles. In addition,
criterion-related validity was found to be strong. This was determined by correlating
parental nurturance with each of the three parenting styles. That is, consistent with
Baumrind’s (1971) descriptions, authoritativeness correlated positively with parental
nurturance, authoritarianism correlated negatively with nurturance, and permissiveness
did not correlate significantly with nurturance (Buri, 1991). Moreover, the PAQ did not
appear to be vulnerable to social desirability response biases. Lastly, the PAQ was norm
tested and determined to be appropriate for both male and female older adolescents and
young adults. In the current study, the Cronbach alpha coefficients were .73, .83, and .87
for the permissive, authoritarian, and authoritative parenting style subscales respectively.
49

Acculturation. The independent variable of acculturation was measured using
the Bidimensional Acculturation Scale for Hispanics (BAS) (Marin & Gamba, 1996).
This scale measures “bidirectional changes in behavior that are central to the individual
in two cultural domains (Hispanic and non-Hispanic)” (Marin & Gamba, 1996, p. 299).
While there are many different acculturation measures, some scales focus solely on
Mexican Americans (e.g. the Acculturation Rating Scale for Mexican Americans-II) and
earlier scales are unidimensional. This bidimensional aspect of acculturation provides
four different categories of acculturation rather than a linear continuum ranging from not
acculturated to complete acculturation. The BAS was developed as a bidimensional
measurement to assess the acculturation level of Hispanics rather than a specific
subgroup. Thus, the BAS was chosen for this study because it is a bidimensional
acculturation scale and has been shown to have high reliability and validity among
Mexican Americans as well as Central Americans (Marin & Gamba, 1996).
The BAS is a 24 item scale that gives an acculturation score for 2 major cultural
domains: Hispanic and non-Hispanic. Each dimension consists of 12 items. In addition,
the scale uses 3 language related subscales: Language Use, Linguistic Proficiency, and
Electronic Media. The BAS does not address values and norms. While the BAS may be
offered in English or Spanish, this study only offered the measure in English. In the
current study, the Cronbach alpha coefficients were .83for the non-Hispanic domain
subscale and .96 for the Hispanic domain subscale.
Responses for the Language Use Subscale and the Electronic Media Subscale
were scored on a 4-point Likert-type scale ranging from 1 - almost never to 4 - almost
always. Responses for the Linguistic Proficiency Subscale were scored on a 4-point
50

Likert-type scale ranging from 1 - very poorly to 4 - very well. Sample questions
included: “How often do you speak in English with your friends?” and “How well do
you understand music in Spanish?” (Marin & Gamba, 1996, p. 311).
Scores were obtained by averaging the total scores on both the Hispanic domain
items and the non-Hispanic domain items for each student. Thus, each student was
assigned two scores, one for the average of the 12 items within the Hispanic domain
(items 4 through 6, 13 through 18, and 22 through 24) and another for the 12 items within
the non-Hispanic domain (items 1 through 3, 7 through 12, and 19 through 21). For each
cultural domain, the total score range is from 1 to 4. Both scores were used to define the
level of acculturation with higher scores indicating a stronger orientation to the particular
domain.
The BAS has been widely used and is generally considered valid (Unger, Ritt-
Olson, Wagner, Soto, & Baezconde-Garbanati, 2007). Marin and Gamba (1996)
validated the subscales by correlating them with seven criteria used by other scales. In
addition, internal consistency for the combined score of the three subscales gave high
alpha coefficients of .90 for the Hispanic domain and .96 for the non-Hispanic domain
(Marin & Gamba, 1996).
Achievement. For the current study, achievement was measured using the
student’s end-of-semester grade in the current math course, either prealgebra or
elementary algebra. With consent from the student, the math grade was obtained from
the Institutional Planning and Research Office at the school. All letter grades were
converted to a 4-point scale with A’s equivalent to 4 points, B’s equivalent to 3 points,
C’s equivalent to 2 points, D’s equivalent to 1 point and F’s equivalent to 0 points.
51

Persistence. For the current study, persistence was defined as course completion.
This was measured by whether the student withdrew from the class and hence received a
W in the class as opposed to receiving a letter grade (A, B, C, D, or F). With consent
from the student, this information was obtained from the Institutional Planning and
Research Office at the site.
Procedure
For this study, all students enrolled in 15 different sections of prealgebra or
elementary algebra during the 2011 spring semester at a particular Southern California
community college were invited to participate. There were seven sections of prealgebra
and eight sections of elementary algebra with a range of 17 to 32 students in each section
participating in the study. Participation was voluntary. Permission to administer this
survey was obtained from the Institutional Review Board at the University of Southern
California, the Dean of Mathematics at the community college site, and the individual
professors of each course. Students were given the description of the study and a notice
of confidentiality. Participants completed an informed consent form and the survey
during one class session in the fifth week of the spring 2011 16-week semester. The
survey was administered and collected by the researcher. As an incentive, students were
offered the opportunity to enter a raffle for six gift cards ranging in value from $25 to
$100.
Data Analysis
All quantitative data were analyzed using the Statistical Package for the Social
Sciences (SPSS) 18.0 program. For descriptive statistics, frequencies were computed for
the nominal variables such as race, gender and math course level, and the means and
52

standard deviations were computed for continuous variables. Pearson product correlation
analyses were conducted to examine the relationship between demographic variables as
well as the motivational, parental and cultural variables. Multiple regression analyses
were conducted with motivational, parental and cultural variables as the independent
variables and math achievement as the dependent variable. Logistic regression analyses
were conducted with motivational, parental and cultural variables as the independent
variables and persistence in a math course as the dependent variable. Group differences
between Hispanic and European American students were investigated using two t-tests, 2
MANOVAs and a chi-square test. Finally, three linear regression analyses were
conducted with acculturation of Hispanics as the independent variable and with the
motivational and parental variables as the dependent variables.

53

CHAPTER IV: RESULTS
This chapter presents the results of the study including preliminary analysis and
analysis of the research questions.
Preliminary Analysis
Descriptives. Preliminary analysis revealed that of the 354 participants who
consented to the release of their math grades, 64.7% (n = 229) passed the math course
with an A, B, or C, 26.6% (n = 94) failed with a D or F, and 8.8% (n = 31) withdrew
from the course. Of those who persisted through the course, Caucasian students achieved
a higher math grade (M = 2.89, SD = 1.355) than Hispanic students (M = 2.09, SD =
1.22). Overall, Caucasian students reported a higher time and study environment
regulation (M = 5.53, SD = 1.107) than Hispanic students (M = 5.01, SD = 1.148).
Students reported higher authoritative parenting (M = 3.38, SD = .796) and authoritarian
parenting (M = 3.38, SD = .733) than permissive parenting (M = 2.53, SD = .618). A
summary of the means and standard deviations of the measured variables is listed in
Table 2.
Correlations. Pearson product correlation analyses were conducted to examine
the relationship between demographic variables as well as the motivational, parental and
cultural variables. Results are summarized in Table 2. For this study, the gender of the
student was significantly correlated with permissive parenting (r = -.113, p < .05) such
that male students were more likely to perceive their parents as being permissive than
female students. Gender was not significantly correlated to authoritative or authoritarian
parenting. For the Hispanic students, gender was significantly correlated with both the
Hispanic cultural domain (r = .141, p < .01) and non-Hispanic cultural domain (r = .130,
54

p < .01) subscales of the acculturation measure with females being more likely to report
higher scores in both domains. Age of the student was significantly correlated with GPA
(r = .138, p < .01), units taken (r = .253, p < .01), and authoritarian parenting (r = .186, p
< .01) indicating that as the age of the student increased, GPA, units taken and
authoritarian parenting also increased. On the other hand, age of the student was
significantly negatively correlated with persistence (r = -.199, p < .01), permissive
parenting (r = -.228, p < .01), and authoritative parenting (r = -203, p < .01) indicating
that as age of the student decreased, persistence and permissive and authoritative
parenting increased.
As expected, generation status correlated significantly with the non-Hispanic
domain (r = .247, p < .01) and correlated negatively with the Hispanic domain (r = 0.484,
p < .01); that is, the greater the generation status of the participant, the higher the score
was on the non-Hispanic domain and the lower the score was on the Hispanic domain.
The number of years the student had resided in the United States was positively
correlated with number of units taken (r = .228, p < .01) and authoritarian parenting (r =
.180, p < .01) while inversely correlated with persistence (r = -.149, p < .01), permissive
parenting (r = -.264, p < .01), authoritative parenting (r = -.229, p < .01), and self-
efficacy (r = -.126, p < .05) As one would expect, the number of years a Hispanic
student had resided in the United States significantly correlated with acculturation in the
non-Hispanic domain (r = .168, p < .01) and correlated negatively with the Hispanic
domain subscale.
55

Table 2
Means, Standard Deviations, and Pearson Product Correlations for Measured Variables
Variables
M SD 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
1. Age 22.4 6.09 -
2. Gender -.053 -
3. YrsEd 1.90 1.67 .207
**
.060 -
4. YrsInUS 20.60 7.49 .740
**
-.052 .058 -
5. Generation .091 -.006 .014 .358
**
-
6. GPA 2.5 .743 .138
**
.044 .022 .073 -.001 -
7. UnitsTaken 28.3 18.2 .253
**
.023 .323
**
.228
**
.001 .253
**
-
8. MathGradeNum 2.04 1.56 .038 .011 -.005 -.065 .045 .649
**
.034 -
9. Persistence .91 .282 -.199
**
-.069 -.173
**
-.149
**
-.050 .039 -.016 .
a
-
10. SelfEfficacy 5.76 1.07 -.090 -.066 -.032 -.126
*
-.025 .200
**
-.124
*
.355
**
.238
**
-
11. MetaCogReg 4.92 .996 .051 .017 .048 -.041 -.050 .217
**
.020 .212
**
.061 .475
**
-
12. TimeStudyReg 5.14 1.13 .091 -.016 .042 .037 .059 .253
**
-.001 .312
**
.164
**
.460
**
.617
**
-
13. EffortReg 5.70 1.10 .084 .053 .004 .019 .005 .205
**
-.024 .260
**
.106
*
.482
**
.608
**
.654
**
-
14. AUTHVV 3.38 .796 -.203
**
.078 -.020 -.229
**
.018 .019 .031 .008 .001 .171
**
.299
**
.265
**
.195
**
-
15. AUTHNN 3.38 .733 .186
**
-.062 .079 .180
**
.005 -.056 .089 -.086 -.003 -.064 -.088 -.055 -.043 -.207
**
-
16. PERMSSV 2.53 .618 -.228
**
-.113
*
-.082 -.264
**
-.044 -.068 -.144
**
-.049 .042 .069 .094 -.039 -.083 .188
**
-.466
**
-
17. BASHispDmn 2.48 .786 -.163
*
.141
*
-.144
*
-.259
**
-.484
**
.066 -.051 -.021 .021 .045 -.017 -.017 .037 .060 -.014 .017 -
18. BASNonHispDmn 3.83 .243 .016 .130
*
-.028 .168
*
.247
**
-.010 -.030 .002 -.023 .136
*
.142
*
.123 .193
**
.155
*
-.138
*
.011 -.296
**
-
Note: 1. Age; 2. Gender; 3. Years of Education after high school; 4. Years lived in US; 5. Generation status; 6. Grade Point Average; 7. Units Taken; 8. End-of-semester grade in math course on 4.0
scale; 9. Persistence in math course (0=withdrew from the course; 1=did not withdraw from the course); 10. Math Self-efficacy; 11. Metacognitive self-regulation; 12. Time and Study Environment
Regulation; 13. Effort Regulation; 14. AUTHVV = Authoritative Parenting; 15. AUTHNN = Authoritarian Parenting; 16. PERMSSV = Permissive Parenting; 17. BASHispDmn = Hispanic Domain of
BAS; 18. BASNonHispDmn = Non-Hispanic Domain of BAS.
**. Correlation is significant at the 0.01 level (2-tailed).
*. Correlation is significant at the 0.05 level (2-tailed).
a. Cannot be computed because at least one of the variables is constant.
56

In regards to motivation, self-efficacy significantly correlated with all three
subscales of the self-regulation measure: metacognitive regulation (r = .475, p < .01),
time and study environment regulation (r = .460, p < .01) and effort regulation (r = .482,
p < .01). This indicates that as self-efficacy increased metacognitive regulation, time and
study environment regulation and effort regulation increased, too. In addition, self-
efficacy was positively correlated to math grade (r = .365, p < .01) and persistence (r =
.238, p < .01) as well as to authoritative parenting (r = .171, p < .01) indicating that as
self-efficacy increased math grade, persistence, and authoritative parenting increased.
No significant relationship was found between self-efficacy and permissive or
authoritarian parenting. Each of the self-regulation subscales significantly correlated
with measures of achievement. Specifically, metacognitive regulation correlated
significantly with GPA (r = .217, p < .01) and math grade (r = .212, p < .01); time and
study environment regulation correlated with GPA (r = .253, p < .01) and math grade (r =
.312, p < .01); and effort regulation correlated with GPA (r = .205, p < .01) and math
grade (r = .260, p < .01).
In regards to parenting style, only authoritative parenting was found to
significantly correlate with any of the motivational variables, and it correlated with all
four subscales: self-efficacy (r = .171, p < .01), metacognitive regulation (r = .299, p <
.01), time and study environment regulation (r = .265, p < .01) and effort regulation (r =
.195, p < .01). Thus, as students reported higher authoritative parenting, they also
reported higher self-efficacy, metacognitive regulation, time and study environment
regulation and effort regulation. For Hispanic students, authoritative parenting correlated
significantly with the non-Hispanic domain of the acculturation scale (r = .155, p < .05)
57

while authoritarian parenting correlated inversely with this domain (r = -.138, p < .05).
Thus, as Hispanic students reported higher acculturation to the dominant culture, they
reported higher authoritative parenting and lower authoritarian parenting.
Analyses of Research Questions
Results of research question 1. To determine the extent to which self-efficacy,
self-regulation and parenting style predict math achievement and persistence among basic
skills math students in community colleges, a simultaneous multiple regression was
performed using the self-efficacy scale, the three subscales of self-regulation as well as
the three parenting style subscales. The criterion variable used for analysis was the grade
obtained in the math course. The regression results revealed an overall significance for
the prediction model (F (7, 299) = 9.16, p = .000) with 17.7% of the variance being
explained. Self-efficacy and regulation of time and study environment were significant
predictors of math grade (see Table 3). Results of this analysis suggest that students with
higher self-efficacy and greater regulation of time and study environment achieved higher
math grades. No significant relationships were found for metacognitive or effort
regulation. Authoritarian parenting was also negatively related to math grade, suggesting
that students who reported coming from authoritarian households also reported lower
math grades.
Since the second dependent variable of persistence is categorical, logistic
regression was performed to assess the relationship of self-efficacy, self-regulation and
parenting style on the likelihood that students would persist in their math course. The
model contained seven independent variables (self-efficacy, metacognitive regulation,
time and study environment regulation, effort regulation, authoritarian parenting,
58

authoritative parenting and permissive parenting). The full model containing all
predictors was statistically significant, χ
2
(7, N = 317) = 26.192, p = .000, indicating that
the model was able to distinguish between students who persisted and those who did not.
The model as a whole explained between 7.9% (Cox and Snell R square) and 17.3%
(Nagelkerke R squared) of the variance in persistence, and correctly classified 91% of
cases. As shown in Table 4, only two of the independent variables, self-efficacy and time
and study environment regulation, made a unique statistically significant contribution to
the model. The strongest predictor of persistence was self-efficacy, recording an odds
ratio of 2.2. This indicated that for every unit increase in self-efficacy, the odds the
student persists in math class increase by a factor of 2.2, controlling for all other factors
in the model. The odds ratio for time and study regulation was 1.7, indicating that for
every additional increase of one unit on the time and study environment regulation scale,
students were 1.7 times more likely to persist in their math class, controlling for other
variables in the model.
Table 3
Summary of Simultaneous Regression Analysis for Variables Predicting Math
Achievement
Variables R
2
F B SE B β ρ
Math Achievement .177 9.161 .000
Self-efficacy .346 .077 .284 .000
Self-Regulation
Metacognitive Regulation -.040 .097 -.031 .681
Time and Study Environment Reg. .239 .087 .208 .007
Effort Regulation .013 .090 .011 .886
Parenting Style
Authoritative Parenting -.157 .093 -.096 .091
Authoritarian Parenting -.219 .107 -.123 .041
Permissive Parenting -.203 .129 -.096 .116

59

Table 4
Summary of Logistic Regression Analysis for Variables Predicting Persistence in a
Math Course
Variables R
2
df B SE B e
B

Persistence 26.192 7

Self-efficacy .794*** .216 2.213

Self-Regulation
Metacognitive Regulation -.438 .330 .645
Time and Study Environment Reg. .530* .258 1.699
Effort Regulation -.105 .257 .901

Parenting Style
Authoritative Parenting -.301 .293 .740
Authoritarian Parenting .038 .334 1.038
Permissive Parenting .312 .401 1.366

Constant -1.808 2.270 .164
Note: e
B
= exponentiated B.
*p < .05. **p < .01. ***p < .001.

Results of research question 2: To determine whether there were group
differences between Hispanics and European American basic skills math students at a
community college in math self-efficacy, self-regulation, parenting style, math
achievement and persistence in a math course, two t-tests, a Chi-square test, and two
multivariate analyses of variance were performed.
Group differences across self-efficacy, math grade, and persistence. First, an
independent-samples t-test was conducted to compare the self-efficacy scores for
Hispanics and Caucasians. There was no significant differences in self-efficacy scores
for Hispanics (M = 5.74, SD = 1.09) and Caucasians (M = 5.82, SD = .98), t (289) = -
.475, p = .635. A second independent-samples t-test was conducted to compare the math
60

grade for Hispanics and Caucasians. This initial analysis revealed that the math grades
for Hispanic students (M = 2.09, SD = 1.22) were lower than the math grades of
Caucasian students (M = 2.89, SD = 1.36), t (243) = -3.962, p = .000. A Chi-square test
for independence (with Yates Continuity Correction) indicated no significant association
between Hispanics or Caucasians and persistence, χ
2
(1, n = 270) = .02, p = .88, phi = -
.03.
Group differences across self-regulation. A one-way between-groups
multivariate analysis of variance was performed to investigate group differences in self-
regulation. Three dependent variables were used: metacognitive regulation, time and
study environment regulation, and effort regulation. The independent variable was
ethnicity with only two groups: Hispanics and Caucasians. There was a statistically
significant difference between Hispanics and Caucasians on the combined dependent
variables, F (3, 283) = 4.35, p = .005; Wilks’ Lambda = .96; partial eta squared = .05.
When the results for the dependent variables were considered separately, the only
difference to reach statistical significance, using a Bonferroni adjusted alpha level of
.017, was time and study environment regulation, F (1, 281) = 8.91, p = .003; partial eta
squared = .03. An inspection of the mean scores indicated that Caucasians had slightly
higher scores on time and study environment regulation (M = 5.53, SD = 1.11) than
Hispanics (M = 5.01, SD = 1.15).
Group differences across parenting styles. A one-way between-groups
multivariate analysis of variance was performed to investigate differences in parenting
styles among Hispanics and Caucasians. Three dependent variables were used:
authoritative, authoritarian, and permissive parenting styles. The independent variable
61

was ethnicity with only two groups: Hispanics and Caucasians. There was no statistically
significant difference between Hispanics and Caucasians on the combined dependent
variables, F (3, 265) = .69, p = .56; Wilks’ Lambda = .99; partial eta squared = .01.
Results of research question 3. To determine the extent to which self-efficacy,
self-regulation, parenting style, and acculturation predict math achievement and
persistence among Hispanic basic skills math students in community colleges, a
simultaneous multiple regression was performed using the self-efficacy scale, the three
subscales of self-regulation, the three parenting style subscales, as well as the two
acculturation subscales on data from only Hispanic students. The criterion variable used
for analysis was the grade obtained in the math course. The regression results revealed
an overall significance for the prediction model (F (9,178) = 4.99, p = .000) with 20.2%
of the variance being explained. Self-efficacy and regulation of time and study
environment were significant predictors of math grade (See Table 5). Results of this
analysis suggest that Hispanic students with higher self-efficacy and greater regulation of
time and study environment achieved higher math grades. No significant relationships
were found for metacognitive or effort regulation. No significant relationships were
found for any of the parenting style or acculturation subscales.
For the second dependent variable of persistence, logistic regression was
performed to assess the relationship of self-efficacy, self-regulation, parenting style, and
acculturation on the likelihood that Hispanic students would persist in their math course.
The model contained nine independent variables (self-efficacy; metacognitive, time and
study environment, and effort regulation; authoritarian, authoritative, and permissive
62

parenting styles; Hispanic and non-Hispanic domains of acculturation). The full model
containing all predictors was not statistically significant.
Results of research question 4. To determine the extent to which acculturation
predicts math self-efficacy, self-regulation and parenting style among Hispanic basic
skills math students in community colleges, seven multiple regressions were performed
using the two acculturation subscales: Hispanic domain and non-Hispanic domain. Three
of these seven regression results revealed an overall significance for the particular
prediction model while the other four revealed no overall significance. The details of
these seven regression results are given below.
When the criterion variable used for analysis was math self-efficacy, the
regression results revealed an overall significance for the prediction model (F (2, 232) =
3.16, p = .044) but with only 2.7% of the variance being explained. Using a Bonferroni
adjusted alpha level of .025, only the non-Hispanic domain score was a significant
Table 5
Summary of Simultaneous Regression Analysis for Variable Predicting Math
Achievement among Hispanics
Variable R
2
F B SE B β ρ
Math Achievement .202 4.992 .000

Self-efficacy .321 .089 .285 .000
Self-Regulation
Metacognitive Regulation -.112 .118 -.089 .342
Time and Study Environment Reg. .232 .104 .217 .027
Effort Regulation .093 .118 .083 .434
Parenting Style
Authoritative Parenting -.169 .115 -.106 .142
Authoritarian Parenting -.216 .129 -.125 .097
Permissive Parenting -.248 .168 -.113 .141
Acculturation
Hispanic Domain -.081 .111 -.052 .464
non-Hispanic Domain -.411 .369 -.082 .266
63

predictor of self-efficacy in which, when the Hispanic domain was controlled for , the
non-Hispanic domain explained 2.5% of the variance in math self-efficacy (see Table 6).
When the criterion variable used for analysis was effort regulation, the regression results
revealed an overall significance for the prediction model (F (2, 232) = 5.72, p = .004)
with 4.7% of the variance being explained. Using a Bonferroni adjusted alpha level of
.025, the non-Hispanic domain score was a significant predictor of effort regulation in
which, when the Hispanic domain was controlled for, the non-Hispanic domain explained
4.6% of the variance in effort regulation (see Table 7). When the criterion variable used
for analysis was authoritative parenting, the regression results revealed an overall
significance for the prediction model (F (2, 221) = 4.16, p = .017) with 3.6% of the
variance being explained. Using a Bonferroni adjusted alpha level of .025, the non-
Hispanic domain score was a significant predictor of authoritative parenting in which,
when the Hispanic domain was controlled for, the non-Hispanic domain explained 3.3%
of the variance in authoritative parenting (see Table 8).

Table 6
Summary of Simultaneous Regression Analysis for Acculturation Variables Predicting
Math Self-efficacy among Hispanics
Variable R2 F B SE B β ρ
Math Self-efficacy .027 3.16 .044
Acculturation
Hispanic Domain .129 .094 .093 .171
non-Hispanic Domain .732 .303 .164 .016
64

Table 8
Summary of Simultaneous Regression Analysis for Acculturation Variables Predicting
Authoritative Parenting among Hispanics
Variable R2 F B SE B β ρ
Authoritative Parenting .036 4.156 .017
Acculturation
Hispanic Domain .133 .067 .116 .095
non-Hispanic Domain .596 .218 .189 .007

Lastly, in the remaining four regressions, the criterion variables used for analysis
were metacognitive self-regulation, time and study environment regulation, authoritarian
parenting and permissive parenting. The regression results revealed no overall
significance for each of these prediction models.

Table 7
Summary of Simultaneous Regression Analysis for Acculturation Variables Predicting
Effort Regulation among Hispanics
Variable R2 F B SE B β ρ
Effort Regulation .047 5.719 .004
Acculturation
Hispanic Domain .144 .093 .104 .124
non-Hispanic Domain 1.003 .301 .223 .001
65

CHAPTER V: DISCUSSION
The purpose of this study was to address the gap in the current literature on
community college students in basic math courses by examining motivational, parental
and cultural factors as predictors of achievement and persistence of students enrolled in
basic skills mathematics courses at a community college. Specifically, the purpose of
this study was to investigate the degree to which self-efficacy, self-regulation, and
parenting style predict achievement and persistence of community college students in
prealgebra and elementary algebra. For Hispanics in particular, an additional variable of
acculturation was considered. The previous chapter provided a quantitative analysis of
the relationship between these variables. The current chapter provides a discussion of the
main findings, implications for research and practice, limitations of the current study, and
recommendations for future research.
Discussion of Results
Relationship between motivational and parental variables and achievement
and persistence. The first research question sought to determine the extent to which
self-efficacy, self-regulation and parenting style predict math achievement and
persistence among basic skills math students in community colleges. Previous research
has indicated that self-efficacy (Chemer et al., 2001; Multon et al., 1991; Pietsch, Walker
and Chapman, 2003; Zimmerman et al., 1992), self-regulation (Kitsantas et al. 2008) and
an authoritative parenting style (Silva et al., 2008; Turner et al., 2009) are positively
linked to student achievement. The current study sought to futher explore these
relationships at the community college level and specifically with the basic skills math
student population.
66

All four motivational variables (math self-efficacy, metacognitive self- regulation,
time and study environment regulation, and effort regulation) correlated significantly
with math grade as well as persistence in a math course. That is, basic skills math
students reporting higher self-efficacy for achieving in their math course or greater self-
regulation achieved higher grades in their basic skills math course and were less likely to
withdraw from their math course. Further analysis revealed that self-efficacy
contributed the strongest unique contribution to explaining the higher math grade. These
findings were consistent with previous research. In particular, the meta-analysis by
Multon et al. (1991) found stronger relationships between self-efficacy and performance
among low-achieving students than among average achieving students. Participants of
the current study could be considered “low-achieving” in math simply based on both their
current level of math ability and, for some, based on their performance in their particular
math course. Thus, the findings of the current study as well as of Moulton et al. (1991)
suggest that efforts to increase the self-efficacy of students in basic skills math classes at
community college may be particularly beneficial to their academic achievement.
While all three self-regulation variables correlated significantly with the
participant’s math grade, further analysis revealed only regulation of time and study
environment to be a significant predictor of the student’s grade in the basic skills math
course as well as their persistence through the course. This is similar to findings by
Kitsantas et al. (2008) in which time and study management strategies correlated
significantly with first- and third- year college GPA. However, unlike the findings in
Kitsantas et al. (2008), metacognitive regulation did not contribute significantly to math
achievement in the current study. Perhaps this is due to the differences in the population.
67

While the population in the Kitsantas et al. (2008) study involved students at a four-year
institution, it also was comprised of 64% White students and only 4% Hispanic which is
much different from the current study’s population of 61% Hispanic and 14% White. As
noted earlier, more research is still needed on the self-regulation strategies of Hispanics,
particularly at the community college level.
Using Baumrind’s (1971) parenting framework, studies have been inclusive
regarding the extent to which parenting styles predict achievement in college students
(Silva et al. 2008; Turner et al., 2009; Joshi, Ferris, Otto, & Regan, 2003). The results
from the current study were similar. Parenting style did not correlate significantly with
math grade or with persistence through the math course. However, an authoritative
parenting style did correlate significantly with self-efficacy as well as all three self-
regulation variables; and as previously discussed, self-efficacy and regulation of time and
study environment contributed significantly to explaining one’s grade in a math class.
Thus, the relationship between authoritative parenting, self-efficacy, self-regulation and
math achievement for basic skills college students is complex and perhaps not a direct
relationship. Perhaps, for college students, there are other mediating or moderating
factors present in the relationship between authoritative parenting and academic
achievement.
Group differences. The second research question sought to examine the
differences in self-efficacy, self-regulation, parenting style, math achievement, and
persistence in a math course between Hispanic and Caucasian basic skills math students
at the community college. The findings suggest there was a statistically significant
difference between Hispanics and Caucasians on the combined self-regulation variables
68

as well as on math achievement. Specifically, when the results for the three self-
regulation variables were considered separately, the only difference to reach statistical
significance was time and study environment regulation. An inspection of the mean
scores indicated that Caucasians had slightly higher scores on time and study
environment regulation. That is, Caucasian basic skills math students reported higher
self-regulation of their time and study environment than their Hispanic counterparts.
In addition, Caucasians had significantly higher grades than Hispanics. These
results suggest that the achievement gap between Hispanics and Caucasians exists at the
college level among basic skills students. Even though all basic skills students,
Caucasian or Hispanic, are entering college unprepared to enter college level math
courses, this study found that the Hispanic students are still more likely to obtain a lower
math grade than their Caucasian counterparts in their basic skills math course. Results of
this study suggest this may be influenced by the reported lower amounts of self-
regulation from the Hispanic students as overall greater self-regulation of time and study
environment was related to greater achievement and persistence. Thus, as with self-
efficacy, efforts to increase the use of self-regulation strategies of students, including the
Hispanic students, in basic skills math classes at community college may be particularly
beneficial to their academic achievement.
Relationship between self-efficacy, self-regulation, parenting style,
acculturation and math achievement and persistence for Hispanic students. The
third research question sought to determine the extent to which self-efficacy, self-
regulation, parenting style, and acculturation predict math achievement and persistence
among Hispanic basic skills math students in community colleges. Previous research has
69

indicated that higher levels of acculturation are associated with both positive and negative
outcomes among Hispanic adolescents and young adults (Carranza et al., 2009; Ewert,
2009; Martinez et al., 2004).
Specifically, some studies have found that higher acculturation levels are
associated with higher academic achievement (Carranza et al., 2009; Lopez, Ehly, &
Garcia-Vazquez, 2002) while others have found no relationship (Fuligni, Witkow, &
Garcia, 2005; Hurtado-Ortiz & Gauvain, 2007; Martinez et al., 2004). In the current
study, acculturation of Hispanics did not correlate significantly with achievement. That
is, there was no significant correlation between students’ scores either in the Hispanic
cultural domain or non-Hispanic cultural domain of the BAS with GPA, grade in a math
course, or persistence in a math course. This is similar to the findings which found no
relationship between acculturation levels and academic achievement (Fuligni, Witkow, &
Garcia, 2005; Hurtado-Ortiz & Gauvain, 2007; Martinez et al., 2004).
Further analysis revealed self-efficacy and regulation of time and study
environment were significant predictors of math grade for Hispanic basic skills math
students. Results of this analysis suggest that Hispanic students with higher self-efficacy
and greater regulation of time and study environment achieved higher math grades.
Therefore, the development of interventions to increase math self-efficacy as well as the
use of self-regulation strategies is crucial for the success of Hispancic basic skills math
students at the community college.
Relationship between acculturation and self-efficacy, self-regulation and
parenting style. The fourth research question sought to determine the extent to which
acculturation predicts math self-efficacy, self-regulation and parenting style among
70

Hispanic basic skills math students in community colleges. Previous research suggests
that acculturation has been considered an important factor influencing Hispanic students’
educational outcomes. Specifically, greater acculturation to the dominant culture
correlated with higher academic achievement (Carranza et al., 2009; Lopez, Ehly, &
Garcia-Vazquez, 2002), predicted a lower likelihood of high school dropout (Martinez et
al., 2004), yet also predicted a greater frequency of school misbehavior (Ewert, 2009).
In the current study, greater acculturation to the non-Hispanic cultural domain of
the BAS was shown to be a significant predictor of two of the motivational variables in
the regression analysis. Specifically, acculturation to the dominant culture significantly
predicted self-efficacy and self-regulation of effort in the basic skills math class at the
community college. At the correlational level, there was a weak but significant positive
correlational relationship between acculturation to the dominant culture and three of the
motivation variables (self-efficacy, metacognitive regulation, and effort regulation). That
is, basic skills math students reporting greater acculturation to the dominant culture also
reported having greater self-efficacy in their math class, greater metacognitive self-
regulation and greater regulation of their effort in their math class.
Furthermore, previous research has found Hispanic parents to be more
authoritarian and less authoritative than Caucasian parents (Dornbusch et al., 1987;
Steinberg, Dornbusch & Brown, 1992). In the current study, acculturation to the non-
Hispanic dominant culture was shown to be a significant predictor of authoritative
parenting in the regression analysis. At the correlational level, there was a weak but
significant positive correlational relationship between acculturation to the non-Hispanic
culture and authoritative parenting as well as a weak but significant negative correlational
71

relationship between acculturation to the non-Hispanic culture and authoritarian
parenting. That is, students reporting greater acculturation to the dominant culture were
more likely to report coming from an authoritative home and less likely to report coming
from an authoritarian home.
Implications for Research and Practice
This study raises important issues which have implications for community college
administrators and faculty. Colleges may need to redesign their curriculum for basic
skills courses as well as for professional development to address the different factors that
contribute to students’ motivation. Commendably, many colleges are already
implementing “college success courses” or “first-year experience” programs which
incorporate aspects of motivational and learning strategies such as self-efficacy and self-
regulation into the curriculum. Perhaps, more of similar programs are necessary to close
the achievement gap particularly for Hispanic basic skills math students at the community
college.
However, this study focused specifically on students within a basic skills
mathematics course, and thus the results of this study suggest that improvement can be
made within the math classroom itself. The responsibility of nurturing and developing
students’ self-efficacy and self-regulation skills does not lie solely with counselors.
Instead, all community college math faculty must assume their share of the responsibility
of influencing their students’ beliefs which contribute to self-efficacy beliefs and self-
regulation skills which ultimately are related to academic achievement. Thus, results of
this study suggest that community college math faculty need to be more than just experts
in their discipline. Basic skills community college math faculty would benefit from an
72

understanding of motivational principles and how to incorporate them into their teaching.
Professional development for content faculty may need to include training to address the
motivational factors that influence achievement and persistence.
Specifically, math professors should have knowledge regarding the sources of
self-efficacy: mastery experience, vicarious experience, social persuasion, and
physiological states (Bandura, 1997). Mastery experiences have been found to have the
most influence on the development of self-efficacy (Britner & Pajares, 2006; Klassen,
2004; Usher & Pajares, 2006). Thus, by providing students opportunities for success
within the classroom on a daily basis, math professors can help raise students’ math self-
efficacy. Furthermore, self-efficacy is raised through vicarious experiences, also known
as social modeling, in which one observes someone similar to oneself having success.
Accordingly, math professors can create situations in which students can observe each
other successfully solving math problems, thereby raising the student’s belief that he or
she, too, possesses the capability to solve the specific math problem. Finally, math
faculty can use social persuasion to increase students’ math self-efficacy. Social
persuasion includes the phenomenon in which self-efficacy beliefs are formed through
comments or feedback from others (Bandura, 1997). Hence, math faculty may benefit
from learning how to give feedback which is effective, explicit, and timely, and which
ultimately raises students’ math self-efficacy.
The results of this study also suggest that math faculty at the community college
would benefit from learning strategies for integrating self-regulatory skills and practices
into their curriculum. Specifically, the regulation of time and study environment was
found to have a significant relationship to achievement and persistence in a basic skills
73

math course. Math professors could encourage the development of their students’ self-
regulation skills by assisting students with setting goals specific to their math class.
When goals are proximal, specific, and moderately difficult, self-efficacy and motivation
to attain these goals is increased. Thus, math faculty could be explicit about which tasks
are necessary to prepare for upcoming exams allowing students to better create realistic
daily and/or weekly schedules. In addition, math faculty can use the course syllabus to
inform students from the start of the semester of major assignments, tests, and due dates
so that students can plan accordingly.
Additionally, professional development should address solutions to the
achievement gap between basic skills Hispanic and Caucasian students at the community
college. Hispanics continue to be over-represented in basic skills courses and earn lower
grades in these basic skills math courses. Results of this study revealed that basic skills
Hispanic math students reporting greater acculturation to the dominant culture also
reported having greater self-efficacy in their math class, greater metacognitive self-
regulation and greater regulation of their effort in their math class. Thus, while care must
be taken to increase the self-efficacy and self-regulation skills of all students, particular
concern must also be on those less acculturated to the dominant culture. Faculty would
benefit from an understanding of the sources which influence self-efficacy in general and
how best to provide experiences for first-generation Americans in which to raise their
math self-efficacy and gain self-regulation skills.
Limitations of the Study
There are several limitations of this study. First, this study measured self-efficacy
only once. However, self-efficacy is not considered a stable construct. That is, students’
74

self-efficacy may vary from week to week or even from day to day. In this study, self-
efficacy was measured during the fifth week of a 16-week semester. Most classes had
administered the first exam during this 5 week period. Thus, students’ self-efficacy for
succeeding in their math class may be very influenced by their performance on the first
exam. The fact that self-efficacy significantly correlated with achievement in this study
may be more of a result of students’ self-evaluation based on their first test results than
the students’ general assessment of their ability to succeed in a basic skills math course.
A second limitation is related to the use of the PAQ as an instrument with basic
skills students. The PAQ is a long instrument containing 30 items at a difficult reading
level. Most basic skills mathematics students are also at below college level in English.
Thus, the basic skills mathematic students in this study may have had difficulty fully
comprehending the questions on PAQ, and hence, it may be inappropriate to expect PAQ
to accurately assess the parenting style of the students in this study.
A third limitation is the self-reporting of responses in pencil-and-paper format.
Many of the items involved personal issues, namely attitudes and beliefs surrounding
one’s ability, behavior, class work and parenting. Even though students in this study
were informed that only the principal investigator would have access to their responses
and identifying information, results may be inaccurate due to social desirability which
may bias student answers. That is, students may have over-reported desirable responses
or under-reported undesirable ones while other participants may honestly give an overly
positive self-assessment (Paulhus, 1984). Furthermore, studies have found self-
disclosure to be increased when using a computerized questionnaire versus a pencil-and-
paper one (Booth-Kewley, Larson & Miyoshi, 2007).
75

A fourth limitation comes from the classification of all Hispanics into one group.
The study’s population was 60% Hispanic. While this study did consider within-group
differences of acculturation, overall results were not analyzed based on any break down
of this group into different Hispanic ethnic groups. Caution must be taken into
generalizing these results to all Hispanic ethnic groups.
Recommendations for Future Research
Based on a review of the literature, this study addressed four specific research
questions but acknowledges that the community college basic skills environment is
complex and dynamic. Thus, there continues to be issues and questions that future
research can address.
Considering the limitations accompanying the use of self-report surveys, future
research may want to include additional methods of measuring the motivational, parental
and cultural variables included in this study. Perhaps, these methods could include
interviews with teachers, students and/or parents as well as case studies involving basic
skills community college students. A combination of research methods would provide a
deeper and perhaps more accurate understanding of the relationship of these variables to
achievement and persistence. For instance, interviews with teachers or observations of
student behaviors in class may provide additional insight into a student’s self-efficacy or
use of self-regulation strategies.
In addition, future research may wish to explore students’ goals for taking a basic
skills mathematics course. In order to transfer or earn most certificates at a community
college, students are required to take prealgebra and elementary algebra whether the
student has chosen a STEM (Science/Technology/Engineering/Mathematics) major or
76

not. Perhaps there exists a difference in how motivation effects math achievement and
persistence for STEM majors vs. non-STEM majors.
Moreover, within the Hispanic community are many different ethnic groups. It
may be helpful for future research to consider these various groups separately in order to
better understand the role of motivational, parental and cultural factors on the
achievement of Hispanic community college students.
Conclusion
This study sought to bridge the gap in the current literature on community college
students in basic math courses by examining motivational, parental and cultural factors as
predictors of achievement and persistence of students enrolled in basic skills mathematics
courses at a community college. Results of this study revealed that motivational
constructs and math achievement are related. Specifically, this study revealed that
students reporting greater mathematics self-efficacy, as assessed by self-efficacy for
succeeding in one’s current math course, or greater self-regulation of one’s time and
study environment were more likely to earn higher grades in that math course. This
finding held for the entire population as well as for a Hispanic subgroup. Overall, this
study sheds light on the need for community college math faculty to be more than just
experts in their discipline. Community college mathematics faculty can assist their
students by gaining an understanding of motivational principles such as self-efficacy and
self-regulation and how to incorporate them into their teaching. Lastly, results of this
study revealed that Hispanics earn significantly lower grades in their basic skills math
class at the community college than their Caucasian counterparts. Hence, community
college math faculty must address motivational issues for the entire basic skills student
77

population but also specifically for the Hispanic student population in order to close this
achievement gap.
78

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86

APPENDIX A: INFORMATION SHEET FOR NON-MEDICAL RESEARCH
University of Southern California
Rossier School of Education
Waite Phillips Hall
Los Angeles, CA 90089-4038

INFORMATION/FACTS SHEET FOR NON-MEDICAL RESEARCH

Motivational, Parental, and Cultural Influences on Achievement in Basic Skills
Mathematics at the Community College

You are asked to participate in a research study conducted by Donna E. Nordstrom, M.A., M.S.,
and Ruth H. Chung, Ph.D., from the Rossier School of Education at the University of Southern
California. The results will contribute to the completion of Donna Nordstrom’s doctoral
dissertation. You are eligible to participate because of your enrollment in a Prealgebra or
Elementary Algebra course. You must be at least 18 years of age to participate. Your
participation is voluntary.

PURPOSE OF THE STUDY
The purpose of this study is to understand how your math self-efficacy and self-regulation, along
with your relationships with your parents and your cultural background, may influence your
achievement and persistence in your mathematics course. Your participation in this study will
help us to understand the factors that are important for community college students to succeed in
basic skills math courses.

You should read the information below, and ask questions about anything you do not understand,
before deciding whether or not to participate. Please take as much time as you need to read the
consent form. You may also decide to discuss it with your family or friends.

Completion and submission of the questionnaire will constitute consent to participate in this
research project.

PARTICIPANT INVOLVEMENT
If you volunteer to participate in this study, you are asked to complete a survey that will take
approximately fifteen minutes to complete. The survey will ask for background information such
as age, gender and the course you are taking. It will also ask you questions about your
experiences and feelings of your current math course as well as questions about your relationship
with your parents and your cultural background.

The study would also like to include, with your permission, the grade you receive in this course,
as well as some demographic and transcript information. This information will only be viewed
by the Principal Investigator and the data will be fully protected. Furthermore, instructors will
have NO access to the information you provide on this survey and your answers will NOT affect
your grade.
87

PAYMENT/COMPENSATION FOR PARTICIPATION
You will not receive direct payment for your participation. However, by participating in this
survey, you are eligible to enter a drawing for a $100 gift card, a $50 gift card, and four $25 gift
cards. In order to enter the drawing, you will need to provide your name and e-mail address at
the end of the survey. This information will be stored separately from your survey responses. If
you are a winner, you will be notified by e-mail.

CONFIDENTIALITY
Information obtained in the survey will only be reported in aggregated form without any
potentially identifiable descriptions connected to the individuals. Any information that is
obtained in connection with this study and that can be identified with you will remain
confidential. Your name and email address will be destroyed once gift cards have been
distributed and will not be associated with your responses.

Only members of the research team will have access to the data associated with this study. When
the results of the research are published or discussed in conferences, no information will be
included that would reveal your identity. The data will be stored in the investigator’s office in a
locked file cabinet and password protected computer. The data will be stored for three years after
the completion of this study and then destroyed.

Course instructors will have NO access to the information you provide on this survey and your
answers will NOT affect your grade.

PARTICIPATION AND WITHDRAWAL
You can choose whether to be in this study or not. If you volunteer to be in this study, you may
withdraw at any time without consequences of any kind.

INVESTIGATOR CONTACT INFORMATION
If you have any questions or concerns about the research, please feel free to contact Ruth Chung,
Ph. D. at rchung@usc.edu or Donna Nordstrom at donna.nordstrom@usc.edu.

IRB CONTACT INFORMATION
You may withdraw your consent at any time and discontinue participation without penalty. You
are not waiving any legal claims, rights or remedies because of your participation in this research
study. If you have any questions about your rights as a study participant or you would like to
speak with someone independent of the research team to obtain answers to questions about the
research, or in the event the research staff cannot be reached, please contact the University Park
IRB, Office of the Vice Provost for Research Advancement, Stonier Hall, Room 224a, Los
Angeles, CA 90089-1146, (213) 821-5272 or upirb@usc.edu.

88

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 the information sheet.

Permission to Access School Records:

□ YES, I agree to allow the Principal Investigator to access my records to obtain
demographic and transcript information such as my grade in this class and placement
results. I understand all information will be kept confidential.

□ No, I do not agree to allow the Principal Investigator to access my records to obtain
demographic and transcript information such as my grade in this class and placement
results.

Student’s Name

Student’s Signature Date

___________________________________ _____________________________
Student Identification # Last Four Digits of Social Security #

89

APPENDIX B: DEMOGRAPHIC INFORMATION
Please provide the following information:
1. 8-digit student ID number:________________________
2. Last 4 digits of social security number:__________________
3. Age:__________
4. Gender: _____Male _____Female
5. How many years of education do you have after high school? ____________
6. What is your racial/ethnic background (check all that apply)?
____African American
____Asian American
____Caucasian
____Hispanic or Latino
____Other (specify) ______________
7. In what country were you born?____________________
8. How long have you lived in the U.S.?_______________
9. Please indicate the generation that best applies to YOU.
_____1
st
generation (if you were NOT born in the U.S.)
_____2
nd
generation (if you were born in the U.S. but at least one parent was not)
_____3
rd
generation (if at least one grandparent was born in the U.S.)
_____4
th
generation (if at least one great-grandparent was born in the U.S.)
_____Above 4
th
generation.
10. What is your family structure?
_____Intact (parents are married)
_____Remarried
_____Divorced
_____Other
11. What is your annual family income?
_____ less than $25,000
_____$25,001-50,000
_____$50,001-75,000
_____$75,001-100,000
_____$100,001-150,000
_____over $150,000
12. How would you describe the socioeconomic class background of your family?
o Working class
o Lower middle class
o Middle class
o Upper middle class
o Upper class
90

APPENDIX C: MATH SELF-EFFICACY AND SELF-REGULATION SCALE
The following questions ask about your motivation for and attitudes about your current MATH
class. Remember there are no right or wrong answers; just answer as accurately as possible for
you. Answer the questions below by circling the number that best represents you. A score of 7
means that the statement is very true of you, and a score of 1 indicates that the statement is not at
all true about you. If the statement is more or less true of you, find the number between 1 and 7
that best describes you.

1 2 3 4 5 6 7

Not at all
true of me
Very true
about me
1. I believe I will receive an excellent
grade in this class.

1 2 3 4 5 6 7
2. I’m certain I can understand the most
difficult material presented in the
readings for this course.
1 2 3 4 5 6 7
3. I’m confident I can understand the
basic concepts taught in this course.
1 2 3 4 5 6 7
4. I’m confident I can understand the most
complex material presented by the
instructor in this course.
1 2 3 4 5 6 7
5. I’m confident I can do an excellent job
on the assignments and tests in this
course.
1 2 3 4 5 6 7
6. I expect to do well in this course. 1 2 3 4 5 6 7
7. I’m certain I can master the skills being
taught in this class.
1 2 3 4 5 6 7
8. Considering the difficulty of this
course, the teacher, and my skills, I
think I will do well in this class.
1 2 3 4 5 6 7
91

The following questions ask about your learning strategies and study skills for your MATH class.
Remember there are no right or wrong answers. Answer the questions about how you study in
this class as accurately as possible. Use the same scale as before to answer these questions.
Circle the number that best represents you.
1 2 3 4 5 6 7

Not at all
true of me
Very true
about me
9. During class time I often miss important
points because I’m thinking of other things.
1 2 3 4 5 6 7
10. I usually study in a place where I can
concentrate on my course work.
1 2 3 4 5 6 7
11. When reading for this course, I make up
questions to help focus my reading.
1 2 3 4 5 6 7
12. I often feel so lazy or bored when I study
for this class that I quit before I finish what
I planned to do.
1 2 3 4 5 6 7
13. When I become confused about something
I’m reading for this class, I go back and try
to figure it out.
1 2 3 4 5 6 7
14. I make good use of my study time for this
course.
1 2 3 4 5 6 7
15. If course materials are difficult to
understand, I change the way I read the
material.
1 2 3 4 5 6 7
16. I work hard to do well in this class even if I
don’t like what we are doing.
1 2 3 4 5 6 7
17. I find it hard to stick to a study schedule. 1 2 3 4 5 6 7
18. Before I study new course material
thoroughly, I often skim it to see how it is
organized.

1 2 3 4 5 6 7
92

1 2 3 4 5 6 7

Not at all
true of me
Very true
about me
19. I ask myself questions to make sure I
understand the material I have been
studying in this class.
1 2 3 4 5 6 7
20. I try to change the way I study in order to fit
the course requirements and the instructor’s
teaching style.
1 2 3 4 5 6 7
21. I often find that I have been reading for this
class but don’t know what it was all about.
1 2 3 4 5 6 7
22. When course work is difficult, I either give
up or only study the easy parts.
1 2 3 4 5 6 7
23. I try to think through a topic and decide
what I am supposed to learn from it rather
than just reading it over when studying for
this course.
1 2 3 4 5 6 7
24. I have a regular place set aside for studying. 1 2 3 4 5 6 7
25. I make sure that I keep up with the weekly
readings and assignments for this course.
1 2 3 4 5 6 7
26. I attend this class regularly. 1 2 3 4 5 6 7
27. Even when course materials are dull and
uninteresting, I manage to keep working
until I finish.
1 2 3 4 5 6 7
28. When studying for this course I try to
determine which concepts I don’t
understand well.
1 2 3 4 5 6 7
29. I often find that I don’t spend very much
time on this course because of other
activities.

1 2 3 4 5 6 7
93

1 2 3 4 5 6 7

Not at all
true of me
Very true
about me
30. When I study for this class, I set goals for
myself in order to direct my activities in
each study period.
1 2 3 4 5 6 7
31. If I get confused taking notes in class, I
make sure I sort it out afterwards.
1 2 3 4 5 6 7
32. I rarely find time to review my notes or
readings before an exam.
1 2 3 4 5 6 7

94

APPENDIX D: PARENTAL AUTHORITY QUESTIONNAIRE
For each of the following statements, circle the number on the 5-point scale that best indicates
how that statement applies to you and your parents. Try to read and think about each statement as
it applies to you and your parent(s) (both mother and father together or one parent or guardian)
during your years growing up at home.

There are no right or wrong answers, so don’t spend a lot of time on any one item. We are
looking for your overall impression regarding each statement. Be sure not to omit any items.
1 2 3 4 5

Strongly
Disagree
Disagree Undecided Agree Strongly
Agree
1. While I was growing up, my parents felt that in
a well run home the children should have their
way in the family as often as the parents do.
1 2 3 4 5
2. Even if their children didn’t agree with them,
my parents felt that it was for our own good if
we were forced to conform to what they thought
was right.
1 2 3 4 5
3. Whenever my parents told me to do something
as I was growing up, they expected me to do it
immediately without asking any questions.
1 2 3 4 5
4. As I was growing up, once family policy had
been established, my parents discussed the
reasoning behind the policy with the children in
the family.
1 2 3 4 5
5. My parents have always encouraged verbal
give-and take whenever I have felt that family
rules and restrictions were unreasonable.
1 2 3 4 5
6. My parents have always felt that what children
need is to be free to make up their own minds
and to do what they want to do, even if this does
not agree with what their parents might want.
1 2 3 4 5
7. As I was growing up, my parents did not allow
me to question any decision that they had made.
1 2 3 4 5
8. As I was growing up, my parents directed the
activities and decisions of the children in the
family through reasoning and discipline.
1 2 3 4 5
9. My parents have always felt that more force
should be used by parents in order to get their
children to behave the way they are supposed to
.
1 2 3 4 5
95

1 2 3 4 5

Strongly
Disagree
Disagree Undecided Agree Strongly
Agree
10. As I was growing up, my parents did not feel
that I needed to obey rules and regulations of
behavior simply because someone in authority
had established them.
1 2 3 4 5
11. As I was growing up, I knew what my parents
expected of me in my family, but I also felt free
to discuss those expectations with my parents
when I felt that they were unreasonable.
1 2 3 4 5
12. My parents felt that wise parents should teach
their children early just who is boss in the
family.
1 2 3 4 5
13. As I was growing up, my parents seldom gave
me expectations and guidelines for my behavior.
1 2 3 4 5
14. Most of the time as I was growing up, my
parents did what the children in the family
wanted when making family decisions.
1 2 3 4 5
15. As the children in my family were growing up,
my parents consistently gave us direction and
guidance in rational and objective ways.
1 2 3 4 5
16. As I was growing up, my parents would get very
upset if I tried to disagree with them.
1 2 3 4 5
17. My parents feel that most problems in society
would be solved if parents would not restrict
their children’s activities, decisions, and desires
as they are growing up.
1 2 3 4 5
18. As I was growing up, my parents let me know
what behaviors they expected of me, and if I
didn’t meet those expectations, they punished
me.
1 2 3 4 5
19. As I was growing up, my parents allowed me to
decide most things for myself without a lot of
direction from them.
1 2 3 4 5
20. As I was growing up, my parents took the
children’s opinions into consideration when
making family decisions, but they would not
decide for something simply because the
children wanted it.
1 2 3 4 5
96

1 2 3 4 5

Strongly
Disagree
Disagree Undecided Agree Strongly
Agree
21. My parents did not view themselves as
responsible for directing and guiding my
behavior as I was growing up.
1 2 3 4 5
22. My parents had clear standards of behavior for
the children in our home as I was growing up,
but they were willing to adjust those standards
to the needs of each of the individual children in
the family.
1 2 3 4 5
23. My parents gave me direction for my behavior
and activities as I was growing up and they
expected me to follow their direction, but they
were always willing to listen to my concerns
and to discuss that direction with me.
1 2 3 4 5
24. As I was growing up, my parents allowed me to
form my own point of view on family matters
and they generally allowed me to decide for
myself what I was going to do.
1 2 3 4 5
25. My parents have always felt that most problems
in society would be solved if we could get
parents to strictly and forcibly deal with their
children when they don’t do what they are
supposed to as they are growing up.
1 2 3 4 5
26. As I was growing up, my parents often told me
exactly what they wanted me to do and how
they expected me to do it.
1 2 3 4 5
27. As I was growing up, my parents gave me clear
direction for my behaviors and activities, but
they were also understanding when I disagreed
with them.
1 2 3 4 5
28. As I was growing up, my parents did not direct
the behaviors, activities, and desires of the
children in the family.
1 2 3 4 5
29. As I was growing up, I knew what my parents
expected of me in the family and they insisted
that I conform to those expectations simply out
of respect for their authority.
1 2 3 4 5
30. As I was growing up, if my parents made a
decision in the family that hurt me, they were
willing to discuss that decision with me and to
admit it if they had made a mistake.
1 2 3 4 5
97

APPENDIX E: BIDIMENSIONAL ACCULTURATION SCALE FOR HISPANICS
If you are Latino/Hispanic, please continue and answer the following questions.If you are
not Latino/Hispanic, please move ahead to Part E to enter the drawing for a gift card.
For each of the following statements, circle the number on the 4-point scale that best
indicates how that statement applies to you.
1 2 3 4

almost
never
sometimes often almost
always
1. How often do you speak English? 1 2 3 4
2. How often do you watch television
programs in Spanish?
1 2 3 4
3. How often do you think in English? 1 2 3 4
4. How often do you speak in Spanish with
your friends?
1 2 3 4
5. How often do you think in Spanish? 1 2 3 4
6. How often do you listen to radio programs
in English?
1 2 3 4
7. How often do you speak Spanish? 1 2 3 4
8. How often do you listen to music in
English?
1 2 3 4
9. How often do you watch television
programs in English?
1 2 3 4
10. How often do you listen to radio programs
in Spanish?
1 2 3 4
11. How often do you speak in English with
your friends?
1 2 3 4
12. How often do you listen to music in
Spanish?
1 2 3 4
98

1 2 3 4

Very
Poorly
Poorly Well Very Well
13. How well do you speak English? 1 2 3 4
14. How well do you understand television
programs in Spanish?
1 2 3 4
15. How well do you write in English? 1 2 3 4
16. How well do you understand music in
English?
1 2 3 4
17. How well do you read in Spanish? 1 2 3 4
18. How well do you understand television
programs in English?
1 2 3 4
19. How well do you understand radio
programs in Spanish?
1 2 3 4
20. How well do you read in English? 1 2 3 4
21. How well do you speak Spanish? 1 2 3 4
22. How well do you write in Spanish? 1 2 3 4
23. How well do you understand radio
programs in English?
1 2 3 4
24. How well do you understand music in
Spanish?
1 2 3 4

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Asset Metadata

Creator Nordstrom, Donna E. (author)

Core Title Motivational, parental, and cultural influences on achievement and persistence in basic skills mathematics at the community college

School Rossier School of Education

Degree Doctor of Education

Degree Program Education (Leadership)

Publication Date 05/02/2012

Defense Date 03/07/2012

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

Tag acculturation,community college,math achievement,OAI-PMH Harvest,parenting styles,self-efficacy,self-regulation

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Chung, Ruth (committee chair), Hirabayashi, Kimberly (committee member), Klein, Brock (committee member)

Creator Email denordstrom@pasadena.edu,denordstrom@yahoo.com

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c3-23389

Unique identifier UC11288299

Identifier usctheses-c3-23389 (legacy record id)

Legacy Identifier etd-NordstromD-716.pdf

Dmrecord 23389

Document Type Dissertation

Rights Nordstrom, Donna E.

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