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Correlations among selected demographic variables, counseling utilization, and intent to transfer
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Correlations among selected demographic variables, counseling utilization, and intent to transfer
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Content
CORRELATIONS AMONG SELECTED DEMOGRAPHIC VARIABLES,
COUNSELING UTILIZATION, AND INTENT TO TRANSFER
by
Rosina (Zina) Chacon
_____________________________________________________________________
A Dissertation Presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the Requirements
for the Degree of
DOCTOR OF EDUCATION
August 2008
Copyright 2008 Rosina (Zina) Chacon
ii
DEDICATION
I want to dedicate my dissertation to the many people who were there for me:
To my son, Zen. I love being your mommy.
For my Mom. It has always been my dream to become a Dr. in the family.
Thank you Mom and I love you. To my Dad, thank you for your strength and
guidance. You are always there for me. Thank you and Francine for loving me
unconditionally. To my Auntie (Elsie) and to all your family, for your love and
support. I love you. To my best friends Jamie, Nelson and Kristen. Your love is
unconditional, patient and kind. To my niece Desiree, thank you for believing in me.
To Maria and Robert Saenz, thank you for going through everything with me and
keeping me strong throughout it all.
I want to thank my mentors and friends, Dr. Marshall Jung, Dr. Edward and
Linda Morante, Dr. Doug Larson, David Mills, Dr. Arvid Spor, Dr. Sandy Mayo, Dr.
Dawn Lindsay, Dr. Diane Dieckmeyer, and my counseling colleagues and staff. All of
you have helped me grow emotionally, academically and professionally. I am blessed
to have you in my life.
Thank you to the Puente Program and all the students who have inspired me to
follow my dreams and set the example to finish my education. Si Se Puede!
I also want to thank all my friends and family who I have not mentioned but you know
who you are. These past few years were challenging for me, but your support and
love were never left unnoticed. I learned so much from this experience and each day I
continue to learn and count my blessings.
iii
ACKNOWLEDGEMENT
I would like to thank Dr. Dennis Hocevar, my committee Chair, for all the
years of his commitment and work with me. I could not have done it without you!
To my committee members: Dr. Melora Sundt and Dr. Ilda Jimenez y West. I
am truly grateful for the USC Doctoral Support Center, dissertation acceleration
workshop, and the support I received. Thank you for your commitment toward the
completion of my doctorate degree. Thank you Dr. Jimenez y West, I am forever
grateful to you. You are like family to me and I will never forget how you took the
time to help me finish. I also want to thank Dr. Linda Serra Hagedorn. You supported
me in my first years at USC and made a positive impact on me with your personal,
academic and career advising. Thank you for the Transfer Retention of Urban
Community College Students, (TRUCCS ) research Project surveys and data sample,
and especially all the work that was dedicated to make this research possible.
iv
TABLE OF CONTENTS
Dedication ............................................................................................................. ii
Acknowledgements .............................................................................................. iii
List of Tables ........................................................................................................ v
List of Figures ....................................................................................................... vi
Abstract ................................................................................................................. viii
CHAPTER ONE:
The Problem and Its Underlying Theoretical Framework ........................ 1
Role of Counseling ................................................................................... 3
Background of the Problem ...................................................................... 6
Data Source .............................................................................................. 11
Significance of the Study .......................................................................... 12
Research Questions .................................................................................. 15
Definition of Terms .................................................................................. 17
Methodology ............................................................................................. 20
Limitations ................................................................................................ 21
Organization of the Study ......................................................................... 21
CHAPTER TWO:
Literature Review ..................................................................................... 23
Introduction .............................................................................................. 23
Documentation ......................................................................................... 24
Background of Study ................................................................................ 24
Tinto’s Model of Student Retention ......................................................... 26
Astin’s Model of Student Involvement .................................................... 27
Pascarella and Terenzini Model of Student Persistence ........................... 29
Bean and Metzner Model of Student Persistence ..................................... 32
Transfer ..................................................................................................... 36
Transfer in California ............................................................................... 39
Counseling Utilization .............................................................................. 43
Variables of Community College Students (Age, Gender, Ethnicity
Nontraditional) ................................................................................... 45
Ethnic Group Membership ....................................................................... 45
Gender ...................................................................................................... 47
Age ........................................................................................................... 47
Level of Parent Education of Community College Students .................... 48
Implications for Future Research ............................................................. 49
v
Conclusions .............................................................................................. 50
CHAPTER THREE:
Methodology ............................................................................................. 52
Research Questions .................................................................................. 52
Research Design ....................................................................................... 53
Population and Sample ............................................................................. 53
Procedure .................................................................................................. 56
Instrumentation ......................................................................................... 58
Demographic Variables ............................................................................ 59
Dependent Variables ................................................................................ 60
CHAPTER FOUR:
Results ...................................................................................................... 63
Descriptive Results ................................................................................... 63
Analysis of the Research Questions ......................................................... 64
CHAPTER FIVE:
Conclusion and Recommendations .......................................................... 78
Introduction .............................................................................................. 78
The Purpose of the Study ......................................................................... 79
Summary of Findings ............................................................................... 79
Discussion ................................................................................................. 85
Recommendations for Future Research .................................................... 89
Conclusion ................................................................................................ 90
REFERENCES ..................................................................................................... 92
vi
LIST OF TABLES
Table 1: Frequency Table: Students Who Plan to Transfer .............................. 56
Table 2: Frequencies of Students Who Spoke with an Academic Counselor .. 57
Table 3: Counseling Utilization Recoded to “yes” and “No” ........................... 57
Table 4: Plan to Transfer Frequencies .............................................................. 63
Table 5: Counseling Utilization Frequencies ................................................... 64
Table 6: Gender and Plan to Transfer Cross-tabulation ................................... 65
Table 7: Chi-square Test: Gender by Intent to Transfer .................................. 64
Table 8: Chi-square Tests: Age by Intent to Transfer ..................................... 66
Table 9: Cross-tabulation of Age and Intent to Transfer .................................. 67
Table 10: Ethnic Group Membership and Intention to Transfer ........................ 69
Table 11: Chi-square Tests: Ethnic Classification and Intent to Transfer ......... 69
Table 12: Parent Education by Intent to Transfer Cross-tabulation ................... 70
Table 13: Chi-square Tests: Parent Education and Intent to Transfer ............... 69
Table 14: Counseling Utilization by Gender ...................................................... 71
Table 15: Chi-square Tests: Counseling Utilization by Gender ......................... 71
Table 16: Chi-square Tests: Counseling Utilization by Age .............................. 72
Table 17: Cross-tabulation of Counseling Utilization by Age ........................... 73
Table 18: Cross-tabulation of Ethnic Group and Counseling Utilization ........... 74
Table 19: Chi-square Tests: Ethnic Group and Counseling Utilization ............ 75
Table 20: Cross-tabulation of Parent Education and Counseling Utilization ......... 76
Table 21: Cross-tabulation of Parent Education and Counseling Utilization ......... 76
vii
Table 22: Cross-tabulation of Intention to Transfer and Counseling Utilization ... 77
Table 23: Chi-square Tests: Intention to Transfer and Counseling Utilization ..... 77
viii
ABSTRACT
In this study, a nonexperimental approach was used to estimate the
relationship of intention to transfer and utilization of counseling among students of
different ethnicities. The study’s primary purpose was to determine if students who
have the intent to transfer to a 4-year college or university are more likely to utilize
counseling in their first year of study in community college.
Key demographic variables such as gender, age, ethnic group membership,
and parent education were correlated with intent to transfer and counseling
utilization. The data collection derived from a secondary analysis of the Transfer
and Retention of Urban College Students (TRUCCS) survey (Hagedorn, 2003).
The TRUCCS project team collected data from a distributed survey to 5,000
community college students from the nine community colleges within the Los
Angeles Community College District in 2001.
The results of this study showed that the relationship of counseling utilization
and intent to transfer among community college students was significant. Students
who intended to transfer did use counseling services to a greater extent in their first
year of study. However, the small number of students who sought counseling
overall, less than 30%, suggests that counseling’s potential for increasing transfer
rates has not been fully realized.
Results are interpreted in light of the retention theories of Tinto
(1975/1993), Astin (1984/1996), Pascarella and Terenzini (1991/2005), and Bean
ix
and Metzner (1985) and the practical implications of the study’s findings are
discussed. Several important limitations to the study’s findings also are identified.
1
CHAPTER 1
THE PROBLEM AND ITS UNDERLYING
THEORETICAL FRAMEWORK
The majority of students who attend the community college are minority
students who have a desire or intent to transfer and become transfer ready (CCCCO,
2004). Yet due to the barriers of transfer, utilization of counseling, and the component
of retention, the community college transfer rate is very low at a 5% to 8% (CCCCO,
2004). In the past, the primary retention-staying indicator at community colleges was
course completion, yet today, transfer readiness is a different indicator of retention. A
transfer ready student is a student who is able to persist at college and complete
college transferable courses, thus becoming ready to transfer to a university. It is
almost contradictory in that we want the student to leave the community college and
transfer to a 4-year university, where most literature assumes the student stays at the
community college to obtain a degree or goal.
Based on the data from the mid 1990s, Suarez (2003) reported that approxi-
mately 20% of all community college students intend to transfer, and there is some
evidence that intent to transfer is increasing rapidly with recent findings from the
Transfer Retention of Urban Community College students survey results (Hagedorn &
Lester, 2006). Students with the intent or desire to transfer make community colleges
their first choice based on cost, convenience, proximity to home, and the need for a
college education to prepare them in their academic skills before pursuing a
Bachelor’s degree.
2
Community colleges educate over 5 million students annually and almost half
of those enrollments are students of color (CCCCO, 2004). The overall 2-year college
enrollment is also projected to increase by nearly 20% during the next decade
according to the California Community Colleges Chancellor’s office. In the 2002-
2003 academic years, the California Community Colleges (CCCCO, 2004) system
enrolled approximately 1.7 million students throughout their 109 campuses statewide.
Of these students about 900,000 or 53% were minority students. Another important
demographic characteristic of the 1.7 million students is the fact that almost 600,000
or 35% of the students received a fee waiver for tuition based upon the student’s
financial need (CCCCO, 2004). Latinos attend community colleges at a rate
disproportionate to all other groups in the United States. While over 55% of Latinos
are enrolled in community colleges, only 35% of White, 40% of African American,
and 40% Asian Pacific Islander students are enrolled in community colleges (NCES,
2003, table 210).
From 1972 to 1995 the percentage of college students from minority ethnicities
grew at 2 to 14 times the rate of nonminority groups. The minority population
increased from about 15% to 25% of all students (NCES, 1998). Growth in the
enrollment was due to an increase of Hispanic and Asian students, however,
enrollment as a percentage of all college students increased about 4% each year.
During this time period, enrollment rates for 18 to 24 year old African American
students who had completed high school increased from 27% to 36%; corresponding
rates for students who were African American accounted for 10% of the total college
3
and university enrollment. Students who were Hispanic accounted for 8%, Asian-
Pacific Islander accounted for 6%; and American Indian-Alaskan natives constituted
1% and these numbers that constitute 1 in 4 students was a member of minority
populations (NCES, 1998).
Role of Counseling
The emerging role of counseling involves helping students to complete their
academic objectives, and thus, the reduction of student attrition is a priority.
Counselors must perform the roles of student developers and learning agents (Noel &
Levitz, 1984). As student developers, they must communicate to students the
importance of skill building and other academic requirements and help them
understand the value of their academic endeavors. As learning agents, counselors
must assist, manage and encourage students to build a pattern of success.
Community college counselors’ initial contact prior and during enrollment,
provide students with valuable information about academic and student support
programs, placement in beginning courses, and understanding of course requirements
and college articulation agreements. These services are aimed at increasing retention
and impact both the student’s knowledge and intent to transfer. Community college
counseling, as well as other relationships between faculty and students, has historically
been seen as a benefit for successful college enrollment and for preparing students for
vocational, career, and academic goals, as well as transfer to a 4-year university.
Community college counseling can provide students the information and guidance on
4
the progression from lower division courses to higher education degrees at the 4-year
universities.
Since the adoption of the California Master Plan for Higher Education in 1960,
the importance of transfer rates at the community colleges has been critical to
California Community Colleges. The transfer process provides the diverse community
college student population an effective and affordable way to continue their education
beyond their years at the community college, and counseling plays an important role
in this endeavor. The utilization of counseling at community colleges is designed to
inform, advise, and guide students through the transfer process and increase student
transfer rates to a 4-year university. However, the utilization of counseling is different
among all community colleges due to the manner in which students seek out
counseling.
Community colleges are the central point of entry into higher education for
both lower income and working adult students. Formalization of academic advising
and counseling on most campuses was in response to two issues: (a) student
populations that were increasing in diversity, and (b) facilities that were devoted to
research. By the late 1970s, the National Academic Advising Association
(NACADA) was formed in order to increase interest and inform improved practice,
the association supported an annual national conference, advising-related research, a
refereed journal, and other outlets for publication and professional development
(Gordon & Habley & Assoc., 2000).
5
With the changing characteristics of students attending community colleges
and the decline in financial support, community colleges have redefined the role of
counseling in the community college. In the 1950s and 1960s, counselors served in a
quasi -parental role (Leach, 1984), by providing personal counseling, vocational
guidance, and social support for the traditional community college student. In the
1970s and 1980s, ethnic minorities, older women, adult re-entry, part-time students,
and displaced workers began enrolling in community colleges. The community
college and counselors began to meet the needs of these new students, and reinstated
testing and placement, dismissal and probation policies, general education
requirements, and select admissions programs.
NACADA appeared to have improved advising programs and enhanced the
professional status of advisors. Today, NACADA flourishes and works to improve
both knowledge and practice related to advising. National interest in improving the
experience of first year students also developed during this time under the leadership
of John Gordon (Gordon, Habley & Assoc., 2000). How has NACADA influenced
transfer? NACADA has influenced transfer with the impact of advising and career
planning to help students. The following are several recommendations from
NACADA for academic advising students, given the diversity of students today
(Gordon et al., 2000, p. 81).
1. Know your students.
2. Know your institution’s resources and how to access them.
3. Advocate for campus resources that may be needed.
6
4. Reconsider academic advising training programs in light of today’s
changing students.
5. Develop collaborative relationships between teaching faculty and
academic advisors.
6. Reconsider academic advising policies and practices.
7. Be alert.
These recommendations have been written by NACADA to influence transfer
and provide advising and counseling to students in community college, and have not
differed from the theories on student retention since the 1970s to present.
Background of the Problem
Tinto (1993) reported that first year attrition is 50% at 2-year colleges and 33%
at 4-year institutions. Academic and social experiences during the first few weeks of
college strongly influence students’ integration into the academic and social
community. Important variables to research are age, gender, ethnicity and retention
for community college students. The community college system is an important part
of higher education and of society, however, community colleges are known for a
history of low retention and transfer rates, particularly among economically
disadvantaged students of color. It is widely known that the problems of lack of
success and failure to make academic and social connections are even more
pronounced in students of color, who are educationally disadvantaged prior and after
enrolled in community colleges (Parker, 1998).
7
Persistence models for students of color in community college are representa-
tive of those typically used with studies on 4-year university students. In his model
for college student attrition, Tinto (1993) postulated that a student’s tendency to stay
in college was related to the degree to which the student felt integrated into the social
and academic life of the college. Although much of the research on Tinto’s model
largely affirms his original theory, other researchers such as Bean and Metzner (1985)
and Astin (1984/1993/1996) have argued that additional factors need to be considered
in studies of the success of educationally disadvantaged or underrepresented students
of color, who are not White. Also, most of the theories were developed on traditional
college populations and based on traditional White students ranging from ages 18 to
24 that now, are atypical students in community colleges. Community college
students are typically nontraditional students of color and have different pre-entry
characteristics, goals and beliefs about college compared to the traditional university
student.
Tinto (1993) bases his theory of retention on the institution itself and the
effects the institution has on students and their decision to stay or leave. His belief is
that the institution’s goal of retention is for the education of students, their social and
intellectual growth and the guiding principle of the institution. In contrast to Tinto
(1993), Astin (1985) argues that students learn by becoming involved. He explained
the dynamics of how students change or develop and sees his theory of elements as the
investment of psychological and physical energy, as objects of one sort or another
such as tasks, people or activities (p. 133). According to Astin’s (1993) theory, the
8
development or change of a student is not the consequence of college’s impact on a
student, but rather a function of the quality of student effort or involvement with the
resources provided by the institution. Ultimately according to Astin’s theory, it is the
student’s choice to be involved. Astin emphasizes that personal effort impacts the
student’s overall decision to stay at the college or institution, and Tinto (1993)
believes that it is the student’s decision to stay or leave the institution, yet it is also the
institution’s responsibility to create change or impact the student effort and decision to
stay or leave.
Community colleges have as one of their missions to assist students to transfer.
It is important to recognize this transfer mission of community college and that many
students desire to transfer to a 4-year institution. Cohen (1998) instituted a national
effort to produce a uniform measure of transfer rates. According to Cohen, a transfer
rate can be validly calculated by counting students who are beginning their
postsecondary education in a community college, complete at least 12 units and
transfer to a 4-year university. Cohen (1991) defines transfer rate as,
All students entering the 2-year college in a given year who have no prior
college experience and who complete at least 12 college credit units (referred
to as the Cohen cohort) divided into the number of that group who take one or
more classes at a university within 4 years. (Cohen, 1991, p. 3)
Until recently, no national database existed which would allow a single college to
track their own students (Romano & Wisniewski, 2005).
The National Student Clearinghouse data was created in 1993 to verify
enrollment status of financial aid recipients. The electronic registry includes 2,700
9
colleges and covers 91% of U.S. college enrollments (Romano & Wisniewski, 2005).
Although the NSC registry was not created for tracking transfer students, studies have
found that NSC is a useful and accurate means for following students as they move
from one institution to another. The major limitation at the current time is that the
core database can only be used to track a student’s enrollment versus transfer.
However, the NSC is in the process of collecting information on degrees received
(Romano & Wisniewski, 2005). Once verified and completed, the NSC will be
helpful to confirm whether community college transfers actually get a Bachelor’s
degree.
Transfer rate has also been calculated with the number of students who transfer
to a 4-year college divided by the number of potential transfer students with the
numerator and denominator defined in a number of different ways. Obviously with so
many variations in transfer rate formulae, arbitrary decisions can have a significant
impact on transfer rate estimates (Bradburn & Hurst, 2001). In community colleges,
reliable, valid and comparable transfer rate data can be difficult to obtain.
The California education code Title 5 requires that all districts have a transfer
center and minimum program standards (CCCCO, 2002) to address transfer issues,
leading to all 109 of the community colleges in California having some form of
transfer center. The primary mission of the transfer center is to promote student
transfer and support students who have intent to transfer to a 4-year university
(Zamani, 2001). In the past, estimates in the Los Angeles Community college district
10
show that only 5% to 8% of the total student population will transfer to a 4-year
college (Los Angeles Community College District, 2001).
Historically, the community college system has not had an official transfer
rate, and as a result, outside entities requesting system transfer rates have relied on
estimates (California Community Colleges Chancellor’s Office, 2002). Typically, the
community colleges take an annual count of transfers divided by the annual
enrollment and estimate the transfer rate. According to California Community
Colleges Chancellor’s Office (2002), this is not a valid way to estimate transfer rates,
and would imply that all transfers come from a single year cohort of students whose
goal was to complete all their transfer requirements in 1 year. This also implies that
all students enrolled in California community colleges are attempting to achieve
transfer as a goal. However, transfer is only one of the missions of the community
colleges and many students do not intend to transfer.
According to the California Community Colleges Chancellor’s Office (2002),
the new transfer rate methodology defines a cohort of students with “intent to transfer”
as students who began their collegiate careers as first-time students in a fall term, who
within a period of 6 years, attempted transfer level math or English (regardless of the
outcome) and completed at least of 12 units in the CCC system (p. 25). The method of
defining “intent to transfer” has the ability of identifying over 80% of the students
who actually did transfer, although some students also are able to transfer without
attempting transfer math or English or do not attempt either of these and do not
complete at least 12 units. With this methodology, a yielded statewide estimate of
11
33%-34% indicated that one-third of the students in the CCC system have intent to
transfer under this definition (CCCCO, 2002).
Data Source
The data source was the Transfer and Retention of Urban Community College
Students, TRUCCS, survey sponsored by the United States Department of Education,
the University of Southern California (USC), the University of California, Los
Angeles (UCLA) and the Los Angeles Community college District (LACCD).
TRUCCS began as a 3-year, longitudinal and comprehensive study of the goals,
success and academic patterns of 5,000 community college students in urban Los
Angeles. The project subsequently received renewed funding from the Lumina
Foundation for Education and was continued by researchers for 2 more years. This
renewal allowed the project to do follow up with the original 5,000 students, to
analyze collected survey and transcript data and to determine the factors that promote
success for all types of LACCD students.
The community college system is an important part of higher education,
however, community colleges are known for a history of low retention rates. The
TRUCCS research helps provide the knowledge and data to understand how
counseling can affect persistence and academic integration that promotes student
success. All TRUCCS data collections were located on the nine campuses of the Los
Angeles Community College District, which comprises the largest community college
district in the nation. TRUCCS research can also be generalized to other large urban
areas with multi-campus districts (TRUCCS Survey, 2004).
12
Significance and Purpose of Study
Underrepresented students of different ethnicities are not graduating from 4-
year colleges, thus the income gap is persisting in the United States. The complicated
combination of financial need and a lack of knowledge of what financial aid is
available is an obstacle. Students who fail to seek advice, students who cannot be
accommodated by a limited counseling staff, and students who frequently change their
goals may not know what is required to transfer (CCCCO, 2002). The community
colleges and 4-year universities and colleges have suffered budget cuts, which
ultimately adversely affects transfer rates.
A student who is transfer ready has been defined as a student who completes or
takes courses that are transferable and progressing at their own pace despite all the
obstacles of personal, social, academic and career issues that may become barriers
toward transfer (Hagedorn, 2003). “The TRUCCS data show that traditional linear
transfer (high school to community college to university) is actually rare among urban
students and is thus the exception rather than the rule. Using a weighting algorithm to
correct for a slight bias by gender and age, among the TRUCC sample, less than one-
fifth of the samples directly entered community colleges following high school
graduation (Hagedorn, 2003, p. 6).
Community colleges have to be accountable and help students become transfer
ready. Barriers to student success consist of problems in staffing the transfer centers
and funding and institutional commitment throughout the community college system.
Successful articulation from community colleges to 4-year institutions is difficult for
13
both the institutions involved and the students who are served by the institutions.
Fiscal budget concerns with the Assist Project, the official resource of articulation
agreements for the public institutions and a key component of transfer and articulation
information for students (CCCCO, 2002), make the process even more difficult. Loss
of matriculation funding will exacerbate the challenge of supporting student progress
toward transfer also is a widespread concern.
To better solve this important societal and institutional problem of transfer,
more resources and strategies are needed for improving coordination and information
referrals with financial aid, matriculation, assessment and faculty involvement.
Strategies to stabilize the annual funding and prioritization of the funds varies within
the system and depends on the priority each institution has on transfer. Strategies to
stabilize the funding of transfer vary among community college campuses, yet if
implemented, may lead to greater readiness and capacity to serve student needs
(CCCCO, 2002).
One of the greatest challenges for students in community college counseling is
helping students to achieve their academic success while supporting their personal,
vocational, and transfer needs. A key problem is how colleges define counseling, for
example, 4-year universities define counseling as academic advising, and community
colleges define counseling as an all encompassing and supportive role. However,
counseling can have a negative connotation to students based on their experiences
from middle and secondary school due to the disciplinary involvement of high school
14
counselors, or because of the community college academic and probation policies in
place for students who are experience failure.
Community college counseling is a valuable resource in the retention of
students, especially during the initial enrollment. Community college students have
many different levels of needs regarding college goals, courses, requirements,
financial aid, transfer, and resources available. The student’s needs and level of
understanding on college varies, and the community college counselor is often the first
person who may provide that information to help them sort through their goals or
aspirations. Counseling helps students identify and focus on their own goals and
interests (Goodlad, 1997). Community college counseling is provided for students to
receive information on general education course planning, degree completion,
information on transfer, and all levels of counseling varying from academic to
personal, social and career.
College student characteristics and needs are generally changing. Students on
community college campuses have a variety of backgrounds and experiences differing
from even a decade ago (Miller, Pope, & Steinmann, 2005). Current college students
are more likely to need or make use of counseling services. Community college
enrollments are increasingly focused on articulation of general education, leading
community colleges to be more transfer-focused rather than occupational. By better
understanding the utilization of counselors and their role in how counseling affects
academic transfer readiness among community college students, it is expected that
transfer rates will ultimately increase.
15
Transfer to a 4-year university is one of the key missions of community
colleges. Transfer is also the top goal of many students entering community college.
Unfortunately, too many students do not achieve their goals including transfer. This
research will focus on the role played by counseling in assisting community college
students to successfully transfer to a university. Other variables traditionally found to
impact student success such as: (a) gender, (b) age, (c) ethnicity, (d) parent education,
and (e) intent to transfer, will also be examined for possible impact on utilization of
counseling. Implications for this research include increased understanding of which
students utilize counseling and of the relationship of the intent to transfer and
counseling utilization.
Research Questions
The analysis of gender, age, parent education, ethnic group membership, intent
to transfer and counseling, utilization is carried out within the context of the following
research questions:
1A. Is gender related to intention to transfer?
1B. Is age related to intention to transfer?
1C. Is ethnic group membership related to intention to transfer?
1D. Is parent education related to intention to transfer?
2A. Is gender related to counseling utilization?
2B. Is age related to counseling utilization?
2C. Is ethnic group membership related to counseling utilization?
16
2D. Is parent education related to counseling utilization?
3. Is counseling utilization related to intention to transfer?
Community college counseling provides a process of helping students, who are
often diverse in ethnicity and socioeconomic status. It is an important source of
intervention and can provide information to students to enhance the skills, insight and
understanding that are necessary to be successful in college. The role of community
college counselor varies according to the student population and the needs of the
college, and accordingly, the main purpose of this study is to determine the degree of
relationship of utilization of counseling and intent to transfer among students of
different ethnicities who have the perceived desire to transfer to a 4-year college or
university. The LACCD consists of nine colleges and covers an area of more than 882
square miles. LACCD educates almost three times as many Latino students and
nearly four times as many African-American students, as all of the University of
California campuses combined. Eighty percent of LACCD students are from
underserved populations. Community colleges in this district serve adults of all ages,
meeting the needs of a society where, “lifelong learning” is the rule and multiple
careers and continual retraining are the norm. More than half of all LACCD students
are older than 25 years of age, and more than a quarter are 35 or older (LACCD
Website, 2004).
17
Definition of Terms
Academic and Social Integration
Tinto (1975/1993) contends that social and academic integration, including the
combination of and intervention over time of variables such backgrounds, initial
commitments to college study, and connections with peers and faculty both socially
and academically.
Articulation
Sets of community college courses that California State University and
University of California faculty agree to accept as having the focus, content and rigor
necessary to meet course requirements at the baccalaureate institutions. Formal course
requirements generally fall within on of three areas: (a) general education breadth
agreements, such as IGETC (see below); (b) transferable course agreements, such as
those approved by the State University in various system wide degrees; and (c) course-
by-course agreements, which are generally used to build articulation of lower division
coursework required for a particular major.
ASSIST
The Articulation System Stimulating Inter-institutional Transfer Project
(Project ASSIST, 1985). ASSIST is a computerized articulation and transfer planning
system for the public sector jointly supported by each of the three public higher
education systems.
18
Counseling Utilization
Counseling utilization is defined by the number of students who spoke to an
academic counselor within the past 7 days at Los Angeles Community College District
from the TRUCCS data survey (2004).
Ethnic Group Membership
Students from different ethnic groups derived from the TRUCCS data survey
(2004) and created for the analysis based on LACCD student population.
The Intersegmental General Education Transfer Curriculum
This program-often referred to as the “core transfer curriculum,” is a general
education program that community college students may use to fulfill all of their
lower-division general education requirements for either the CSU or UC while
enrolled at the community college (IGETC, 1992).
Integration
Defined as the level of involvement to which an individual shares the
institution’s values, and follow the formal and informal rules required for membership
or sense of belonging there (Pascarella & Terrenzini, 1991).
Intent to Transfer
Students who enter the community college with an intent or desire to transfer
to a 4-year university or college.
19
Matriculation
Matriculation is a statewide effort to improve student success in the
community colleges by helping students determine appropriate educational goals,
including transfer (The Seymour-Campbell Matriculation Act AB 3, Chapter 1467,
statutes of 1986).
Parent Education
Level of education or degree achieved by either parent of a student in the
TRUCCS survey (2004).
Persistence
An indicator that a student remained successfully enrolled in college for more
than one semester.
Retention
The institutional measure of student enrollment until end of semester.
Reverse Transfer
Students who return to a community college from a 4-year university
(Townsend, 2012).
Students of Color
Students from different ethnic group membership other than White or Asian.
Transfer to a 4-year Institution
A measure of students who transfer from postsecondary community colleges to
4-year colleges or universities.
20
Transfer Center
All 109 colleges (72) districts have some form of transfer center. Title 5 of the
California Education Code requires all districts to have a transfer center and defines
minimum program standards. It must be a physical location on the community college
campus for students to receive information and learn about the transfer process
(Zamani, 2001).
The Transfer Center Initiative (1985)
Established transfer center in California to provide intersegmentally consistent
assistance to potential transfer students and advises and counsels them through their
community college education and helps in their preparation to transfer.
Transfer Rate
Can be calculated by the ratio of those students who transfer over the perceived
potential number of transfer students who indicate they want to transfer (Banks, 1990).
Transfer Readiness
Students who have the potential to transfer to a 4-year college or university
(Hagedorn, 2004).
Methodology
Assumptions
It is assumed that all subjects who participated in the Transfer and Retention of
Urban Community College Students (TRUCCS) surveys answered the questionnaires
honestly, that questionnaire data were accurately recorded and analyzed by the
original researchers, that the TRUCCS surveys measure what they purport to measure,
21
and that the results of this study can be generalized to other urban community colleges
throughout the United States.
Limitations
1. This study is limited to volunteer subjects who agreed to participate in
the TRUCCS study.
2. Conclusions depend on the reliability and validity of the TRUCCS
questionnaires. No self-report measurement is perfectly reliable or valid.
3. The measurement of counseling utilization, the main variable of interest
in the study, is a fallible measurement.
4. Even if a relationship between intent to transfer and counseling
utilization is established, the relation does not prove causation
Organization of the Study
Chapter 1 of the study presents the introduction, the problem and its underlying
theoretical framework, role of counseling, data source, the significance and purpose of
the study, research questions to be answered, and definition of terms. Chapter 1 also
includes a brief description of the methodology, the assumptions, limitations, and the
organization of the study.
Chapter 2 contains a review of the literature. It addresses the following topics:
How gender, age, ethnic group membership, parent education affects intent to transfer
and counseling utilization.
22
Chapter 3 briefly presents the methodology used in the study, including the
research design; population and sampling procedure; and the selection, validity, and
reliability of the TRUCCS survey.
Chapter 4 includes the findings of the study.
Chapter 5 presents the findings, conclusions and recommendations.
References conclude the study.
23
CHAPTER 2
LITERATURE REVIEW
Introduction
A number of journal articles have been written in the last fifty years regarding
the issues with student persistence and retention in higher education; however lacking
in such literature is the focus of transfer as an integral role of why students are
attending community college and their persistence toward that goal. Community
college students are reported to persist an average of 44% compared to the 27% drop
out rate of university students (Tinto, 1993).
Much of the research is based upon the theories that were conducted at
universities and where the majority of students were not from any ethnic membership
other than White (Bean & Metzner, 1985). With the diversity of students at many
community colleges, these research studies do not address the changing student
demographics. The age, gender, ethnic membership and parent education level of
such students has been changing over the past 20 years and the literature regarding
students of color is rarely found until the 1990s. Although many of the retention
theories were developed in the 1970s, by the 1990s to 2000, the research has been
revisited and redesigned to correlate with the new century of students.
The journal articles highlighted in this literature review include information on
students from different ethnicities as well as theories on retention, persistence and
transfer in the context of community colleges and higher education. For this reason,
the majority of the literature referenced in this review will be from articles from 1970s
24
to the present. Such a synthesis of research theories and findings support the research
questions of this study and allow for implications toward future research in areas of
retention, persistence, transfer and community college counseling.
Documentation
An electronic search was conducted for articles using terms such as retention,
persistence, student attrition, minority students, low-income students, community
college, 2-year college, community college counseling, transfer, transfer rates and
intervention strategies to find the following research studies to review relevant to this
topic of intent to transfer. Such search engines as ERIC, PsychINFO, NCES and
California Community College Chancellors databases, and a manual search of
hardcover books written on retention, college advising, and at-risk student
interventions booklets were tapped. The searches showed multiple factors that may
affect a college student’s retention and ultimate goal of transfer such as the variables
of (a) gender, (b) age, (c) ethnicity, and (d) the nontraditional student.
Background of Study
In the research of college student retention and persistence, there are five
theorists that are often referenced in this area. Such theorists are Vincent Tinto (1975,
1987/1993) and his model of student retention, Patrick Terenzini and Ernest
Pascarella’s (1985) longitudinal and institutional sample model of student-faculty
informal contact, student’s educational choices such as decisions to stay or leave and
diversity experiences, and John Bean’s and Barbara Metzner (1980) conceptual model
of student persistence which is dependent on cultural, academic and environmental
25
factors and social integration. Additionally, Alexander Astin (1984/1993/1996)
creates another model of student involvement and persistence. His theory relies on the
basic idea that if students are involved both academically and socially in their college
experience, they will be successful in persistence and retention. Astin’s belief is that
the student must be involved in all facets of college life with a relationship with
faculty inside and outside of the classroom which also influences persistence.
Similar to Astin (1984/1993/1996), Tinto’s (1975) model for college student
attrition believed that student’s tendency to stay in college was related to the degree to
which the student felt integrated into the social and academic life of the college. Bean
and Metzner (1985) followed Tinto by developing developed the next major
conceptual model of student attrition and how it relies heavily on socialization.
Furthermore, Terenzini, and Pascarella (1977) theorized that the greater the students’
involvement in the life of the college, the grater the likelihood that they will persist.
These models and theories are very similar because their belief of students persisting
in college is greatly related to whether the student had success integrating into the
system academically and/or socially. These theories may all apply to community
college students yet the circumstances, educational, cultural experiences; variables of
ethnicity, age, and parent education level, can affect integration and persistence in
college. For the purposes of this review, each one of these variables will be explored
in the aforementioned studies.
26
Tinto’s Model of Student Retention
Tinto (1987) states that new college students adopt or at least learn to adopt the
behaviors of the college community by associating with other college students, faculty
members and other college staff. Tinto’s theory of student departure is a longitudinal
and interactional model of institutional impact that seeks to understand college
withdrawal process. He theorizes that students enter a college or university with a
variety of patterns and behaviors of personal, family and academic characteristics and
skills, including initial assumptions and beliefs with respect to college attendance and
personal goals. The adopted behaviors are both formal and informal by way of the
classroom activities and instruction and through extracurricular activities, college
activities and athletic games, residential dorms or living environments, fraternities and
sororities. The students, who are most successful according to Tinto, accept the
beliefs and norms found at the college. How well the student acclimates to the college
is dependent on the student’s integration. The students who come from different
cultures and communities of norms and beliefs may have some difficulty with the
transition than other students, familiar already with such college norms. According to
Tinto, students who are from economically disadvantaged and minority students are
generally not prepared for the change from their home environment and prior cultural
community into the college community.
Tinto (1993) reported that for such students, first year drop-out rate is 26.8% at
4-year institutions and 44% at 2-year colleges. Academic and social experiences and
connections during the first weeks or first semester of college strongly influence
27
student’s integration and decision to remain in college. These experiences ultimately
affect student persistence in college, positively or negatively. Tinto (1993) stated that
students must feel a sense of belonging and connection within the campus environ-
ment and culture to stay in their chosen institution. Tinto’s model on retention is
influenced by a student’s goals, commitments, and academic and social integration. A
counseling center that is concerned about the lack of social interaction of students may
provide a sense of belonging or resource for the student to become involved.
Tinto (1984) also stated that new college students adopt the behaviors of the
college environment by connecting with faculty, students, and other college staff.
However, typically students from different backgrounds and ethnicities will transition
differently to the college environment. This especially relates to community college
students who are diverse and come from different cultures and ethnic backgrounds.
Their transition reflects on the student and the behaviors that the student will or will
not adapt during the first semester or longer than 1 year, and the services that the
student utilizes either socially or academically with peers and with faculty.
Astin’s Model of Student Involvement
Alexander Astin (1984/1993/1996) created another model of student
involvement and persistence. Similar to Tinto (1984), Astin (1984/1993/1996) also
believed that students are more successful and learn more if they are involved in both
the academic and social experiences of college. However, like Tinto (1984), Astin
(1984/1993/1996) believes that a student must have an active involvement in all areas
of college life which includes: (a) academics, (b) athletics, (c) student activities,
28
(d) student organizations, and most importantly, (e) there must be an established
relationship with faculty inside and outside of the classroom. Astin (1984/1993/1996)
also posits that the quality and quantity of a student’s involvement will influence the
amount of student learning and development which impacts persistence (p. 297). This
is a more detailed view compared to Tinto’s (1984) model and truly places the
responsibility on the student. Furthermore, Astin’s (1984/1993/1996) model believes
that the focus should be taken off the course content and put on the student which
would increase student involvement and more time will be committed to the learning
process. Astin’s model is a more holistic approach which focuses on the behavior and
motivation of the student which is more individualized toward the method of
persistence.
The argument of Astin’s (1984/1993/1996) model is that the motivational and
behavioral factors could be somewhat burdensome for college students because of the
transitional stages, especially with minority students to get involved academically and
socially on campus. However, in contrast to Tinto (1984) and Astin’s (1984/1993/
1996) models, Pascarella and Terenzini (1991) give emphasis to the importance of
academic integration utilizing measured variables that include grades, academic
development, peer group interaction, extracurricular activities, and relationships with
faculty. The difference of Pascarella and Terenzini’s model is the psychological
approach compared to Tinto (1984) and Astin’s (1984/1993/1996) sociological
approach which offers a more comprehensive evaluation on retention especially
among more diverse populations such as the community college.
29
Pascarella and Terenzini Model of Student Persistence
Pascarella and Terenzini (1991) completed and published their synthesis of
nearly 2,600 studies on the impact of college primarily in the 1970s and 1980s, hence,
believed that the factors that facilitated student growth and development had a wide
range of outcomes. Over time, the research done in the 1970s and 1980s, was
reviewed and revisited to see the affects in the 21
st
century and the impact of college
on today’s students. According to Pascarella and Terenzini (1991), “traditional”
White undergraduates, ages 18-22, who attended 4-year institutions full-time, lived on
campus, did not work and had few, if any, family responsibilities and the studies done
on those students has changed and does not reflect the diversity of the community
college student and the nontraditional student which varies in age, work response-
bilities, ethnicity, gender, full or part-time attendance (or even interrupted), and
resident versus commuter status in estimating the impact of college (p. 2).
To some extent, the research from the 1990s attempted to be more diverse, yet
there was still a bias of studies that reflected the student populations of those
institutions that employ the majority of scholars doing research on college impact and
retention (Pascarella & Terenzini, 1991, p. 2). Because their focus was primarily on
freshman and students of traditional age and background, researchers analyzed
specific educational choices, such as decision to attend college and the intent to
persist. Research on college impact was and still is significantly underrepresented
The literature on college impact was estimated to be only reflected in about 5% to
10% of research according to Pascarella (1999). Nevertheless, the logic of the models
30
adapted toward retention in college has evolved from studies of traditional-age,
middle-class students without fully considering the diverse patterns of choice related
to the diversity of experiences across different groups of students.
The literature written on college students in the 1990s has shifted focus in this
century to now focus in important ways of the changing, and increasingly diverse,
national undergraduate student body (Pascarella & Terenzini, 2005). The research
findings from the 1990s reflected a conditional effect, when different kinds of students
benefit differently from the same experience. The literature in the 1990s also
evidenced an expanded notion of the kinds of higher education institutions worthy of
study. Although the women’s colleges and historically Black institutions reflected
continued change and more sophisticated evidence, the most dramatic change is
evidenced in the community colleges.
According to Pascarella and Terenzini (2005), between 1978 and 1991,
enrollments in community colleges increased by 31% versus 23% for 4-year
institutions, and community college enrollments were expected to increase at least
11% in the 21
st
century (p. 2). In 1996, community college constituted about 28% of
all U. S. colleges and universities and about 39% of all public institutions, and these
colleges enrolled about 37% of all U. S. undergraduates and about 50% of all
undergraduates in public institutions (Callen, 1997; Terenzini, 1998). Such change in
demographics form the base of the aforementioned models of those to follow and
include a theme of student and faculty interaction which influences the decision of a
student to remain in college.
31
A central theme suggested in Pascarella’s (1980) model which relates to the
theories used in this study, show that the interactions between students and faculty,
will be formed by the student’s background characteristics and educational goal
commitments, and the institution’s characteristics and mission. The student
background characteristics include (a) gender, (b) ethnicity, (c) socioeconomic status,
and (d) high school academic success. Student educational goal commitment refers to
the importance the student places on graduating from college and the institutional
characteristics include faculty, cultures, classroom experiences, peer-culture
involvement, the policies of the college, extracurricular and social activities.
The main contribution of Pascarella’s (1980) model is that it provided a
conceptual framework for the effect on the student experience in the college and the
influences of these interactions informally and formally. The model is based on the
informal and social interactions between the faculty members and students which
occur early in the freshman year with socialization to college being finalized by the
end of the first academic year. The interactions, in turn, support the students’
educational and social experiences positively or negatively, which also influences the
student’s educational outcome to stay or leave the college. These influences have
impact on student change or development into the college culture, “within-college
effects.”
However, adapting the model to community college and interactions with
students is dependent upon the informal and formal interactions of faculty and the
institution. Bean and Metzner’s (2005) conceptual model also addresses the
32
background characteristics of ethnicity, varying socioeconomic factors and academics
of students who may not have been as academically prepared than students from a
university, however, the conceptual model still addresses the student socialization and
interaction with faculty which occurs by the end of the semester or first year does
influence student persistence in college. With students of color, Bean and Metzner
(2005) stated that such students may not be comfortable with asking questions to a
faculty member, initiation from social peer groups may be reinforced to help students’
interactions, and the students may take longer than one semester or a year, if at all to
speak to faculty, compared to White students.
In summary, providing a conceptual model of change for the students of
diverse populations and the variables which include (a) gender, (b) age, and
(c) ethnicity can influence the interaction with faculty. The interaction of the student
and faculty inside the institution and by the normative influences of peers, can also
influence another set of variables that include the frequency and contact of students’
interactions with major socialization influences on campus, and the quality of effort
which is also shaped by the student’s experience positively or negatively and
ultimately affects the decision to stay or leave the college campus.
Bean and Metzner Model of Student Persistence
Bean and Metzner (1985) developed a model conceptualizing student
persistence as dependent on background, academic variables, and environmental
variables such as employment and finances, as well as social integration on or off the
campus. The literature throughout the past century has consistently revealed that older
33
students, part-time students, minority students, and working adults have higher drop-
out rates. For example, student retention over shorter time periods of 1 year or 2
semesters does not show that students who temporarily stop out can still have a
successful experience later if they return (Bonham & Luckie 1993; Grosset, 1993).
According to Bean and Metzner (1985), they believe that the problems of
community college drop-out status stems from the great diversity of the students
enrolled. This diversity is created by: (a) students who intend to transfer to a 4-year
university who may transfer before completing the program they are enrolled in;
(b) students who enroll in technical training and who after a course or two in technical
fields, such as computer programming or accounting, leave the college; (c) students
who want skills, and after they obtained the level of skill demanded by their employer
or prospective employer, leave before completing the course; for example, computer
and secretarial programs where students leave when they reach a certain level of
typing, or word processing skill; (d) students who are simply curious about a subject,
also called personal development, and leave when they feel they have satiated that
curiosity (p. 394).
While transfer is not the sole goal of all community college students, it is the
desired goal of at least 75% of students, thus the importance of looking at this
population and their intent to transfer matters in persistence within the community
college system.
Bean and Metzner (1985) offer a more detailed model of the effects of
students’ noninstitutional lives on persistence such as the academic and social
34
communities within an institution and the external environment of family, friends and
other commitments that places its demands on students in ways that greatly influence
the student’s institutional worlds. In 1991, Pascarella and Terenzini found that it is
essential for student interaction with faculty and such interaction is related to
increasing student retention, especially in the freshman year. This interaction not only
includes formal structured experiences in academic settings such as classrooms, labs,
work groups but also includes informal contact with faculty outside of these settings.
This can also be related to counselor contact. They believe that non classroom
contact, and particularly, the frequency of interactions with faculty matters; for
example, to discuss academic matters.
Other than the studies thus far reviewed, there are conflicting findings among
many of the theories as to whether gender, student goals, and contact with faculty can
be related to student persistence and transfer. These studies have revealed that older
students, part-time students, minority students, and working adults have higher drop-
out rates (Bers & Smith, 1991; Clagett, 1996; Feldman, 1993; Voorhees, 1993;
Windham, 1995). In addition, student transfer was not included in many of the studies
and theories described in the literature. However, the theories on retention relates to
goals which includes transfer, and persistence and also can provide new insights and
influences that affect the many variables among community college students.
These central themes of this study and literature review include the correlations
of the variables of transfer, gender, age, ethnic group membership, counseling
utilization in community college. Nontraditional students make up approximately
35
40% of all college students (Lundberg, 2003). The nontraditional student includes
students over the age of 23, primarily female, a minority student of different ethnicity,
commuters, students enrolled part-time, almost exclusively in need of financial aid,
work over 20 hours off campus and have limited time available for on-campus
involvement(Bean & Metzner, 2005). The role of academic and social involvement
among non-traditional students is very unclear for such students. The studies based on
student experiences and connections consistently support the role of academic and
social involvement (Astin, 1993; Hagedorn, & Terenzini, 1996; Pascarella &
Terenzini, 2005; Tinto 1987/1993). However, such studies were based primarily on
the experience of White, middle-class students younger than 23-years-old, so
understanding the community college students, also known as the nontraditional
students may have some limitation yet the theme of student and faculty interaction,
which is part of the academic and social involvement is crucial to the student in spite
of the students’ nontraditional or traditional status (Terrenzini & Pascarella, 2005).
Although the diversity and nontraditional student demographic change is a
concern for, community college’s staff and faculty members at all levels, community
college counselors are responsible for assisting these students with academic
preparation, connection to the college and information (Ray & Altekruse, 2000,
p. 423). Counselors are available to provide academic and social support which
includes counseling, career development, advising, and orientation (Coll & House,
1991). Coll (1993) found that community college counselors perceived the severity of
36
students’ academic and personal problems to be increasing, and these counselors
reported spending a significant amount of time responding to these needs (p. 425).
In this literature review, the variables of transfer, counseling utilization, age,
gender and ethnic group membership will be examined to show how the conceptual
model and retention theories impact these variables in the community college.
According to the literature from the 1970s to the present, the traditional student of age
18-21 has changed and more females are attending community college than males.
These variables have created a change from the traditional community college student
who was typically male, White and age 18-21 is now nontraditional of age 24 or older,
female and a student from a different ethnicity such as Hispanic, African American or
other than White. The variable of age is important because the varying age groups of
community college students. The traditional student is no longer age 18-21, and the
vast majority of students include ages 24 or 25 and older. The variable of gender
shows that the majority of students at a community college are more likely females.
The ethnicity of students is very diverse at community college and all of these
variables affect transfer and counseling utilization. However, this study shows that no
matter the gender, age, ethnicity, that community college students want to transfer to a
university.
Transfer
One of the primary roles of the community colleges is transfer, which prepares
students to attend a community college and take courses necessary for transfer to a 4-
year university or college. A main reason for students to attend community college is
37
the access that is provided to transfer and although any student has the opportunity, the
transfer rate from community colleges is very low. According to the National Center
for Education Statistics, a study was conducted and the results show that a uniform
definition of transfer does not exist and varies in transfer numbers (Bradburn & Hurst,
2001). The research also found that transfer is difficult to measure due to the complex
nature of tracking student progress and the differences in institutions (Hagedorn, 2004;
Harbin, 1997; Helm, & Cohen, 2001; Surette, 2001). Another concern or the
difficulty to measure transfer among community college is the non-related counts of
transfer to generate a ratio of current year transfer to current year of enrollment, often
resulting in a low percentage rate of transfer. The estimates in a large urban
community college district of Los Angeles indicate that only 5% to 8% of the total
student population transfer to a 4-year institution (Los Angeles Community College
District, 2001).
According to Hagedorn (2004) and Nora and Rendon (1990), contrary to low
transfer rates, students have high aspirations and intent to transfer which includes
modest GPA’s, low college assessment scores, and placement, obstacles in the system
and students also have a desire to obtain a graduate degree such as Master’s Degree
and beyond. Thus, the intent to transfer can be a measure of transfer when students
indicate a desire to transfer and can provide a reasonable estimate of students as the
denominator when used with taking specific transferable English and Math courses,
measured longitudinally, using a combination of both or measuring the number of
students who intend to transfer compared to those who do not. The transfer rate is
38
commonly calculated as the ration of those students who transfer over the potential
number of students who intend to transfer (Banks, 1990; Hagedorn, 2005).
Inconsistent measures of transfer arise when attempts to define which students qualify
as true potential transfers. Banks (1990) used an analysis of credits to measure a more
accurate transfer ratio. Students were considered potential transfers based on the
number of transferable course credits completed. Most transfer rate measures seek to
eliminate those students who intend to transfer but will likely not be able to do so
(Hagedorn, 2004). Thus, the reality that many students aspire to transfer and progress
toward a goal is obscured measure of transfer defined in most community colleges.
Another reality of transfer is when colleges measure transfer and it ignores the
students who are on the transfer path, but who do not complete the process.
The argument can be mentioned that education and persistence still provides
benefits even when it does not measure transfer, yet community colleges should
ultimately not ignore the students who intend on transfer and do not reach their goal .
According to Hagedorn (2004) transfer is not linear, it is convoluted, zig-zag, or flows
in the opposite direction (p. 227). Many students also participate in a “reverse
transfer” process, moving from a 4-year university to a community college, then
transfer back to the university. Other types of transfer students which affect the
transfer rates are the students in high school who are dual enrollment which has
become a form of nontraditional enrollment, and has further threatened the integrity of
transfer measures from high school to community college to university (Hagedorn,
2004). This is rare among urban students thus exception to the rule. The account-
39
ability of the community college to address their role in transfer and measure their
outcome is still lacking and sorted.
Transfer in California
In June 2004, the California Postsecondary Commission (CPEC) developed the
“Accountability Framework” for California public higher education. Essentially, it
created a framework with 17 measures of progress toward general goals: Student
Preparation for College, Affordability and Access, Student Success in Progressing
through College and Public Benefits of Postsecondary Education, and it provided a
baseline of measurement for regular measurements of transfer student and time-to-
degree. The 1960 Master Plan for Higher education was developed to create a
seamless transfer of community college students into the state’s public and
independent baccalaureate degree, granting institutions a means of access to those
students who did not get accepted initially from high school (CPEC, 2006). The
master plan recognized that the transfer function is an important component of access
in California higher education because many students cannot afford the average cost
of attendance at a CSU or UC campus, which is more than $20,000. This master plan
also addresses the independent and private baccalaureate college also but does not list
the higher costs of these institutions. On average, the students who intend to transfer
have factors both academically and financially that puts degree attainment at risk.
Colleges do not have full control over the transfer function; ultimately the
students decide when and where they are going to transfer yet the universities such as
University of California (UC), and California State University (CSU), have admission
40
requirements, general education patterns, major course preparation and course
offerings, impacted programs and financial, academic and cultural pressures that can
affect transfer. These factors include course-taking decisions by students such as
(a) enrolling part-time for some academic terms, (b) changing majors, repeating earlier
courses to improve grade point averages and grades, (c) or stopping out of the college
for one or more terms. In 1988, California passed assembly Bill 1725 that promoted
governing boards and academic senates from the California public postsecondary
segments (University of California, California State University, and the community
colleges) to mutually “develop, maintain, and disseminate a common core curriculum
in general education for the purpose of transfer” (Board of Governors, California
Community Colleges, 1991, p. 2).
The result was a statewide agreement for articulation between the California
community colleges and the public 4-year universities. The IGETC, (pronounced by
educators as eye-get-see), the state identified six to seven distinct areas, consisting of
modules of several courses, that when completed with a grade of C or better generally
satisfies the lower division education requirements for transfer to the public university
system, UC and CSU. The CSU general education pattern consists of six modules and
the UC requires seven with an additional requirement for the Language other than
English module, equivalent for students who did not take 2 years of high school
foreign language (Board of Governors, CCC, 1991). Completion of the IGETC and
CSU general education patterns does not guarantee admission but it does provide a
framework of transfer-level courses that provide college credit at the community
41
colleges and certifies students from taking additional lower-division or general
education courses at the 4-year university. Careful advising is still recommended and
a priority for students with majors such as science, engineering, pre-med and business
programs, because the UC’s may have prerequisite and major courses that the students
need to prioritize over general education. This can be another factor that affects
transfer because the CSU requires general education yet the UC, may still not use
IGETC with some of the aforementioned majors. Students may get confused if not
advised correctly on their major and if the UC or CSU varies on the general education
and major courses for transfer.
According to the California Postsecondary Education Commission (2006),
other factors that affect students from transfer and graduation are increases in student
fees and costs of attendance, which for the UCs, the fees have increased 64% to
$6,312 and CSU fees increased 55% to $2,916; housing, transportation and living
expenses also continue to rise in the 21
st
century (CPEC, 2006, p. 5). There are a
variety of reasons that students decide whether or not to persist, graduate and transfer
to universities, such as the changes in the student’s declared majors and deficiencies in
prior major coursework preparation may require the student to take additional courses
at the community college or prevent admission based on the impacted major and
competitiveness of the program. The state’s economic recession from 2001-2904
resulted in budget cuts and impacted college operations including reductions in course
sections, reductions in student support services, and early faculty retirements (p. 5).
42
The student’s personal and social choice which includes events and
circumstances in student’s lives can also affect enrollment decisions and the ability,
willingness, and commitment to continue in college. The changes in financial
assistance such as increases in the student loan and student and family contribution
portions of financial aid, paired with reductions in the share of the total aid package,
might have affected student persistence. The research on transfer in community
colleges indicate that transfer is a difficult process. The barriers mentioned and
identified in the literature review stem from two sources such as coming from student,
the personal and social decisions to attend college and transfer and the other source as
institutional, the factors coming from either community college or the intended college
or university of transfer (Hagedorn, 2004). The support and interaction of faculty and
counseling advising can help with the barriers that exist with students, especially the
connections personally and institutionally.
Transfer service counselors and providers engage students via feedback on
educational progress, connection with college and provide additional services through
collaboration with university partners can greatly benefit students (De Tro, 2005).
While studies have found some demographic differences in student performance after
transfer, the behavioral differences that can be potentially changed through advising
and support services merit particular attention by the institution’s administration and
mission. For example, knowing that community college students who transfer with or
without an Associate degree are most likely to complete a Bachelor’s degree is the
shortest time after transfer. This could be useful for community college counselors,
43
faculty, administration, 4-year college admissions and enrollment, directors and
advisors (De Tro, 2005).
Counseling Utilization
Counseling services have an influence on students’ academic and social
integration and their ability to teach and perform the duties of a faculty and teacher,
both crucial areas in student persistence (Pascarella & Terenzini, 1991). The
collaboration between faculty and counseling services staff is crucial for the continued
viability of college counseling services (Archer & Cooper, 1998). The literature
continues to state that the collaboration between faculty and counseling services still
needs to continue proactive communication efforts to positive promote student
development (Archer & Cooper, 1998). Students need to seek out counseling and
faculty at community college to understand the degree attainment requirements and
transfer process.
Keeping students informed about the transfer process is an important role of
the community college counselors. The utilization of counseling and community
college student transfer services is designed to inform, advise and guide students
seamlessly through the transfer process and increase transfer. However, students are
not seeking out counseling and faculty, despite the importance of the faculty contact
and the guidance to help the student academically, career-related and socially. The
counselor advises the student on course selection toward their goal of personal,
vocational, academic, career, and transfer. The counselor can help the student
interpret the various general education transfer patterns such as the CSU general
44
education and the Intersegmental General Education Transfer Curriculum, IGETC.
Community college counseling provides resources ranging from technology and
registration to intensive personal and academic contact, and navigation through the
system. The utilization of counseling is still underrepresented in most literature yet
the information is valuable for students to follow transfer guidelines and requirements
from the 4-year universities and independent, private universities.
Counseling can provide the information necessary to be successful in college.
Counseling also known as advising is a specific process using prescriptive, develop-
mental and integrated advising approaches (Gordon, Habley & Assoc., 2000). For
example, counselors can assist in helping students make appropriate decisions about
developmental or remedial courses or help students understand the effects of outside
wok commitments on the achievement of their educational goals. Tinto’s (1975)
theory of student integration relates informal academic experiences such as
interactions with the faculty or staff during non class periods such as office or after
hours, which can include a dialogue between the student and the faculty and focus on
course content, academic advising or career related information to the successful
integration into college life. The faculty and staff connection is the central theme of
the literature and especially includes the counselor. The counselor is a faculty
member that has the ability to create the formal and informal connections with the
student as mentioned in the theories from Tinto theory on retention, Pascarella and
Terenzini (1979) conceptual model, Astin’s (1984) student and faculty involvement
45
and Bean and Metzner (1985) social integration model. In summary, counseling and
advising has an influence on student’s involvement and connection in college
Variables of Community College Students
(Age, Gender, Ethnicity, Nontraditional)
The following independent variables that were researched in the study are
(a) gender, (b) age, (c) ethnicity which includes students of color, and (d) parent
education level of the community college student. Students from different ethnicities
or minority groups have been the focus of retention research because of their high
attrition, drop-out rates, which also affects transfer.
Ethnic Group Membership
Students of different ethnic membership or students of color are also
categorized as nontraditional students of color which includes Hispanics, African-
Americans, and Native Americans. Students of color are also called minorities and do
not include White or Asian students. Such students entering college have a myriad of
challenges and obstacles, which need a period of adjustment and transition. Minority
students, which often are the majority students at most community colleges progress at
different rates and lack the social and academic skills to understand the college
environment (Hagedorn, 2004). Students of color, despite adversity, have the ability
to embrace their reality about the challenges they face and acclimate to the
environment and culture of college by getting connected and meeting the same
requirements of as the general student population. The theorists included in the
literature found that it depends on the student’s decision and the institution itself to
46
experience college positively or negatively. The cultural change that students of color
experience is related to the connection of two worlds, such as one that is a new culture
of education and the other which is their family support system. Thus, the socializa-
tion process into their new college environment and their de-socialization from family
and friends has strong potential to be incomplete and disconnected (Pascarella &
Terenzini, 2005).
Tinto viewed the two worlds that students of color experience as colleges and
universities as organizations composed of two interacting systems: (a) an academic
system and (b) a social system. The first time student entering into college, especially
if a minority student, may have much more difficulty with transition based on family
background, skills and abilities, and prior education of the student and his or her
parent. Pascarella and Terenzini (1991) also note the “absence of studies dealing with
identity development among Black or other minority students” (p. 166).
The absence of the studies in the 1990s on minority students has forced faculty
and administrators to apply identity development theories from studies of White
students, often not including women, to all students regardless of gender, race,
ethnicity, or other differences. Many studies of minorities may also put them in the
category of “nontraditional students” along with commuters, part-time students,
students who work many hours, first generation college students and students of color
(Bean & Metzner, 1987). Minority students are also viewed as nontraditional students
because of the diversity, the many variables and features they possess as mentioned
47
before of their gender, age, ethnicity, experience at the institution and at home, as well
as financial and work obligations.
Gender
The female enrollment is reported at 58% of the community college student
population, compared to 55.4% in national 4-year colleges, including state colleges
and research universities (CPEC, 2002; Los Angeles Community College District,
2001). Female students have high aspirations to transfer to a 4-year university, thus
requiring transfer level course completion and student success ratios of C or better in
the courses. Thus, the success ratios for transfer-level courses taken at community
college, favors White males and females while minorities fall behind (Lester &
Hagedorn, 2004).
Age
The community college student is different from the traditional student of the
past, such as the typical White middle-class male which ranges in age from 18-24, also
described as “Traditional” (Coll, 1993/1995). The students older than the traditional
college student is typically older than 25. Persistence rates among older students are
lower and usually the student attends part time (Naretto, 1995). However, a
supportive social environment relates positively to the retention of older adults (Ashar
& Skenes, 1993; Naretto, 1995). Richardson (1994) asserted that there are
misconceptions that older students generally lack academic skills and abilities.
48
Level of Parent Education of Community College Students
The community college student population has changed since the 1990s and
the Parent education of students can influence the likelihood of the student to persist
and graduate. Students whose parents did not attend college, also called first-
generation college students may be less likely to persist due to a lack of support from
home (Hoyt, 1999). Parents who have not earned a 4-year degree may not fully
understand or appreciate the value of higher education nor expect their children to
finish their degree. These parents often lack the economic means to assist their
children financially. According to Hoyt (1999) parents without college experience
may be less informed about the process and less able to guide and support their
children through the college experience (p. 60). The parent education can ultimately
have an influence on students’ persistence in college and transfer to a university.
Overall, the variables discussed in this literature review, gender, age, ethnicity,
parent education, have a relationship with transfer and counseling utilization. The
gender of a student at a community college is more likely to be a female than male due
to the changing demographics. The student population is a majority of females at
community colleges. The age of students at community college still includes ages 18-
24, yet the majority of students are typically 25 or older based on the literature. The
parent education of students may influence the decision of transfer to a 4-year
university; however, the literature shows that students want to transfer at any age, any
gender depending on their experiences socially, academically, informally and formally
at the community college. The faculty connection with students ultimately has an
49
impact with students informally and formally to help the students stay or leave the
college and feel like they belong, which is an indicator for transfer.
Implications for Future Research
Although many community college students have a desired intent to transfer,
the reality is that few make actual progress toward achieving that goal. The TRUCCS
research indicates that few students are taking required transfer modules, even if their
goal is to transfer (Hagedorn, 2004). The literature revealed that the accountability
from community college to measure transfer is difficult and obscure. It raises the
awareness of the low attention given to transfer at community colleges specifically of
nontraditional students or students that reflect the new century. Also, the literature
addresses faculty but still fails to mention counselors as faculty, and the same role they
play as an advisor because the majority of literature, is still predominantly done at the
university level. Community colleges are not accountable to measure their transfer
rates.
The literature also discusses that the barriers to transfer affect students and
retention. The research does address the need to understand the role of finances in
student choice, persistence and transfer, while also focusing on understanding of class
differences in students’ experiences with financial factors in their enrollment
decisions. Many worry that financial problems may force low-income students to
drop out; however, persistence is affected by a variety of factors as well as income.
This would be a future study for educators to address in the literature and research.
Another factor that would also increase transfer and graduation rates amongst colleges
50
would be the implementation of intensive counseling and faculty support groups and
an intensive orientation given for all students who attend community college.
Counseling and advising is either based on the student decision or mandated
probationary guidelines for academic probation students. The stigma attached to
counseling, thus creates a negative counterintuitive connotation to students who would
otherwise be more successful if understood how counseling can affect transfer and
retention in college.
Conclusion
The literature review focused on the theories of five prominent theorists,
compared similarities and differences of each theories, and provided critical
perspectives to various components of the theories. The background of the study
reviewed the application of the theories to community college students with specific
attention to the variables of different students attending community college from the
past such differences as (a) gender, (b) age, (c) minority students, (d) parent education,
and (e) how these variables relate to counseling utilization and intent to transfer. The
final section of the literature review examined the influence of counseling and faculty
interaction and transfer. All the literature confirms the research design of this study
that explores correlations of selected demographic variables, counseling utilization,
and intent to transfer. The utilization of counseling and advising, which is also faculty
interaction could lead to increased rates of retention, persistence and ultimately
transfer if the students make the decision to make the connections academically and
socially.
51
The review of the literature summarizes the importance that students who
utilize counseling and build a relationship with faculty have a more positive outcome
academically and socially especially with their decision to stay in school and transfer.
It is also important to know that the students who make academic and social
connections with faculty, counseling may have a positive outcome in regards to
transfer. However, the community college students who intend to transfer have shown
that making connections with faculty, and who utilize counseling and/or faculty, need
to know how important this can affect their goals, especially if the student comes from
varied factors of (a) gender, (b) age, and (c) parent education. In conclusion, the
review of the literature does not support that students are likely to be successful in
their desired goal at college if they seek out faculty interactions.
The methodology and research design for this study includes the variables that
address the nontraditional student and most of the research is still adapting to the
diverse student populations at community college, therefore, the findings of this study
may be important to recognize large sample of students who intend to transfer, it may
highlight the need for students to seek out support from counseling and faculty
interactions informally and formally to succeed in their actual goal of transfer. This
may likely increase the rates of transfer in community colleges to 4-year universities.
52
CHAPTER 3
METHODOLOGY
The main purpose of this study is to determine the relationship of intention
to transfer and the utilization of counseling among students of different ethnicities.
Included in this chapter are the research questions on the relationships of key
demographic variables such as (a) gender, (b) age, (c) ethnic group membership,
(d) parent education, and (e) intent to transfer and counseling utilization. Also
included in this chapter are the sampling procedure, population, instrumentation,
and procedures for data collection and analysis. The methodology in this study is a
correlational design to determine if students who have the desire to transfer to a 4-
year college or university are more likely to utilize counseling in their first year of
study in community college. The following nine research questions are the focus
of this study,
Research Questions
1A. Is gender related to intention to transfer?
1B. Is age related to intention to transfer?
1C. Is ethnic group membership related to intention to transfer?
1D. Is parent education related to intention to transfer?
2A. Is gender related to counseling utilization?
2B. Is age related to counseling utilization?
2C. Is ethnic group membership related to counseling utilization?
53
2D. Is parent education related to counseling utilization?
3. Is intention to transfer related to counseling utilization?
Research Design
The data collected is from the Transfer and Retention of Urban Community
College Students Project (TRUCCS). The TRUCCS Project was a 5-year longitudinal
study of 5,000 community college students within the Los Angeles Community
College District (LACCD). The TRUCCS Project was initially funded by the U.S.
Department of Education, and recently supported from benevolence of the Lumina
Foundation (Hagedorn, 2003). TRUCCS (2003) researchers administered three (one
initial and two follow-up) surveys to community college students at the nine colleges.
The research design is a correlational and only the initial survey results were used in
this study. The independent variables are (a) gender, (b) age, (c) ethnic group
membership, and (d) parent education. The dependent variables are counseling
utilization and intent to transfer.
Population and Sample
The sample for this study includes 5,010 community college students in a
large Southern California community college district that participated in a 5-year
longitudinal study that was conducted by researchers from the University of
Southern California (USC) and the University of California at Los Angeles (UCLA).
The TRUCCS study team examined various aspects of transfer and retention of
urban community college students. The 2001 survey was composed of a 47-item
survey to identify the goals of community college students in an urban environment.
54
The TRUCCS initiative was designed for urban community college campuses with
diverse student enrollments and backgrounds. For purposes of this study, the
responses to questions on (a) gender, (b) age, (c) ethnic group membership, and
(d) parent education are examined to answer the aforementioned research questions.
The two outcomes of primary interest are intention to transfer and counseling
utilization.
Surveyed students were self-reported to: (a) be from the age of 16 on up to a
category listed as 55 or older; be Asian, African American, Hispanic, or Caucasian;
(b) be of educational backgrounds that varied from no-post secondary experience to
some graduate work; (c) be speakers and writers of some English or only English;
(d) have had at least one unit on up to more than 60 accumulated college units; and
(e) work full-time, part-time or be unemployed.
In the initial survey, 4,968 surveys were returned. The survey was
administered to 300 English courses in the Los Angeles Community College District
(LACCD). The total number of students reporting their ethnicity was 4,852, for a
difference of 116 who did not respond. For purposes of this study, ethnic
membership was grouped as Asian, Black, Hispanic, White, Mixed (students
reporting multiple ethnicities), and Other. According to the TRUCCS data, Asian
students comprised 11.2% of the sample, Black students 13.5%, Hispanic, 44.8%,
White 10.9%, Mixed 10.4% and Other, 6.8% of the student population within the
Los Angeles Community College District. Students were coded “yes” on parent
education or “no” if either one of their parents had completed some college. The
55
data indicated 42.1% of the students said, “Yes” to at least one parent with some
college education. The age of students attending Los Angeles Community College
District was coded into ten age groupings from 16 or less to 55 or more. The
majority of the students were in age group 21-24 (29.2% of the student population),
30.9% of the respondents were in younger age groupings, and 42.5% were in older
age groupings. Finally, according to the data, 39.2% of the students attending school
in the Los Angeles Community College District were male, and thus, the majority of
students (60.8%) were female.
For this analysis, the total TRUCCS sample was divided into groups of
students who had intent to transfer to 4-year institutions, and students who did not
intend to transfer on the basis of a single survey question (Appendix A, #10). In the
TRUCCS sample of students, almost 74% of the students completing the survey
responded “yes” to their intent to transfer to a 4-year college or university, and the
remainder of 26% of students indicated that they did not intend to transfer. Five
percent did not respond to the question on intent to transfer. Table 1 displays these
results. Table 1 below also shows the percentages of students who indicated yes or
no on the survey of whether they have an intent to transfer while enrolled at the
community college.
The students in the TRUCCS sample also completed a question (Appendix A,
#13) on the survey to indicate whether they had spoken to an academic counselor in
the past 7 days. Students were asked to indicate the number of times with a range
from 0 to 5 or more times. The sample of students in the table was divided into two
56
groups; the number of students who utilized counseling (yes) and compared to the
group who did not (no). Slightly more than 70% of the students responded that they
Table 1. Frequency Table: Students Who Plan to Transfer
Plantran
Frequency
Percent
Valid
percent
Cumulative
percent
Valid No 1242 25.0 26.4 26.4
Yes 3462 69.7 73.6 100.0
Total 4704 94.7 100.0
Missing System 264 5.3
Total 4968 100.0
had not spoken to a counselor within the last week. Thus, more than a quarter of the
students, 27%, had spoken to a counselor within the last week. Four percent of the
students did not respond to this item. These results are displayed in Tables 2 and 3.
Procedure
The Transfer and Retention of Urban Community College Students
(TRUCCS) Project was a longitudinal study of 5,000 community college students.
The initial survey was given to 241 classrooms of community college students from
nine campuses in Los Angeles County from March 5, 2001 to April 28, 2001. The
diversity from Los Angeles Community College District allowed multiple compari-
sons with different groups of students and variables of (a) gender, (b) age,
(c) ethnicity, (d) parent education, (e) intent to transfer, and (f) counseling
utilization.
57
Table 2: Frequencies of Students Who Spoke with an Academic Counselor
Counseling utilization
Frequency Percent
Valid
percent
Cumulative
percent
Valid 0/no time 3430 69.0 72.2 72.2
1 time 765 15.4 16.1 88.3
2 times 272 5.5 5.7 94.1
3 times 125 2.5 2.6 96.7
4 times 47 .9 1.0 97.7
5+ times 110 2.2 2.3 100.0
Total 4749 95.6 100.0
Missing System 219 4.4
Total 4968 100.0
Table 3: Counseling Utilization Recoded to “Yes” or “No”
Counseling utilization
Counsel Total
No Yes No
College no Count 1923 791 2714
% within college 70.9% 29.1% 100.0%
yes Count 1507 528 2035
% within college 74.1% 25.9% 100.0%
Total Count 3430 1319 4749
% within college 72.2% 27.8% 100.0%
All data were coded to identify these variables and the results were tabulated and
analyzed in accordance with the research questions for this study.
58
Instrumentation
The TRUCCS researchers developed a Community College Student Survey
in 1999, piloted the survey in 2000 with a final version approved for administration
in 2001. The final version was titled the initial survey. The initial Community
College Student Survey contained 47 multipart questions regarding college and
related academic and social activities, demographic information (gender, age,
ethnicity, language spoken in college and at home, and disabilities), familial
information (marital and wage-earner status, student status, number of family
members living with the student, mother’s and father’s highest level of education,
and mother’s and father’s current occupations), and the student’s desired educational
goal (ranging from a vocational certificate, intent to transfer, associate and
Bachelor’s degree to doctorate).
Participants were asked to read each question and fill in complete and
accurate responses. Survey question responses included: (a) either/or response
when answering a question such as choice of (a) gender; and (b) marking all
responses that apply for questions that listed multiple items with a frequency
response scale for each item, such as marking one response per line to best match
each statement in a question and write-in responses.
Only a limited number of questions from the TRUCCS survey were used to
formulate the independent and dependent variables in this study. The focus of this
study was on the relationship of (a) gender, (b) age, (c) parent education, and
59
(d) ethnic group membership, to two dependent variables: intent to transfer and
counseling utilization.
Demographic Variables
For this study, the data for four demographic variables were taken from the
initial TRUCCS survey. The variables were (a) gender, (b) age, (c) ethnic group, and
(d) parent education. These variables were derived from questions 28, 29, 30 and 41
(Appendix A for the complete survey).
Gender
Responses to question 28 indicated the gender of students, male or female.
Age
Question 29 asked students: How old will you be on December 31 of this
year? The initial choices were: Seven age subgroups were established for descriptive
purposes: youngest (< 21); middle (21-24) and oldest (over 24).
Ethnic Membership
The ethnic classifications that were used from the initial Community College
Student Survey for this study are shown below: Question 30 (Appendix A) was used
to code students into 22 ethnic groups. Because the original 22 categories, (shown
below) had too small of a sample size in many categories, ethnic group was recoded
into six groups: Asian, African-American, Hispanic, White, Mixed and Other. The
mixed category was used whenever a student chose more than on ethnic group.
60
Chinese Mexican
Filipino Mexican American/Chicano
Japanese South American
Korean Central American
Thai Other Latino/Hispanic
Laotian Alaskan Native
Cambodian American Indian
Vietnamese Other Pacific Islander
South Asian (Indian Subcontinent) Caucasian/White
Arab Other
African-American/Black Pacific Islander/Samoan, Hawaiian, or
Guamanian
Parent Education
Question 41 was used to determine an index of education obtained by each
respondent’s parents in either the United States or in another country. The question is
shown below:
Responses to this question were dichotomized into two groups, students who had at
least one parent who attended college and students who did not.
Dependent Variables
Intent to Transfer
Students who enter the community college with an intent or desire to transfer
to a 4-year university or college is the first of two outcomes in this study.
41. What is the highest level of formal education obtained by your parents
either in the U.S. or in another country? (Mark one in each column.)
61
Father Mother
6
th
grade or less
Junior high or middle school
Some high school or GED
Some community college
Completed community college
Some 4-year college
Completed 4-year college degree
Some graduate school
Graduate degree
I do not know
An intent to transfer index was developed from question 10:
10. As things stand today do you think you will transfer to a 4-year college
or university?
The choices for each statement ranged from “Definitely Not,” “Probably Not,”
“Maybe,” “Probably,” and “Definitely.” For analytic purposes, these answers were
divided into two groups: “No” and “Yes.” The “Yes” group was comprised of
students who answered maybe, probably or definitely. The “No” group was
comprised of students who responded no to transfer to a 4-year college or university.
Counseling Utilization
Counseling utilization was defined by the number of times students spoke to an
academic counselor within the past 7 days. The utilization of counseling variable was
based on question 13 which measured whether or not a student spoke to an academic
counselor while at community college:
62
Approximately how many times in the past 7 days, did you speak with an
academic counselor? The responses of the question were “0, or didn’t have time,” “1
time,” “2 times,” “3 times,” “4 times,” “5 times or more.” For this study, one or more
times were used to indicate “Yes,” on the index of counseling utilization. All other
respondents were coded “No.”
63
CHAPTER 4
RESULTS
Descriptive Results
Shown in Tables 4 and 5 are the descriptive findings for the plan to transfer
variable and the counseling utilization variable. A clear majority of the sample in the
initial TRUCCS survey (73.6%), answered that they “probably“ or “definitely”
planned to transfer to a 4-year college or university. For further analysis, this
variable was reduced to a binary (“yes,” “no”) variable by coding this majority as
“yes.” Table 4 shows the frequencies for the self-report of the number of times a
student met with a counselor within the last week. A clear majority of the students
had not met with a counselor (72.2%) within the last 7 days. This variable also was
reduced to a binary variable by recoding the 27.8% students who reported meeting
with a counselor to “yes” on the recoded variable.
Table 4. Plan to Transfer Frequencies
Frequency Percent Valid percent
Cumulative
percent
Valid Definitely not 224 4.5 4.8 4.8
Probably not 298 6.0 6.3 11.1
Maybe 720 14.5 15.3 26.4
Probably 846 17.0 18.0 44.4
Definitely 2,616 52.7 55.6 100.0
Total 4,704 94.7 100.0
Missing System 264 5.3
Total 4,968 100.0
64
Table 5. Counseling Utilization Frequencies
Frequency Percent Valid percent
Cumulative
percent
Valid 0/no time 3,430 69.0 72.2 72.2
1 time 765 15.4 16.1 88.3
2 times 272 5.5 5.7 94.1
3 times 125 2.5 2.6 96.7
4 times 47 .9 1.0 97.7
5+ times 110 2.2 2.3 100.0
Total 4,749 95.6 100.0
Missing System 219 4.4
Total 4,968 100.0
Analysis of the Research Questions
Research Question 1A: Is Gender Related to
Students Who Plan to Transfer?
Table 6 shows the cross-tabulation of gender and intention to transfer. The
statistical findings indicate that the relationship of gender to intent to transfer was not
significant statistically (p > .05). That is, the proportion intending to transfer was not
different for males and females. As shown in Table 7, 2,023 females and 1,358 males
surveyed planned to transfer. The percentages of students are similar with 75.2% of
males and 72.9% of females who plan to transfer. Although females are less likely
than males to plan to transfer according to the responses given from the survey, the
chi-square statistic of .090 is statistically not significant.
65
Table 6. Gender and Plan to Transfer Cross-tabulation
Plantran Total
No Yes No
Your gender Male Count 449 1,358 1,807
% within your gender 24.8% 75.2% 100.0%
Female Count 752 2,023 2,775
% within your gender 27.1% 72.9% 100.0%
Count 1,201 3,81 4,582
% within your gender 26.2% 73.8% 100.0%
Table 7. Chi-square Test: Gender by Intent to Transfer
Value df
Asymp. sig.
(2-sided)
Exact sig.
(2-sided)
Exact sig.
(1-sided)
Pearson Chi-Square 2.868(b) 1 .090
Continuity
Correction(a)
2.753 1 .097
Likelihood Ratio 2.880 1 .090
Fisher's Exact Test .092 .048
Linear-by-linear
association
2.867 1 .090
N of valid cases 4,582
Note. (a) Computed only for a 2 x 2 table
(b) 0 cells (.0%) have expected count less than 5. The minimum expected
count is 473.64
Research Question 1B. Is Age Related
to Intention to Transfer?
Shown in Table 8 below are the statistical results. The relationship between
age and intent to transfer and age was significant (p = .001). The age group of 16 or
less indicate 80.6% of the students plan transfer. Ages 17 and 18 indicate 76.9%
66
Table 8. Chi-Square Tests: Age by Intent to Transfer
Value df
Asymp. sig.
(2-sided)
Pearson chi-square 226.567(a) 9 .000
Likelihood ratio 218.074 9 .000
Linear-by-linear
association
188.495 1 .000
N of valid cases 4,641
Note. (a) 0 cells (.0%) have expected count less than 5. The minimum expected count
is 6.85.
80.2%, respectively, age 19 is at 84.6%, age 20 at 79.9%, and ages 21-24 79.2%. The
age group of 25-29 indicate 70.8% intention to transfer, 30-39 is at 64.2%, 40-54 is at
54.0%, and the intention to transfer rate for the 55 or more group is 43.3%. It is
important to note that the although the percentages of the older, nontraditional students
from the age groups of 25-55 or more, are lower than those of the traditional students,
they are surprisingly high in that more than one-half of the nontraditional students plan
to transfer.
Research Question1C: Is Ethnic Group Membership
Related to Intention to Transfer?
Shown in Table 9 is the cross-tabulation of ethnic group with intention to
transfer. The statistical findings are given in Table 10. The association of ethnic
group membership and intention to transfer was not significant (chi-square = 10.854,
p = .054). While the proportions for each ethnic group intending on transferring to a
4-year university ranged from 68.8% to 75.8%, these differences could be attributed to
67
Table 9. Cross-tabulation of Age and Intent to Transfer
Plantran Total
No Yes No
Age on
December 31
of this year
16 or
less
Count
6
25
31
% within age on
December 31 of this year
19.4%
80.6%
100.0%
17 Count 6 20 26
% within age on
December 31 of this year
23.1%
76.9%
100.0%
18 Count 17 69 86
% within age on
December 31 of this year
19.8%
80.2%
100.0%
19 Count 102 561 663
% within age on
December 31 of this year
15.4%
84.6%
100.0%
20 Count 133 528 661
% within age on
December 31 of this year
20.1%
79.9%
100.0%
21-24 Count 263 999 1262
% within age on
December 31 of this year
20.8%
79.2%
100.0%
25-29 Count 199 483 682
% within age on
December 31 of this year
29.2%
70.8%
100.0%
30-39 Count 268 480 748
% within age on
December 31 of this year
35.8%
64.2%
100.0%
68
Table 9 (continued).
Plantran Total
No Yes No
Age on
December 31
of this year
40-54
Count
194
228
422
% within age on December
31 of this year
46.0%
54.0%
100.0%
55 or more Count 34 26 60
% within age on December
31 of this year
56.7%
43.3%
100.0%
Total Count 1,222 3,419 4,641
% within age on December
31 of this year
26.3%
73.7%
100.0%
a sampling error. However, it is noteworthy that the White sample reported the
smallest rate for intention to transfer (68.8%) and the African American and Hispanic
student samples reported the highest rates of 74.2% and 75%.
Research Question 1D. Is Parent Education
Related to Intention to Transfer?
Tables 12 and 13 show the results for the cross-tabulation of highest level of
parental education with intent to transfer. Students who have at least one parent, who
attended college, report higher levels of intent to transfer than students whose parents
did not attend college (77.4% versus 70.8%). Table 9 indicates that this difference in
proportions was highly significant (p = .001).
69
Table 10. Ethnic Group Membership and Intention to Transfer
Plantran Total
No Yes No
Ethnic Asian Count 144 378 522
% within ethnic 27.6% 72.4% 100.0%
Black Count 163 470 633
% within ethnic 25.8% 74.2% 100.0%
Hispanic Count 535 1,607 2,142
% within ethnic 25.0% 75.0% 100.0%
White Count 159 351 510
% within ethnic 31.2% 68.8% 100.0%
Mixed Count 121 379 500
% within ethnic 24.2% 75.8% 100.0%
Other Count 90 223 313
% within ethnic 28.8% 71.2% 100.0%
Total Count 1,212 3,408 4,620
% within ethnic 26.2% 73.8% 100.0%
Table 11. Chi-square Tests: Ethnic Classification and Intent to Transfer
Chi-square tests
Pearson chi-square 10.854
a
5 .054
Likelihood ratio 10.632 5 .059
Linear-by-linear association .024 1 .878
N of valid cases 4,620
Note.
a
O cells (.0%) have expected count less than 5. The minimum expected count
is 82.11.
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Table 12. Parent Education by Intent to Transfer Cross-tabulation
Plantran Total
No Yes No
College No Count 790 1,911 2,701
% within college 29.2% 70.8% 100.0%
Yes Count 452 1,551 2,003
% within college 22.6% 77.4% 100.0%
Total Count 1,242 3,462 4,704
% within college
26.4% 73.6%
100.0%
Table 13. Chi-Square Tests: Parent Education and Intent to Transfer
Value df
Asymp. Sig.
(2-sided)
Exact Sig.
(2-sided)
Exact Sig.
(1-sided)
Pearson chi-square 26.429(b) 1 .000
Continuity
Correction(a)
26.086 1 .000
Likelihood ratio 26.701 1 .000
Fisher's Exact Test .000 .000
Linear-by-linear
association
26.423 1 .000
N of valid cases 4,704
Research Question 2A. Is Gender Related
to Counseling Utilization?
As shown in Table 14, the cross-tabulation of gender and counseling utilization
shows the percentage of male students who utilized counseling is 25.9% and the
percentage of females is 29.3%. Females are more likely to utilize counseling within
the 7 days from when the survey was answered. The chi-square statistic of (continuity
71
Table 14. Counseling Utilization by Gender
Counsel Total
No Yes No
Your gender Male Count 1,368 454 1,822
% within your gender 75.1% 24.9% 100.0%
Female Count 1,986 822 2,808
% within your gender 70.7% 29.3% 100.0%
Total Count 3,354 1,276 4,630
% within your gender 72.4% 27.6% 100.0%
corrected chi-square = 10.285, p = .001) is statistically significant (Table 15).
Females utilize counseling more than males according to the respondent sample of
students.
Table 15. Chi-Square Tests: Counseling Utilization by Gender
Value df
Asymp. sig.
(2-sided)
Exact sig.
(2-sided)
Exact sig.
(1-sided)
Pearson chi-square 10.502(b) 1 .001
Continuity
correction (a)
10.285 1 .001
Likelihood ratio 10.584 1 .001
Fisher's Exact
Test
.001 .001
Linear-by-linear
association
10.499 1 .001
N of valid cases 4,630
72
Research Question 2B. Is Age Related
to Counseling Utilization?
Table 16 shows that age is related significantly to counseling utilization,
chi-square (9) = 34.95, p = .001. Table 14 provides a breakdown of counseling
utilization and age. The main finding is that nontraditional students are less likely
to have used counseling in the last week.
Table 16. Chi-square Tests: Counseling Utilization by Age
Value df
Asymp. sig.
(2-sided)
Pearson chi-square 34.954 9 .000
Likelihood ratio 34.735 9 .000
Linear-by-linear association 18.853 1 .000
N of valid cases 4,689
Research Question 2C. Is Ethnic Group Membership
Related to Counseling Utilization?
According to Table 18, the cross-tabulation of ethnic group membership and
counseling utilization shows that Asian students utilize counseling at 24.1% and Black
students 40.1%. The Hispanic students utilize counseling at 26.3%, White students at
21.2%, Mixed ethnic group students 23.0% and in Other ethnic groups, 35.4% are
utilizing counseling. The chi-square statistic (chi-square = 80.75, p = .000) is
statistically significant (Table 19). The striking finding is the Black students are more
likely to have used counseling in the last week.
73
Table 17. Cross-tabulation of Counseling Utilization by Age
Counsel Total
No Yes No
Age on
December 31
of this year
16 or less Count 21 8 29
% within age on
December 31 of this year
72.4%
27.6%
100.0%
17 Count 16 10 26
% within age on
December 31 of this year
61.5%
38.5%
100.0%
18 Count 60 27 87
% within age on
December 31 of this year
69.0%
31.0%
100.0%
19 Count 521 150 671
% within age on
December 31 of this year
77.6%
22.4%
100.0%
20 Count 513 156 669
% within age on
December 31 of this year
76.7%
23.3%
100.0%
21-24 Count 912 360 1,272
% within age on
December 31 of this year
71.7% 28.3% 100.0%
25-29 Count 509 179 688
% within age on
December 31 of this year
74.0%
26.0%
100.0%
30-39 Count 519 230 749
% within age on
December 31 of this year
69.3%
30.7%
100.0%
40-54 Count 285 146 431
% within age on
December 31 of this year
66.1%
33.9%
100.0%
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Table 17 (continued).
Counsel Total
No Yes No
Age on December
31 of this year
55 or
more
Count 41 26 67
% within age on
December 31 of this year
61.2%
38.8%
100.0%
Total
Count 3,397 1,292 4,689
% within age on
December 31 of this year
72.4%
27.6%
100.0%
Table 18. Cross-tabulation of Ethnic Group and Counseling Utilization
Counsel Total
No Yes No
Ethnic Asian Count 400 127 527
% within ethnic 75.9% 24.1% 100.0%
Black Count 382 256 638
% within ethnic 59.9% 40.1% 100.0%
Hispanic Count 1,598 570 2,168
% within ethnic 73.7% 26.3% 100.0%
White Count 408 110 518
% within ethnic 78.8% 21.2% 100.0%
Mixed Count 386 115 501
% within ethnic 77.0% 23.0% 100.0%
Other Count 204 112 316
% within ethnic 64.6% 35.4% 100.0%
Total Count 3,378 1,290 4,668
% within ethnic 72.4% 27.6% 100.0%
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Table 19. Chi-square Tests: Ethnic Group and Counseling Utilization
Value df
Asymp. sig.
(2-sided)
Pearson chi-square 80.755 5 .000
Likelihood ratio 77.608 5 .000
Linear-by-linear association .402 1 .526
N of valid cases 4,668
Research Question 2D. Is Parent Education
Related to Counseling Utilization?
Table 20 shows that cross-tabulation of parent education (coded “yes” if one
parent reported at least some college) and counseling utilization, and Table 22 shows
the statistical findings; 29.1% of the students who had a parent who did not attend
college, reported that they utilized counseling or spoke with a counselor. However,
25.9% of students who had at least one parent with college education utilized
counseling. This difference in proportions is statistically significant (continuity
corrected chi-square = 5.93, p = .016).
Research Question 3. Is Counseling Utilization
Related to Intention to Transfer?
Table 21 shows the cross-tabulation of students who intend to transfer and
counseling utilization; 24.6% of students who did not intend on transfer utilized
counseling. Slightly more, 28.7% of students who intend to transfer, utilized
counseling. As shown in Table 23, this difference in is statistically significant
(chi-square = 7.407, p = .008). The statistical findings show that students who intend
76
Table 20. Cross-tabulation of Parent Education and Counseling Utilization
Counsel Total
No Yes No
College No Count 1,923 791 2,714
% within college 70.9% 29.1% 100.0%
Yes Count 1,507 528 2,035
% within college 74.1% 25.9% 100.0%
Total Count
3,430 1,319
4,749
% within college 72.2% 27.8% 100.0%
Table 21. Cross-tabulation of Parent Education and Counseling Utilization
Value df
Asymp. Sig.
(2-sided)
Exact Sig.
(2-sided)
Exact Sig.
(1-sided)
Pearson chi-square 5.934 1 .015
Continuity
correction
5.775 1 .016
Likelihood ratio 5.956 1 .015
Fisher's Exact Test .015 .008
Linear-by-linear
association
5.932 1 .015
N of valid cases 4,749
to transfer, are more likely to use counseling, but it is important to note that 71.3% of
this group did not see a counselor within the last week.
77
Table 22. Cross-tabulation of Intention to Transfer and Counseling Utilization
Counsel Total
No Yes No
Plantran No Count 915 299 1,214
% within plantran 75.4% 24.6% 100.0%
Yes Count 2,433 977 3,410
% within plantran 71.3% 28.7% 100.0%
Total Count 3,348 1,276 4,624
% within plantran 72.4% 27.6% 100.0%
Table 23. Chi-Square Tests: Intention to Transfer and Counseling Utilization
Value df
Asymp. sig.
(2-sided)
Exact sig.
(2-sided)
Exact sig.
(1-sided)
Pearson chi-square 7.247 1 .007
Continuity correction 7.047 1 .008
Likelihood ratio 7.359 1 .007
Fisher's Exact Test .007 .004
Linear-by-linear
association
7.246 1 .007
N of valid cases 4,624
78
CHAPTER 5
CONCLUSION AND RECOMMENDATIONS
Introduction
This chapter includes an introduction and review of the purpose of the study, a
summary of findings, conclusion of the findings and implications and recommenda-
tions for further research. Most of the literature from the 1970s to the present has
focused on the issues of student persistence and retention in higher education. The
low rates of transfer from a community college to a 4-year university, has been an
important issue for more than a century. Thus, this study also addresses the importance
of looking at the intent to transfer as it relates to the changing demographics of
community college students and the variables that influence intent to transfer such
as (a) gender, (b) age, (c) ethnic group membership, (d) parent education, and
(e) counseling utilization. The literature review focused on the theories of persistence
and retention with special attention to the affect it has on transfer and one of the
underlying themes uncovered in this study was the importance of personal connections
such as counseling utilization by students.
This study is a secondary analysis from the students who voluntarily
participated in the Transfer Retention of Urban Community Colleges Students,
TRUCCS initial survey (Hagedorn, 2002). Of the 5,010 surveys that were
administered to students at nine community colleges within the Los Angeles district,
4,968 were returned with responses given to a 47-item questionnaire. The findings
were derived using a quantitative approach which measures statistically significant
79
differences among students who intend to transfer and those who do not and the
variables that impact this intent. This approach also looks at research in areas of
retention, persistence, transfer and the utilization of community college counseling by
students.
The Purpose of the Study
The literature review in chapter 2 focused on theories of college student
retention and persistence from the five theorists. Vincent Tinto (1975/1987/1993) and
his model of student retention, Patrick Terenzini and Ernest Pascarella’s (1985)
longitudinal and institutional model of student-faculty informal contact, student’s
educational choices such as decisions to stay or leave and diversity experiences and
finally John Bean’s and Barbara Metzner (1980) conceptual model of student
persistence and cultural, academic and environmental factors and social integration.
This study also included Alexander Astin’s (1984/1993/1996) model of student
involvement and persistence. His theory relies on the basic premise that faculty
connections inside and outside of the classroom will help students be successful in
college, especially in persistence and retention. Based on such research and models,
the purpose of the study was to assess the relationships of the selected demographic
variables which include (a) gender, (b) age, (c) ethnicity, (d) parent education with
two outcome variables, (e) counseling utilization, and (f) intent to transfer.
Summary of Findings
The analysis of the data looked at the variables of gender, age, ethnicity,
parent education, and showed the relationship and significance of these variables
80
with intent to transfer and counseling utilization. The TRUCCS initiative was
designed for urban community college campuses with diverse student enrollments
and backgrounds. For purposes of this study, the responses to questions on gender,
age, ethnic group membership, parent education plan to transfer to a 4-year
university and counseling utilization are examined to answer the following research
questions.
Research Question 1A. Is Gender Related
to Intention to Transfer?
The results indicated that gender is not related to intention to transfer. The
relationship sample of females and males was not significant because the results
showed a non-significant chi-square. Females intent to transfer was 72.9% and males
was 75.2%, but this difference in proportions can be attributed to chance. According
to the data, it does not matter whether the student is female or male, because both
genders have intent to transfer from a community college to a university.
Research Question 1B. Is Age Related
to Intention to Transfer?
Age is significant in this analysis. The age of students in community colleges
is changing. The traditional age of students from 18-21 still exists, however, the non-
traditional age student of 25 or older becoming more prevalent in community colleges.
The age related to intention to transfer analyzed showed in this study that students 16
or less have an 80% intention to transfer. According to the results: (a) other age
groups of 17 indicate 76.9%, (b) age 18 is 80.2%, (c) age 19 is 84.6%, (d) age 20 is
79.9%, (e) ages 21-24 is 79.2%, (f) ages 25-29 is 64.2%, (g) ages 40-54 is 54.0%, and
81
(h) ages 55 or more is 43.3%. The age variables support the literature that students
who attend community colleges are much older, however, it is very important to see
the data shows that students who are older than 25 still indicate a high percentage of
intent to transfer despite their age. The literature does not discuss the intent to transfer
and age relationship, but this study supports the underlying theme that the majority of
students, no matter what age, who attend community college, have a desire to transfer.
Research Question 1C. Is Ethnic Group Membership
Related to Intention to Transfer?
Intention to transfer results for different ethnicity groupings were (a) Asian
72.4%, (b) Black 74.2%, (c) Hispanic 75.0%, (d) White 68.8%, (e) Mixed 75.8%, and
(f) Other 71.2%. Intent to transfer and the variables of ethnicity have a significant
relationship based on the findings, and it is important to Black and Hispanic students,
Mixed and Other ethnicities had a higher intent to transfer. Yet the literature from
chapter 2 states that students from color have a lower transfer rate compared to White
students. Although, the intent is high for students of color, these data would help
counselors and faculty as well as student service staff to see the need for transfer
counseling and should continue efforts and outreach to help students transfer.
Research Question 1D. Is Parent Education
Related to Intention to Transfer?
The students surveyed were coded “yes” or “no” if one or both parents had any
college education, and the cross-tabulation of their intention to transfer with parent
education was analyzed from the data given. Of the students whose parents had no
college education, 70.8% indicated the intent to transfer, and 77.4% of the students
82
with parents who had some college indicated the intent to transfer. A highly
significant chi-square statistic indicated that the variables students with parents who
attended college are more likely to intend to transfer. The implication of this finding
that students with parent education are more likely to plan to transfer suggests that
socio-economic factors influence intent to transfer.
Research Question 2A. Is Gender Related
to Counseling Utilization?
The gender difference was not significant. Gender does not play a role in
utilization of counseling: 24.9% of males indicated that they had spoken to a
counselor. The females had a higher percentage (29.3%) who had utilized counseling,
but this result can be attributed to chance. The results from this study indicate fewer
numbers of expected males and females, who utilized counseling compared to the
overall high intent and aspiration to transfer and it is important to understand why this
happens.
Research Question 2B. Is Age Related
to Counseling Utilization?
The highest percentages who spoke to a counselor were age 17 with 38.5% and
ages 55 or older with 38.8%. The results for the remaining age groups were: (a) ages
40-54 at 33.9%, (b) age 18 at 31%, (c) age 30-39 at 30.7%, (d) 21-24 at 28.3%,
(e) ages 24-29 at 26.0%, and (f) 16 or less at 27.6%. The ages least likely to seek out
counseling were age 20 at 23.3%, and age 19 at 22.4%. Overall, students who seek
out counseling vary within age groups, and the chi-square shows that age does play a
factor when utilizing counseling. These findings support the research from the
83
literature review that younger students are less likely to seek out advising. The
literature supports that students of diverse age groups, also referred to as the non-
traditional student who is typically older than 24 years old are attending community
college and more likely to utilize counseling. This information is important to help
understand how age relates to counseling utilization and why the older student is more
likely to seek out assistance than the younger student. However, the results support
the literature that there is a continued need for assistance despite any age group, and
students are not utilizing the assistance at the rate expected of at least 50% or more.
The overall results in this study show that students are utilizing counseling at an
average of 29% in the Los Angeles Community College district, TRUCCS project.
Research Question 2C. Is Ethnic Group Membership
Related to Counseling Utilization?
Ethnicity is related to counseling utilization according to the data in this study.
The Pearson chi-square was significant and showed that students’ ethnicity is related
to speaking to an academic counselor. The data shows that Black students are more
likely to seek out counseling at 40% compared to other student ethnicity. Mixed race
students reported 35.4% while Hispanic students saw a counselor at a 26.3% rate. The
White students were the least likely to speak to a counselor at 21.2% compared to all
other groups including Asian students at 24.1%. These results differ with the literature
which states that students of color are less likely to seek out counseling. According to
these data, the most underrepresented students did seek out counseling, however, the
data does not show the reasons for their visit and this would help understand whether
84
or not it helped with successful outcome with academic or social connection at
community college.
Research Question 2D. Is Parent Education
Related to Counseling Utilization?
In this study, whether the student had a parent with or without a college
education was not significantly related to counseling utilization. Students who
answered “yes” to either parent with college education spoke to a counselor at a 25.9%
compared to students with no college education from either parent spoke to a
counselor at 29.1%. The sample chi-square is not significant which overall means
parent education is not related to counseling utilization.
Research Question 3. Is Counseling Utilization
Related to Intention to Transfer?
In this study, the results show that yes there is a relationship of counseling
utilization and the intent to transfer from the TRUCCS data. 28.7% of students spoke
to a counselor who intended to transfer. However, while the rate was slightly lower
for students who did not intend to transfer (24.6%). The results from the data also
show that 71.3% of students who did not speak with a counselor still indicated intent
to transfer. The data is consistent with the literature that students who intend to
transfer and utilize counseling are more likely to be successful through connection to
faculty and the assistance received. However, more students ultimately need to seek
out counseling to understand transfer and obtain guidance and support to complete
their educational goal.
85
Discussion
Although the analysis identified several interesting correlates of intent to
transfer, the main finding was that a clear majority of the students in the study, 73.6%,
indicated that they “probably” or “definitely” intended to transfer to a 4-year
university. According to Hagedorn (2004) and Rendon (1987), contrary to low
transfer rates, students have a high aspirations and intent to transfer but also have
modest GPAs, will college assessment scores, and obstacles in the system. The intent
to transfer can be used to measure transfer readiness when students indicated desire to
transfer income provide a reasonable estimate of students as the denominator when
compared to performance in transferable English and math courses. The transfer rate
is commonly calculated as the ratio of those students who transfer over the potential
number of students who intend to transfer (Banks, 1990; Hagedorn, 2005).
Inconsistent measures of transfer arise when attempts to defined which students
qualify his true potential transfers. Banks (1990) used an analysis of credits to
compute a more accurate transfer ratio. Students were considered potential transfers
based on the number of transferable course credits completed. Most transfer rate
measures seek to eliminate those students who do not intend to transfer, but will likely
not be able to do so (Hagedorn, 2004). Thus, the reality that many students aspire to
transfer and progress toward the goal is obscured.
The argument can be mentioned that education and persistence still provides
benefits even when it does not result in transfer, yet community colleges should
ultimately not ignore the students who intend on transfer and do not reach their goal.
86
According to Hagedorn (2004) transfer is not linear; it is convoluted, zig-zag, or flows
in the opposite direction (p. 227). Many students also participate in a quote, “reverse
transfer” process, moving from a 4-year university to a community college, and
transfer back to the university. Other types of transfer students which affect the
transfer rates are the students in high school, who are dual enrollment and they have
further threatened the integrity of transfer measures from high school to community
college to university (Hagedorn, 2004). This is rare among urban students thus
exception to the rule. Accountability of the community college to address their role in
transfer and measure their outcome is still lacking and sorted.
A second significant finding in this study was that counseling utilization was
very low, and in this study, the average rate was less than 30%. Students from the
TRUCCS survey did not seek out counseling. As discussed in chapter 2, students who
seek out counseling and have a high intent to transfer, are more likely to achieve their
educational goals. Counseling services have an influence on student’s academic and
social integration and in their ability to teach and perform the duties of a faculty and
teacher, both crucial areas in student persistence (Pascarella & Terezini, 1991). The
literature and student involvement in and collaboration between student and academic
services is helpful towards promoting positive student development and connection to
the faculty and institution itself.
The utilization of counseling is informative for the students to learn the
transfer process and the important role of the community college counselors is to be
able to explain it to them. The utilization of counseling and community college
87
student transfer services are designed to inform, advise and guide students seamlessly
through the transfer process and increase transfer. However, the results of this study
in the literature, support the students are not seeking out counselors despite the
importance of the faculty contact and the guidance to help the student academically,
career related and socially. The low rate of counseling utilization can hinder students
toward their goal of academic, personal, social career in transfer. The counselor is
vital for the students to interpret the various general education transfer patterns such as
the CSU general education requirements and the Intersegmental General Education
Transfer Curriculum, IGETC, also known as transfer articulation tools for transfer.
The low utilization of counseling is discussed in most of the literature yet it is referred
to the faculty advising and student services connections at community college.
Seeking out counselors and faculty and the importance of formal and informal
advising is significant to college retention and ultimately transfer, however students
are not utilizing the assistance and this has an impact on their educational goal and
persistence in community college, specifically with transfer, despite the high intent to
transfer.
The data also shows that 25 or older have a 50% or more intent to transfer to a
4-year university. The large number of students who want to transfer, no matter their
older age, to a 4-year university was unexpected. This information supports literature,
the students from community college are much more diverse in ages of 25 or older
compared to students from 4-year universities. However, the data indicate that
students intend to transfer at higher rates than expected, particularly the 55 and older
88
within at least 40% plan to transfer. Based on these data, it would help community
college faculty to explore and identify new and creative ways to support older students
with information on transfer and to understand they also need to connect to faculty just
as much as the younger students to have successful outcomes. It would also lead to a
new awareness that community colleges are more diverse and nontraditional than ever
and thus, the goal of transfer becomes more prevalent than before.
The importance of faculty connections and resources for the success of the
student whether at a community college or 4-year university, has been well
established. Seeking out counselors and faculty during office hours in the importance
of formal and informal advising, is significant to college retention and ultimately
transfer. The roles of counselors, faculty, staff connecting with students, inside and
outside the classroom, are important for students in persistence and community
college in transfer to a 4-year university. Similar to Astin (1984/1993/1996), I believe
that successful students are students who make connections on campus to achieve their
educational goal.
One could theorize that this lack of problem-solving, admittance of the need
for help, ignorance of services and/or lack of motivation all contribute to lack of
success, however, there are many ways to retain community college students such as
structured and intrusive support and services even if mandated, specifically before the
students run into difficulty or go on probation. Creating college success courses
required for basic skills students rather than simply offering counseling to proactive
89
students would be an example of the intrusive, structured intervention that most high
risk students need.
The data set up the TRUCCS study which acquire data from the nine Los
Angeles community colleges in Los Angeles is problematic because counseling is
mandated for students on academic probation. The utilization of counseling has a
strong negative connotation and counter intuitive reaction among students. In this
circumstance, it is believed that students relate counseling with a negative stigma. It
can also lead to the question on the various reasons why students do not seek out
counseling unless it is mandated. In general, community college students tend to not
seek out the many resources, whether it is counseling, tutoring, financial aid, etc. The
literature from chapter 2 reinforces the successful outcome, the student has after
seeking out assistance, yet there are still so many reasons why they still do not.
Recommendations for Future Research
Our data from this study suggest a qualitative study to further research and
interview students who visited a counselor when they experience academic failure.
The study could also include the various reasons that students seek out counseling and
their response and attitude about counseling services. The survey asked students if
they had spoke to a counselor in the past 7 days this semester, but did not address the
various reasons students utilize counseling at the community college where their
satisfaction about the services they received.
Based on the literature, students are more likely to do better in school after
they have talked with someone and the universities still need to know the importance
90
of outreach at the community college level. Students are more likely to transfer when
the information is given via a college counselor or faculty member. Thus,
recommendations for more transfer outreach by the 4-year universities such as
University of California (UC), California State Universities (CSU), and private
universities are warranted.
Conclusion
The literature from Tinto (1975/1993), Pascarella and Terenzini (1977), Bean
and Metzner (1985), supports the argument that students who seek out assistance
through counseling are more likely to transfer. However, there are many reasons why
students are not seeking counseling, and the overall low rate in the present study
(27.8%) was expected. Because the survey asked if the student had spoken to an
academic counselor “in the past 7 days,” 27.8% is probably an underestimate of
counseling utilization in the case, but nonetheless, there is a clear indication in the
literature that many students who intend to transfer to a four-year institution do not
(Hagedorn & Lester, 2006). Counseling is a potential solution to the problem. But the
reality is that community college students and students who attend universities, do not
seek out counseling or advising, unless it is forced on them via probation, dismissal, or
a negative action from the institution. The students who need assistance often do not
seek out counseling. Retention theories propose that this could be the result of a lack
of problem-solving, admitting the need for help, ignorance of services and/or lack of
motivation.
91
Another important finding in this study was the overall intent to transfer rate
was 73.6%, a far greater rate than was expected. Because the TRUCCS survey only
was distributed to English classes, it is likely that 73.6% is an upwardly biased
estimate. (Assuming students who do not intend to transfer are less likely to take
English.) Nonetheless, it is clear that a large number of students do intend to transfer
and thus, this study concludes with the question of what would be the best way to help
community college students with the intent to transfer? One answer would be to
mandate counseling services to all students regardless of their educational goal. This
would ensure that all students with intention to transfer would receive counseling
services proven to increase transfer rates. Presently, most students seek counseling
due to probation or academic failure and thus seeking counseling can have a negative
connotation. Mandating counseling for all students could improve students’ attitudes
about counseling in general.
92
REFERENCES
Adelman, C. (1999). Answers in the toolbox: Academic intensity, attendance
patterns, and bachelor’s degree attainment. (Brochure). Washington, DC:
U.S. Department of Education, Office of Educational Research and
Improvement.
Archer, S. E., & Cooper, J. A. (1998). Counseling and mental health services on
campus. A handbook of contemporary practices and challenges. San
Francisco, CA: Jossey-Bass.
Ashar, H., & Skenes, R. (1993). Can Tinto’s student departure model be applied to
non-Traditional students?” Adult Education Quarterly, 43(2), 90-100.
Astin, A. W. (1982). Minorities in American Higher Education: Recent Trends,
Current Prospects, and Recommendations. San Francisco, CA: Jossey-Bass.
Astin, A. W. (1984). Student involvement: A developmental theory for higher
education. Journal of College Student Personnel, 297-308.
Astin, A. W. (1985). Achieving Educational Excellence. San Francisco, CA: Jossey-
Bass.
Astin, A. W. (1985). Assessment for excellence: A critical assessment of priorities
And practices in higher education. San Francisco, CA: Jossey-Bass.
Astin, A. W. (1986). The importance of student involvement. Journal of Counseling
and Development, 65, 92-95.
Astin, A. W. (1993) What matters in college: Four critical years revisited. San
Francisco, CA: Jossey Bass.
Astin, A. W. (1996). Student involvement: A developmental theory for higher
education. Journal of College Student Personnel, 25, 297-308.
Astin, A. W., Tsui, L., & Avalos, J. (1996). Degree attainment rates at American
colleges and universities: Effects of race, gender, and institutional type. Los
Angeles: Higher Education Research Institute, University of California.
Banks, D. L. (1990). Why a consistent definition of transfer?: An ERIC review.
Community College Review, 18(2), 47-53.
93
Bauman, P. (2001). Student retention: What you can control, & how. Distance
Education Report, 6(16), 8.
Bean, J. P. (1982). Student attrition, intentions, and confidence: Interaction effects in
a path model. Research in Higher Education, 17(4), 291-320.
Bean , J. P., & Metzner, B. S. (1985). A conceptual model of non-traditional
undergraduate student attrition. Review of Educational Research, 55(4), 485-
540.
Billson, J. M., & Terry, M. B. (1982). In search of the silken purse: Factors in
Attrition among first-generation students. College and University, 58(1), 57-
75.
Board of Governors, California Community Colleges. (1991). Intersegmental general
education transfer curriculum. Report (March 15, 1991). Retrieved August
13, 2003, http://www.curriculum.cc.ca.us/Curriculum/RegulationsGuidelines/
IGETC_Standards.htm
Bonham, L., & Luckie, J. A. (1993). Community college retention: Differentiating
among stopouts, dropouts and optouts. Community College Journal of
Research and Practice, 17, 543-554.
Borglum, K., & Kabala, T. (2000). Academic and social integration of community
college students: A case study. Community College Journal of Research and
Practice, 24(7), 567-576.
Bowles, S., & Gintis, H. (1976). Schooling in capitalist America. New York: Basic
Books.
Bradburn, E. M., & Hurst, D. G. (2001). Community college transfer rates to 4-year
institution using alternative definitions of transfer. Education Statistics
Quarterly, 3(3), 119-125.
Brawer, F. B. (1996). Retention-attrition in the nineties. Eric Digest, 4.
Braxton, J. M., Vesper, N., & Hossler, D. (1995). Expectations for college and
student persistence. Research in Higher Education, 36, 595-612.
Bray, C. S. (1985). Early identification of dropout prone students and early
intervention strategies at a private university. Dissertation Abstracts
International, 47(01A), 0095.
94
Brotherton, P. (2001). It takes a campus to graduate a student. Black Issues in
Higher Education, 18(18), 34.
Bryant, A. N. (2001). ERIC Review: Community college students: Recent
findings and trends. Community College Review, 29(3), 77.
Cabrera, A.F., & Castaneda, M. B., Nora, A., & Hengstler, D. (1992). The
convergence between two theories of college persistence. Journal of Higher
Education, 63(2), 143-164.
Cabrera, A. F., Nora, A., & Castaneda, M. B. (1993). College persistence. Journal of
Higher Education, 5(2).
Cabrera, A. F., & Nora, A. (1994). College students’ perceptions of prejudice and
Discrimination and their feeling of alienation. Review of Education,
Pedagody, and Cultural Studies, 16, 387-409.
Callen, P. (1997). Stewards of opportunity: America’s public community colleges.
Daedalus, 126, 95-112.
California Community Colleges Chancellor’s Office (CCCCO). (2002). Transfer
capacity and readiness in the California community colleges: A progress
report to the legislature. Report prepared by Student Services and Special
Programs Division and the Technology, Research, and Information Systems
Division.
California Community Colleges Chancellor’s Office. (2004). Chancellor’s Office
Data Mart: Student Demographics, 2003. [Data file]. Available from
California Community Colleges Chancellor’s office site
http://misweb.cccco.edu/mis/ onlinestat/studdemo_coll.cfm
Carkhuff, R., & Pierce, R. (1967). Differential effects of therapist race and social
class upon patient depth of self-exploration in the initial clinical interview.
Journal of Consulting Psychology, 31,632-634.
Carter, D., & Wilson, R. (1994). Annual status report on minorities in higher
Education. Washington, DC: American Council on Education.
Carter, D., & Wilson, R. (1996). Annual status report on minorities in higher
Education. Washington, DC: American Council on Education.
Chickering, A. W. (1974). Commuting versus resident students. San Francisco, CA:
Jossey-Bass.
95
Chickering, A. W., & Gamson, Z. F. (1987). Seven principles for good practice in
Undergraduate education. AAHE Bulletin, 39(7), 3-7.
Claggett, C. A. (1996). Correlates of success in the community college: Using
research to inform campus retention efforts. Journal of Applied Research in
the Community College, 4(1), 49-68.
Clark, R. E., & Estes, F. (2002). Turning research into results. A guide to selecting
the right performance solutions. CEP Press: Atlanta, GA.
Cofer, J., & Somers, P. (2000). Within-year persistence of students at two-year
college. Community College Journal of Research and Practice, 24(10), 785-
807.
Cofer, J., & Somers, P. (2001). What influences student persistence at two-year
colleges? Community College Review, 29(3), 56-76.
Cohen, A. M. (1988). Degree achievement by minorities in community colleges.
Review of Higher Education, 11, 383-402.
Cohen, A. M., & Brawer, F. (2002). The American community college (4
th
ed.). San
Francisco, CA: Jossey-Bass.
Coll, K. M. (1993). Community college counseling: Current status and needs.
Washington, DC: International Association of Counseling Services.
Creswell, J. W. (2003). Research design, qualitative, quantitative and mixed methods
approaches. (2
nd
ed.). Thousand Oaks, CA: Sage Publications.
Dale, P. M. (1998). A successful college retention program. College Student
Journal, 30, 354-360.
De Tro, G. (2005, September 22). Keeping students informed of the transfer process.
Academic Exchange Quarterly.
Edwards, R., & Person, D. (1997). Retaining the adult student: The role of
admissions counselors. Journal of College Admissions, 154, 18-21.
Gordon, V. N., Habley, W. R. & Assoc. (2000). Academic advising: A
comprehensive handbook. National Academic Advising Association
(NACADA). San Francisco, CA: Jossey-Bass.
96
Grimes, S. K., & David, K. D. (1999). Underprepared community college students:
Implications of attitudinal and experiential differences. Community College
Review, 27(2), 73-92.
Grunder, P. G. & Hellmich, D. M. (1997). Academic persistence and achievement of
remedial students in a community college’s college success program.
Community College Review, 24, 21-33.
Hagedorn, L. S. (2003). TRUCCS Project: Executive Reports (Individual reports of
Course completion behaviors for East Los Angeles, Harbor, Los Angeles City,
Mission, Pierce, Southwest, Trade Technical, Valley, and West Los Angeles
Community Colleges.
Hagedorn, L. S. (in press, 2004). Course Completion of Urban Community College
Students: Transcript stories. Journal of Applied Research in the Community
College.
Hagedorn, L. S., & Lester, J. (2006). Hispanic Community College Students and the
Transfer Game: Strikes, Misses, and Grand Slam Experiences. Community
College Journal of Research and Practice, 30(10), 827-853.
Hagedorn. L. S., Moon, H. S., Cypers, S., Maxwell, W. E., & Lester, J. (2003)
Transfer between community colleges and four-year colleges: The All
American Game. Presentation to the Association for the Study of Higher
Education (ASHE), Portland, OR.
Hagedorn, L. S., & Tierney, W. G. (2002). Increasing access to college: Extending
possibilities for all students. New York: SUNY Press.
Harbin, C. E. (1997). A survey of Transfer Students at Four-Year Institutions Serving
a California Community College. Community College Review, 25(2), 21-40.
Heisserer, D. L., & Parette, P. (2002). Advising at-risk students in college and
university settings. College Student Journal, 36(1), 69-83.
Helm, P. K., & Cohen, A. M. (2001). Leadership Perspectives on Preparing Transfer
Students. New Directions for Community Colleges, 30(2), 99-104.
Hoachlander, G., Sikora, A.C., & Horn, L. (2003). Community College Students:
Goals, Academic Preparation, and Outcomes (NCES 2003–164).
Hoyt, J. E. (1999). Remedial education and student attrition. Community College
Review, 27(2), 51-72.
97
IGETC. (1992). Retrieved on March 22, 2008, from http://www.igetc.org/index.php
Inman, W. E., & Mayers, L. (1999). The importance of being first: Unique
characteristics of first generation community college students. Community
College Review, 26(4), 3-22.
Jacobi, M. (1991). Mentoring and undergraduate academic success: A literature
review. Review of Educational Research, 61(4), 505-532.
James, D. P. (1989). Increasing retention rates of Black students. Mentoring
International, 3(2), 34-39.
Jencks, C., & Peterson, P. E. (Eds.). (1991). The urban underclass. Washington, DC:
The Brookings Institution.
Laden, B. V. (1998). An organizational response to welcoming students of color.
New Directions for Community Colleges, 102.
Leach, E. R. (1984). Toward the future vitality of student development services.
Iowa City, IA: American College Testing.
Lee, W. Y. (1999). Striving toward effective retention: The effect of race on
mentoring African-American students. Peabody Journal of Education, 74, 2.
Leonard, M. Q. (2002). An outreach framework for retaining nontraditional students
at open-admissions institutions. Journal of College Counseling.
Levin, M., & Levin, J. (1991). A critical examination of academic retention programs
for at-risk minority college students. Journal of College Student Development,
32, 323-34.
Liu, E., & Liu, R. (1999). An application of Tinto’s model at a commuter campus.
Education, 119(3), 537-541.
Los Angeles Community College District (LACCD). (2001). Retrieved from Fast
Facts, December 1, 2003, http://www.laccd.edu/
Lundberg, C. A. (2003). The influence of time-limitations, faculty, and peer
relationships on adult student learning: A causal model. The Journal of
Higher Education, 665-688.
Marlow, C. (1998). Identifying the problems and needs of nontraditional students.
NASPA Journal, 26, 272-277.
98
Martin, W. E., Swartz-Kulstad, J., & Madson, M. (1999). Psychosocial factors that
predict the college adjustment of first-year undergraduate students:
Implications for college counselors. Journal of College Counseling, 2(2), 121.
Maxwell, W. E. (2000). Student peer relations at a community college. Community
College Journal of Research and Practice, 24, 207-217.
Maxwell, W., Hagedorn, L. S., Cypers, S., Moon, H. S., Brocato, P., Wahl, K., &
Prather, G. (2003). Community and diversity in urban community colleges:
Coursetaking among entering students. Community College Review, 30(4), 21-
46.
McDonough, P. M. (1997). Choosing colleges: How social class and schools
structure opportunity. Albany, NY: SUNY Press.
McDonough, P. M. (1998). Structuring college opportunities: A cross-case analysis
or organizational cultures, climates, and habiti. In C.A. Torres, & T.R.
Mitchell (Eds), Sociology of education: Emerging perspectives (pp. 181-210).
Albany, NY: SUNY Press.
McDonough, P. M., Antonio, A. L., & Trent, J. W. (1997). Black students, black
colleges: An African American college choice model. Journal for a Just and
Caring Education, 3, 9-36.
Miller, M. T., Pope, M. L., & Steinmann, T. D. (2005). A profile of contemporary
Community college student involvement, technology use, and reliance on
Selected college life skills. College Student Journal, 39(3), 596.
Morrow, R. A., & Torres, C. A. (1998). Education and the reproduction of class,
gender, and race: Responding to the postmodern challenge. In C. A. Torres,
Mitchell (Eds.), Sociology of education: Emerging perspectives (pp. 19-45).
Albany, NY: SUNY Press.
Naretto, J. A. (1995). Adult student retention: The influence of internal and external
Communities. Naspa Journal, 32, 90-97.
National Center for Education Statistics (NCES). (1996). The national postsecondary
student aid. Washington, DC: U.S. Department of Education.
National Center for Educational Statistics (NCES). (1998). First-generation students:
Undergraduates whose parents never enrolled in postsecondary education.
Washington, DC: U.S. Department of Education. (ERIC Document
Reproduction Service No. ED 420 235).
99
National Center for Education Statistics (NCES). (1999). The condition of education
1998: Supplement and standard error tables (NCES) 99-025. Washington,
DC: U. S. Government Printing Office.
Newman, P. R., & Newman, B. M. (1999). What does it take to have a positive
impact on minority students’ college retention? Adolescence, 34(135), 483.
Noel, L., & Levitz, R. (1984). Toward the future vitality of student development
services. Iowa City, IA: American College Testing.
Nora, A., & Rendon, L. I. (1990). Determinants of predisposition to transfer among
Community college students. A structural model. Research in Higher
Education, 31, 235-255.
Nutt, C. L. (2000). One-to-one advising. In V. N. Gordon, & W. H. Habley (Eds.),
Academic Advising. A comprehensive handbook (pp. 220-237). San
Francisco, CA: Jossey-Bass.
O’Brien, E. (1988). Dr. Charles Willis prescribes mentoring methodologies for
Minorities. Black Issues in Higher Education, 5(5), 15.
Paratore, J. (1984). The relationship between participation in a mentoring Program
and development growth and persistence of freshman students at Southern
Illinois University at Carbondale. Unpublished doctoral dissertation, Southern
Illinois University, Carbondale, Illinois.
Parker, C. E. (1998). Cultivate academic persistence-now! Black Issues in Higher
Education, 14(26), 104.
Parker, C. E. (1998). Getting serious about retention. Community College Week,
11(4), 4.
Pascarella, E. T. (1980). Student-faculty informal contact and college outcomes.
Review of Educational Research, 50(4), 545-95.
Pascarella, E., T., & Terenzini. P. T. (1977). Patterns of student-faculty informal
interaction beyond the classroom and voluntary freshman attrition. The
Journal of Higher Education, 48(5), 540-552.
Pascarella, E. T., Edison, M., Nora, A., Hagedorn, L. S., & Terenzini, P. T. (1996).
Influences on students' openness to diversity and challenge in the first year of
college. Journal of Higher Education, 67, 174-195.
100
Pascarella, E. T., Edison, M., Whitt, E. J., Nora, A., Hagedorn, L. S., & Terenzini, P.
T. (1996). Cognitive effects of Greek affiliation during the first year of
college. NASPA Journal, 33, 242-259.
Pascarella, E. T., & Terenzini, P. T. (1979). Interaction effects in Spado’s and Tinto’s
conceptual models of college drop-out. Sociology of Education, 52, 197-210.
Pascarella, E. T., & Terenzini, P. T. (1980). Predicting voluntary freshman year
persistence and withdrawal behavior in a residential university: A path
analytic validation of Tinto’s model. Journal of Educational Psychology, 51,
60-71.
Pascarella, E. T., & Terenzini, P. T. (1986). Long-term persistence of two-year
college students. Research in Higher Education, 24, 47-71.
Pascarella, E. T., & Terenzini, P. T. (1991). How college affects students. San
Francisco, CA: Jossey-Bass.
Pascarella, E. T., & Terenzini, P. T. (2005). How college affects students. San
Francisco, CA: Jossey Bass.
Paulsen, M. B. (1990). College choice: Understanding student enrollment behavior.
ASHE-ERIC Higher Education Report No. 6. Washington, DC: The George
Washington University, School of Education and Human Development.
Paulsen, M. B. (1991). College tuition: Demand and supply determinants from 1960
to 1986. Review of Higher Education, 14, 339-358.
Paulsen, M. B. (1998). Recent research on the economics of attending college:
Returns on investment and responsiveness to price. Research in Higher
Education, 39, 471-489.
Perez, L. X. (1998). Sorting, supporting, connecting, and transforming: Intervention
strategies for students at risk. Community College Review, 26(1), 63.
Phillips-Jones, L. (1982). Mentors and proteges. New York: Arbor House.
Pike, G. R. (2000). The influence of fraternity or sorority membership on students’
college experiences and cognitive development. Research in Higher
Education, 41(1), 369-382.
Prime, G. (2001). A missing element in the retention discussion. Black Issues in
Higher Education, 18(21), 250.
101
Ray, D., & Altekruse, M. (2000). Introduction: Counseling in the community
college. Community College Journal of Research and Practice, 24, 423-425.
Reiff, H. B. (1997). Academic advising: An approach from learning disabilities to
research. Journal of Counseling and Development, 75, 443-441.
Rendon, L. (2000). Fulfilling the promise of access and opportunity: Collaborative
community colleges for the 21
st
century. Washington, DC: New Expeditions,
American Association of Community Colleges.
Richardson, J. T. E. (1994). Mature students in higher education. A literature survey
pm approaches to studying. Studies in Higher Education, 30, 5-17.
Rhine, T. J., Milligan, D. M., & Nelson, L. R. (2000). Alleviating transfer shock:
Creating an environment for more successful transfer students. Community
College Journal of Research & Practice, 24(6), 443-453
Romano, R. M., & Wisniewski, M. (2003). Tracking community college transfers
using national student clearinghouse data (CHERI Working Paper #36).
Retrieved (2005), from Cornell University, ILR School site:
http://digitalcommons.ilr.cornell.edu/cheri/16/
Roueche, J. E., & Roueche, S. D. (1994). Responding to the challenge of the at-risk
student. Community College Journal of Research and Practice, 18(1), 1-11.
Santa, R. E., & Bacote, J. (1997). The benefits of college discovery pre-freshman
summer program for minority and low-income students. College Student
Journal, 31, 161-73.
Siu-Man, R. T. (1998). Predicting first-year grades and academic progress of college
students of first–generation and low-income families. Journal of College
Admission, 158, 14-23.
Stough, J. (1996). Puente by the numbers. Puente News (University of California,
Oakland, 4.
Stovall, M. (2000). Using success courses for promoting persistence and completion.
New Directions for Community Colleges, 112, 45-54.
Strage, A. A. (1999). Social and academic integration and college success:
Similarities and differences as a function of ethnicity and family educational
background. College Student Journal, 33(2), 198-205.
102
Suarez, C. M. (2002). Hispanic women: Building a room for self-efficacy. Journal
of Hispanic Higher Education, 1(3), 238-250.
Suarez-Balcazar, Y., Orellana-Damacela, L.,Portillo, N., Rowan, J. M., & Andrews-
Guillen, C. (2003). Experiences of differential treatment among college
students of Color. The Journal of Higher Education, 74(4), 428-444.
Sue, D. W., & Sue, D. (1990). Counseling the culturally different: Theory and
practice. (2
nd
ed.). New York: Wiley.
Sydow, D. L., & Sandel, R. H. (1998) Making student retention an institutional
priority. Community College Journal of Research & Practice, 22(7), 35.
Szelenyi, K. (2001). Minority student retention and academic achievement in
community colleges. Eric Digests, EDO-JC-01-02.
Terenzini, P. T., Springer, L., Yaeger, P. M., & Pascarella, E. T. (1996). First
generation college students: Characteristics, Experiences, and Cognitive
Development. Research in Higher Education, 37(1), 1-22.
Tharp, J. (1998). Predicting persistence of urban commuter campus students utilizing
student background characteristics from enrollment. Community College
Journal of Research & Practice, 22(3), 279.
Thayer, P. (2000). Retention of students from first generation and low income
backgrounds. The Journal of the Council for Opportunity in Education, 9, 2-8
Tinto, V. (1997). Classrooms as communities: Exploring the educational character
of student persistence. The Journal of Higher Education, 68, 599-623.
Tinto, V. (1998). Stages of student departure. Reflections on the longitudinal
Character student leaving. Journal of Higher Education, 59(4), 438-455.
The TRUCCS surveys (2005?). Retrieved on March 24, 2008, from
www.usc.edu/dept/education/ truccs/Papers/TRUCCS_Newsletter_3.pdf
Tierney, W. G. (1992). An anthropological analysis of student participation in
college. Journal of Higher Education, 63, 603-618.
Tinto, V. (1993). Leaving college. Chicago, IL: University of Chicago Press.
103
Tinto, V. (1975). Dropout from higher education: A theoretical synthesis of recent
research. Review of Educational Research, 45(1), 89-125.
Tinto, V. (1987). Leaving college. Chicago, IL: University of Chicago Press.
Tinto, V. (1993). Leaving college: Rethinking the causes and cures of student
attrition. (2nd ed.). Chicago, IL: The University of Chicago Press.
Tinto, V. (1997). Classrooms as communities: Exploring the educational character
of student persistence. The Journal of Higher Education, 68, 599-623.
Tinto, V. (1998). Stages of student departure. Reflections on the longitudinal
Character student leaving. Journal of Higher Education, 59(4), 438-455.
Tinto, V., Russo, P. E., & Kadel-Taras, S. (1996). Learning communities and student
involvement in the community college: Creating environments of inclusion
and success. The community college: Opportunity and Access for America’s
First–Year Students. National Research Center for the Freshman Year
Experience and Students in Transition, 393-486.
Voorhees, R. A. (1993). Toward building models of community college persistence:
A logic analysis. Research in Higher Education, 26(2), 115-129.
Whigman-Desir, M., & LaVeist, T. A. (2001). Making the most of freshman year.
Black Enterprise, 31(6), 64.
Windham, P. (1995). The relative importance of selected factors to attrition at a
public community college. Journal of Applied Research in the Community
College, 3(1), 65-78.
Wyman, F. J. (1997). A predictive model of retention rate at regional two-year
colleges. Community College Review, 25, 29-58.
Zamani, E. M. (2001). Institutional responses to barriers to the transfer process. In F.
S. Laanan (Ed.), Transfer students: Trends and issues (New Directions for
Community Colleges, No. 114), (pp. 15-24). San Francisco, CA: Jossey-Bass.
Zwerling, L. S., & London, H. B. (1992). First-generation students: Confronting the
will of cultural Issues. San Francisco, CA: Jossey Bass.
Abstract (if available)
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University of Southern California Dissertations and Theses
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Asset Metadata
Creator
Chacon, Rosina (Zina)
(author)
Core Title
Correlations among selected demographic variables, counseling utilization, and intent to transfer
School
Rossier School of Education
Degree
Doctor of Education
Degree Program
Education (Leadership)
Publication Date
07/24/2008
Defense Date
04/15/2008
Publisher
University of Southern California
(original),
University of Southern California. Libraries
(digital)
Tag
community college counseling,community college counseling utilization,demographic variables that influence transfer,intent to transfer,OAI-PMH Harvest,student retention and persistence,transfer
Place Name
Los Angeles County
(counties)
Language
English
Advisor
Hocevar, Dennis (
committee chair
), Jimenez y West, Ilda (
committee member
), Sundt, Melora A. (
committee member
)
Creator Email
chaconlo@usc.edu
Permanent Link (DOI)
https://doi.org/10.25549/usctheses-m1393
Unique identifier
UC1104783
Identifier
etd-Chacon-20080724 (filename),usctheses-m40 (legacy collection record id),usctheses-c127-198152 (legacy record id),usctheses-m1393 (legacy record id)
Legacy Identifier
etd-Chacon-20080724.pdf
Dmrecord
198152
Document Type
Dissertation
Rights
Chacon, Rosina (Zina)
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
Tags
community college counseling
community college counseling utilization
demographic variables that influence transfer
intent to transfer
student retention and persistence