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DOES INTRUSIVE COUNSELING INTERVENTION POSITIVELY
IMPACT THE RETENTION OF AT-RISK, FIRST TIME TO
COLLEGE STUDENTS?

presented by
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DOES INTRUSIVE COUNSELING INTERVENTION POSITIVELY IMPACT THE
RETENTION OF AT-RISK FIRST-TIME-TO-COLLEGE STUDENTS?

By

Stanley Scott Chase

A DISSERTATION

Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of

DOCTOR OF PHILOSOPHY
Graduate College of Education

2004

ABSTRACT
DOES INTRUSIVE COUNSELING INTERVENTION POSITIVELY IMPACT THE

RETENTION OF AT-RISK FIRST-TIME-TO-COLLEGE STUDENTS?

Stanley Scott Chase

The question whether intrusive counseling positively impacts the retention of at
risk students was motivated by national and local high attrition rates. If colleges are to
increase or maintain enrollment, creative means for retaining students is crucial; this
factor was a primary driving force of this study. The purpose of this study is to
investigate retention tendencies of at-risk first-time-to-college students at Lansing
Community College.

This study examined intrusive counseling intervention with a population of at-risk
students and their re—enrollment in subsequent terms. Intrusive counseling focused on the
areas of student need, such as coping skills, self-confidence, self-image, anxiety, beliefs,
expectations, prejudices, academic ability, and connectedness to the college campus and
its resources. A pilot study was conducted to identify factors that were strong predictors
of students who may be at-risk of dropping out (find jobs before degree completion) or
stopping out (leave for a semester or two and return). The study revealed several
characteristics that provided high predictability of success and identified at-n'sk students.

The items utilized were:

0 Ethnic background 0 High school grade point average

0 Number of hours employed 0 College financial situation
i The methodological design of the study allowed for the predictors of success to be
included on the admissions application, resulting in the identification of the target
population of those students who are at-risk of not continuing in the subsequent term.
Over a three-semester time-span, each of 897 students who did or did not meet with a
counselor became a member of the research sample group.

The target population was tracked to determine the number of students who re-
enrolled in subsequent terms and whether there existed a significant difference between
the re-enrollrnent of the target group who did meet with a counselor and those who did
not meet with a counselor. The results of the study revealed students who did meet with
a counselor were single and non-white; students who did not meet with a counselor were
white. Further, the study showed that students who meet with a counselor were generally
more academically oriented and tended to carry more credits. The study found that the
academic performance of students who did meet with a counselor was not significantly
different from those students who did not meet with a counselor. The study revealed that
students who did meet with a counselor across all semesters were significantly more
likely to re—enroll in subsequent semesters than those who did not meet with a counselor.

The results of the study allowed for the following conclusions to be made by this
researcher. Emphasis should be placed upon the importance of counselor intervention on
at-risk first-time-to-college students. The data indicates a strong relationship between
intrusive counseling and re-enrollrnent in subsequent semesters. The lack of significant
differences in academic performance should not minimize the significant benefit that can

be achieved relative to the retention of at-risk students who meet with a counselor.

Cepyright by
STANLEY scorr CHASE
2004

Dedicated to my wife, Yvette Chase, whose steadfast belief in my capabilities
served to sustain me throughout this entire process. Yvette’s love, her prayers, words of
encouragement, patience and quiet, deep, strength has allowed this dream to become a
reality. To my mother, Doris Rose-Ella Cephas, and my aunt and uncle, Mary Chase and
Reverend Harvey G. Chase, Jr. who have always encouraged and challenged me to
achieve excellence and who instilled in me the knowledge and power of, and the love for,
education. Their faith and encouragement in me never ceased. My deep love and thanks

to you all.

Acknowledgements

First and foremost, I thank God for the wisdom, courage, and strength He so
graciously and unselfishly instilled within me. “What shall I render unto the Lord for all
his benefits toward me? I will pay my vows unto the Lord now in the presence of all His
people.” To God be the glory.

I would also like to extend a special thanks to Dr. Christopher Dunbar, the chair
of my Dissertation Committee, for his constant encouragement and support. He provided
a balance of optimism and realism throughout the journey, a perspective which allowed
me to persist to completion. Also a special thanks to Dr. David Arsen, Dr. Phillip
Cusick, and Dr. Elaine Yakura, my Dissertation Committee, for their continued guidance,
support, and push toward greater scholarship and excellence.

I am especially gratefiJI to Professor Robert Bentley, Dr. William Brown,
Professor Paul Elam, Dr. David Evans, Ms. Cheryl Schofield, and Professor Jennie
Weber who’s intellectual, statistical, and computer expertise assisted me in the attainment
of this goal.

Finally, I acknowledge a huge debt of gratitude to many of Lansing Community
College’s administrators, faculty, and staff who provided the support and encouragement

needed for me to attain my goal.

vi

TABLE OF CONTENTS

LIST OF TABLES ........................................................................................................... viii
LIST OF FIGURES ........................................................................................................... ix
CHAPTER 1: INTRODUCTION ...................................................................................... 1
Statement of the Problem ................................................................................................ 1
Background ..................................................................................................................... 2
Purpose ............................................................................................................................ 3
Significance .................................................................................................................... 3
CHAPTER 2: LITERATURE REVIEW ........................................................................... 5
Introduction ..................................................................................................................... 5
Relevance Of Retention .................................................................................................. 5
Factors Affecting Retention ............................................................................................ 7
What Works (Features of the Institution that Affect Success and Retention ............... 11
Student Services and the Impact of Counseling on Retention ...................................... 16
CHAPTER 3: METHODOLOGY ................................................................................... 18
Introduction ................................................................................................................... 18
Predictors of Success — Pilot Study .............................................................................. l9
Intervention ................................................................................................................... 22
Program Theory ............................................................................................................ 24
Addressing Sample Selection Bias ............................................................................... 27
Data Collection and Analysis ....................................................................................... 28
Role of Researcher ........................................................................................................ 28
CHAPTER 4: ANALYSIS AND RESULTS .................................................................. 29
Description of Test ........................................................................................................ 29
Description of Data ....................................................................................................... 29
Design of the Analysis .................................................................................................. 30
A Note on Interpretation ............................................................................................... 31
Expected Outcome Measures ........................................................................................ 32
CHAPTER 5: CONCLUSIONS, IMPLICATIONS OF RESEARCH, and
FUTURE RESEARCH SUGGESTED ............................................................................. 50
Introduction ................................................................................................................... 50
Finding, Implication for Practice, and Conclusions ..................................................... 51
Recommendation for Future Research ......................................................................... 56
Final Comments ............................................................................................................ 58
APPENDIX ...................................................................................................................... 61
Appendix A ................................................................................................................... 62
BIBLIOGRAPHY ............................................................................................................. 66

vii

LIST OF TABLES

Predicted Completion Rates .............................................................................................. 20
Table 1 Early Warning Group Proportions across Semester ............................................ 33
Table 2a Early Warning Spring 1999: Demographic Profile across Groups .................... 34
Table 2b Early Warning Spring 1999: Student Profile across Groups ............................. 36
Table 2c Early Warning Spring 1999: Academic Profile across Groups ........................ 37
Table 3a Early Warning Fall 1999: Demographic Profile across Groups ....................... 38
Table 3b Early Warning Fall 1999: Student Profile across Groups ................................. 39
Table 3c Early Warning Fall 1999: Academic Profile across Groups .............................. 41
Table 4a Early Warning Spring 2000: Demographic Profile across Groups .................... 42
Table 4b Early Warning Spring 2000: Student Profile across Groups ............................. 43
Table 4c Early Warning Spring2000: Academic Profile across Groups .......................... 44
Table 5a Early Warning Spring 1999: Subsequent Enrollment across Groups ................ 45
Table 5b Early Warning Fall 1999: Subsequent Enrollment across Groups .................... 47
Table 5c Early Warning Spring 2000: Subsequent Enrollment across Groups ................ 48

viii

LIST OF FIGURES

Figure 1: Program Theory Model ..................................................................................... 26

ix

CHAPTER 1
INTRODUCTION
Statement of the Problem

Student attrition has been a focal point in higher education for many years.
Despite all of the efforts to address the needs of the student through programming and
dialogue, an enormous number of students continue to drop out of college before they
achieve their educational goals. National Center for Education Statistics (N .C.E.S.)
(1999) and American College Testing (A.C.T.) (1998) report that it is not uncommon for
colleges and universities to experience attrition rates ranging from twenty-five to sixty
percent of their freshmen classes. One study shows, four-year universities report that
49.8% of their students drop out, while two-year colleges experience dropout rates of
67.6% ACT (1998).

Figures on the persistence rates among community college students reported as
early as 20 years ago (London, 1989 and Zwerling, 1976) remain as consistent today as in
earlier studies. Public, private, two year, and four-year institutions express continued
interest in reducing their dropout rates (Tinto, 1984 and 1993). Two year public colleges
(for the purposes of this study, two-year public colleges include liberal arts and
vocational colleges) have been the most likely to experience the highest, most sustained
attrition rates. This has been attributed to the open enrollment policies of the community
college, where, for example, the college admits students who have been turned down
previously by other four-year colleges. Among institutions, it is clear that keeping

students is as important as attracting them.

Sixty-three percent (63%) of students who began their postsecondary education at
United States (US) community colleges in 1989-90 had not completed a degree at an
institution by 1994. Further, 22% of the 37% who graduated college completed an
Associates Degree at their first institution (US. Department of Education 1998). The
relatively high dropout rates from the two-year colleges can be attributable partially to
the relatively high dropout-proneness of their entering students (Cope, Hannah 1975).
“About two-thirds of high school graduates continue to pursue a higher education,” said

Wes Hadley, Director of the ACT office for the Enhancement of Education Practices, but

 

some of these are not prepared whether academically or socially to succeed (ACT 2001 ).
There must be a reason or reasons this occurs. Studies on why students leave or drop out
may be beneficial to college officials and may, in some cases indicate clear, corrective
actions that could reduce attrition.
Background

Beginning in1991, Lansing Community College (LCC) began to experience a two
pronged concern: a decline in its enrollment and a constant struggle to reduce both
attrition rates and to improve student retention. The attempts by the college to reduce
student attrition through programs such as freshman orientation, mentoring programs, and
student success courses used as tools employed to improve attrition have achieved
marginal success.

In an attempt to reverse this trend, the college (LCC) decided to institute a student
success initiative to reduce the attrition rates of at-risk first-time-to-college students (for
the purpose of this study, at-risk students are defined as those student who are at risk of

stopping-out, dropping-out, or not achieving their academic goals).

The problem was addressed by instituting an intrusive counseling program that
established a one-to-one counselor/student relationship and guidance in an effort to
support the academic and social needs of students.

Purpose

This study researches the impact of intrusive counseling on this population of
community college students. This study investigated whether intrusive counseling
impacts the retention and academic success of students who are at-risk of leaving the
college. Intrusive counseling is defined as a process of connecting students early in their
educational journey with counselors to engage in a systematic approach that incorporates
academic, social, emotional, and individual counseling at regular intervals. Further,
intrusive counseling is a holistic approach that addresses the student’s situational factors
affecting persistence including role conflict, time management, financial and
transportation needs, and children. Finally, intrusive counseling addresses psychological
influences such as coping skills, self-confidence, self image, anxiety about school based
upon prior experience, beliefs, expectations, prejudices real or imagined, and the
student’s ability to be successful.

For the purposes of this dissertation, “success” is defined as completing the
enrolled course with a grade of 2.0 or higher, and re-enrolling in the subsequent term
(retention).

Significance

College enrollment revenues, in most cases, can be increased significantly by a

modest increase in the percentage of students who re-enroll. This research can be

invaluable to college administration when planning for retaining students, stabilizing

enrollment, projecting budgetary needs, solidifying budgets in tough economic times, and
planning strategy. It is more economical to have students re-enroll than to continually

market for a new group to fill the void.

CHAPTER 2
LITERATURE REVIEW
Introduction

A review of the literature on student retention at the community college reveals
four primary considerations which will be explored in this section. The first section
reviews factors that have made student retention an important issue. The second section
reviews research on factors that affect college success and retention. The third section
discusses research on institutional factors that impact student retention and the fourth
section of the review discusses student services and the impact counseling has on student
retention.

Relevance Of Retention

Student attrition is a concern at all educational levels. Beginning with McNeely
(193 8), education researchers using retention rate as an indicator of performance report
that 55% of students were retained until college graduation. Over time retention research
moved beyond simply tracking rates to examining the causes, impacts, and remedies of
student attrition (Cope & Hannah, 1925, Noel et al., 1985; Tinto, 1987). At elementary
and secondary levels, retaining students for poor performance is a mandate of state and/or
local governing bodies. However, at postsecondary levels, student retention is not
mandated. Despite all of the attention (governmental concern, legislative mandates,
policy changes, or community awareness of the problem), many students still drop out of
college before they achieve their educational goals. Approximately half of the freshmen
enrolled in colleges and universities drop out before completing their programs; this rate

is fairly stable (US. Department of Education 1998). Department of Education statistics

verify that the dropout rate at community colleges is greater than that of four-year
institutions, which substantiates the importance of this study to the community college
arena.

Studies investigating retention and attrition of students in community colleges
indicate high dropout rates can be attributable particularly to the relatively high drop out
proneness of their entering students (Cope, Hannah 1975). Additionally, greater
accountability in higher education has resulted in enhanced reliance by colleges and
universities, governmental agencies, and the general public on measures of economic
accountability and institutional effectiveness. Nedwek and Neal (1994) note that through
the 1992 Reauthorizations of the Higher Education Act of 1965, the United States
Congress has established fresh opportunities for scrutiny of higher education institutions
using a vast array of measures. The institutional overall focus has shifted accordingly.
An institution’s retention rate is one widely employed indicator of its effectiveness, yet
other increased accountability in higher education necessitates a greatly expanded
understanding of retention rate analysis, of tracking, of behavior, and how this
information can be used in evaluating college or university effectiveness. Studies on why
students leave or drop out can be beneficial by indicating corrective actions that could
reduce attrition. Success in lowering attrition rates could also promote many associated
benefits, including stabilized enrollments, utilization of unused capacity, increased goal
attainment (graduation) rates, and improved student academic performance. Further,
these studies can help to focus financial resources on students most likely to be

successful. Retention is a paramount concern that colleges and universities should

monitor, analyze, and consider in their decision making on a regular basis says Whiteley,
Porter and Fenske (1992), and the American Association of Community Colleges (1994).

Large numbers of students dropping out of community colleges can have an
impact on college operations and funding. This study will be viewed from the lens of the
college administrator because first, the student-centered focus of the college is a key
factor in students reaching their goals, and second, the utilization of counselors with at-
risk students is a great investment that could result in the reduction of student attrition,
enrollment stabilization, and revenue enhancement. Stabilization of enrollment allows
for predictive enrollment capabilities for strategic planning and budgeting. Executive
leadership will find enrollment stabilization valuable to the entire college community,
both student and administration.

This study will fill gaps that exist in the literature relating to retention of at-risk
community college students and will provide information on the role that counselor
intervention has upon student retention.

Factors Affecting Retention

Attributing factors basic to understanding the successful retention of college
students is a frequent and at times complex discussion. Learning why some students are
able to achieve success and others struggle with social and academic issues is important.
Research has focused on determining and understanding those factors that influence both
retention and attrition.

Much of the research on retention is guided by Tinto’s model that focuses on the
academic and social integration of students into college and university life. Tinto (1993)

argues that students enter college with family influences, attained academic skills, and

preconceived ideas of what the college experience will be. He claims that these
individual attributes interact with the academic and social environment of the college to
positively or negatively influence students’ commitment to complete their educational
goals and to persist at the institution.

The academic arenas of the college are characterized by grades and intellectual
development while the social arena includes interaction with faculty, students, and
college administrators, and can also include student participation in the extra-curricular
activities of the college. Tinto’s model of connectedness and social integration has been
tested and generally supported in studies of four-year, residential institutions. Grosset
(1989) reviewed some of the research that applied to Tinto’s model at nonresidential
colleges, inclusive of two-year and four-year colleges. This later study suggested that
Tinto’s model may not explain retention/attrition at commuter colleges and may be even
less explanatory at community colleges. Grosset concluded her review by suggesting that
there is no generalized, all-purpose, attrition model applicable to all institutions. Studies
by Brooks-Leonard (1991), Daniels, (1990), Grosset, (1989), Voorhees, (1987), and
Sarkar (1993) each analyzed one or two specific factors to determine whether they
influenced retention or attrition rates. The approach in these studies contributed to a
listing of substantial factors but do not identify which may be more important and which
may contribute uniquely to retention and attrition. Based on her study of retention at the
community college of Philadelphia, Grosset found that a student’s ethnicity, basic skills,
admission test scores, and type of high school attended (public or private) were tied to

persistence.

Voorhees (1987) studied community college persistence among 369 new and
continuing students who responded to ACT student’s opinion survey. He tested four
different models and studied two factors at a time:

1. Gender and full-time/part-time status

2. Purpose for enrolling and ethnicity

3. Intent to return and satisfaction with the institution

4. Factors of grade-point average, informal interaction with faculty, and weekly
study hours.

Voorhees concludes that the only factors related to persistence were purpose for
enrolling, intent to return, and gender. His findings suggest that while ethnicity, grade
point average, interactions with faculty outside of the classroom, number of hours
studying, and full-time or part-time status were important, they did not significantly
correlate with persistence.

Brooks and Leonard (1991) tested the impact of educational objectives, full-time
or part-time status, hours worked, age, gender, income, prior educational level, remedial
need, marital status, and race on 796 first-time students) at the Indiana Vocational
Technical College. They found that the factors evident in those who persisted compared
to those who did not persist were educational objectives, full-time or part-time status,
age, hours worked, and first term grade point average. Students who were employed full-
time, and those over 40 years of age, exhibited lower retention.

1557 first time college students from the four campuses of Saskatchewan Institute
of Applied Science and Technology who were seeking either certificate or degree goals

were studied by Sarkar (1993) questioning the impact on student success using seven

factors. These were (1) reasons for taking program, (2) goal commitment, (3) educational
ability, (4) academic/social integration, (5) satisfactory/use of services, (6) student
characteristics, and (7) labor market conditions. Sarkar found that non-completers
differed significantly from completers except in the area of academic and social
integration. Sarkar’s findings also revealed that when students identified reasons for
selecting a specific program, non-completers had lower educational goals. Goal
attainment was lower for non-completers who were less certain about their career choice,
expressed less goal commitment, and had set for themselves lower final educational
goals. Educational ability and previous educational achievement were lower for non-
completers. There was no significant difference in academic and social integration
between non-completers and the total sample, measured by participation in various
activities and groups. Tutorial help, counseling services, computer labs, and library
facilities were more frequently used by non-completers. Within student characteristics,
non-completers are more likely to be disabled, of aboriginal ancestry, female, married,
and have dependent children. They are more frequently employed and work more hours.
Non-completers were more influenced by the current economic conditions. Sarkar
(1993) did not focus on the types of support services that must be accessible, but he does
indicate that these services must allow greater flexibility and that counseling services are
an integral part of this process.

Feldman (1993) conducted a quantitative study with l 140 first-time community
college students considered most likely to persist. She found student gender, ethnicity,
age, status, goals, and basic skills need all had significant influence on retention.

Feldman noted that all but remedial need was associated with whether or not a student

10

returned in one year. F eldman states that four factors were significant predictors of
attrition: ethnicity, full-time/part-time status, age, and high school grade point average.
Feldman also suggested that factors identified as significant predictions of student risk
are available prior to the beginning of the students’ college program. Further, students
who are at-risk would be better served the earlier they could be identified. She continues
by suggesting that colleges could utilize known at-risk characteristics to positively impact
attrition rates.

While Tinto’s model has been repeatedly validated and has served as a foundation
for much of the studies on retention, the focus of these studies has been at four-year
institutions and shows the needs of community college students as being different. The
literature on community college retention is somewhat limited. However, the data
available suggest characteristics that are statistically associated with student retention and
attrition which can serve as indicators for early identification of at-risk students. Given
this information, community colleges can take a logical next step. This step is to develop
strategies that will utilize this body of knowledge to identify those students who are at-
risk and to intervene as early in the matriculation process as possible, and thereby
improve the possibility of student success.

What Works
(Features of the Institution That Affect Success and Retention)

Institutions have been charged to provide service to a diverse student population,
a population whose face drastically changed over a 10-year period. During this span
(1984- 1994), the number of white undergraduates increased by 51% compared to a 61%

increase of Native American, African American, Asian American, and Hispanics

ll

graduates (Pascarella and Terenzini, 1998). Accountability for the success of these
students is partnered with the responsibility of the college to provide service. In this role
institutions are expected to provide an effective strategy that will promote retention by
this diverse population of first generation, adult, educationally disadvantaged, at-risk, and
minority students. Retention and persistence result from the interaction of a variety of
student characteristics, circumstances, and educational environment. The influence that
institutions have over student characteristics and circumstances is limited. It is suggested
that a more effective way to improve retention is to establish and communicate an
institutional perspective, policy, and attitude toward potential dropouts.

It is essential that the institution first define “dropout” before any such policy or
position on retention be developed. Wlodkowski (1985) says there are different types of
attrition. These include stopouts (those students who leave for a semester or two and then
return), dropouts (those who find jobs before degree completion), and personal interest
students. The first step is to identify those factors leading to attrition which are harmful
to the vitality of the institution and to student objectives. Tinto (1993) argues that the
practical question of what institutions can do to increase retention depends on why a
student drops out. This identification will assure that limited college resources are
targeted correctly, and the appropriate students receive service.

It is the role of the college to determine which type of dropout should be the focal
point of institutional action for the purpose of developing programs to retain these
potential dropouts. From a macro perspective, all students who withdraw can be labeled
as dropouts regardless of their motivations for departing, and the departure of some

students may be amenable to institutional action. Some actions may involve specific

12

segments of the student populations and include a number of different types of students.
Some actions by students may result in their permanent withdrawal from all forms of
higher educational endeavors. Some students may transfer to other institutions, some
may temporarily withdraw, some may stop out from their studies (Tinto, 1993). Student
departure for any of the above reasons results in a reduction of the seat count, the loss of
a potential graduate, and a reduced revenue source for the college. Without unlimited
supplies of replacement students, dropping out can have a devastating impact on the
institution and its potential for continued existence.

The definition and identification of specific types of student dropouts will permit
the institution to target specific programs for the implementation of an effective and
economically efficient retention program. For the purpose of this study, the focus is on
at-risk first-time-to-college students enrolled in a degree or certificate program who are
at-risk of dropping out/stopping out before they have graduated or have achieved their
academic goals.

The literature documents many retention programs that have been successful;
many of these programs share common features. Tinto (1993) enumerated these
commonalities in his identification of the “The Principles of Effective Retention.”

0 Effective retention programs are committed to the students they serve. They put the
welfare of students ahead of other institutional goals.
0 Effective retention programs are, first and foremost, committed to the education of

all, not some of their students.

13

0 Effective retention programs are committed to the development of supportive social
and educational communities in which all students are integrated as competent
members.

0 Institutions should provide resources for program development and incentives for
program participation that reach out to faculty and staff alike.

0 Institutions should commit themselves to a long-term process of program
development.

0 Institutions should place ownership for institutional change in the hands of those
across the campus who will implement that change.

0 Institutional actions should be coordinated in collaborative fashion to ensure a
systemic, campus wide approach to student retention.

0 Institutions should act to ensure that faculty and staff possess the skills needed to
assist and educate their students.

0 Institutions should continually assess their actions with an eye toward improvement.

0 Institutions should front load their efforts on behalf of student retention
Clearly, support for these expectations is found in the professional literature of

American College of Personnel Services (1994), Helgot and Culp (1995), Lyons, Miller,

and Trow (1994), and O’Banion (1987) and community colleges across the nation have

developed outstanding programs and practices enveloping these expectations. As they
have been put into practice, these expectations have been refined into goal statements
with a specific focus for professionals of student affairs, such as those characterized in

Becherer and Becherer (1995);

I4

Professionals of student affairs should provide leadership:

0 For a student-centered environment throughout the college.

0 For an instructional faculty collaboration to ensure student success.

0 For an array of enrollment services that ensure student access and smooth

transition from the enrollment of the student through matriculation.

o For an advising and counseling program that appropriately both challenge and

support student success.

0 For ensuring that the first time college student receives special attention and

support.

0 For ensuring appropriate educational interventions for students who seem

unlikely to meet their educational objectives.

0 For facilitating a program of student involvement that encourages institutional

community building through student/faculty interaction.

0 For developing and disseminating information about students to faculty and

policymakers and for building practices assuring student success.

The question of “what works” is identified here by what constitutes a student
dropout and is accompanied by institutional principles that must be in place for student
retention to be increased. Consider what programs an institution should adopt to reduce
student attrition, given the fact that student retention and learning are shaped by those
institutional characteristics shown above (Becherer and Becherer 1995). Students’ needs
should be identified and addressed from their first encounter with the college or

university before potential problems become full-blown issues.

15

Student Services and the Impact of Counseling on Retention

Student services continue to play an important part in the planning in two-year
college. As student services are analyzed from the perspective of retention, literature
strongly reiterates that counseling services for students is critical. O’Banion (1989)
argues that counseling has been ‘touted as the heart’ of the function of student affairs.
Other literature expresses varied opinions as to the importance of the role counseling or
counselors should play within the college or university. Recently, the need for
counselors has increased due to the changing nature of students at the community college.
Campuses are impacted by the increased numbers of minorities, by academically
disadvantaged, by economically deprived, by adults and, by women enrolling in colleges
says C011 (1993). He states not only campuses are impacted by the need for services, but
students have expressed an increased need for counseling. It has been suggested by some
that counseling support should be restricted to the academic needs of students rather than
the focus on vocational education. Others suggest career and vocational counseling must
be offered. Still another group espouses the whole-person philosophy; the individual is
more than a student so a holistic approach that addresses personal, psychological,
academic, and vocational needs should be included in the delivery of counseling services.

At Lansing Community College, the counseling process is viewed first as a
developmental process that assists students in the clarification of life and career goals.
Second, the design process assists students in the development of educational plans for
the realization of their goals and to provide connections with other campus resources
within the college environment. Last, the counselor serves as an anchor, a -

communication facilitator, and an ombudsperson charged with assisting the student from

16

goal declaration to goal attainment. Proponents of a counselor-focused system suggest
that counselors are in a better position to refer students to institutional resources because
counselors have greater experience in goal setting, career selection, life planning, and
personal problem solving.

General support exists for the importance of good counseling in student success
and retention. Theories of integration (Tinto, 1993) and involvement (Astin, 1993)
address the importance of the interaction between the student and the environment. A
study by Seidman (1991) supports the premise that student interaction with counselors
resulted in a significantly higher rate of retention than the group that did not interact with
a counselor. This study planned a series of ongoing interactions between students and
counselors that began from the moment a student expressed intent to attend the college
and continued through the first semester. Seidman (1991) concluded that early and
persistent intervention can make a difference. The pre/post admissions/counseling

process positively affected student retention rates.

17

CHAPTER 3
METHODOLOGY
Introduction

The purpose of this study was to test the impact of intrusive counseling strategies
with at-risk first-time-to-college students at Lansing Community College. It is a known
factor and not uncommon for colleges and universities to experience attrition rates
ranging from 25% to 60% of their freshman classes, with one example showing retention
rates of 59% for low income students compared to 71% for their non-poor counterparts.
(N CES, 2000). In this study, student data was extracted from the college management
records and student contact tracking systems and was analyzed to identified strategies
that may be instituted to increase retention of at-risk first-time-to-college students. An
established factor in retention is student connectedness. It is important for colleges to
know whether counseling of students during their first semester contributes to
connectedness and aids in student retention.

Success is the dependent variable for this population of at-risk first-time-to-
college students who completed first semester courses and returned for the subsequent
semester. In general, continued enrollment for LCC students from Spring 1999 to Fall
1999 was 53.1 percent; continued enrollment from Fall 1999 to Spring 2000 was 57.7
percent (LCC Office of Institutional Research, 2001).

This research investigated how intrusive counseling would impact and aid the at-
risk student to be persistent and successful. Tinto and Spady’s theory of social and
academic integration was utilized as a foundation to guide this study. Tinto’s (1988)

model was developed to explain the learning behavior of students in educational

18

institutions. He argues that student departures would be reduced if their interactions with
the institutions social and academic systems were deepened. Spady’s model stated that
such interactions give the student opportunities to succeed in the social and academic
system of the institution.

The focus of this study was on the weaknesses in college planning, rather than on
what is wrong with the student that causes them to leave. This study seeks to determine
how the college can increase the retention rates of at-risk first-time-to-college students by
providing intrusive counseling.

Predictors of Success — Pilot Study

This study was conducted at Lansing Community College, a North Central
Association Accredited college. A large urban college that enrolls approximately 18,000
students, the population is varied with 77.5% white students and 15.3% minority students
and 7.2% are of undisclosed races. The average age of the student is 27.5 years. The
sample is being selected from the total population of entering first-time—to-college
students of Spring 1999, Fall 1999, and Spring 2000.

This pilot project was conducted to identify factors that are strong predictors of
students who may be at-risk of dropping out or stopping out. Involved were 897 students
who responded to a series of 32 survey questions asked of first-time-to-college students
enrolled in Gateway courses (Appendix A). Following the completion of the survey,
these students were tracked to determine their persistence to successfully complete their
course(s) and to correlate that success to the responses in the survey. In this pilot study,
student success is acquiring a 2.0 grade point average or higher in the courses in which

they had enrolled, and their persistent re—enrollment in the following semester. The

19

findings of the study revealed that several questions could be used to provide a high
prediction of success. The statistical procedure used for this analysis was logistic
regression. Areas showing a high correlation are shown as completion rates in the
following table. '

Predicted Completion Rates

 

 

 

 

 

 

 

 

 

 

 

 

 

SURVEY ITEM Predicted Completion Rate
Item 1: Course
MATH 107 .48
PSYC 200 .68
ELTE 100* .74
Item 2: Course Taken Before
Yes .36
No .65
Item I 3: Average High School Grade
A .76
B .65
C .53
D .38
E/F .27
Item 14: Self-reported Assignment
Always complete .72
Usually complete .56
Sometimes complete .33
Never complete "
Item 15: Last attend school fitlI-time
35 years ago .71
1 year ago .61
2 years ago .51
3 years ago .54
4 years ago .50
Item 16: Last level of education registered fitll—time
HS, Vocational, University .65
Community College .53
Item 19: Level of math education
Basic math (arithmetic) .4]
Algebra I .49
Geometry .57
Algebra II .65
Pre-calculus or higher .72
Item 24: Employment hours working per week
Less than 10 .68
Between 10 and 20 .65
Between 20 and 30 .61
Between 30 and 40 .57
More than 40 .54
*Electrical Technology ** Sample size too small

20

These questions and data elements were placed on the admission application, and
were used to identify students at-risk, and were selected as the sample for this study:
0 Ethnic Background
0 My high school grade point average
4.0 3.0 2.0 1.0 0.0
o How many hours per week do you plan to work your first semester?
0 Not Working
o 10 hours per week or less
0 11 to 20 hours/week
o 21 to 30 hours/week
o 31 to 40 hours/week
o more than 40 hours/week
0 My financial situation regarding college is as follows:
0 I will have enough money
0 I will need financial assistance
0 I don’t know yet
Average high school grade: American College Testing Report states “the factor of
students’ course work taken and the grades earned in high school most strongly relate to
their performance in college” (ACT, 2001).

Hours employed: Economic factors can play a significant part in the student’s

 

persistence in college. Significant numbers attend college part-time as a result of
competing priorities. Feldman (1993) and Price (1993) concur that the most prevalent

characteristic among studies of non-persisters is part-time attendance.

21

Ethnicity: Attrition rates for both minorities and non-minorities continue to be a
serious problem in most community colleges. Nora and Rendon (1998) note attrition
rates for minority students in some two-year colleges is about 60% and in some instances
as high as 80%.

Financial situation: While the factors indicate a marginal relationship between

 

financial status and persistence, this was included in the indicators. The inclusion of this
information was based on research that stated 59% of low-income students complete
college compared to 71% of their counterparts (NCES, 2000).

When answered in a specific manner, the completion of the admission application
containing the data elements and questions resulted in the identification of the target
population (students at high risk of not completing). Subsequent to identification of the
target population, all identified students were contacted to come in for a voluntary
meeting with a counselor. Students who accepted the invitation entered into a
relationship with a counselor and became members of the research sample group.

Intervention
Once the students were identified, the following process was implemented:

0 A group of students was randomly assigned to a counselor.

o A letter was sent to each student requesting a meeting with a counselor to get
acquainted with the college and its resources and to discuss the student’s
academic goals.

0 A follow-up telephone call was made to each student by peer advisors inviting the

student to the college.

22

0 Contact by the counselor or peer advisor was made with the students during
weeks 3, 6, 9, and 12 of the semester. Students who had not responded to the
initial contact were again invited in. If the student had made contact, this contact
was used to check their progress.

0 Information on students who did meet with a counselor was recorded in the
Counseling Advising Tracking System (CATS).

0 Following the end of the semester, academic information was assessed using the
Academic Records Sofiware System.

0 This information record in the system contained data on:

0 students flagged as at-risk and who did meet with a counselor.
0 students flagged as at-risk and who did not meet with a counselor.
0 performance data of the total college student population.

Currently, student demographic data are kept in the college student records
system and were accessible for the study. Additionally all dropouts (students who leave
during or at the end of a semester and do not return), stopouts (students who leave for a
semester and return), course grades, and curricula status are kept in the same system.

Student academic records involved in the study are in the record system; however,
a separate database is utilized to track student/counselor contact. The student services
(SRVS) tracking system is utilized to track all contacts between counselors and students
and to document anecdotal notes; while the information is confidential, for the purpose of

this study permission was given to retrieve relevant information on counselor contact.

23

Program Theory

The Program Theory model (Figure 1) provides a visual of the overarching
theoretical assumptions on which the Intrusive Counseling Initiative is based. It is an
inductive model that guided the research on the counseling interventions of Lansing
Community College. There is strong support for the Intrusive Counseling Initiative and
its impact on future college activities and student outcomes inclusive of initial,
intermediate, and/or long-term support. College administrators and program directors
have the discretion of deciding where the activities and/or outcomes should lie within this
spectrum.

In the Intrusive Counseling Initiative, the initial activities by the College are the
development of early intervention mechanisms; such as questions placed on the
admissions application and the improvement of academic counseling. These activities
lead to intermediate activities to assure students are scheduled properly and receiving the
support necessary to assist in their success that consists of faculty and staff involvement
in retention efforts and the development of a college-wide referral system. Once these
activities are in place, long-term activities will take place; these consist of the
development of student-centered attitudes and a sense of community.

Student outcomes for the Intrusive Counseling Initiative are portrayed in a similar
manner within the Intrusive Counseling model where outcomes are measurable and can
be compared over a period of time to indicate progression or lack thereof. Initial student
outcomes consist of identification of educational goals and increased course completion
rates. When students identify an educational goal, they are more likely to take and to

complete courses that move them closer to that goal. Intermediate outcomes involve the

24

development of college-wide support systems and educational goal commitment. Last,
increased Ieaming, increased student retention rates, and increased graduation rates
identify long-term outcomes.

While the model may appear linear in nature, the assumptions are not linear at all.
The theory assumes that these activities and outcomes are needed to present the model in
its entirety, but does not assume that every outcome or every activity must be performed

to achieve the educational goal attainment of all students.

25

Figure l

 

 

PROGRAM THEORY MODEL

Intrusive Counseling

 

 

Colleqe Activities Student Outcomes
Initial Activities/Outcomes 1
Develop Early Intervention Educational Goal Identification

Techniques

1 1 Increased CourselCompletion

 

 

Improve Academic Counseling t b
1 Educational Goal Commitment
Intermediate
Activities/Outcomes
Development of Referral System Development of Support
1 l Systems
Faculty and Staff Involvement 1
¢ —> Increased Student Retention
Long-Term l
Activities/Outcomes
Student Centered Attitudes
l Increased Learning

 

Increased Graduation Rates

Sense of Community \ /

Achieve Educational Goals

1 ‘ j ’ l

 

Program Theory Model (diagram and explanation)

26

 

Addressing Sample Selection Bias

This study identifies at-risk first-time-to-college students using the Lansing
Community College admissions application form and the pro-active efforts to provide
counseling for those students. The research is designed to evaluate the impact of
counselor intervention on the retention of at-risk first-time-to-college students.

A variety of explanations exists for any differences observed between the students
who did meet with a counselor and those who did not, only one of which is the positive
influence of counseling services. All invited students who come in may be motivated by
something other than counselor intervention. Out of ethical considerations, it was not
appropriate to withhold services to establish a control group. The issue of multiple
competing explanations is of concrete relevance to the present study, as a variety of
explanations for differences between students who did or did not meet with a counselor
are addressed. One alternative explanation is that students who seek counseling are more
motivated to succeed than other at-risk students who do not. Better performance may be
due to traits such as time management, desire to succeed, and other such factors.

To account for these explanations, a slight alteration in the focus of the analysis
adequately addressed this issue. Rather than conceptualizing the systemic differences
between students who did or did not meet with a counselor as a nuisance variable, both
the demographic and academic profiles of these two groups were examined in detail.
Thus, an extended focus of the analysis is to understand the nature of the students who

make use of the intrusive counseling services available to them.

27

Data Collection and Analysis

This study consisted of at-risk first-time-to-college students identified through the
application process and the intrusive counseling for these students. Names of students
who fit the at-risk characteristics were obtained from the college records system.
Following the end of each semester, (Spring 1999, Fall 1999, Spring 2000) student
counselor contact with the target population was gathered from the Student Services
Tracking System and subsequent enrollment data collected from the student records
system. The purpose was to examine the effectiveness of counseling in enhancing
student academic performance and increasing continued student enrollment.

The design of the analysis is to compare students who did meet with a counselor
with students who did not meet with a counselor during Spring 1999, Fall 1999, and
Spring 2000.

A Chi-square test was utilized to determine if the subsequent enrollment of at-risk
students who did meet with a counselor was significantly greater than those at-risk
students who did not meet with a counselor.

Role of Researcher

This study is based upon this researcher’s experience in tracking the persistence
of at-risk first-time-to-college students. Such monitoring has revealed a need to identify
strategies that will assist first-time-to-college and at-risk students to achieve success
(defined as the student achieving a 2.0 or higher GPA and persisting from semester to
semester). Both nationally and locally, continued high attrition rates have motivated this
researcher to investigate practical strategies that may be implemented to reduce attrition

rates for at-risk first-time—to-college students.

28

CHAPTER 4
ANALYSIS AND RESULTS

This research was guided by the question, “Does intrusive counseling positively
impact the retention of at-risk first-time—to-college students?” This research question
concerned the relationship between one or more meetings with a counselor and the
impact of this connection on student retention. A cohort study was utilized to analyze the
impact of counselor intervention on academic success and retention. Those who received
counselor intervention were compared with similar students who did not receive
counselor intervention.

Description of Test

Chi-square tests were used to determine whether the rates of retention differed
significantly. A one-time t-test designed with a control group was employed to determine
if the results indicated whether students who did meet with counselors re-enrolled the
next semester at a higher rate from those students who did not.

Description of Data

The first segment of the analysis focused on the demographic characteristics and
student profiles of the sample population. The second segment examined the
effectiveness of counseling interaction in enhancing student academic performance and
increasing subsequent enrollment.

Data for this analysis came fiom several sources. The Counseling Services staff
provided 897 names and student numbers that formed the basis of the sample population.
From the Counselor Advising Tracking System (CATS) database information was

obtained showing the number of students who had met with a counselor. Enrollment

29

"._

Tracking Files (ETF) maintained by Institutional Research, Analysis, and Reporting
(IRAR) provided the student profile data, grades, and performance indicators for these
students.
Design of the Analysis
The design of the present analysis designates specific comparisons between
students who did meet with a counselor and those who did not:
Section 1.) General Report on Sample. Comparison of
0 Students who did meet with a counselor
0 Students who did not meet with a counselor
Section 2.) Early Warning Spring 1999. (Tables 2a, 2b, and 2c) Comparison of
0 Students who did meet with a counselor
0 Students who did not meet with a counselor
Section 3.) Early Warning Fall 1999. (Tables 3a, 3b, and 3c) Comparison of
0 Students who did meet with a counselor
0 Students who did not meet with a counselor
Section 4.) Early Warning Spring 2000. (Tables 4a, 4b, and 4c) Comparison of
0 Students who did meet with a counselor
0 Students who did not meet with a counselor
Section 5.) Early Warning Subsequent Enrollment Across Groups.
(Tables 5a, 5b, and Sc) Comparison of
0 Students who did meet with a counselor
0 Students who did not meet with a counselor

- General college population

30

In this study, “Early Warning” refers to students who were “identified on their
LCC admissions application as showing two or more of the ‘at-risk’ factors, including
first-generation college enrollment or minority status.” Identified at-risk students
received an introductory letter that assigned a counselor for them; peer advisors contacted
students and encouraged them to meet with their counselor. Students received two
additional follow-up letters over the semester advising them of relevant workshops and
events and contained additional counseling and registration information.

The CATS database used by LCC counselors was utilized to record names of
students who did or did not meet with a counselor. Note that the accuracy of the database
is dependent upon each counselor having met his/her responsibility in recording whether
the student received support services.

A Note on Interpretation

When interpreting the findings of this analysis, it should be noted that student
participation in this study was voluntary and based solely on whether to engage a
counselor. A variety of explanations exists for any differences observed between the
students who did meet with a counselor and those who did not, only one of which is the
positive influence of counseling services. Students who took the initiative to meet with a
counselor may have been those who maintained a higher level of academic performance
compared with those students who did not meet with a counselor. Their potentially
higher rates of course completion or better academic performance could be attributed to
their own scholastic abilities, tenacity, or motivation, including as well the influence of
counseling services. Multiple explanations for the observed findings are inherent in any

design that does not use random assignment to the treatment or service under evaluation.

31

In this study, the staff of Counseling Services chose to forgo random assignment out of
an ethical consideration that counseling should be provided to all students who could
benefit from it. However, the issue of multiple competing explanations is of concrete
relevance to the present study and is available to determine differences between groups of
students who did or did not meet with a counselor.
This issue by conceptualizing the systemic difference between students who did
or did not meet with a counselor as a nuisance variable examined both the demographic
and academic profiles of these two groups in detail. The primary focus of this segment of
the analysis is to understand the nature of students who make use of services available to
them.
Expected Outcome Measures
By targeting at-risk first-time—to-college students, the following outcomes were
anticipated:
0 An improvement in year-to-year student retention rates
0 An enhanced level of involvement among counseling staff in retention efforts
0 The development and implementation of a strong research base for evaluating
retention activities.
From the research, the expectation was for higher academic success and retention rates

among the at-risk targeted experimental group compared with the at-risk control group.

32

Section 1: Report on Samjle.

 

Table 1 Early Warning Group Proportions across Semester.

 

Did Meet with No Record of Meeting

 

 

Prole ct Counselor with Counselor Total Sample
Early Warning Spring 2000
Count 80 191 271
% of Total 29.5% 70.5% 100.0%
Early Warning Fall 1999
Count 149 335 504
% of Total 29.6% 70.4% 100.0%
Early Warning Spring 1999
Count 90 32 122
% of Total 73.8% 26.2% 100.0%
Table 1:

Each of these three groups (cohort) represent students enrolling at LCC in the

respective semester. These data are provided primarily to indicate the sample sizes of the

subsequent analyses. Due to incomplete documentation from the CATS database, the

absolute proportions of students in these groups should be interpreted with caution.

Information available indicated that the proportion of Early Warning students who

did meet with counselors was considerably higher in the Spring 1999 semester than in

both the Fall 1999 and Spring 2000 semesters. This proportional difference may be

attributed to an increased student realization of the need for counseling assistance, or the

degree of counselor effort in contacting students, or the enthusiasm of counselors and

peer advisors in contacting students.

33

Section 2: Early WarningSpring 1999

Table 2a Early Warning Spring 1999: Demographic Profile across Groups.

 

 

 

No Record of
Did Meet with Significance of
Meeting with Total Cohort
Counselor Counselor Difference
Demographics
As.
Mean 27.0 29.1 t(107) =.919, nonsig 27.5
SD 9.9 1 1 .4 10.2
Gender
Male 42 52.5% 13 54.2% {(1) = .021 , nonsig 55 52.9%
Female 38 47.5% 1 1 45.8% 49 47.1%
Marital Status
Single 66 78.6% 16 64.0% {(1) = 2.78. sig 82 78.6%
Married 14 16.7% 8 36.0% p=.096 22 20.2%
Unknown 4 4.8% 1 4.0% 5 4.6%
Ethnicity
White 34 40.5% 16 64.0% {(1) = 4.29. sig 50 45.9%
Non White 50 59.5% 9 36.0% p=.038 59 54.1%
Am. Indian 3 3.6% 0 0.0% 3 2.8%
Asian 1 1.2% 1 4.0% 2 1.8%
African-American 30 35.7% 5 20.0% 35 32.1%
Latino/Latina 7 8.3% 2 8.0% 9 8.3%
White 34 40.5% 16 64.0% 50 45.9%
Nonresident Alien 2 2.4% 0 0.0% 2 1 .8%
Unknown 7 8.3% 1 4.0% 8 7.3%
Residency Status
Resident 56 60.0% 15 60.0% {(3) = 1.22, nonsig 71 65.1%
Out-of-district 23 27.4% 9 36.0% 32 29.4%
Out-of-state 3 3.6% 1 0.9% 4 3.7%
lntemational 2 2.4% 0 0.0% 2 1 .8%
Table 2a:

The above table summarizes the demographic characteristics of the Spring 1999
Early Warning students who did or did not meet with a counselor. Chi-square correlated
factors tests were run for the demographic variables of gender, marital status, race and
ethnicity, and residency status. Using these characteristics the tests indicate whether
students who did meet with a counselor differed systematically by these characteristics
from those who did not meet with a counselor.

Results indicate that a significantly larger proportion of the students who did meet
with a counselor were single and non-White (59.9%) compared with students who did not

meet with a counselor (36.0%). The higher participation rate for non-erite students is

34

(1':—

most likely the result of African-American students who were more likely to meet with a
counselor. However, the age, gender, and residency status of the students did not differ

significantly across the two groups, and did not affect the research.

35

Table 2b Early Warning Spring 1999: Student Profile across Groups.

 

 

 

No Record of
Did Meet with . Significance of
Meeting with Total Cohort
Counselor Counselor Difference
Student Profile
Reason for Attending
Ocarp.‘ Program 16 30.8% 5 33.3% 13(4)= 1.61. nonsig 21 31.3%
Upgrade Skills 3 5.8% 1 6.7% 4 6.0%
Gain New Skills 10 19.2% 1 6.7% 1 1 16.4%
Transfer 19 36.5% 6 40.0% 25 37.3%
Personal Interest 4 7.7% 2 13.3% 6 9.0%
Educational Goals
Associate Degree 24 46.2% 7 46.7% {(2) = 2.03. nonsig 31 46.3%
Certificate 15 28.8% 2 13.3% 1 7 25.4%
Courses/Transfer 13 25.0% 6 40.0% 19 28.4%
Educational Background
Some HS 8 15.4% 5 33.3% {(5) = 9.06. nsig 13 19.4%
HS Graduate 32 61.5% 5 33.3% p=.107 37 55.2%
Some COIIOQO 8 15.4% 4 26.7%: 12 17.90/11
Associate Degree 0 0.0% 1 6.7% 1 1.5%
Bachelors Degree 3 5.8% 3 4.5%
Master's Degree 1 1.9% 1 1.5%
Employment Status
Full-Time 25 48.1% 10 66.7% {(3) = 2.00. nonsig 35 52.2%
Part-Time 15 28.8% 2 13.3% 17 25.4%
Seeking Emplm'nt 9 17.3% 2 13.3% 11 16.4%
Other Responsibl. 1 6.7% 3 5.8% 4 6.0%
Full-TimeIPart-Tima Status
Full-Time 13 15.5% 5 20.0% f(1) = .286. nonsig 18 16.5%
Part-Time 71 84.5% 20 80.0% 91 83.5%
Financial Aid Status
Not Receiving 56 66.7% 21 84.0% {(1) = 2.79. sig 77 70.6%
Receiving 28 33.3% 4 16.0% p=.095 32 29.4%
Class Times
Day Only 36 42.9% 13 52.0% {(2) = 1.62. nonsig 49 45.0%
Night Only 24 28.6% 8 32.0% 32 29.4%
Both 24 28.6% 4 16.0% 28 25.7%
'Occupational .
Table 2b:

Profiles across groups of Spring 1999 Early Warning students who did meet with
a counselor did not differ significantly from those who did not. A trend showed that
those who did meet with a counselor were more likely to be high school graduates and to
be receiving financial aid, although neither of these differences were significant by

conventional standards (p < .05).

36

a»

'—‘ ‘-

Table 2c Early Warning Spring 1999: Academic Profile across Groups.

 

 

 

Did Meet with “(3:13:13 significance of Total Cohort
Counselor Counselor Difference
Academic Profile

Withdraw by
State Count‘
Spring 1999 Semester

Withdrew 6 6.7% 7 21.9% {(1) = 5.74. sig 13 10.7%

Remained 84 93.3% 25 78.1% p=.017 109 89.3%
Enrolled
Credits Carried

Mean 6.45 5.92 t(107) = .547. nosig 6.33

SD 4.27 4.27 4.26
Mean Grade Spring 1999

Mean 2.11 2.67 t(91) =1.44. nosig 2.39

SD 0.18 0.34 0.19
Lowest Grade .

Mean 1.8 2.52 t(91) =1.82. nosig 2.16

SD 0.19 0.35 0.20
Highest Grade

Mean 2.42 2.74 t(91) =.791, nosig 2.58

SD 0.19 0.36 0.20
Failed to Complete At Least One Course

No 34 41.5% 13 59.1% {(1) = 2.18. nosig 47 45.2%

Yes 48 58.5% 9 40.9% 57 54.8%
Failed to Complete All Courses

No 58 70.7% 17 77.3% {(1) = .369. nosig 75 72.1%

Yes 24 29.3% 5 22.7% 29 27.9%
Number of Courses Carried

Mean 2.10 1.96 t(107) =.468. nosig 2.06

SD 1.30 1.17 1 .26
Credits Earned

Mean 7.65 6.62 t(106) =.702. nosig 7.14

SD 0.51 0.95 0.54

'State of Michigan educational count day

Table 2c:

The academic profiles of Spring 1999 Early Warning students who did meet with
a counselor were significantly less likely to have withdrawn from LCC by the State of
Michigan educational count day of Spring 1999 compared with those who did not meet
with a counselor. None of the other Academic Profile variables differed significantly

across the two groups.

37

Section 3: Early Warning Fall 1999.

Table 3a Early Warning Fall 1999: Demographic Profile across Groups.

 

 

 

Did Meet with :figrjig Significance of Total Cohort
Counselor Counselor Difference
Demographics
Mean 21.6 22.3 t(496) = 1.02. nosig 22.1
SD 6.8 7.2 7.1
Gender
Male 70 49.3% 171 50.3% {(1) = .040. nosig 241 50.0%
Female 72 50.7% 169 49.7% 241 50.0%
Marital Status
Single 128 85.9% 284 80.0% {(5) = 4.80. nosig 412 81 .7%
Married 13 8.7% 35 9.9% 48 9.5%
Other/Unknown 8 5.3% 36 10.1% 44 8.7%
Ethnicity
White 76‘ 51.0% 219 61.7% {(1 ) = 4.94.519 295 58.5%
Non-White 73 49.0% 136 38.3% p=.026 209 41.5%
Am. Indian 4 2.7% 8 2.3% 12 2.4%
Asian 1 0.7% 5 1.4% 6 1.2%
African- 47 31.5% 71 20.0% 118 23.4%
Ameriean
Latino/Latina 17 11.4% 38 10.7% 55 10.9%
White 76 51.0% 219 61.7% 295 58.5%
Unknown 4 2.7% 14 3.9% 18 3.6%
Residency Status
Resident 86 58.9% 187 55.5% {(3) = .881 . nosig 273 56.5%
Out-of-district 57 39.0% 142 42.1% 199 41.2%
Out-of-state 3 2.1% 7 2.1% 7 2.1%
lntemational 0 0.0% 1 0.3% 10 2.1%
Table 3a:

The above .table summarizes the demographic characteristics of Fall 1999 Early
Warning students who did meet or who did not meet with a counselor. As Spring 1999
tests results indicate that a significantly larger proportion of at-risk first-time-to-college
students who did meet with a counselor were non-White compared with at-risk first-time-
to-college students who did not meet with a counselor. Remaining demographic

variables did not differ significantly across the two groups.

38

 

Table 3b Early Warning Fall 1999: Student Profile across Groups.

 

No Record of

 

 

Did Meet with Significance of
Meeting with Total Cohort
Counselor Counselor Difference
Student Profile
Reason for Attending
Occup.‘ Program 27 20.0% 69 22.7% {(4) = 17.9. sig 96 21.9%
Upgrade Skills 6 4.4% 28 9.2% p=.001 34 7.7%
Gain New Skills 18 13.3% 27 8.9% 45 10.3%
Transfer 82 60.7% 147 48.4% 229 52.2%
Personal Interest 2 1 .5% 33 10.9% 35 8.0%
Educational Goals
Associate Degree 52 40.0% 123 42.1% {(4) = 9.23. sig 175 41.5%
Certificate 3 2.3% 27 9.2% p=.056 30 7.1%
Coursesffransfer 72 55.4% 130 44.5% 202 47.9%
Personal Interest 1 0.8% 4 1.4% 5 1.2%
Educational Background
Some HS 6 4.4% 9 3.0% {(3) = 1.73. nosig 15 3.5%
HS Graduate 108 80.0% 251 83.9% 359 82.7%
Some College 20 14.8% 35 11.7% 55 12.7%
Associate Degree 1 0.7% 4 1.3% 5 1.2%
Employment Status
Full-Time 69 51 .1 % 148 48.7% {(2) =.844, nosig 217 49.4%
Part-Time 48 35.6% 105 34.5% 153 34.9%
Seeking Emplm'nt 18 13.3% 51 16.8% 69 15.7%
Full-time - Part-time Status
Full-Time 65 44.5% 1 10 32.6% {(1 ) =6.22. sig 1 75 36.2%
Part-Time 81 55. 5% 227 67.4% p=.013 308 63.8%
First Time in Any College
No 30 20.5% 58 17.2% {(1) = .761. nosig 88 18.2%
Yes 116 79.5% 279 82.8% 395 81.8%
First Time at LCC
No 4 2.7% 9 2.7% {(1) <0.01. nosig 13 2.7%
Yes 142 97.3% 328 97.3% 470 97.3%
'Occupational

Table 3b:

Results from the Spring 1999 analysis and results from the Fall 1999 analysis

indicate a significant difference between Early Warning students who did meet or who

did not meet with a counselor on three significant student profile variables: reasons for

attending, educational goals, and full-time versus part-time status. Students who did

meet with a counselor were more likely to report transfer plans to a 4-year institution or

to the acquisition of new job skills as their primary reasons for attending LCC. Of the

firll and part-time students who did meet with a counselor observed differences are

39

 

consistent with what may be expected. It is difficult for someone employed part-time or
full-time to get in to see a counselor because no late evening or weekend counseling was
available. A preponderance of Early Warning students of both groups entering LCC as
their first college enrollment partially validated the “at-risk” designation derived from the
LCC application.

(Note: Due to the conversion from the SOLAR system to Banner (software
system used to maintain student academic records, registration processes, and other
student info) that took place between the Spring and Fall 1999 terms, some of the student

and academic profile variables were not available for analysis across both terms.)

40

Table 3c Early Warning Fall 1999: Academic Profile across Groups.

h. n--.— A'

 

 

No Record of

 

Did Meet with Significance of Total Cohort
Meeting with .
Counselor Counselor Difference
Academic Profile

Withdraw by State Count'
Fall 1999 Semester

Early Withdraw 3 2.0% 18 5.1% {(1) = 2.46. nsig 21 4.2%

Remained 146 98.0% 337 94.9% p=.1 17 483 95.8%
Enrolled
Credits Carried

Mean 9.50 8.04 t(442) = 3.56. sig 8.50

SD 3.33 4.29 p<.001 4.06
Mean Grade Fall 1999

Mean 2.18 1.96 t(446) = 1.62. nsig 2.03

SD 1.18 1.40 p=.087 1.33
Lowest Grade

Mean 1.63 1.65 t(411) = .117. nonsig 1.65

SD 1.34 1.44 1.41
Highest Grade

Mean 2.91 2.65 t(411) = 1.83. sig 2.74

SD 1.20 1.46 p=.051 1.39
Failed to Complete At Least One Course

No 99 70.2% 232 76.6% {(1) = 2.04. nosig 331 74.5%

Yes 42 29.8% 71 23.4% 113 25.5%
Failed to Complete All Courses

No 134 97.1% 280 93.0% {(1) =2.93. sig p=.070 414 94.3%

Yes 4 2.9% 21 7.0% 25 5.7%

 

'State of Michigan educational count day

Table 3c:

As was the case in Spring 1999, Fall 1999 Early Warning students who did meet

with a counselor were less likely to have withdrawn from LCC by State of Michigan

count day than those who did not meet with a counselor. This difference approached

significance only for the Fall 1999 cohort. Figures show that though Fall 1999 Early

Warning students who did meet with a counselor also carried more credits, a lower

percentage of them failed to complete all courses compared with students who did not

meet with a counselor. Further, the number of Fall 1999 students who did meet with a

counselor showed significantly higher average grades across all courses and more A and

B grades compared with students who did not meet with a counselor.

41

Section 4: Early Warning Spring 2000.

Table 4a Early Warning Spring 2000: Demographic Profile across Groups.

 

 

 

No Record of
Did Meet with Significance of
Meeting with Total Cohort
Counselor Counselor Difference
Demographics

Arie

Mean 25.7 24.6 t(266)=.308 nonsig 25.0

SD 8.2 7.6 7.8
Gender

Male 43 53.8% 118 61.8% {(2) = 1.508. nonsig 161 59.4%

Female 37 46.3% 73 38.2% 1 10 40.6%
Marital Status

Single 18 22.5% 38 19.9% {(2) = 4.472. nonsig 56 20.7%

Married 1 1.3% 15 7.9% 16 5.9%

Unknown 61 76.3% 138 72.3% 199 73.4%
Ethnicity

White 36 45.6% 120 63.5% {(1) = 7.357. sig 156 58.2%

Non White 43 54.4% 69 36.5% p=.007 112 41.8%

Am. Indian 5 6.3% 4 2.1% 9 3.3%

Asian 2 2.5% 10 5.2% 12 4.4%

African-American 27 33.8% 37 19.4% 64 23.6%

Latino/Latina 8 10.0% 17 8.9% 25 9.2%

White 36 45.0% 120 62.8% 156 57.6%

Unknown 2 2.5% 3 1.6% 5 1.8%
Residency Status

Resident 50 62.5% 108 56.5% {(3) = 4.777. nonsig 158 58.3%
. Out-of-district 25 31 .3% 79 41.4% 104 38.4%

Out-of-state 5 6.3% 4 2.1% 9 3.3%

Table 4a:

Table 4a summarizes the characteristics of Spring 2000 Early Warning students.
Chi-square tests were run for the demographic variables of gender, marital status,
pr0portion of white and non-white students, and residency status.

Test results continue to show that a significantly larger proportion of students who
did meet one or more times with a counselor were non-White compared with students
who did not meet with a counselor. However, age, gender, and residency status of

students did not differ significantly across the two groups.

42

 

Table 4b Early Warning Spring 2000: Student Profile across Groups.

 

No Record of

 

 

Did Meet with Significance of
Meeting with Total Cohort
Counselor Counselor Difference
Student Profile
Reason for Attending
Occup. " Program 18 30.8% 39 29.8% {(4) = 6.614. 57 29.7%
Upgrade Skills 5 5.8% 21 16.0% nonsig 26 13.5%
Gain New Skills 9 19.2% 12 9.2% 21 10.9%
Transfer 25 36.5% 40 30.5% 65 33.9%
Personal Interest 4 7.7% 19 14.5% 23 12.0%
Educational Goals
Associate Degree 41 46.2% 99 52.9% {(3) = 2.179. 140 52.8%
Certificate 4 28.8% 19 10.2% nonsig 23 8.7%
Courses/Transfer 30 25.0% 61 32.6% 91 34.3%
Other/Unknown 3 25.0% 8 4.3% 1 1 4.2%
Educational Background
Some HS 9 15.4% 29 15.3% {(3) = 2.834. 38 14.1%
HS Graduate 46 61.5% 119 62.6% nonsig 165 61.1%
Some College 23 15.4% 38 20.0% 61 22.6%
2/4 Year Degree 2 0.0% 4 2.1% 6 2.2%
Employment Status
Full-Time 35 48.1% 92 59.4% {(3) = 3.330. 127 56.2%
Part-Time 1 7 28.8% 37 23.9% nonsig 54 23.9%
Seeking Emplm'nt 7 17.3% 10 6.5% 17 7.5%
Not Employed 12 6.7% 16 10.3% 28 12.4%
Full-TImeIPart-Time Status
Full-Time 59 15.5% 148 81.3% { (1 ) = .389. nonsig 207 79.9%
Part-Time 18 84.5% 34 18.7% 52 20.1%
Financial Aid Status
Not Receiving 46 66.7% 143 74.9% {(1) = 8.061. sig 189 69.7%
Receiving 34 33.3% 48 25.1% p=.005 82 30.3%
Class Times
Morning 12 15.6% 34 18.7% {(4) = 1.677. 46 17.8%
Afternoon 7 9.1% 19 10.4% nonsig 26 10.0%
Evening 23 29.9% 53 29.1% 76 29.3%
Weekend/Arranged 3 3.9% 12 6.6% 15 5.8%
Combination 32 41.6% 64 35.2% 96 37.1%
‘Occupational
Table 4b:

On most student profile variables, Early Warning students who did meet one or

more times with a counselor did not differ significantly from those students who did not.

Those who did meet with a counselor were slightly more likely to be high school

graduates and to not be receiving financial aid, although neither of these differences was

significant by conventional standards (p < .05).

43

 

Table 4c Early Warning Spring 2000: Academic Profile across Groups.

 

No Record of

 

Did Meet with Significance of
Meeting with Total Cohort
Counselor Counselor Difference
Academic Profile
Withdraw by State Count‘
Fall 1999 Semester
Early Withdraw 3 (3.8%) 9 (4.7%) {(1) = .725, nonsig 12 (4.4%)
Remained Enrolled 77 (96.3%) 182 (95.3%) 256 (95.6%)
Credits Carried 7.26 6.91 t(257) = .408. nonsig 7.02
Mean 3.68 4.03 3.93
SD
Mean Grade Spring 2000
Mean 2.44 2.34 t(366) = .381. nonsig 2.37
SD 1.39 1.59 1.45
Lowest Grade
Mean 2.16 2.14 t(198) = .004. nonsig 2.15
SD 1.63 1.41 1.47
Highest Grade
Mean 2.68 2.62 t(198) = .088. nonsig 2.64
SD 1.6 1.31 1.4
Failed to Complete
At Least One Course
No 34 (42.5%) {(1) = 1.184. nonsig 129 (47.6%)
Yes 46 (57.5%) 142 (52.4%)
Number of Sections Carried
Mean 2.04 t(269) = .785. nonsig 1.94
SD 1.12 1.12

 

'State of Michigan educational count day

Table 4c:

The academic profiles of Spring 2000 Early Warning students who did meet one

or more times with a counselor did not differ significantly from those students who did

not meet with a counselor. Although a fairly large proportion (57.5%) of students in this

cohort failed to complete one or all of the courses in which they were enrolled during the

Spring 2000 semester (i.e. withdrew or received average grades of zero in courses), these

numbers did not differ significantly across the two groups.

 

Section 5: Early Warning Subse_quent Enrollment Across Groups.

Table 5a Early Warning Spring 1999: Subsequent Enrollment across Groups.

 

 

 

No Record of
Did Meet with Significance of Total Cohort
Counselor M.” ting with Difference
Subsequent Enrollment
Enrolled Summer 1999
Yes 15 16.7% 1 3.1% {(1) = 3.80. sig p=.051 16 13.1%
No 75 83.3% 31 96.9% 106 86. 9%
Enrolled Fall 1999
Yes 34 37.8% 7 21.9% {(1)= 2.68. sig p=.102 41 33.6%
No 56 62.2% 25 78.1% 81 66.4%

 

Early Warning Spring 1999: Subsguent Enrollment Pie Graphs.

Continued Enrollment from Spring 1999 to Summer 1999

  
     

   

Did Meet with Counselor Did “°‘ "1°“ “'1‘" c°“"“'°' LCC
17% 3% 23%
83% i 97% 77%
DContinued IDid not continue DContinued IDid not continue DContinued IDid not continue

Continued Enrollment from S rin 1999 to Fall 1999

 

Did Meet with Counselor Did not meet with Counselor LCC
38% . 22% 53%

DContinued IDid not continue DContinued I Did not continue DContinued I Did not continue El

Table 5a:

Spring 1999 Early Warning students who did meet one or more times with a
counselor were significantly more likely to enroll both in the Summer 1999 term and in
the Fall 1999 term compared with students who did not meet with a counselor. These
findings may be interpreted in light of an auxiliary analysis showing that 22.7% of LCC
students in general continued their enrollment from Spring 1999 to Summer 1999 and
53.1% continued enrollment to Fall 1999. The retention from Spring to Fall of both
Early Warning students who did meet with a counselor and those who did not was
significantly lower than the base rate among all LCC students, {(1) = 8.48, 12,52
respectively, ps < .01 . However, the retention of those who did meet with a counselor

was significantly closer to the rate among all LCC students.

46

 

Table 5b Early Warning F all 1999: Subsequent Enrollment across Groups.

 

No Record of

 

Did Meet with "ecu" with Significance of Total Cohort
Counselor .. g . Difference
Subsequent Enrollment
Enrolled Spring 2000
Yes 109 73.2% 167 47.0% {(4) = 17_9' sig p=.001 228 45.2%
No 40 26.8% 188 53.0% 276 54 .8%

 

 

Early Warning Fall 1999: Subspguent Enrollment Pie Graphs.

Continued Enrollment from Fall 1999 to Spring 2000

Did Meet with Counselor Did not meet with Counselor LCC
73% 47% 58%
27%. 53%. 42%
DContinued 'Did "01 continue DContinued I Did not continue 0 Continued I Did not continue
Table 5b:

Replicating the differences in student retention found in the Spring 1999 term,
Fall 1999 Early Warning students who did meet one or more times with a counselor were
significantly more likely to enroll in the Spring 2000 term compared with students who
did not meet with a counselor. An auxiliary analysis (Table 5b) showed that 57.7% of all
LCC students continued from Fall 1999 to Spring 2000. A Chi—square test confirmed that
the retention of Early Warning students who did meet with a counselor significantly
exceeded this base rate, {(1) = 14.62, p < .001 , whereas the retention of Early Warning
students who did not meet with a counselor was significantly lower than the base rate,

{(1)=16.49,p<.001.

47

Table 5c Early Warning Spring 2000: Subsequent Enrollment across Groups.

 

 

Did Meet with $330313: Significance of Total Cohort
Counselor .. g . Difference
Subsequent Enrollment
Enrolled Summer 2000
Yes 19 23.8% 21 11.0% {(1) = 7.291. sig p=.007 40 14.8%
No 61 76.3% 170 89.0% 231 85.2%
Enrolled Fall 2000
Yes 35.0% 48 25.1% {(1) = 2.721 . nonsig 76 28.0%
No 52 65.0% 143 74.9% 195 72.0%

 

Earl Wamin S rin 2000: Subse uent Enrollment Pie Gra hs.

 

Continued Enrollment from S rin 2000 to Summer 2000

 

Did Meet with Counselor Did not meet with Counselor LCC

24% 1 1% 22%

   

   
  

   

 

76% 89% 78%

DContinued I Did not continue 0 Continued . Did "01 continue DContinued I Did not continue

Continued Enrollment from S rin 2000 to Fall 2000

 

Did Meet with Counselor Did not meet with LCC
Counselor

35% 25% 47%

   

   

 

65% 75% 53%
E1 Continued I Did not continue DContinued I Did not continue Doonfinued I Did not continue

48

 

Table 5c:

Spring 2000 Early Warning students who did meet one or more times with a
counselor were significantly more likely to enroll in the Summer 2000 term compared
with students who did not meet with a counselor. These findings may be interpreted in
light of an auxiliary analysis (Table 5c) showing that 22% of LCC students in general
continued their enrollment from Spring 2000 to Summer 2000, and 47% continued their

enrollment to Fall 2000.

49

CHAPTER 5
CONCLUSIONS, IMPLICATIONS OF RESEARCH, FUTURE RESEARCH
SUGGESTED
Introduction

Traditionally, college and university leaders have been concerned with students
dropping out of college, many in the first several weeks of their first year. The indication
by NCES 1999, ACT (1998) that colleges and universities experience exceptionally high
attrition rates of twenty-five to sixty percent of their freshmen class, was supported
through this research. One example shows four year universities reporting 49.8% of their
students drop out, while two-year colleges experience drop out rates of 67.6% ACT
(1998). Attributed to the open enrollment policies of cormnunity colleges, two year
public colleges have been the most likely to experience the highest, most sustained
attrition rates.

Why do some college students continue to enroll while others drop out? What
factors exist within the college environment that results in non-persistence for some
students and persistence to completion for others? Tinto’s (1974, 1989) theoretical
model of student retention has been repeatedly validated as his model has established
some understanding of why some college students remain while others drop out. Further,
Tinto’s (1999) theory of college student attrition states that success or lack of success of
college students to integrate themselves into the social and academic structure of college
correlates to the student continuing to persist. Astin (1984), as well as Tinto, sought to
analyze student retention in terms of the relationship between persistence and the

student’s social and academic integration into the college community. In his Theory of

50

Student Involvement, Astin (1984) states that the more personal commitment the student
invests in the college experience, the greater the possibility of the student remaining
enrolled. Both theorists (Astin and Tinto) espoused that there exists a correlation
between a student’s level of interaction and involvement (connectedness) in the campus
environment and in retention. Student retention models of Tinto, Feldman and Seidman
were utilized to guide this study on college student retention.

This study investigated whether intrusive counseling impacted the ability of at-
risk first-time-to-college students to continue their coursework and achieve academic
success. The findings provide community colleges, universities, and professional
organizations with research that may help them make informed decisions regarding ways
to set priorities and identify the most effective services, such as tutoring, extra-curricular
involvement, and the implementation of retention programs and strategies.

Finding, Implication for Practice, and Conclusions

The findings of this research study are consistent with the research findings of
other investigators, including Tinto (1975, 1993) and Astin (1989, 1993). Specifically,
findings support the ideas that integration and involvement in the college environment
contribute to a significantly higher rate of subsequent semester enrollment for at-risk
first-time-to-college students. These findings are consistent with Siedman (1991), who
supports the premise that students who interact with counselors have a significantly
higher rate of retention than the group who did not interact with a counselor.

The following significant findings were revealed:

1. A larger number of students who did meet one or more times with a counselor

were single and non-White compared with the number of students who did not meet with

51

a counselor. A greater number of Afiican-American students did meet one or more times
with the counselor. The study revealed, however, that the age, gender, and residency of
the students did not differ across the two groups.

Implications for Practice: To increase the counselor’s knowledge of factors that
contribute to the success of black students, counselors may need to become more aware
of literature promoting understanding of African-American student culture and its impact
upon retention of black students. Counselors may acquire enhanced insight for accessing
and recommending support services for this population. This learning may be facilitated
through professional development. Additionally, administrators may want to identify
reasons why White students are not taking advantage of the counseling resources that are
available and that have been offered to them. Identification could be achieved by the
college through development of a satisfaction survey used within the counseling services
department to measure factors, such as (1) reasons for services to be used, (2) quality of
information received, (3) customer service provided, (4) whether the problem was solved,
(5) wait time for service, and (6) usage if service hours are expanded.

Conclusion for finding #1 : In this study, these findings (1) reflected the desires of
Afiican-American students to seek assistance in achieving their goals, (2) showed White
at-risk students do not take advantage of counseling services, and (3) demonstrated
outreach strategies of the counseling staff were effective in encouraging non-traditional
and at-risk students to arrange for counseling.

2. This study identified the students who did meet with a counselor one or more
times were generally more academically oriented (transfer students who were seeking

transfer to four year colleges and universities) compared with those students who did not

52

meet with a counselor. The study identified that students who did not meet with a
counselor were occupationally oriented or interested in classes for personal development.
Across all semesters, students who did meet one or more times with a counselor carried
more credits and were more likely to be enrolled full-time compared with students who
did not meet with a counselor and who tended to attend part-time and to carry fewer
credits.

Implications for Practice: These findings suggest that the college should target
more retention efforts on students who carry fewer credits and who attend part-time.
Data shows that students who did meet with a counselor were more likely to carry more
credits, to be enrolled full-time, and to be employed full-time. These factors would
support expanding the hours of counseling services to include non-traditional
appointment times, such as weekday evening hours, Saturdays, and Sundays. This
scheduling could allow access to counseling services for this population of students.
Additionally an expanded strategy should be developed to encourage both part-time, full-
time at-risk students to more frequently use all counseling services and thereby increase
this population’s persistence rates.

Conclusion for finding #2: In this study, a disproportionate use of counselor
services between transfer students and non transfer students and between firll-time and
part-time students was revealed. The conclusion may be drawn that at-risk students who
carry fewer credits and who work part-time are not taking advantage of counseling
services and not persisting. Expanded programs and strategies should be developed to

encourage these students to take advantage of services.

53

3. This study found that the academic performance of students who did meet one
or more times with a counselor was not significantly different from that of students who
did not. The absence of a significant difference does not necessarily indicate that the
program held no beneficial effect, especially if students who did meet with a counselor
did so as a result of experiencing difficulties with their classes.

Implications for Practice: These findings suggest that continued intervention by
counselors may serve to assist at-risk students in establishing a firm foundation in
seeking aid and in encouraging a higher rate of retention from them. Further, it is hoped
these findings will encourage instructors to more often refer their at-risk students to
counseling support services, since a higher number of those who saw a counselor
frequently were more persistent.

Conclusion for finding #3: The conclusion may be drawn that student counselor
interaction may not enhance academic performance in any group; however, at-risk
students who did meet with a counselor achieved a higher rate of persistence than those
who did not.

4. Students who did meet one or more times with a counselor across all semesters
were significantly more likely to enroll in subsequent semesters than those who did not.
Note the greatest differences between the two samples: 16% of students who did meet a
counselor one or more times in Spring of 1999 enrolled in Summer of 1999 compared
with 3.1% of students who did not meet a counselor; furthermore 37.8% of at-risk
students who did meet with a counselor in Spring of 1999 enrolled in Fall of 1999

compared to 21 .9% of those who did not.

54

The same pattern was observed for at-risk first-time-to-college students entering
Fall 1999 and Spring 2000. Fully 73% of the students who saw a counselor in Fall 1999
enrolled in Spring 2000 compared to 47% of students who did not receive counseling.
The pattern persisted for at-risk first-time-to-college students enrolled from Spring 2000
to Summer 2000. Tables indicate 24% of the students who saw a counselor one or more
times in Spring 2000 enrolled in Summer 2000 compared to 11% who did not receive
counseling. Moreover, 35% of at-risk first-time-to—college students who did meet with a
counselor one or more times in Spring 2000 continued in Fall 2000 compared to 25%
who did not meet with a counselor.

Implications for Practice: These findings suggest that the student-counselor
relationship should be expanded so that all students would be exposed to a strategy that
encourages student success and persistence. This could be accomplished by establishing
a program of mandatory counseling for all at-risk first-time-to-college students entering
Lansing Community College. On a broader scale, a mandatory counseling program could
be established for all first-time students entering Lansing Community College. The
college administration should continue to ensure that appropriate funding be directed to
this program to maintain it at its current level or to increase funding to expand services to
develop and continue the proposed mandatory counseling plan.

Additionally, these findings have possible implications for creating a K-12 “Pre-
Collegiate Outreach Program” that would build a positive support base between at-risk
college bound students and counselors at the receiving college.

First conclusion for finding #4: In this study, the research findings emphasize the

importance of counselor intervention on at-risk first-time-to-college students, and the

55

data indicates a strong relationship between intrusive counseling intervention and
subsequent student re—enrollment.

Implications for Practice: Community colleges and universities have historically
used recruitment and marketing strategies to increase declining enrollments. An
aggressive investment in counselor intervention strategies could prove to be a more
effective and less expensive process resulting in student retention in addition to
recruitment and marketing. Keeping the student enrolled in classes more cost effective
than seeking new students in new markets to replace them.

Recommendation for Future Research

In a time of shrinking budgets and increased accountability, student retention is a
critical issue for community colleges and universities. College leadership may be well
served to re-examine institutional commitment and resources both human and monetary
and better direct funds to activities related to the variables of retention: counseling,
orientation, tutorial services, and student life.

This study examined the relationship between at-risk first-time-to-college
students and the relationship between intrusive counseling intervention and retention.
Several recommendations for future research have emerged as a result of the findings
from this study. It is hoped that these recommendations will be helpful to others
conducting research on retention of students in community colleges and universities.
Moreover, it is hoped professional associations will be interested in these findings and
implications.

This study revealed a larger number of non-White students took advantage of the

counseling program. The study did not, however, address the issue of why some students

56

were more likely to take advantage of counseling services or why other students were
not. It is recommended that a follow-up qualitative study he considered targeting at-risk
first-time-to-college students who meet one or more times with counselors and entering
at-risk first-time-to-college students who do not take advantage of counseling services. A
study such as this will be key to understanding the perception of students regarding the
value of counseling services, and why students did or did not participate in campus
counseling programs. To reap the full benefit of innovative practices, a study could be
conducted to determine why there existed a disproportionate number of non-White
students using counseling intervention. This study examined the effectiveness of
counseling intervention efforts as a positive contribution to retaining ethnic minorities.
The ultimate goal of this study is to develop models that two year colleges can modify
and incorporate according to the specific dynamics of their student population to increase
the retention rates of minority students.

Since a positive relationship was found between counseling intervention and
student retention, researchers may want to replicate this study using other variables
(tutoring, orientation, and student life) in an effort to enhance understanding regarding
student retention and whether this understanding can impact further program planning.

Community colleges are engaged in a variety of efforts to facilitate the retention
and achievement of its diverse student population by both facilitating the connection and
integration of ethnic minority students into the educational community. A strong
recommendation is made that studies be conducted to examine the effectiveness of
strategies such as counseling, tutoring, and other variables on minority populations.

Additionally, community colleges should be encouraged to investigate current innovative

57

practices so that the full benefit of successful practices to facilitate student success can be
realized.

The study revealed that the implementation of counselor intervention had a
positive impact on retention. Future studies may assess the value of more specific types
of intervention and how they may contribute to the economic health and/or growth of the
institution or to the lack of economic benefit.

Based upon the findings of this study which showed a positive impact of
counselor intervention on at-risk first-time-to-college students; a pilot project is proposed
to connect high school at-risk college-bound seniors and college counselors during the
student’s senior year (Pre-Collegiate Outreach Program) to determine if early intrusive
counseling intervention would help the students be successful. This project would
include an on-going relationship throughout the student’s freshman year and would
assess the impact of the counselor intervention on the persistence of these students
compared to a similar cohort who did not receive this intervention.

Final Comments

Using the findings from this study, as well as current retention literature and
retention studies to further examine the relationship between the students’ involvement
and interaction with their college environment and the likelihood of their retention,
community colleges and universities may want to direct their own institutional research
on student retention.

This researcher, as a result of this study, has gained a greater understanding of the
issues of at-risk first-time—to-college students and retention. Student retention is complex

and involves a plethora of variables (interaction with faculty, students, and college

58

administrators, student participation in extra curricular activities, ethnicity, etc.) requiring
consideration. While there are no simple answers to discovering the complexities of
retention, it is this investigator’s conclusion that both institutional and environmental
variables are factors that lead to retention. How the student interacts or how the
institution establishes programs for students to interact with these variables impacts
retention.

This research study has demonstrated that intrusive counseling does positively
impact at-risk first-time-to—college student retention. Further, the research indicates that
while this variable can have a positive impact on student retention extraordinary efforts
must be made by the institution to connect students to these important services. A
counselor must bring to this process the motivation and desire to facilitate the task of
student retention. One counselor said:

They’ve been identified as possibly at-risk, and our job is to contact these

students. My preference is to make personal contact by phone, inviting them to

come in for firrther intervention. 1 offer to them that I can help them with study
tips, how to study better, or to identify other things that might get in the way
of their success. Sometime, there is a lack of information on their part, and just
letting these students know about the resources that are available to them makes
all the difference in the world. If there is anything I can do to help these students
feel they have a personal connection to LCC - that they are just not a number in a

huge organization - that’s what I try to do.

A student who was a part of the study said the following of his counselor

interaction and of his first year’s experience:

59

I had nothing to do in everyday life, just hanging out with fiiends. I didn’t ever

think I would find myself in college. I know the life I was living is no life. I

came here without nothing, really. And now I’ve got a lot. They helped me so 1

can get what I need to go to school. . .books, bus passes. By them helping me, it

makes me try even that much harder.

Finally, when reviewing the data on these variables of counselor intervention, I
realize the finding of this study may not be applicable to all institutions of higher learning
and to all counselor intervention programs. However, the results of this research make a
contribution to the literature in the field by exploring the one variable of counselor
intervention that has been little explored previously but that does have significant impact
on retention of at-risk first-time—to-college students.

While the faculty, staff, and administrators at the college exhibit an intense on-
going interest in retention, it is desirable to see this research serve as a catalyst in re-
igniting meaningful discussions covering retention issues at this institution, to fuel the
interest in retention at other institutions, and to emphasize and support the values added

by counseling professionals to the goal of student retention and persistence.

60

APPENDIX

61

10.

11.

APPENDIX A
LANSING COMMUNITY COLLEGE

Demographic Survey Questions

. Course (chose one only)

0 Mathematics 107 0 Psychology 200 C1 Electrical Technology 100
Have you taken this course before?
0 Yes D No
Name
Last First
Student Number
SSN
Age
Sex
C1 Male CI Female

Is this your first semester at College? (select one)

D Yes. first semester at LCC D No, I’ve attended LCC before
D Yes. first semester at any college 0 No. I’ve attended another college before
I applied to Lansing Community College:
D Prior to June 1, 1997 0 Between July 16 and the beginning of
classes
0 Between June 1 and July 15, 1997 D After classes began. Fall 1997
What factors influenced our enrolling LANSING COMMUNITY COLLEGE (as opposed to

another college)? (select all that apply)

D LCC is close to home 0 Athletics

0 LCC outreach efforts CI Fine Arts events (music concerts. art and
theater)

CI Employer recommendation 0 Lower relative cost (compared to a four year
university)

0 Specific careers certificate/program E] Special Support Services (i.e. disability
services. tutorial services)

CI Visit to LCC Cl Open enrollment

D The reputation of LCC programs 0 Scholarships

CI The reputation of LCC faculty

Before you registered at LANSING COMMUNITY COLLEGE, did you have friends
registered at LANSING COMMUNITY COLLEGE?
D Yes D No

While attending high school, to what extent were you involved in extracurricular

activities?
0 Alot C1 Some Cl Very little

62

12.

13.

14.

15.

16.

17.

18.

19.

20.

21.

Are you planning on getting involved in any of the following activities while at LCC?

0 Student Government 0 Athletics (intramural)

0 Student clubs/organizations El Fine Arts Activities (theater, music or
1:! Athletics (intercollegiate) art)

What was your overall average in your last years of high school?

CIA El D

D B D E or F

D C D Did not complete H.S.

In the past, I have completed assignments (school homework or work related) on time:
D Always D Sometimes

0 Usually Cl Never

The last time I attended school (high school, college, university) full-time was:
D1996/1997 D1993/1994

01995/1996 0 1992/1993

0 1994/1995 0 Before 1992

The last level of education in which I was registered full-time was:

D High School CI 4 Year College or University

0 Community College 0 Vocational Training Program

What was your primary activity during the 12 months prior to entering LCC? (select one)
0 High school Cl Employed full-time

Cl Community College, full-time Cl Employed parHime

0 Community College. part-time CI Working full-time as a homemaker

Cl 4 year College/University, full-time 0 Vocational Training Program

0 4 year College/University, part-time El Seeking work while unemployed

CI Adult Education Program (i.e. reading. 0 Other

writing, ESL, or math)

What is your highest educational completion?

0 Earned a US High School Diploma CI GED or received a High School
equivalency certificate

CI Special student, currently enrolled in CI Earned a Foreign Secondary diploma or

grade 12 or below certificate

0 Not a High School graduate D Earned an Associate’s degree

What is the highest level Math class you have completed?

Cl High School Basic Math (arithmetic) CI High School Intermediate Algebra

C] High School Algebra 1 (elementary) El High School Pre-calculus or higher level
math course

0 High School Geometry 0 College level math (algebra or higher)

What is the highest level English class that you have completed?

Cl High School honors Cl College English/Composition

Cl High School College Prep CI English as a Second Language. College

121 High School Basic English Cl English as a Second Language. High

13 College, Basic English School

Have you ever taken the SAT or the ACT?

0 Yes D No

63

23.

24.

25.

26.

27.

28.

29.

DYes DNo

. Have you ever attended the START (orientation) Program?

My plans for employment, while attending LCC are as follows:

D Do not intent to be employed
El Hope to find employment on campus
Cl Hope to find employment off campus

D I am already employed
0 I am uncertain

If you are employed, how many hours a week do you plan to work while a student?

Cl Less than 10 hours/week
0 Between 10 and 20 hours/week
CI Between 20 and 30 hours/week

D Between 30 and 40 hours/week
CI More than 40 hours/week

My financial situation regarding college is as follows: (select one)

D Have enough money
Cl Do not have enough money
0 Depends on employment

El Depends on College financial aid
El Depends on employer sponsorship
Cl Not sure

Which factors do you feel could affect the completion of your educational goals at

LCC? (select all that apply)

DAdjustment to the Lansing community

0 Not able to cope with school and work at
the same time

D Not having enough money

0 Lack of support from family and friends
0 Coping with stress

El Health factors
0 Child care

0 Support for special needs (i.e.
disabilities)

D Other personal reasons

CI Non of the above

Prior to classes beginning, I had met at least one academic instructor at LCC.

D Yes D No

At this point in time, I have concerns with the following: (select all that apply)

0 Reading skills

0 Writing skills

0 Oral communication skills
CI Math skills

0 Math anxiety

D Problem solving skills

CI Science reasoning skills

CI Application of information from on area to
another

0 Computer skills

CI Study skills

C] Time management

0 Ability to learn

El Skills needed for job retraining

0 None of the above

At this point in time, my feelings about attending college include the following:

(select all that apply)
D Not sure what I’m getting into
121 Anxious about my college performance

D Not what I really wanted
Cl 1 would prefer to work full-time
CI Eager to get started

CI Confident of success

CI Determined to complete my college
education

0 Looking forward to an exciting
profession/career

Cl None of the above

30. Which one of the following best describes your future plans after completing course

31.

32.

work at LCC?
D Continue present employment
CI Continue with job retraining

CI Transfer to a four year college/university

CI Attend another community college

D Obtain full-time employment
0 Obtain part-time employment
0 Start up a business

CI Other

Do you feel you will require help in: (select all that apply)

0 Reading skills

CI Writing skills

0 Math skills

0 Math anxiety

0 Study skills

0 Computer skills

0 Time management
E1 Personal counseling

0 Career counseling

0 Academic transfer counseling
:1 Specific course tutoring

D Securing financial aid

D Reasoning skills

CI Disability support services

0 None of the above

Are you willing to accept help in: (select all that apply)

0 Reading skills

C1 Writing skills

0 Math skills

0 Math anxiety

Cl Study skills

C] Computer skills

[:1 Time management
0 Personal counseling

65

13 Career counseling

D Academic transfer counseling
0 Specific course tutoring

Cl Securing financial aid

C1 Reasoning skills

0 Disability support services

0 None of the above

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