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The impact of remedial mathematics on the success of African American and Latino male community college students

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The impact of remedial mathematics on the success of African American and Latino male community college students

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Content THE IMPACT OF REMEDIAL MATHEMATICS ON THE SUCCESS OF
AFRICAN AMERICAN AND LATINO MALE COMMUNITY COLLEGE
STUDENTS
by
Kaneesha K. Miller
A Dissertation Presented to the
FACULTY OF THE ROSSIER SCHOOL OF EDUCATION
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF EDUCATION
December 2006
Copyright 2006 Kaneesha Miller
ii
Dedication
To Mom and Dad
iii
Acknowledgements
I am most grateful to all those who supported me throughout this process.
First, I would like to thank Dr. William Maxwell, my advisor, for pushing me
to do my best work, supporting me in times of doubt, and cheering my
successes along the way. Thank you for all the time and effort you spent on
each draft of this work.
Next, I would like to thank Dr. George Prather for giving me access to the Los
Angeles Community College Database. Not only did he provide me with the
necessary data, but he also spent time advising me on SPSS and data analysis.
I would like to thank the members of my dissertation cohort: Shalamon Duke,
Lia Lerner, Gregory Schulz, Jenny Simon, Daniel Soodjinda, Andrew
Truong, and Manoj Wickremesinghe. You each played an integral role in me
completing this process. We spent numerous hours supporting each other,
reading and critiquing drafts, and pushing each other along. I thank you all
from the bottom of my heart.
Finally, I want to thank my friends and family, without their love, support and
understanding, none of this would have been possible. Thank you to my
parents for believing in me when I didn’t believe in myself, for pushing me
when I thought I couldn’t go, and for being my inspiration each and every
day.
iv
Table of Contents
Dedication ii
Acknowledgements iii
List of Tables v
List of Figures vii
Abstract viii
Chapter 1: Introduction 1
Chapter 1 Endnotes 4
Chapter 2: Literature Review 8
Persistence Theory 8
Student Age and Remedial Math Success 11
Course Load and Remedial Math Success 14
Early versus Delayed Enrollment in Remedial Math 16
Academic Performance in College Level Courses 18
Summary 20
Chapter 2 Endnotes 22
Chapter 3: Methods 25
Methodology 25
Sample 25
Data Collection 26
Research Design and Definitions 26
Limitations 37
Measures 37
Chapter 4 Endnotes 38
Chapter 4: Results and Findings 41
Hypothesis One 41
Hypothesis Two 43
Hypothesis Three 45
Hypothesis Four 49
Chapter 5: Conclusion 54
Recommendations 57
Future Research 58
Chapter 5 Endnotes 61
References 63
v
List of Tables
Table 1: Population of first-time LACCD male students in remedial
mathematics for Fall 2000 and Fall 2001 26
Table 2: Number of enrollments by ethnicity and level of remedial
mathematics taken by LACCD male remedial mathematics students in
Fall 2000 and Fall 2001 cohort 31
Table 3: Number of attempts in Math 105 and Math 112 remedial mathematics
courses taken by LACCD male students for Fall 2000 and Fall 2001 cohorts 32
Table 4: Age Distribution of LACCD male remedial mathematics students
within Fall 2000 and Fall 2001 cohorts 33
Table 5: Male students excluded due to multiple attempts in a remedial
mathematics course 36
Table 6: Correlation of Mean Grade Point Average (GPA) of Males
in Remedial Mathematics by Age Group 42
Table 7: Correlation of Success Ratio of Male Community College Students
in Remedial Mathematics by Age Group 43
Table 8: Correlation of Success Ratio of Male Community College Students
in Remedial Mathematics by Units Attempted 44
Table 9: Correlation of Mean GPA of Male Community College Students
in Remedial Mathematics by Units Attempted 45
Table 10: Percentage of Male students who enrolled in remedial mathematics
in their first term versus those who did not 46
Table 11: Semester in which male students enrolled in their first remedial
mathematics by term cohort Fall 2000 47
Table 12: Semester in which male students enrolled in their first remedial
mathematics by term cohort Fall 2001 47
vi
Table 13: Average GPA overall and in math courses of male students
who enrolled in remedial mathematics in their first term versus those
who did not 48
Table 14: Success Rate in remedial mathematics of male students who
enrolled in remedial mathematics in their first term versus those who did not 49
Table 15: Success and non-success of male students in Math 125 after
successfully completing Math 105 50
Table 16: Success and non-success of male students in Math 125 after
successfully completing Math 112 51
Table 17: Success and non-success of male students in Math 125 after
successfully completing Math 115 52
vii
List of Figures
Figure 1: Mathematics Course Sequence from the 2005-2006
Los Angeles Mission College General Catalog 27
Figure 2: Mathematics Course Sequence from the Los Angeles Harbor
College 2004-2006 General Catalog 28
Figure 3: Mathematics Course Sequence from the 2005-2006 Los Angeles
Southwest College General Catalog 29
Figure 4: Mathematics Course Sequence from the 2005-2006 Los Angeles
Valley College General Catalog 30
viii
Abstract
This study examined course taking patterns in remedial mathematics and their
possible impact on the success of first-time African American and Latino male
community college students in the Los Angeles Community College District
(LACCD). The questions that this study answered focused around student
background characteristics and performance in remedial mathematics. This study’s
independent variables were ethnicity, age, course load, and level of remedial math
and time of entry into remedial mathematics courses. Remedial mathematics courses
represented those courses below the designated transfer course and were analyzed by
levels. These independent variables were paired with the dependent variable of
student success, which was measured in terms of grade point average (GPA) and
course completion rates. The study utilized academic integration as first discussed in
Tinto’s Student Departure theory and hypothesized that student characteristics and
student success was correlated with course-taking patterns in remedial mathematics.
Data utilized were from the Los Angeles Community College District (LACCD)
dataset.
The study found that remedial mathematics courses impact the success of
African American and Latino male community college students. The four hypothesis
addressed were partially supported by the data. Older students were more successful
in remedial mathematics than younger cohorts in terms of GPA and course
completion rates. Full-time students also had higher success rates in remedial math
than part-time students. Both findings supported Tinto’s original hypotheses
regarding age and course load. This study also found a high correlation between
performance in college-level mathematic courses following successful completion of
ix
remedial mathematics courses. Additionally, delayed entry in remedial
mathematics past the first semester led to higher overall GPA’s and course
completion rates. The implications of this study were that the majority of first-time
African American and Latino male community college students are not progressing
through the remedial mathematics sequence; however the likelihood of success in
college level math courses is correlated with successful completion of remedial
mathematics courses. Student age and the timing of enrolling in the remedial
mathematics course were found to be significant factors. Therefore, students should
be required to complete remediation; but encouraged to delay enrollment past the
first semester.
1
Chapter 1
Introduction
Community colleges
1
are currently the primary institutions that offer remedial
education
2
, and improving the effectiveness of remedial education is one of the most
important issues confronting community colleges today (Bailey & Alfonso, 2005).
Nationwide approximately half of all students entering the higher education system
enroll in remedial courses. Within the community college setting approximately 64%
of students take some remedial courses (Adelman, 1995; Venezia, Kirst, & Antonio,
2000). Remedial courses are commonly defined as those courses below college-level
and can be offered in reading, writing and mathematics; however mathematics
3
is the
most common area of need (Lazarick, 1997; Oudenhoven, 2002). Students enrolled
in remedial mathematics classes are starting at a disadvantage in the postsecondary
setting (Hagedorn, Siadat, Fogel, Nora & Pascarella, 1999). As an example, at
Baltimore City Community College (BCCC), of the first-time students enrolled in
fall 2000, 95% required remediation in mathematics. Nearly one half of these
students placed into the lowest level of remedial mathematics, which would require
them to complete as many as nine courses (27 credits) before taking credit courses in
math (Venezia et al, 2000).
While students of all backgrounds entering the community college setting are
represented in the remedial education population, the number of minority students,
particularly African American and Latino students is disproportionately higher in
comparison to other racial groups
4
(Bensimon, 2004; Hoyt, 1999; Moore et.al., 2002;
Shaw, 1997). According to Shaw, the number of African American
5
and Latino
6
students enrolled in remedial courses is 1.5 to 2 times higher than White and Asian
2
students. In addition to being over-represented, this population tends to need more
remediation than their peers, often starting at the lowest levels of remedial math.
College mathematics serves as a barrier that many students of all
backgrounds are unable to overcome (Maxwell, Hagedorn, Cypers, Lester, & Moon,
2004; Stage & Kloosterman, 1995). However, African American and Latino students
continue to be outperformed by White and Asian students (Tate, 1997). African
American and Latino students suffer the most losses at each step in the educational
process, from high school graduation and college enrollment to earning degrees and
certificates, resulting in continued growth of the achievement gap between minority
and majority students (McCabe, 2001).
This situation is further magnified for the males of these subgroups, as African
American and Latino males are more likely to begin their higher education careers in
remedial courses and enter remedial mathematics at greater rates than other
ethnic/racial groups (Grimes, 1997). African American ethnicity has been found to
be negatively correlated with performance in remedial and subsequent college level
mathematics (Penny & White, 1998). Additionally, Latinos have made few gains in
mathematics course-taking rates and achievement (Nora and Horvath, 1990).
Furthermore, minority male students continue to fall far behind their female
counterparts in math achievement and attainment (Oakes, Joseph, and Muir, 2000).
Analysis and theoretical frameworks to explain this issue for African American and
Latino males in the community college setting are minimal (Davis, 1994; Hagedorn,
Maxwell, Chen, Cypers, & Moon, 2002; Mason, 1998). Therefore this dissertation
will attempt to add to the existing literature base regarding the course-taking
3
patterns
7
in remedial mathematics for first-time African American and Latino male
community college students. The specific questions that will guide this study are:
Does student age impact the success of first-time African American and Latino
male community college students in remedial mathematics?
Does course load impact the success of first-time African American and Latino
male community college students in remedial mathematics?
Does delayed entry into remedial mathematics courses for first-time African
American and Latino male community college students negatively or positively
impact their educational success?
Does completion of remedial mathematics increase success in community
college-level mathematics for first-time African American and Latino male
community college students?
4
Chapter 1 Endnotes
1
Remediation has been a part of the higher education system dating back to the 17th century
(Merisotis and Phipps, 2000). Historically in the United States, remedial education was first
offered in the traditional resident university model, but as the shift moved away from
development of the whole student to the research-oriented university model, remedial
education was moved out of traditional colleges and into the community college setting
(Spann, 1992. Virtually every community college in the country offers some form of
remedial instruction (Zeitlin & Markus, 1996). The “remediation mission” of the community
college system takes up the failure of the K-12 system in preparing students for
postsecondary academic and vocational work as well as the remediation of adults returning
to higher education after a lapse of years (Adelman, 2005, p. 8). The purpose of the
community college has been hotly debated in recent years, especially in relation to the area
of remediation and its impact on student success.
2
The terms remedial education and developmental education are often used interchangeable,
however there are differences. Developmental education usually takes into consideration
cognitive and non-cognitive factors that influence student success (Higbee, Arendale, &
Lundell, 2005), whereas remediation focuses primarily on cognitive variables solely. The
term remediation will be used solely throughout this text.
3
Remediation in all areas is noteworthy; however math is of particular interest due to the
large numbers of students requiring these courses and the profound impact of remedial
mathematics on student success and persistence. Those who are unable to complete the
necessary remedial mathematics courses and progress to transfer level coursework are
unable to earn the associate degree and/or transfer to a four-year institution.
4
This is of particular significance as the Los Angeles Community College District (LACCD)
educates almost 3 times as many Latino students and nearly 4 times as many African-
American students as all of the University of California (UC) campuses combined (Los
Angeles Community College District, 2006).
5
Nationwide, African American students are more likely to begin their college career in a
community college versus a four year institution (Glenn, 2003). African Americans represent
approximately 16% of the 15 to 19 year-old population, but earn only 10 percent of associate
degrees awarded and are more likely to earn vocational degrees than other ethnic groups
(Hagedorn et.al., 2001/2002). In fact, African Americans are the most underrepresented
group at all degree levels (Maple & Stage, 1991).
The state of African American males in higher education is a pressing issue, as the
females of this racial group continue to outperform and attain greater rewards than the males
(Hagedorn et al.; Lang, 1992). African American men are less likely than their female
counterparts to apply and enroll into college (Washingon & Newman, 1991). Nationwide,
5
African American male enrollments have been on decline over the past 15 years (Cross &
Slater, 2000). From 1990 to 1999, African American male enrollments for first-time
freshman grew 4 percent in California community colleges, however female enrollments
outnumbered men by 3 percent (Allen, Bonous-Hammarth, & Teranishi, 2002). While
community colleges are the predominant entry point for the majority of African American
male students, many do not achieve their educational goals (Hagedorn, Maxwell, &
Hampton, 2001).
Unfortunately, African American men are the lowest performing subgroup in
percentage of degrees earned, persistence rates and average cumulative GPA (Bush & Bush
V, 2004).African American ethnicity has been found to be negatively correlated with
performance in remedial and subsequent college level mathematics (Penny & White, 1998).
African American men are disproportionately represented in students who withdraw; those
with lower academic performance and those with more negative college experiences (Davis,
1994).
Davenport et al. (1998) found that African American high school students identify
high education aspirations; however they do not take coursework consistent with those plans.
In fact, African American students are twice as likely to need remedial help in comparison to
their White peers (Rowser, 1997), especially in the area of math.
There are multiple causes; however poor preparation and academic performance of
African American males in the K-12 setting lead them to enroll in community colleges, place
into remedial math, and work in courses that do not apply to their major or a degree (Grimes,
1997). This pattern may lead students to become frustrated and depart the institution, as can
be seen by the less than 10 percent retention rate (Chenoweth, 1998).
There is some research looking in the K-12 setting (Ladson-Billings, 1997), Other
studies (Grosset, 1997; Weissman, Bulakowski, & Jumisko, 1998) have grouped all African
American students together, and not looked specifically at African American males.
Theoretical frameworks to explain this issue for African American males in the community
college setting are minimal (Mason, 1998), and very little analysis has been done to examine
the experience of African American males in diverse college settings (Davis, 1994). In his
study of African American males in the Texas community college setting Glenn (2003),
found that African American males tended to earn lower grade point averages, have higher
attrition rates, lower associate degree completion and transfer. However, Glenn examined
the problem from the level of the institution, rather than from the level of the individual
student and used graduation rates as his determinant of success. In comparison, Hagedorn et
al. (2001) incorporated persistence theory and examined the impact of course load and GPA
on student success of 202 African American males in the community college setting and
found age (younger students) and course load (full-time status) to be positive and significant
predictors of retention.
Nationwide, African American students are more likely to begin their college career in
a community college versus a four year institution (Glenn, 2003). African Americans
represent approximately 16% of the 15 to 19 year-old population, but earn only 10 percent of
associate degrees awarded and are more likely to earn vocational degrees than other ethnic
groups (Hagedorn et.al., 2001/2002). In fact, African Americans are the most
underrepresented group at all degree levels (Maple & Stage, 1991).
6
The state of African American males in higher education is a pressing issue, as the
females of this racial group continue to outperform and attain greater rewards than the males
(Hagedorn et al.; Lang, 1992). African American men are less likely than their female
counterparts to apply and enroll into college (Washingon & Newman, 1991). Nationwide,
African American male enrollments have been on decline over the past 15 years (Cross &
Slater, 2000). From 1990 to 1999, African American male enrollments for first-time
freshman grew 4 percent in California community colleges, however female enrollments
outnumbered men by 3 percent (Allen, Bonous-Hammarth, & Teranishi, 2002). While
community colleges are the predominant entry point for the majority of African American
male students, many do not achieve their educational goals (Hagedorn, Maxwell, &
Hampton, 2001).
Unfortunately, African American men are the lowest performing subgroup in
percentage of degrees earned, persistence rates and average cumulative GPA (Bush & Bush
V, 2004).African American ethnicity has been found to be negatively correlated with
performance in remedial and subsequent college level mathematics (Penny & White, 1998).
African American men are disproportionately represented in students who withdraw; those
with lower academic performance and those with more negative college experiences (Davis,
1994).
Davenport et al. (1998) found that African American high school students identify
high education aspirations; however they do not take coursework consistent with those plans.
In fact, African American students are twice as likely to need remedial help in comparison to
their White peers (Rowser, 1997), especially in the area of math.
There are multiple causes; however poor preparation and academic performance of
African American males in the K-12 setting lead them to enroll in community colleges, place
into remedial math, and work in courses that do not apply to their major or a degree (Grimes,
1997). This pattern may lead students to become frustrated and depart the institution, as can
be seen by the less than 10 percent retention rate (Chenoweth, 1998).
There is some research looking in the K-12 setting (Ladson-Billings, 1997), Other
studies (Grosset, 1997; Weissman, Bulakowski, & Jumisko, 1998) have grouped all African
American students together, and not looked specifically at African American males.
Theoretical frameworks to explain this issue for African American males in the community
college setting are minimal (Mason, 1998), and very little analysis has been done to examine
the experience of African American males in diverse college settings (Davis, 1994). In his
study of African American males in the Texas community college setting Glenn (2003),
found that African American males tended to earn lower grade point averages, have higher
attrition rates, lower associate degree completion and transfer. However, Glenn examined
the problem from the level of the institution, rather than from the level of the individual
student and used graduation rates as his determinant of success. In comparison, Hagedorn et
al. (2001) incorporated persistence theory and examined the impact of course load and GPA
on student success of 202 African American males in the community college setting and
found age (younger students) and course load (full-time status) to be positive and significant
predictors of retention.
6
There is still a lot unknown about the student departure process in relation to Latino
community college students (Hagedorn, Maxwell, Chen, Cypers, & Moon, 2002).
7
Enrollments for Latino males in California community colleges grew 53 percent between
1990 and 1999 (Allen et al., 2002). Latino students are more likely to enroll in community
college than any other racial or ethnic group (Martinez & Fernandez, 2004). Community
colleges showed an 84% increase in Latino enrollments between 1986 and 1996 (Perin &
Charron, 2003). More than 55% of all Latino students begin their college career at a
community college (Saenz, 2002).Latinos comprise approximately 14 percent of the 15 to
19-year old population, but earn only seven percent of associate degrees (McCabe, 2001).
Larger numbers of Latino
6
males are attending college than their female counterparts
(Thomas, 1998); however they are less likely to persist through graduation (Swail, Cabrera,
& Lee, 2004). They are more likely to enroll part-time, delay entry into college, and have a
higher need for remediation (Brown, Santiago, & Lopez, 2003; Fry, 2003). Latinos are also
overrepresented in the older student population in college than their White peers. A higher
percentage of Latino students (45 percent) are enrolled part time than either African
Americans (40 percent) or White students (39 percent) (ERIC, 2001). Latino male students
exhibit similar patterns of low academic success, persistence and retention rates as African
American males. However, few studies have looked at the retention of Latino male students
utilizing Tinto’s theory (Nora, 1987).
Historically, Latinos have made few gains in mathematics course-taking rates and
achievement (Nora and Horvath, 1990), and are more likely to complete high school with
lower-level math courses than other students (Swail, Cabrera, & Lee, 2004). Once enrolled
in the Los Angeles community college setting, Maxwell et al. (2003) found that Latino
students comprised 58% of first-time enrollments in remedial math and only 33% of
enrollments in A.A. applicable/transferable courses. Older latinos students had higher grades
and course completion rates ((Hagedorn, Maxwell, Chen, Cypers, & Moon, 2002).
For the purpose of this study Latinos are grouped as one homogenous unit, however
there exist differences amongst the different Latino subgroups. Cuban Americans have the
highest rate of college attendance with nearly 45% of 18 to 24 year old enrolled in college.
This rate drops to 33 % for Mexican Americans (the largest Latino subgroup) and 30% for
Puerto Ricans and Central/South Americans (Fry, 2003).
7
There is no universal definition or consensus on what constitutes the construct of course-
taking. The existing literature on course-taking in the community college setting is limited,
as most of the research focuses on course-taking in the high school (Spade, Columba, &
Vanfossen, 1997; Teitelbaum, 2003; Useem, 1992) or the four-year setting (Ma & Willms,
1999; Moreno & Muller, 1999; Whiteley & Fenske, 1990). Weissman, Silk, and Bulakowski
(1997) identified three sequences of course-taking in the community college setting: 1)
students who focus solely on remedial coursework, 2) students who took college-level
courses concurrently with their remedial coursework, and 3) students who enrolled solely in
college-level courses (p. 194). Furthermore in the area of remedial math, Maxwell et al.
(2003) categorized course-taking in remedial math based on the level of: 1) remedial, 2)
A.A. applicable/not transferable and 3) A.A. applicable/transferable. Maxwell et al. (2003)
and Nora and Horvath (1990) defined course-taking as individual enrollments in courses
within the curriculum.
8
Chapter 2
Literature Review
Persistence Theory
Several theories
8
exist that attempt to explain persistence in the college setting.
Research in this area ranges from exploratory (i.e. Maxwell et al., 2004), to studies
utilizing economic, organizational, psychological, or societal frameworks (i.e.
Braxton et al, 2000; Clark, 1960; Valadez, 1993). However, the most prominent
theory is Tinto’s (1975) Student Departure theory, which asserts that students enter
an institution with varying background attributes, experiences, and differing levels of
commitment to their educational goals and the institution. The relations between
these variables impacts the level of academic and social integration students’
experience, which in turn impacts their decision to either persist or depart from the
institution
9
.
Tinto (1982) asserts that there are an increasing number of students in all age
groups from diverse backgrounds that enter the higher education arena under
prepared to meet the academic rigor. Furthermore, a direct connection exists between
remediation and student success for minority students, as remedial programs affect
the ability of the student to integrate into the mainstream academic and social life of
the institution. While Tinto’s theory suggests that both academic and social
integration are important in this process, he acknowledged that in urban community
colleges (i.e. LACCD), students are shaped more by external forces (such as work
and family), and that social integration may not be as important in this setting.
Researchers (Halpin, 1990; Mutter, 1992; Tinto 1998) have found academic
integration to be the more important form of involvement in the community college
9
arena, and as such will be the focus of this dissertation. However it is important to
note that other researchers argue the validity of Tinto’s model in the community
college setting (Bailey et al. 2004; Braxton, 2000; Feldman, 1993; Rendon &
Tierney, 1992; Webb, 1989), noting a lack of emphasis on student characteristics
such as age, gender, or ethnicity as well as difficulty defining and measuring
academic and social integration.
In regards to the above mentioned student characteristics, Tinto (1987)
hypothesized that older students would perform better than their younger
counterparts due to the older student’s commitment to their educational goals. He
also hypothesized that male students were more likely to leave higher educational
institutions due to academic difficulties; however he did not differentiate amongst
ethnic groups. He also purported that minority students are more likely to leave
higher education institutions due to academic difficulties and meeting the formal
demands of the academic system, than their peers. Finally, full-time students are
more likely to be successful than part-time students. Again, these hypotheses are
based primarily on Tinto’s work in four-year settings; however these statements, lack
of clear empirical research and the aforementioned problems for African American
and Latino males, are the momentum for this dissertation.
Many researchers have attempted to utilize Tinto’s model and define
persistence
10
in the community college setting from the macro to the micro unit. For
example, Tinto defined persistence as college graduation, which is a challenge to
measure in the community college setting. Adelman (2006) defines persistence as
enrollment from one academic calendar year to the next, which can also be a
challenge as community college students often attend in non-sequential semesters.
While he did find high rates of persistence (approximately 90 percent utilizing
10
NELS: 88/2000
11
cohort data), he included enrollments in any post-secondary
institution, not just the initial entry point. Hagedorn (2005) defines persistence as
course completion, which is very applicable in the community college setting and is
appropriate for measuring success in adult populations (Spanard, 1990). Hagedorn
(2002, 2003, 2005) has used course completion in multiple studies of community
college students, despite a lack of national comparison. Examination at the course
level allows the determination of completed courses (or lack thereof) even though a
student may be retained within the institution or confined system, such as LACCD.
Based on the population and context being studied, my definition of persistence will
be course completion of remedial mathematics.
Tinto’s (1988) Student Departure theory provides one conceptual framework to
explain the interaction between remedial mathematics, course-taking and student
success; because it takes into consideration multiple factors related to student success
and has been tested in multiple settings, including community colleges (Grosset,
1997). Utilizing Tinto’s model, Webb (1989), found academic integration (first
semester GPA and courses passed) to have primary effects on persistence, and
background characteristics (ethnicity and sex) to have secondary effects on
persistence.
Tinto states that student departure for community college students appears to
be strongly influenced by academic difficulties, such as completing remediation,
especially for minority students (Tinto, 1993); which this dissertation hopes to
address. For the purpose of this study Tinto’s Student Departure theory will be
conceptualized in the following manner: background attributes will consist of age,
gender, and ethnicity; student academic experience will be examined through course-
taking patterns in remedial mathematics; and academic integration will comprise
11
grade point average (GPA). Finally persistence will be measured by course
completion rates in remedial mathematic courses. This conceptualization mirrors
similar works by researchers such as Pascarella, Wolniak, & Pierson (2003).
Student Age and Remedial Math Success
Does student age impact the success of first-time African American and Latino
male community college students in remedial mathematics? Student age
12
has been
one of the principal features used to distinguish between community college
populations and four-year institutions (Kim, 2002). Traditionally, age has been
measured in a dichotomous fashion as either: older/younger or
nontraditional/traditional, with the argument that the label nontraditional
13
holds
greater meaning as it incorporates other factors besides age. Some researchers use
24 years old
14
(Bean & Metzner, 1985) and others use 25 years old as the minimum
for classification as nontraditional (Kim, 2002). However Adelman (2005) argues
that nontraditional has become the norm as the majority of students’ exhibit at least
one of the characteristics that would qualify them as a nontraditional student, and
that the majority of community college students are in fact 18 to 24 years old
(traditional age).
Hagedorn (2005) grouped students into four categories: 17 to 21 “traditional”,
22 to 30 “young adults”, 31 to 45 “prime timers”, and 46 or older “last chancers”
based on her work with the Transfer and Retention of Urban Community College
Students Project (TRUCCS). Maxwell et al. (2001) utilized a five category
classification: less than 20 years old, 20 to 24 years old, 25 to 34 years old, and 35 to
44 years old and over 44 years old in examining students in the Los Angeles
Community College District (LACCD), acknowledging that the majority of students
are under 25 years old (50%), however there are significant numbers in the
12
remaining age groups. In fact, the under 25 year old group accounts for over 57%
of enrollments in remedial mathematics, followed by 27% for 25 to 34 year olds. As
this study utilizes the same population as discussed by both Hagedorn (2005) and
Maxwell et al. (2001), the terminology and classification of student age will be
defined as follows:
Under 20 years old, traditional
20 to 24 years old, traditional
25 to 34 years old, non- traditional
35+ years old, non-traditional
Many theorists
15
(Astin, 1984; Bean and Metzner, 1985; Tinto, 1998) have
utilized age in their analyses of traditional college students and their levels of
success. There are two distinct groups requiring remediation: recent high school
graduates and older, adult students. Researchers (Adelman, 2005; Ignash, 1997)
argue the importance of not mixing the two groups. This is due in part to differences
in their needs, as recent high school graduates may lack the preparation for college
level, and older students may just need a refresher on skills already learned, but not
put to use in years (Phipps, 1998; Waycaster, 2001).
Age is an important criterion to examine, as it has been shown to be the
strongest predictor of student success in mathematics (Penny & White, 1998).
However, what researchers can not agree on, is what age group performs better. For
example, Feldman (1993) found the attrition rate for 20-24 year old students to be
1.77 times higher than younger (19 and younger) students. Hagedorn (2005) found
on average older students are more frequently placed in lower levels of math, yet
their academic performance is comparable to their traditionally aged counterparts.
Other research has also demonstrated that nontraditional students perform as well as
or better than their younger counterparts (Bean and Metzner, 1985; Donohue and
13
Wong, 1997; Hammons & Mathews, 1999; Johnson, 1996; Leppel, 1984; Leppel,
2001; Umoh, Eddy, and Spaulding, 1994) and identify age as a significant predictor
of success in remedial math; citing the maturity of older students as playing an
important role. Three-fourths of the studies found a positive correlation between age
and success in remedial mathematic courses, with the largest correlation reported of
.32.
While the above studies provide a general understanding of age and remedial
mathematics success, studies examining age as it relates to the two sub-populations
in question within the community college system are minimal. The number of
African American males 25 years old and over has increased substantially (Spradley,
2001). Latinos are overrepresented in the older student population, and have been
found to have statistically significant higher grades (correlation of .15) and course
completion rates (correlation of .093) (Hagedorn, Maxwell, Chen, Cypers, & Moon,
2002). Hagedorn et al. (2001) incorporated persistence theory and examined the
impact of course load and GPA on student success of 202 African American males in
the community college setting and found age (younger students) and course load
(full-time status) to be positive and significant predictors of retention, with younger,
full-time students being more successful than older students. However, Penny and
White (1998) and Walker and Plata (2000) found a significant direct effect between
age and African American and Latino ethnicity and performance in developmental
mathematics. Both studies based on university populations found, older students
passed remedial courses at similar rates to younger students. While contradictory to
the Hagedorn et al. (2001) findings, these studies focused on remedial mathematics,
whereas the former did not.
14
Confusion over age and remedial mathematics success may stem in part
from studies conducted in four-year settings that do not generalize to community
college settings. However, based on the literature available and findings that older
students perform as well or better than traditionally aged students, I hypothesize that
older, nontraditional African American and Latino male students are more successful
in remedial mathematics than their traditionally aged counterparts.
Course Load and Remedial Math Success
Does course load impact the success of first-time African American and Latino
male community college students in remedial mathematics? Course load has many
similar definitions in the literature. Szafran (2001) defined course load in terms of
the number of credits and course difficulty. Adelman
16
(2005) further categorizes
course-taking based on the total number of course units earned in the community
college setting. Course load has also traditionally been dichotomized into either:
full-time or part-time
17
based on the number of units/credits a student enrolls in each
term/semester. Full-time students are those enrolled in 12 or more units, and part-
time is anything less than that. However, most students attend community college on
a part-time basis. According to Bryant (2001), approximately 64% of total
community college enrollments are part-time enrollments. Additionally, Latino
males are more likely to enroll part-time (Brown, Santiago, & Lopez, 2003; Fry,
2003). Therefore, for the purpose of this study, course load will be defined as the
following:
Course load is the total of enrolled units per semester as full (12+), three-
quarter (9.5-11.5), half (6-9) or less than half (1 – 5.5) based on the
financial aid guidelines in LACCD.
15
This will allow for a more thorough analysis of the impact of course-load, as part-
time enrollments can be analyzed for the student enrolled in one class versus those
enrolled in multiple classes.
In relation to African American and Latino males, again the literature is sparse.
Hagedorn et al. (2001) found course load to be a useful measure of academic
integration of African American community college males. When looking at general
populations, researchers have found course-load
18
to both positively and negatively
impact remedial mathematics course-taking patterns. Pascarella et al. (2003) found
course load to be a positive and significant factor for male community college
students. Full-time enrollment was found to be statistically significant for community
college remedial students (Amey & Long, 1998), important for community college
persistence rates (Schmid and Abel, 2000), and statistically significant especially in
mathematics gains for minority students (Hagedorn, Siadat, Nora, & Pascarella,
1997). However Grimes and David (1999) found no significant difference between
the two groups in the community college setting. The literature does not provide a
consistent picture of community college students and remedial mathematics in
relation to course load. This lack of clarity is due in part to sample sizes, populations
and settings (urban versus rural for example).
Again, it is important to note that course load has not been examined
thoroughly in the literature in regards to remedial mathematics and African
American and Latino males. However, I hypothesize that African American and
Latino male students enrolled less than full-time are more likely to be successful in
remedial mathematics than their peers enrolled full-time, based on the premise that
non-traditional students (age and/or course load) have been cited as being more
successful.
16
Early versus Delayed Enrollment in Remedial Math and Student Success
Does delayed entry into remedial math for first-time African American and
Latino male community college students negatively or positively impact their
educational success? Whether or not students should begin remediation immediately
upon entering the community college is largely debated. Remediation is intended to
adequately prepare students for college-level coursework; however due to the open
access nature of community colleges, students may enter or exit the institution
whenever they decide (Higbee et al., 2005), waive remedial courses, delay
enrollment or stop out
19
(Hadden, 2000). According to Tinto (1997) most students
take courses as detached, individual units. Thus, there is the real potential for
students to feel disconnected to the institution, thereby impacting student persistence
and success. Researchers argue that the longer a student waits to continue the
mathematics sequence, the worse his or her chances of success and persistence to the
next course become.
In order to reach community college-level mathematics courses, students must
successfully pass their remedial coursework. Some researchers (Adelman, 2005;
Weissman et al., 1997) have concluded that students should be required to remediate
immediately upon enrollment; however they should also be able to enroll in college-
level courses concurrently, so as to provide the student with an opportunity to make
progress towards his/her goal, improve self-confidence and decrease basic skills
deficiencies (Zeitlin & Markus, 1996). However researchers have noted that students
who struggle in mathematics have academic difficulties overall (Illich, Hagan, &
McCallister, 2004; Wheland et al., 2003) and the college mathematics experience
often negatively impacts first-term GPA (Hoyt, 1999) and impedes retention (Bailey
& Alfonso, 2005; Whiteley & Fenske, 1990). Early failures also lead to feelings of
17
inadequacy and frustration (Leppel, 2002); and remedial classes may stigmatize
students, which can be a profound issue for minority students (Moore et al, 2002;
Rowser, 1997).
McMillan (1997) found that students who were concurrently enrolled in
remedial and college level courses earned a higher average number of credits and
persisted longer than other groups, and thus were more successful except in the area
of GPA. This is further supported by Oudenhoven (2002), who found that students
enrolled solely in remedial courses were less likely to experience positive
achievement and persistence. One study by Weissman et al. (1997), examined
courses taken prior to enrolling in remedial courses, however due to the small sample
(N=12), the impact of the course prior to remediation was difficult to measure.
However, when expanding to include students enrolled in remedial courses only,
college level courses only and simultaneous enrollment in college and remedial
courses (N=236), they did find lower success rates for the last group at .68 in
comparison to .82 (remedial only) and .72 (college level only). As Adelman (2006)
noted, one or two studies do not allow for a definitive conclusion, however they do
provide the beginnings of a basis to build on.
While these studies provide general information regarding course-taking
patterns of community college students, and support for the idea of students enrolling
in both college level and remedial courses, they do not speak exclusively to
mathematics courses, gender or ethnicity and most importantly, they do not
adequately address the idea of delayed entry into remedial mathematics.
As previously stated, males are more apt to leave the higher education setting
due to academic difficulties, therefore if it is known that students who struggle in
mathematics also struggle with academic coursework; delaying remedial
18
mathematics may provide students with an opportunity to build success as a
college student in non mathematics related courses prior to attempting remedial
mathematics courses. As the connection between students academic performance and
integration is important to persistence and if academic integration during the first
year is an important factor in student persistence (Tinto, 1998) then it may be
advantageous for students to delay enrollment in remedial coursework. This area has
not been extensively examined in the literature, and based on what is currently
available, I hypothesize that delayed enrollment into remedial math is correlated
with increased persistence and success for first-time African American and Latino
male community college students.
Academic Performance in College Level Courses
How do students perform in terms of GPA and course completion rates in
community college-level mathematics after successfully completing corresponding
remedial mathematics courses? Student success in the community college setting is
hard to define due to the many reasons students attend (Bryant, 2001). Research
studies focused on mathematics achievement have examined factors such as
mathematics ability, persistence, anxiety, attitudes, backgrounds, and exposure to
mathematics (Hagedorn et al., 1997; Hagedorn, Siadat, Fogel, Nora, & Pascarella,
1999; Ma & Willms, 1999; Thompson, 2001). Other studies have examined GPA,
course completion rates
20
, and subsequent performance in college-level courses
(Hagedorn, 2005; Hoyt, 1999; Keller & Williams-Randall, 1999; Leppel, 2002;
McMillan, 1997; Pierson & Huba, 1997; Weissman et al., 1998). Course completion
as a measure of success is appropriate for the study of community college students as
it accommodates part-time enrollment (Hagedorn et al., 2002). While it is important
to note that GPA and course completion rates essentially measure similar and
19
overlapping features of course performance, these two measures are often used to
determine academic integration. Additionally, performance in college-level
mathematics courses is used as an indicator of the effectiveness of remedial
mathematics. Therefore, student success will be defined as:
Grade point average (GPA) average grades on a scale of 0 to 4.0 in
remedial and college level math courses.
Course success: courses completed with a grade of C or better or CR as
defined by the California Community College Chancellor’s Office.
Course completion ratio: the total number of mathematics units
completed with a successful grade of C or better divided by the total
mathematics units attempted (Hagedorn, 2005).
Many researchers have found a strong correlation between performance in
remedial coursework and success in later coursework (Boylan & Bonham, 1992;
Feldman & Johnson, 1996; Hauser, 1993; Jur, 1998; Penney & White, 1998; Sturtz
& McCarrol, 1993; Wheland, Konet, & Butler, 2003) with correlations as high as .65
reported. Differences were seen based on whether grades or success ratios were
utilized.
Moreno and Muller (1999) utilized grades rather than completion rates, based on
the rationale that grades provided a better indicator that a student was ready to
progress to the next level of math. Jur (1998) found that students who completed
remedial coursework had higher cumulative grade point averages, while Johnson
(1996) found the remedial course grade to be a powerful predictor of success in
entry-level college mathematics. Over half of the students who earned a grade of D,
F, or W in the remedial course withdrew from the college-level course, and 79%
were unsuccessful in their attempt to continue the sequence. The use of the course
20
grade as an indicator of success is further supported by the work of Halpin (1990)
and Pierson and Huba (1997).
Both completion rates and grade point average (GPA) are specific measures of
academic integration (Bean, 1986; Tinto, 1987), and as such will be used in the
analysis of this dissertation. Once again there is no clear consensus on a measure for
success in entry level mathematics coursework, especially as it relates to the
population in question for this dissertation. Grade performance tends to be more
important for male students, especially during the first year of college when most
academic dismissals take place (Tinto, 1975); however the impact of ethnicity is
unknown.
There is the possibility that students may be successful in regular community
college-level courses even without passing remedial classes (Feldman, 1993).
Success in community college-level mathematics classes does not always correlate to
performance in corresponding remedial mathematics course (O’Connor and
Morrison, 1997; Waycaster, 2001). In comparison, Umoh et al. (1994) found student
intent to persist more important than grades earned in remedial mathematics courses.
While the number of studies are small, it does provide another rationale for student
success in the area of remedial mathematics. Therefore, I hypothesize that success in
community college-level mathematics courses is not correlated with success in
remedial mathematics courses for African American and Latino male community
college students.
Summary
The focus thus far has been to examine the ways in which remedial
mathematics can lead to or impede student success and thus academic integration
into the community college setting. By challenging Tinto’s hypotheses and
21
examining the ways in which students with specific characteristics take courses
within this setting, the intent is to provide a coherent picture of the academic
experience of first-time African American and Latino male students in remedial
courses. The following hypotheses will guide this study:
1. Among first-time African American and Latino males, older students are
more likely to be successful in remedial mathematics courses than
younger students.
2. While enrolled in remedial mathematics courses, part-time course load is
correlated with increased success for African American and Latino males.
3. Delayed enrollment into remedial mathematics courses is correlated with
increased success for African American and Latino male community
college students.
4. Success in community college-level mathematics courses is not correlated
with success in remedial mathematics courses.
22
Chapter 2 Endnotes
8
The question of whether remediation in the community college setting enhances or delays
the progress for minority students has been debated at length (Cohen, 1990). Critics’ state
community colleges actually replicate existing social stratification by keeping students in
remedial coursework or vocational programs (Boylan & Bonham, 1994; Bryant, 2001;
Cohen, 1990; Dougherty, 1994; Hadden, 2000). This is of particular concern for minority
students (Moreno, 1998). Deil-Amen and Rosenbaum (2002) equate remedial education in
the community college setting with the cooling out phenomenon first described by Clark
(1960). In this process, remediation negatively affects students in one of two ways: 1)
students recognize their academic deficiencies and lower their aspirations of earning a
bachelor’s degree and settle instead for a two-year degree in vocational or applied programs
or 2) students experience delayed progress towards their goal due to the reduced number of
degree applicable credits earned (Clark). In comparison, functionalist advocates argue that
remediation in the community college setting democratizes college access by affording
increased opportunities for students who would otherwise not have the chance to pursue a
higher education as it: 1) provides students with an opportunity to correct deficiencies from
the high school setting, and 2) provides a chance for returning students to improve skills that
may not be used on a daily basis (Dougherty, 1994).
9
Attempts to explain the same process in the community college setting and for ethnic
minorities have been mixed. Tinto’s theory is widely used throughout academic research;
however it has several shortcomings when looking at the community college setting. The
theory is based primarily on white, traditional aged students in four year postsecondary
settings, whereas community college students tend to be older, attend part-time, and come
from minority backgrounds (Hoyt, 1999). Despite these challenges, researchers continue to
use Tinto’s model as a theoretical background in community college research, albeit with
conflicting results.
10
Persistence is often defined as a student characteristic, whereas retention is defined as an
institutional measure.
11
NELS:88/2000 is the most recently completed national grade-cohort longitudinal study
conducted by the National Center for Education Statistics. This study began with a national
sample of eight-graders in 1988, which were scheduled to graduate from high school in
1992. These students were followed through December 2000, including interviews, high
school and college transcripts (Adelman, 2006).
12
Age is an important factor to study as according to Adelman (1999), the size of traditional-
age high school graduating classes will grow by half a million students over the next decade.
Furthermore, 10 percent of those students will delay enrollment into post-secondary
institutions. Between 1994 and 1996 the median age of community college students
23
decreased from 26 years old to 25 years old, due in part to the increasing number of
traditional age students seeking enrollment in post-secondary institutions. He states that it is
harder to estimate the growth in the older student (over 24 years old) population, but predicts
their numbers will remain steady. Finally, in order to best understand the enrollment trends
of community college students, one must look at among many variables, credit loads and
participation in remedial courses.
13
Characteristics of nontraditional students include older age, delayed enrollment, part-time
status, full-time work, financial independence, dependents other than a spose, sinlge
parenthood, and lack of a standard high school diploma (Adelman, 2005).
14
At 24 years of age, student is considered independent under federal student financial aid
regulations.
15 Chickering’s student development theory identifies,” the competing demands on
community college students’ time” (Higbee, Arendale, & Lundell, 2005, p. 6) as a factor.
Additionally, one of the postulates of Astin’s (1984) Student Involvement theory states “the
time and energy that the student invests in family, friends, job, and other outside activities
represent a reduction in time and energy the student has to devote to educational
development (p.301).” Bean and Metzner’s theory of nontraditional student departure states
that the external environment is more important than social integration in explaining the
success of nontraditional students.
16
Adelman (2005) refers to the community college as a town, and characterizes community
college students as belonging to one of three groups: homeowners, tenants and visitors. Each
group earns differing levels of units within the community college setting and thus has
differing levels of success when one measures transfer rates and terminal degrees earned.
Homeowners earn more than 30 credits at the community college level or 60 percent or more
of all credits from a community college. Tenants earn less than 60 percent of their credits
from the community college. Finally, visitors earn from 1-29 credits from community
colleges. Based on national data sets, Adelman determined that each group displays varying
levels of success.
17
Often students, who attend college on a part-time status, hold jobs either on-campus or off
campus. Several studies found that working off-campus had positive and significant effect
on mathematics gains for minority students (Hagedorn, Siadat, Nora, and Pascarella, 1997;
Thompson, 2001). Whereas others contend that persistence suffers for those who work off-
campus (Astin, 1984; Leppel, 2002).
24
18 The manner in which students take courses in the community college setting can be
shaped by their high school experience. According to Adelman (2005), 44 percent of
traditional aged-students in community colleges never reached Algebra 2 in high school.
Almost one-fifth of traditional-aged community college aged students do not complete 10
credits, partly due to academic problems (Lumina) Davenport et al. (1998) found that
African American high school students aspire to enroll in college; however they do not take
coursework in high school consistent with those plans. The study found that overall high
school males participated in higher levels of math than females, however, most Asian and
White students went beyond geometry whereas African American and Latino students
tended to take more courses in basic skills, general mathematics and pre-algebra (which are
all considered lower level). As one transitions over to the community college setting, these
course taking patterns replicate themselves.
19
Stopping out is the length of time allowed to pass between successive enrollments in the
mathematics sequence (Johnson). There is a paucity of information in the literature regarding
the effects of stopping out of remediation and academic success (Johnson, 1996). It is not
entirely clear how this behavior affects student success.
20
The Transfer and Retention of Urban Community College Students (TRUCCS) and the
Research and Planning Group for California support use of course completion rate. Course
completion ratio is the proportion or percentage of courses that a student completes as
compared to the number of courses in which the student enrolls (Hagedorn, 2005).
25
Chapter 3
Methods
Methodology
This quantitative study investigated the course-taking patterns in remedial
mathematics and the success of first-time African American and Latino male
community college students by utilizing data from the Los Angeles Community
College District (LACCD)
21
. This data set contained all student demographic,
enrollment and transcript data of students enrolled in any of the nine colleges within
the district from 1991 to the present.
Sample
This study utilized enrollment and transcript data for two cohorts of male
remedial mathematics students in LACCD who were first time college students
beginning Fall 2000 or Fall 2001. The sample population was drawn from the larger
data set maintained by LACCD. The dataset also contained complete transcript files
for each student including personal information such as ethnicity, gender, and age.
The students were isolated by using the variable mathlevl, which identified students
who had enrolled in at least one remedial mathematics course beginning in either
Fall 2000 or Fall 2001. Once the initial cohort was identified, those students meeting
the parameters of the study based on age and gender were isolated. This resulted in a
cohort of 3382 students, which included all males of various ethnic backgrounds.
Table 1 presents the distribution of male students in the sample with respect to
ethnicity and enrollment in a remedial mathematics course. As can be seen from
Table 1 Latino males are the largest subpopulation representing over 55% of the
population. African American males are the second largest subpopulation at 16%.
26
Table 1: Population of first-time LACCD male students in remedial mathematics by
ethnicity for Fall 2000 and Fall 2001 cohort (N=3382)*
Ethnic Group N Percentage ________
Asian 183 5.4%
African American 563 16.6%
Filipino 125 3.7%
Latino 1862 55.1%
Caucasian 461 13.6%
Native American 19 0.6%
Pacific Islander 19 0.6%
Other Non-Caucasian 44 1.3%
Decline to State 94 2.8%
Total 3370 99.6% __________________________
*Missing 12 0.4%
After controlling for African American and Latino ethnicity only, the sample was
reduced to 2425 students. These 2425 students were then followed over the
subsequent 8 semesters, including winter and summer terms for a total of 2 years. No
non-remedial mathematics students (those in courses not identified as remedial by
LACCD) were included in this study.
Data Collection
No additional data collection was completed for this study. Demographic data
was collected from the application for admission that all students completed to enroll
within the district; transcript data, course enrollments and grades were generated by
LACCD through the Student Information System (SIS) and then transferred to an
SPSS database. While transcript data was available for students dating back to 1991,
this study limited the population to first-time male African American and Latino
students beginning in either Fall 2000 (cohort one) or Fall 2001 (cohort 2).
Research Design and Definitions
This study analyzed four distinct hypotheses covering the four questions
previously outlined. Prior to answering any of the questions, several variables needed
27
to be created. The variable rem_code represents the four remedial mathematics
offered at all nine colleges within the district that were examined in this study. The
college catalogs for each of the nine campuses were accessed online. Four of the nine
colleges included a visual chart depicting the math sequence; however each chart
differed in relating which courses were remedial, the amount of overall information,
and the visual depiction of the complete mathematics sequence. Figures 1 through 4
provide examples of the community college mathematics sequence found in the most
recent LACCD general college catalogs.
Figure 1: Mathematics Course Sequence from the 2005-2006 Los Angeles
Mission College General Catalog
28
Figure 2: Mathematics Course Sequence from Los Angeles Harbor College
2004-2006 General Catalog.
29
Figure 3: Mathematics Course Sequence from the 2005-2006 Los Angeles
Southwest College General Catalog.
30
Figure 4: Mathematics Course Sequence from the 2005 -2006 Los Angeles
Valley College General Catalog.
31
Based on the analysis of courses offered at all nine colleges, the remedial
mathematics courses under examination in this study included: Math 105, Math 112,
Math 115, and Math 125. While there are many remedial mathematics courses
offered in LACCD, only these four courses are offered at all nine colleges within the
district
22
. These courses were then coded to represent the corresponding level below
community college level as follows: Math 105 = 3 levels below, Math 112 = 2 levels
below, Math 115 =1 level below, and Math 125 = community college level
23
. Table
2 represents the number of enrollments in each level of remedial mathematics
identified above by ethnic group. As noted in the table, the 7148 total includes
multiple attempts at the same course.
Table 2: Number of enrollments* by ethnicity and level of all remedial
mathematics courses taken by LACCD male remedial math students in Fall 2000 and
Fall 2001 cohort (N=7148)
Level of Math Courses
Math Math Math Math
Ethnic Group 105 112 115 125 n
Asian 104 79 183 265 631
African American 312 251 283 103 949
Filipino 53 72 106 85 316
Latino 1038 824 1155 591 3608
Caucasian 210 251 433 322 1216
Native American 11 8 8 5 32
Pacific Islander 8 11 4 12 35
Other Non-Caucasian 22 22 34 46 124
Decline to State 50 44 86 57 237
Total 1808 1562 2292 1486 7148
*Includes multiple attempts at the same course.
The first three sets of analyses will utilize the following sample: first time
African American and Latino male community college students initially enrolled in a
remedial mathematics class (either Math 105 or Math 112). Math 115 was not
included as it currently meets the current LACCD requirements for the Associate of
32
Arts degree. Table 3 represents the number of attempts by ethnicity in the
remedial mathematics courses under investigation. Again, for the first three analyses
this only includes Math 105 and Math 112.
Table 3: Number of attempts in Math 105 and Math 112 remedial mathematics
courses taken by LACCD male students for the Fall 2000 and Fall 2001 cohorts
(N=3382)*
Number of Attempts in Remedial Math Courses
Ethnic Group 1 2 3 4 5 6 Total__________
Asian 92 44 35 8 4 183
African American 297 128 97 35 6 563
Filipino 67 31 20 4 3 125
Latino 858 458 337 150 49 10 1862
Caucasian 242 119 83 10 5 2 461
Native American 13 6 19
Pacific Islander 10 8 1 17
Other Non-Caucasian 18 12 13 1 44
Decline to State 54 20 8 5 6 1 94
Total 1651 826 594 213 73 13 3370
*Missing 12 responses.
The first set of analysis examined the question: Does student age impact the
success of first-time African American and Latino male community college students
in remedial mathematics? The independent variable is age and was gathered from the
variable age contained in the LACCD database. This variable reported the raw age of
the student in Fall 2000 or Fall 2001. The raw age was then converted to the variable
age_g which placed the participants into one of four age groups for comparison:
under 20 years old, 20-24 years old, 25-34 years old and 35 + years old
24
. The first
two groups represent the traditional student population, while the last two groups
represent the non-traditional student population. Table 4 demonstrates the age
distribution of males enrolled in the remedial mathematics courses under
investigation.
33
Table 4: Age Distribution of LACCD male remedial mathematics students within
cohorts Fall 2000 and Fall 2001 (N=3382)*
Age Group
Ethnic Under 20 20-24 25-34 35+
Group years old years old years old years old n
Asian 1.3% 2.0% 1.1% 1.0% 183
African American 6.8% 3.8% 2.7% 3.4% 563
Filipino 2.0% 0.5% 0.8% 0.4% 125
Latino 27.2% 16.0% 8.5% 3.5% 1862
Caucasian 5.0% 2.7% 2.1% 3.9% 461
Native American 0.1% 0.1% 0.1% 0.3% 19
Pacific Islander 0.2% 0.2% 0.1% 0.1% 19
Other Non-Caucasian 0.6% 0.4% 0.1% 0.1% 44
Decline to State 1.0% 0.8% 0.5% 0.4% 94
Total 44.2% 26.5% 16% 13.2% 3370
*Missing twelve responses.
The dependent variable of student success was measured by GPA and course
completion rates in remedial mathematics classes. This information was gathered
from the transcript data entered into the original LACCD database. GPA was
measured in two ways: 1)cumulative overall GPA, all grades earned in all courses
over the time period of the study and 2) math GPA, all grades for all mathematics
courses (remedial and/or community college-level) over the period of the study.
Cumulative overall GPA was coded as gpa and math GPA was coded as mathgpa.
In order to calculate the course completion ratio in remedial mathematics, a new
variable sucr_rm was created. This calculation was made by dividing the number of
remedial mathematics courses passed by the number of remedial mathematics
courses attempted
25
. The age groups were cross tabulated with the cumulative GPA
and the math GPA. Statistical test included the correlation test.
34
The second set of analyses examined the question: Does course load impact
the success of first-time African American and Latino male community college
students in remedial mathematics? The independent variable is course load (full-
time, three –quarter time, half-time or less than half time). Course load is the sum of
all units attempted and completed based on the transcript data entered into the
LACCD database beginning Fall 2000 or Fall 2001 and followed for 8 semesters,
including winter and summer terms, for a total of two years. This information was
gathered from the transcript data entered into the LACCD database. Units attempted
within the semester were grouped into four groups (less than half-time = 1 to 5.5
units, half-time = 6 to 9 units, three-quarter time= 9.5 to 11.5 units, full-time = 12+
units). The raw total of the units were coded as the variable ua_group into the four
groups mentioned above. The dependent variable of student success was measured
by GPA and course completion rates and spanned the time frame indicated above.
GPA was measured in two ways: 1)cumulative GPA, all grades earned in all courses
over the time period of the study and 2) math GPA, all grades for all mathematics
courses (remedial and/or college-level) over the period of the study. GPA and course
completion rates were reported as means. Correlation was the statistical test used.
The third set of analyses examined the question: Does delayed entry into
remedial math for African American and Latino male community college students
negatively or positively impact their educational success? The independent variable
is the time of entry into remedial mathematics class. For each cohort the first
semester, either Fall 2001 or Fall 2002, was considered semester one. A dichotomous
variable rem_firs was created based on whether the student enrolled in Math 105 or
Math 112 in the first semester (either Fall 2000 or Fall 2001). This created two
groups, those who began remediation in the first semester and those who did not.
35
The variable rem_firs was cross-tabulated with the three previously identified
dependent variables of student success: overall GPA, mathematics GPA and course
completion ratio. Mean comparison was utilized to determine if any statistical
significance or relationships existed.
The fourth set of analyses examined the question: How do students perform
(GPA, course completion) in community college-level mathematics after
successfully completing corresponding remedial math courses? The methodology
and analysis differed for this question. This question examined success in the
community college mathematics course of Math 125 (dependent variable), based on
the point of entry into the remedial mathematics sequence (independent variable). In
other words, what is the correlation between the performance in the first remedial
mathematics course and subsequent performance in the community college level
course Math 125?
The point of entry was identified as the first remedial mathematics course
attempt at Math 105, Math 112 or Math 115. Therefore, three different sample sizes
are reported. The student did not need to take the remedial mathematics course in
their first semester of enrollment, but rather the remedial mathematics course needed
to be the first mathematics course attempted. For Math 105, all first-time African
American and Latino males who began with this course as their first math course in
any of the 8 semesters under review were utilized. This resulted in a population of
1350. For Math 112, all first time African American and Latino males who began
with this course as their first course in any of the 8 semesters under review yielded a
population of 1072. Finally, for Math 115, all first time African American and Latino
males who began with this course as their first course in any of the 8 semesters
yielded a population of 1438. The total sample population for this analysis is 3860.
36
This number is larger than the sample used in the three previous analyses, as it
included those students who enrolled in Math 115, a population which was excluded
in the previous analyses.
Another variation for this analysis was the exclusion of students who attempted
the initial remedial mathematics more than once. Table 5 illustrates the number of
students excluded at each level of remedial mathematics due to multiple attempts
within that course. For both African American and Latino males the number of
students excluded due to multiple attempts is approximately 11% of the total sample
population.
Table 5: Male students excluded due to multiple attempts in a remedial mathematics
course (N=3860)
Level of Remedial Math
Math 105 Math 112 Math 115 n
Group
African American (n=862) 28 33 32 93
Latino (n=3014) 118 107 120 345
The remedial mathematics course grade is the independent variable. Remedial
mathematics courses completed with a letter grade of A, B, C, P or CR were coded
as “success”. Remedial mathematics course completed with a letter grade of D, F, or
NC were coded as “non-success”. It is important to note that this differs from the
LACCD pass/fail policy. A grade of D is considered “passing”, however this study
focuses on the concept of “success” as previously discussed in the literature review.
Performance in Math 125 is the dependent variable. The same process outlined
above for coding success and non-success in the remedial course was utilized for
coding success and non-success in Math 125. In addition to the outcomes of success
and non-success, an additional measure was included to capture students who
completed the lower level remedial mathematics course, but did not attempt the
37
community college level course (Math 125).This was labeled as “did not attempt”.
Performance in each of the three remedial mathematics courses (Math 105, Math
112, or Math 115) was individually cross-tabulated with performance in Math 125.
Statistical tests included cross-tabulation and results were reported as percentages.
Limitations
1. Survey data examining other academic and social integration factors were not
available.
2. Modest bias in only utilizing students beginning in the fall term.
3. Assessment scores for placement levels were not available to adequately assess
if students enrolled in the correct level of remedial mathematics.
4. All levels of remediation were not offered at each campus, therefore some
students were excluded
26
.
5. Based on correlations and longitudinal data, the study infers causal
relationships. However, the evidence for causality is limited given the design
of the study with self-selection (non-random assignment) into comparison
groups.
Measures
Student success was measured using multiple measures including GPA and
course completion rates over the course of eight semesters beginning with Fall 2000
or Fall 2001. GPA consists of all letter grades earned by the student in all classes
(total GPA) and the GPA earned solely in remedial math courses (math GPA). The
only exception is the final analysis which examined performance in the community
college-level mathematics courses. The formula for course completion ratio is the
number of remedial mathematics courses completed with a successful grade of A, B,
C, CR, or P divided by the total number of remedial mathematics courses attempted.
38
Chapter 3 Endnotes
21
The Los Angeles Community College District (LACCD) is located in urban Los Angeles,
covering more than 882 square miles. Over 110,000 students from varying age groups,
ethnic, racial, and socioeconomic backgrounds enroll within LACCD per year (Los Angeles
Community College District, 2006).
22
Math levels for LACCD utilized in this study and description:
Math 105 (NDA)* Arithmetic – 3 units
Prerequisite: None
Lecture, 3 hours.
Reviews the fundamentals of arithmetic that are essential to continuing in any field.
Math 112 (NDA)* Prealgebra - 3 units
Prerequisite: None
Recommended: A grade of C or better in Mathematics 105, or appropriate skill level
demonstrated through the math placement process.
Lecture, 3 hours.
Review of Arithmetic and introduction to basic algebraic concepts.
Math 115** Elementary Algebra – 5 units
Prerequisite: None
Recommended: A grade of C or better in Mathematics 112, or appropriate skill level
demonstrated through the math placement process.
Lecture, 5 hours.
Integers, rational numbers and fundamental operations thereon; positive integer exponents,
order of operations, fundamental operations on polynomials and algebraic fractions,
polynomial factoring, square root radicals, linear and quadratic equations, graphing of two
variable equations, solving two variable linear systems, and algebraic solutions of a variety
of verbal problems.
Math 125** Intermediate Algebra - 5 units
Prerequisite: A grade of C or better in both Mathematics 113 and 114, or a grade of C or
better in Mathematics 115, or appropriate skill level demonstrated through the math
placement process.
Lecture, 5 hours.
Sets, field and order properties of the real numbers, fundamental operations on polynomials
and algebraic fractions, radicals, rational exponents, complex numbers, linear, quadratic, and
rational equations and inequalities, functions and graphs, linear systems in two and three
variables, matrix methods, second degree systems, sequences and series, introduction to
exponential and logarithmic functions.
* Non Degree Applicable
** Associate of Arts applicable, non-transferable
*** Associate of Arts applicable, transferable
39
23
Students are placed into the corresponding level of remedial mathematics upon completion
of the assessment test offered at each college at the time of enrollment. The sequence from
the lowest level of remedial math to the community college level is as follows:
Math 105 to Math 112 to Math 115 to Math 125.
Because students can place at any point in the remedial mathematics continuum, the
number of students enrolled in each course (or level) can vary. Furthermore, while controls
are in place to prevent students from enrolling in mathematics courses they have not placed
into, students may have circumvented the system. Lastly, this sequence outlined above is not
always sequential, as students may attempt one level within a semester, and enroll in a lower
level course in a subsequent semester.
25
In order to calculate the course completion rates for remedial mathematics courses, I first
had to account for each attempt in any of the four remedial courses (Math 105, Math 112,
Math 115, Math 125) taken over the eight semesters under investigation. Individual attempts
were calculated for each course and a variable created to reflect the number of attempts as:
math105, math112, math115, math125. Success for each course was defined as a grade of A,
B, C, CR, or P. Students receiving one of these grades was coded as success with the
following dichotomous variable: m105p, m112p, m115p, m125p. The sum of the attempts
was labeled as remmatt and the sum of the successes was labeled as rem_p. Once the sum of
the attempts and successes were calculated, the course completion rate could be found by
dividing rem_p by remmatt. This resulted in the creation of the variable sucr_rm. The range
for sucr_rm is from 0.00 to 1.00.
26
Each level of remedial math was not offered at all college campuses within the district.
The following courses were excluded in the analysis. Colleges that offered the course are
listed in parentheses:
Math 100: Mathematics Workshop, 1 unit, NDC. (City, Harbor, Mission, West)
Math 101: World of Numbers, 3 units, NDA. (Trade).
Math 102: Developmental Mathematics, 6 units, NDA. (East).
Math 104: Mathematics Fundamentals, 3 units, NDA. (Southwest).
Math 110: Introduction to Algebraic Concepts, 5 units, NDA: (Pierce).
Math 113 and Math 114: Elementary Algebra A and Elementary Algebra B, 3 units each.
These courses are the equivalent of Mathematics 115 and allow the student to complete
Elementary Algebra over two semesters, rather than one. (City, Harbor, Mission, Trade,
Valley)
Math 116: Algebra Review, 3 units. (Pierce).
Math 117 and Math 118: Elementary Algebra I and II, 5 units each. These courses are the
equivalent of the first year of high school algebra. (West).
Math 119: Introduction to Mathematical Methods, 5 units, AA applicable, but does not meet
perquisites for higher level math courses. (Pierce).
Math 120: Plane Geometry, 5 units. (East, Harbor, Mission, Pierce, Trade, West, Valley).
Math 121: Essentials of Plane Geometry, 3 units. (City, Mission, Trade).
40
Math 123: Elementary and Intermediate Algebra, 12 units. This course is offered in three
modules Math 122A, B, and C. (Harbor).
Math 124: Intermediate Algebra, 5 units. This course is offered in two modules, Math 124A
and Math 124B. (City).
41
Chapter 4
Results and Findings
The first set of analyses examined age and student success. The independent
variable under examination in this section was student age and its relation to the
dependent variable student success (GPA and course completion rates in remedial
math) and addressed the following hypothesis:
Among first-time African American and Latino males, older students are
more likely to be successful in remedial mathematics courses than younger
students.
The sample was reduced to all male, first time community college students initially
enrolled in a remedial mathematics class (either Math 105 or Math 112). Math 115
was not included as it meets the current LACCD requirements for the Associate of
Arts degree. The ethnic groups included were 1) African American males and 2)
Latino males
27
. Furthermore, students were grouped based on age into the
following categories. 1) under 20 years old 2) 20-24 years old, 3) 25-34 years old,
and 4) 35+ years old
28
.
As can be seen in Table 6, African American males and Latino males in the
younger age groups (under 20 and 20-24 years old) had lower mean GPA’s in
comparison to their older (25-34 years old and 35+) peers. African American males
had the lowest mean GPA across all age groups in comparison to Latino males. In
both ethnic groups, the biggest difference in performance was seen between the two
older age groups. The correlation between age and GPA was significant and positive
in both populations; African American males (r = .386, p< 0.01) and Latino males
(r = .214, p <0.01), accounting for 15% of the variance in the African American
population and only 5% in the Latino population.
42
Table 6: Correlation of Mean Grade Point Average (GPA) of Males in Remedial
Mathematics by Age Group (N=2425)
Group Mean GPA n SD
African American (N=563)
Under 20 years old 1.51 229 .865
20-24 years old 1.49 129 .954
25-34 years old 2.13 90 1.13
35+ years old 2.44 115 .77
r = .386*
Latino (N=1862)
Under 20 years old 1.71 915 .866
20-24 years old 1.80 540 .966
25-34 years old 2.24 288 1.07
35+ years old 2.44 119 1.04
r = .214*
* p< 0.01
Table 7 examines student age and success rates in remedial math. Again, the
relationship between age and success rates correspond to the hypothesis: non-
traditional age groups have higher course success rates in remedial math courses.
African American and Latino males in the under 20 year old age group fared worse,
with success rates at .4268 and .4742 respectively than their peers in the 35+ years
old age group (.6864 and .7231) respectively. Additionally, African American males
fared worse in all age groups, except the 24-34 year old group (.6741) in comparison
to their Latino male peers. For both African American and Latino males, the 35+
year old age group had the highest success rates, with Latino males performing
slightly better (.7231) than African American males (.6864). Once again, age proved
to be a correlated with the success rates of both groups, with a stronger correlation
for African American males (r = .267, p<.01) than Latino males (r = .169, p< .01).
43
Age explained a combined 10% of the variance; at 7% for African American and
3% for Latino males.
Table 7: Correlation of Success Ratio of Male Community College Students in
Remedial Mathematics by Age Group (N=2425)
Group Mean Success Ratio n SD ________
African American (N=563)
Under 20 years old .4268 229 .4364
20-24 years old .4364 129 .4418
24-34 years old .6741 90 .4363
35+ years old .6864 115 .3993
r = .267*
Latino (N=1862)
Under 20 years old .4742 915 .4111
20-24 years old .5384 540 .4393
24-34 years old .6670 288 .4180
35+ .7231 119 .39078
r = .169*
* p< 0.01
The second set of analyses examined course load and student success and
addressed the following hypothesis:
While enrolled in remedial mathematics courses, part-time course load is
correlated with increased success for African American and Latino males.
The independent variable under examination in this section was course load and its
impact on the dependent variable student success. With a few exceptions, the pattern
of relations between course load and course success for African American and
Latino males disconfirms the hypothesis: course success rate tended to be higher for
those students with higher, and more traditional, course loads. As can be seen in
Table 8, African American males and Latino males enrolled in 9.5 to 11.5 units
(three-quarter status) had the highest success rates at .6278 and .6147 respectively.
44
Across groups the lowest success rate was found for students enrolled in the least
amount of units. The correlation between units attempted and success in remedial
mathematics was small and little different for African American males (r =.095,
p<.01) than for Latino males (r = .071, p<.01).

Table 8: Correlation of Success Ratio of Male Community College Students in
Remedial Mathematics by Units Attempted (N=2071)
Group Mean Success Ratio n SD
African American (N=485)
a
1 to 5.5 units .4753 141 .4516
6 to 9 units .5317 183 .4396
9.5 to 11.5 units .6278 33 .4214
12 or more units .5815 128 .4404
Total .5350 485
a
.4433
r = .095*
Latino (N=1586)
b
1 to 5.5 units .5300 528 .4368
6 to 9 units .5388 726 .4216
9.5 to 11.5 units .6147 91 .3995
12 or more units .6019 241 .3951
Total .5498 1586
b
.4223
r = .071*
a. 78 missing cases
b. 276 missing cases
* p< 0.01
Lastly, mean GPA was examined in relation to units attempted. As can be seen
in Table 9, the relationship between units attempted and GPA is consistently the
opposite of the pattern asserted in the hypothesis. The means in this table indicate
that the students with the higher, and more traditional, course loads had the higher
grade point averages. African American males who attempted the least amount of
units had the lowest GPA (1.59). In comparison, Latino males enrolled in 12 or more
units (full-time) had the highest GPA (2.14). The correlation between units attempted
45
and GPA was slightly larger for African American males (r = .177, p<.01) than
Latino males (r= .153, p <.01). The greatest deviation in GPA was seen in the two
younger age groups for both African American and Latino males. Based on these
findings, my hypothesis about course load is disconfirmed: full-time students were
found to have higher GPA’s and course success rates.
Table 9: Correlation of Mean GPA of Male Community College Students in
Remedial Mathematics by Units Attempted (N=2071)
Group Mean GPA Total SD___________
African American (N=374)
1 to 5.5 units 1.59 141 1.01
6 to 9 units 1.80 183 1.04
9.5 to 11.5 units 1.85 33 .8860
12 or more units 2.07 128 .8823
Total 1.81 485
a
.9940
p = .177*
Latino (N=1586)
1 to 5.5 units 1.80 528 1.06
6 to 9 units 1.89 726 .9035
9.5 to 11.5 units 2.02 91 .7041
12 or more units 2.14 241 .8088
Total 1.91 1586
b
.9427
r = .153*
a. 78 missing cases
b. 276 missing cases
* p<0.01
The third set of analyses explored the relationship between early/delayed entry
into remedial math and student success through the following hypothesis:
Delayed enrollment into remedial math is correlated with increased
persistence and success for African American and Latino male community
college students.
46
Table 10 demonstrates that 51.4% of all African American and Latino male
students delayed entry into remedial math in the study
29
.
Table 10: Percentage of Male students who enrolled in remedial mathematics in their
first term versus those who did not (N= 2425)
Group Enrolled Delayed
First Term Enrollment n
African American 265 (47.1%) 298(52.9%) 563
Latino 934(50.2%) 928(49.8%) 1862
Total 1199(48.7%) 1226(51.4%) 2425
Table11andTable12outlinethesemesterinwhichtheFall2000andFall
2001cohortofstudentstooktheirfirstremedialclass(anylevel),demonstrating
enrollmentpatterns.Bothtablesextendpasttheoriginal8semestersor2yearsused
forallotheranalysesandfollowsstudentsforfiveyears.Forthe2000cohort,43%
ofAfricanAmericanmalesand47%ofLatinomalesbegantheircollegecareersin
thefirstsemesterwitharemedialmathclass.Approximately17%inbothstudent
populationsenrolledintheirfirstmathematicscoursethefollowingspringsemester.
Withinthefirstyearthenumberofstudentsenrolledinaremedialmathincreasedto
65%forAfricanAmericanand70%forLatinomales.Thelargestenrollmentsare
seeninFallandspringsemesters,withsmallernumbersseeninWinterandSummer
semesters.WhiletheoverallnumberofstudentsintheFall2001cohortaresmaller,
thepercentageofstudentsenrollinginaremedialmathematicscourseinthefirst
semesterandwithinthefirstyearwerelargerthanthoseseenintheFall2000cohort.
Fifty-threepercentofAfricanAmericanmalesand55%ofLatinomalesbegantheir
collegecareerinaremedialmathematicscourse.Withinthefirstyear75%of
47
African American males and 78% of Latino males enrolled in a remedial
mathematics course.
Table 11: Semester in which male students enrolled in their first remedial
mathematics by term cohort Fall 2000 (N= 1473)
Semester
Group Fall Winter Spring Summer_
African American (n=331)
2000 142
2001 38 9 53 11
2002 14 2 36 6
2003 1 8 4
2004 4 1 2
Latino (n=1142)
2000 541
2001 110 4 194 64
2002 44 10 66 13
2003 28 3 30 6
2004 2 22 5
Table 12: Semester in which male students enrolled in their first remedial
mathematics course by term for Fall 2001 cohort (N= 952)
Semester
Group Fall Winter Spring Summer_
African American (n=232)
2001 123
2002 21 6 42 5
2003 10 1 10 ---
2004 3 1 4 ---
2005 6
Latino (n=720)
2001 393
2002 43 18 123 30
2003 25 5 27 8
2004 6 --- 22 9
2005 1 6 4
48
As can be seen in Table 13, African American and Latino male students who
delayed entry into remedial mathematics averaged higher overall GPA’s than their
peers that began their college career in remedial mathematics. The difference in
GPA’s for those who delayed entry was found to be statistically significant. African
American males who delayed remedial math earned an average GPA of 1.88 in
comparison to 1.70 for those who began taking remedial mathematics courses in
their first term [ F= 4.46, p=.035] Latino males who delayed remedial mathematics
earned an average GPA of 1.96 in comparison to 1.75 for those who began
remediation immediately upon enrolling [F=23.284, p=.000]. In comparison, for
both ethnic groups the grades in the remedial mathematics courses were essentially
the same, as grade point averages equaled approximately 1.3, regardless of the time
of entry into the first of these courses.
Table 13: Average GPA overall and in math courses only of male students who
enrolled in remedial mathematics in their first term versus those who did not
(N= 2425)
Average Average Total
Overall Math
Group GPA GPA
African American (n=563)
Remedial Math 1
st
term 1.70 1.34 265
Delayed Remedial Math 1.88 1.36 298
Latino (n=1862)
Remedial Math 1
st
term 1.75 1.30 934
Delayed Remedial Math 1.97 1.33 928
Successful completion of mathematics courses (success rate) followed the
same pattern. Table 14 illustrates that African American and Latino male students
who delayed enrolling in remedial mathematics had higher success rates than their
peers who began with a remedial math course in their first term. Latino males who
49
delayed entry into remedial math had higher success rates than their African
American male peers. African American males who delayed remedial mathematics
had success rates of .5237 versus .5191 for those who enrolled in a remedial
mathematics course in their first term. While, Latino males who began in remedial
mathematics courses in
the first term had slightly lower success rates than African American males at .5025,
Latino males who delayed remedial mathematics demonstrated success rates at
.5749. Delayed enrollment and its impact on success rates was found to be
statistically significant for Latino males [F=13.487, p=.000], but not for African
American males [F= .015, p=.903]. African American and Latino males who delay
remedial mathematics experience higher overall GPAs, math GPAs, and success
rates. It is important to note however, that the difference in math GPAs is minimal
and statistically insignificant. For African American males [F=.088, p=.767] and
Latino males [F=.211, p=.646].
Table 14: Success Rate in remedial mathematics of male students who enrolled in
remedial mathematics in their first term versus those who did not (N= 2425)
Group Average Success Rate n ________
African American (N=563)
Remedial Math 1
st
term .5191 265
Delayed Remedial Math .5237 298
Latino (N=1860)
Remedial Math 1
st
term .5025 934
Delayed Remedial Math .5749 928
The final analysis investigated student success in community college level
mathematics after completion of remedial mathematic courses and addressed the
following hypothesis:
50
Success in community college-level mathematics courses is not
correlated with success in remedial mathematics courses.
Table 15 demonstrates of the 312 African American males who completed
Math 105 as their first course (successfully or non-successfully), 291 or 93% did not
attempt Math 125. Of those students who “Did not attempt Math 125” (first column),
those who were not successful were less likely to attempt Math 125 in both student
groups. Moving to the second column “Non Success in Math 125”, the percentage of
African American males who were not successful in Math 125 was no more than
0.5%. Interestingly, 2% of students who were not successful in Math 105
demonstrated “Success in Math 125” (third column). However, African American
males who were successful in Math 105 demonstrated a greater percentage of
success at 10% or an 8% differential.
Table 15: Success and non-success of male students in Math 125 whose first
mathematics course was Math 105 (N=1350)
Did not Non Success Success in
Group attempt in Math 125 Math 125 Total % n
African American (n=312)
Math 105 Non Success 98% --- 2% 100% 130
Math 105 Success 89.5% 0.5% 10% 100% 182
Latino (n=1038)
Math 105 Non Success 98.5% 0.5% 1% 100% 433
Math 105 Success 80% 5% 15% 100% 544
Similar patterns existed for the Latino males as well. Again, in turning to Table
15, of the 1038 Latino males who completed Math 105 as their first course
(successfully or non-successfully), 913 or 88% “Did not attempt Math 125” (first
column). Of those students who did not attempt Math 125, those who were not
successful in Math 105 were less likely to attempt Math 125. However a large
51
percentage (80%) of those who were successful in Math 105 did not attempt Math
125 as well. Latino males also demonstrated a low percentage of students who were
“Non successful in Math 125” (second column). However, there were also low
numbers of students who demonstrated “Success in Math 125” (third column), as 1%
of Latino males who were not successful in Math 105 demonstrated success in Math
125. Again, students who were successful in Math 105 demonstrated a greater
percentage of success at 15%. Lastly in looking at both populations, Latino males
demonstrated greater success in Math 125 after completing Math 105 than African
American males.
When examining those students who began the mathematics sequence with
Math 112, some interesting trends present themselves in Table 16. Overall, 89%
Table 16: Success and non-success of male students in Math 125 whose first
mathematics course was Math 112 (N=1072)
Did not Non Success Success in
Group attempt in Math 125 Math 125 Total % n
African American (n=251)
Math 112 Non Success 94% 3% 3% 100% 125
Math 112 Success 76% 8% 16% 100% 126
Latino (n=821)
Math 112 Non Success 93% 4% 3% 100% 354
Math 112 Success 68% 9% 23% 100% 467
of African American males and 78% of Latino males who begin remediation with
Math 112, did not attempt Math 125. However, more students in both groups
attempted Math 125 after successful completion of Math 112 than was seen in Table
15 for those who were successful in Math 105.
In further analyzing those who “Did not attempt” Math 125 (first column), an
18% difference exists for African males and a 25% difference exists for Latino males
52
between those who were successful and non-successful in Math 112. In moving to
the second column “Non-success in Math 125”, less than 10% of students in both
groups were not successful in Math 125. Finally, moving to the last column “Success
in Math 125”, those students who were successful in Math 112 represented a larger
percentage of the students who were successful in Math 125. For African American
males this represented 16% and 23% for Latino males. For both groups, students
who demonstrated success in Math 112 were more likely to be successful in Math
125 than those students who were not successful in Math 112. Finally, Latino males
had a slightly higher percentage in the area of success in Math 125 than African
American males (23% versus 16%).
Lastly, Table 17 demonstrates the outcomes for African American and Latino
male students who begin with Math 115 and their performance in Math 125. This
table clearly outlines the impact of success in remedial mathematics and subsequent
performance in the community-college level mathematics course.
Table 17: Success and non-success of male students in Math 125 whose first
mathematics course was Math 115 (N=1438)
Did not Non Success Success in
Group attempt in Math 125 Math 125 Total % n
African American (n=283)
Math 115 Non Success 86% 8% 6% 100% 128
Math 115 Success 54% 10% 36% 100% 155
Latino (n=1155)
Math 115 Non Success 88% 5% 7% 100% 448
Math 115 Success 38% 14% 48% 100% 707
In this table, one can see that students in both ethnic groups who were successful in
Math 115 are more likely to be successful in Math 125 than those students who were
not successful in Math 115. The third column “Success in Math 125” shows a 30%
53
differential for African American males and a 40% differential for Latino males
between those students who did not have success in Math 115 versus those who did.
Tables 15 through 17 provide one consistent finding that was not expected:
students who were not successful in a remedial mathematics course attempted and on
occasion passed the community college level course. However, the percentage of
students who fell into this category was small. Based on the results reported in
Tables 15 through 17, my hypothesis is false. Success in the community college level
mathematics course is correlated with success in the remedial mathematics course.
54
Chapter 5
Conclusion
The purpose of this study was to examine how remedial mathematics affects
the success of African American and Latino male community college students. I
examined four hypotheses related to student age, course load, delayed enrollment in
remedial mathematics and the relation between remedial mathematics and
performance in college level mathematics. Through analysis of the data several
contradictory findings arose.
In relation to the Tinto’s (1988) Student Departure theory, the data shows that
taking remedial math courses does impact the success of African American and
Latino male community college students. As predicted and based on the data, older
students were more successful in remedial mathematics than younger cohorts. Age
was a significant factor, as older students in both populations performed better than
their younger counterparts, which supports Tinto’s (1987) assertion that older
students outperform their younger counterparts. However, Tinto credited this success
to commitment, which was not under examination in this study. There are other
rationales for this behavior. Some researchers speculate that older students are more
focused on their college careers, as they return to the academic setting with life
experience and perhaps more focused goals.
Johnson (1996) found a correlation of .321 in relation to age and remedial
course grade. This study found a higher correlation for African American males
(r =.386) and lower (r =.214) for Latino males. This only explains between 5 and
15% of the variance, the remaining percent may be due to institutional, personal, or
psychological factors. However, as Hagedorn (2005) notes, community college
students commitment can be measured by their course completion rates. And as seen
55
in this study, older students in both groups had higher completion rates than
younger groups. The lower GPA’s of African American males is inline with the
findings of Weissman, Bulakowski, and Jumisko (1998), who found African
American students had lower GPA’s than Latino students, although the study relied
on student self-report through focus-groups.
The data further support full-time enrollment and its link to increased
persistence and success, as Tinto hypothesized. Full-time students showed the
highest levels of success, although course load explained less than 1% of the
variance. This proves to be a challenge as the majority of students attending
community colleges attend part-time.
While Tinto (1988) did not address the concept of delayed enrollment in
remedial mathematics, he did stress the value of remediation as a way to increase
student success (Tinto, 1993). The data in this study supports participation in
remedial mathematics as a way to increase performance in college level math.
Additionally, delaying remedial mathematics past the first semester was also found
to increase student success. Johnson and Kuennen’s (2004) university study found
that students required to take remedial mathematics courses earned lower overall
GPAs in other non-mathematics courses than those students who needed remedial
mathematics, but did not take the course. Johnson and Kuennen, controlled for one
non mathematics course, however the present study did not. Despite this limitation,
the findings still show students who delayed remedial mathematics earned higher
overall GPA’s. Caution must be exercised as it is not known in this study what
courses other than mathematics that the student enrolled in.
In regards to delayed enrollment in remedial mathematics, the data proved
that this population shows marked success in terms of overall GPA when remedial
56
math is not taken in the first semester. One possible rationale is that students are
able to experience success in other college level courses before embarking on
mathematics courses that may prove challenging. Unfortunately, without knowledge
of the students’ feelings towards math, this is merely as assumption. While students
experienced higher overall GPAs, those who delayed enrollment in remedial
mathematics past the first semester did not experience the same success ratios as
their peers who started remedial math in the first semester. The question then
becomes, which measure to use as a marker of success (overall GPA or math GPA)
and how to ensure alignment between departmental and institutional goals.
The last hypothesis proved to be incorrect in that success in college level math
is related to success in remedial mathematics. Success in college level math followed
similar trends (Easterling, Patten, & Krile, 1998), where success increased the closer
student was to college level math course. While the majority of African American
and Latino male students are not progressing through the remedial math sequence,
the data shows that the likelihood of success increases as students successfully
complete remedial courses leading into the college-level course. These findings are
supported by Maxwell et al. (2004), who found similarly low rates of success (25-
40% of students failed remedial coursework). It is important to note that African
American and Latino males are making multiple attempts at the same math level, or
stopping out prior to completing the sequence.
While this study did provide support for several hypotheses set forth by Tinto,
a few cautionary notes must be extended. The research on minority students is still
relatively young and models such as Tinto’s, may not do enough to fully capture the
experience for minority students. According to Tierney (1992), one fault of utilizing
integration models is that they merely insert minorities into a dominant cultural
57
frame, leaving invisible cultural hierarchies intact (Tierney, 1992). Additionally,
in regards to causality, Bailey et al. (2004) state, “it is difficult to identify a causal
relationship between remedial education and subsequent educational attainment”
(p.40). Students may perform poorly in other classes, but that does not mean that the
remediation was not effective, in fact, without the remediation, the students may
have performed worse.
Recommendations
Non success in remedial mathematics is costly to the student in terms of time,
lost wages and missed educational opportunities. The following recommendations
are offered based on the findings and research acquired during this study.
1. Encourage students to enroll in full-time status.
2. Implement a district policy allowing students to delay enrollment in remedial
mathematics one semester.
3. Ensure course prerequisites are met, and prevent students who have not passed
remedial mathematics classes from enrolling in higher level courses.
In addition to recommendations based on the data, the following recommendations
are based on the examination of LACCD course catalogs. The following are based
on evidence presented in throughout this manuscript (please refer to information in
the parentheses for location of supporting text and/or figures within this manuscript):
1. Course descriptions and titles should be consistent throughout the district
30
.
Currently course descriptions vary from college to college, some colleges have
very limited information, and others are more thorough.
2. Furthermore, consistent and honest labeling of remedial courses. Some courses
are labeled NDA (non degree applicable) or NDC (with no explanation offered),
58
or not labeled at all, possibly leading to confusion amongst students. (refer to
Chapter 5 Endnotes on page 60) .
3. Include a consistent model demonstrating the math sequence in all online and
print publications (refer to Tables 1 through 4 on pages 27 through 30).
Future Research
There are an increasing number of male and female students of all ethnic
backgrounds who are entering the community college setting in need of remediation
in the area of math, however there are specific circumstances that have guided my
decision to study the African American and Latino male population. In LACCD, as
in many other higher education settings, male students are underrepresented. We are
seeing a growing gap in the number of male to female enrollments, with women
outnumbering male students almost 2 to 1 on some campuses. Secondly, 2006 will
see the first group of high school seniors who will be required to pass the California
High School Exit Exam (CAHSEE), in order to graduate from high school. As of
2005, LAUSD showed a pass rate for African American and Latino students of 37%
and 47% respectively for the mathematics portion of the test (CAHSEE, 2005), and
many of these students will enroll in one of the nine colleges in LACCD.
Based on the data presented in this dissertation, it is clear that the majority of
African American and Latino male students entering remedial mathematics programs
are not successfully navigating their way through the sequence. It is clear that a huge
loss of students occurs from Math 105 (the lowest level of remediation in this study)
to Math 125 (the highest level of remediation and the course needed for students to
earn the Associate of Arts degree). What is not clear is how other variables affect
this process. There is a common understanding that studying community college
students, their enrollment patterns and success can be a difficult task, as no two
59
community college students are the same. Therefore the existing study would
benefit from further quantitative and qualitative exploration.
Through this study it was found that age is correlated with several independent
variables such as delayed enrollment into remedial mathematics courses and full-
time/part-time enrollment status. As a result, these independent variables do not have
totally separate effects, but rather joint effects on the dependent variables of student
success (as measured through GPA and success ratios). Therefore, future research
can utilize multivariate analysis to examine the nature of these joint effects for this
sub population.
In examining academic success amongst different ethnic groups, further
analysis of the various Hispanic subgroups including aspects of language is vital.
Additionally, to gain a broader sense of student readiness for college mathematics,
factors from the high school setting including mathematics preparation and GPA, as
well as assessment tests scores and placement need to be addressed.
To further expound on the work of Tinto (1975) and to take into further
consideration nuances related to these two populations, an examination of external
student attributes such as socio-economic status, hours spent working and family
responsibilities, parental level of education and first-generation status would prove
important. Other social integration variables to consider include the amount of time
spent studying, talking with counselors, meeting would peers would also tie in.
Lastly, examination of psycho-social factors such as goals, levels of math self-
efficacy, and minority male behaviors could prove beneficial.
Institutional factors such as the type of curriculum utilized, pedagogical
differences, course offerings (day versus evening), mode of delivery (class meets one
60
day per week, two days per week, online, open entry/open exit), institutional
differences across LACCD, and institutional racism.
According to Allen et al. (2002), California’s problem with higher education in
regards to African American and Latino students mirrors the national problem.
While this dissertation highlighted course taking patterns and the success rates of
students, a large piece of the puzzle missing is the student voice. A qualitative
component would increase the depth of understanding of how students feel about
remedial math, their struggles, how they persist through courses they find difficult
and the value they place on education.
61
Chapter 5 Endnotes
30
Course descriptions for mathematics course vary from college to college, which
may make it difficult for students to adequately understand what course they are taking, as
many students often take courses at multiple colleges within the district. For example, the
following are the various titles and descriptions for Math 105 at the various colleges taken
from the college catalog:
City College
MATHEMATICS 105
Arithmetic for College Students
3 UNITS - NDC
Open to all students.
Reviews the fundamentals of arithmetic that are essential to success in many college courses.
East Los Angeles College
Math 105
Arithmetic for College Students (3) NDA
Note: This course is offered on credit/no-credit basis only.
This course is designed to give students understanding and competency in the basic
operations of elementary arithmetic. Topics include the standard operations with applications
on whole numbers, fractions, decimals, ratio, proportion, and percent. Additional topics may
be chosen from geometric figures and introduction to algebra.
Harbor College
105 - ARITHMETIC FOR COLLEGE STUDENTS (3)
NDA
Lecture 3 hours and 20 minutes per week.
This course explores arithmetic concepts from a modern point of view. It
Includes discussion of pre-algebra topics, applications of arithmetic in
Business and finance, and geometry.
Mission College
105 ARITHMETIC FOR COLLEGE (NDA) 3 UNITS
STUDENTS
Prerequisite: None | Lecture: 3 hours
A review of elementary arithmetic. Topics include whole numbers,
Fractions, decimals, percent, measurements (including the
Metric system), and an introduction to elementary algebra.
Pierce College
105 Arithmetic for College Students (3) (NDA)
62
Lecture 3 hours.
Reviews the arithmetic essential in college and business. Topics include
Fractions, decimals, percent, and measurement. The course emphasizes
Problem-solving techniques that are useful in practical situations.
Southwest College
105 Arithmetic for College Students (3) NDA (Formerly MATH 30) Prerequisite: None.
Lecture 3 hours. This course is a review of elementary arithmetic essential to success in
many college fields and in industrial experience. It includes the systematic development of
sets, whole numbers, fractions, decimals, percentages, ratios and proportions, and practical
applications.
Trade-Tech College
105 Arithmetic for College Students (3) NDA
Prerequisite: Successful completion of Mathematics 101 with a grade of “C” or better or
placement process
Lecture, 3 hours
Topics include operations in addition, subtraction, multiplication and division of fractions,
decimals using prime number factorization, percentages and applications.
Valley College
105 Arithmetic (3) NDA
Prerequisite: None.
Lecture, 3 hours.
Reviews the fundamentals of arithmetic
That are essential to continuing in any field.
63
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Abstract (if available)

Abstract This study examined course taking patterns in remedial mathematics and their possible impact on the success of first-time African American and Latino male community college students in the Los Angeles Community College District (LACCD). The questions that this study answered focused around student background characteristics and performance in remedial mathematics. This study's independent variables were ethnicity, age, course load, level of remedial math and time of entry into remedial mathematics courses. Remedial mathematics courses represented those courses below the designated community college level course and were analyzed by levels. These independent variables were paired with the dependent variable of student success, which was measured in terms of grade point average (GPA) and course completion rates. The study utilized academic integration as first discussed in Tinto's Student Departure theory and hypothesized that student characteristics and student success was correlated with course-taking patterns in remedial mathematics. Data utilized were from the Los Angeles Community College District (LACCD) dataset.

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Asset Metadata

Creator Miller, Kaneesha K. (author)

Core Title The impact of remedial mathematics on the success of African American and Latino male community college students

School Rossier School of Education

Degree Doctor of Education

Degree Program Education (Leadership)

Publication Date 09/28/2006

Defense Date 05/04/2006

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

Tag males,OAI-PMH Harvest,remedial mathematics

Language English

Advisor Maxwell, William E. (committee chair), Prather, George M. (committee member), Rideout, William M., Jr. (committee member)

Creator Email kkmiller@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-m53

Unique identifier UC1112562

Identifier etd-Miller-20060928 (filename),usctheses-m40 (legacy collection record id),usctheses-c127-2563 (legacy record id),usctheses-m53 (legacy record id)

Legacy Identifier etd-Miller-20060928.pdf

Dmrecord 2563

Document Type Dissertation

Rights Miller, Kaneesha K.

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Repository Name Libraries, University of Southern California

Repository Location Los Angeles, California

Repository Email cisadmin@lib.usc.edu