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LI / Four-Year to Four-Year Transfers
207
The Review of Higher Education
Winter 2010, Volume 33, No. 2, pp. 207–238
Copyright © 2009 Association for the Study of Higher Education
All Rights Reserved (ISSN 0162-5748)
They Need Help: Transfer
Students from Four-Year
to Four-Year Institutions
Dai Li
The image of a pipeline that channels students directly from high school
to college and to bachelor’s degree attainment fails to capture the attendance
pattern of many college students nowadays. The past two decades have witnessed a slow but steadily growing trend in multi-institutional attendance
patterns. From the 1970s to the 1990s, the proportion of undergraduates
attending more than one institution increased from 40% to 54% and from
49% to 58% among bachelor’s degree recipients (Adelman, 1999). A more
recent research report from the National Center for Education Statistics
(NCES) showed that, in 1999–2000, nearly half (47.3%) of first-time bachelor’s degree recipients who began in a four-year institution enrolled in
more than one institution; 28.3% enrolled in two, 13% enrolled in three,
and 6.1% enrolled in four or more institutions (Peter & Cataldi, 2005).
Students typically define their postsecondary educational pathways in an
irregular manner—starting, stopping, and swirling—along many different
routes. As Longanecker and Blanco (2003) have noted:
They may not be willing to have their higher education experience limited
by the space and time boundaries set by traditional colleges and universities;
they may care little about finding those experiences in a single institution
over a four-year period. (p. 52)
DAI LI is a Research Analyst at California State University—Channel Islands. Address queries
to her at California State University—Channel Islands, One University Drive, Camarillo, CA
93012; telephone: (805) 437–3152; fax: (805) 437–8951; email: [email protected].
208
THE REVIEW OF HIGHER EDUCATION WINTER 2010
However, various multi-institutional attendance patterns do not receive
equal attention among scholars, policymakers, and practitioners. Students
who start from four-year institutions but do not stay until graduation are
often neglected. These students may stay outside postsecondary education
for a period, then return to their original institutions, attend two-year colleges or other four-year institutions, or completely drop out.
These students receive less attention for three reasons. First, theories
and models of persistence and degree completion still center on students’
academic and social experiences in the institution where they originally matriculate and remain continuously until graduation (Tinto, 1993). Students
who depart from the original institutions are simply labeled “drop-outs,”
and individual institutions have traditionally failed to distinguish between
attrition and transfer (Kearney, Townsend, & Kearney, 1995). The single
heading of “drop-out” lumps together very different departing alternatives
and fails to report students’ follow-up behaviors after they depart from the
original institution.
Second, policymakers have not adequately realized the inefficiency in
four-to-four transfer. Students who transfer from one institution to another
may unnecessarily repeat courses, which delays their degree completion and
increases the cost of postsecondary education for both individual students
and governments. Many states have launched statewide initiatives, such as
articulation agreements, common core curricula, and a common course
numbering system, to facilitate the two-to-four transfer (Creech, Lord, &
Cornett, 2007), but few explicitly include transfers among four-year institutions in their state regulations. The assumption is that students transferring
from four-year institutions are able to return to their original institutions
and to complete the bachelor’s degree there. Yet only a small portion of
them do, in fact, return to their original four-year institutions. Others who
stay in the postsecondary education system may encounter similar obstacles
(or additional hindrances) than two-to-four transfers, because four-to-four
transfers are seldom facilitated by state policies. As a result, four-to-four
transfer students may take longer to achieve their academic goal.
A 2005 U.S. Department of Education study reported that two-to-four
transfer students took about 5.4 years on average to earn a bachelor’s degree,
four-to-four transfers took an average of 5.1 years, while students who did
not transfer took an average of 4.4 years to finish (Enzi, Boehner, & McKeon,
2005). Even though students who make four-to-four transfers can be delayed
in achieving their degrees by other factors, such as change of majors, these
students generally have good academic preparation and high academic
aspirations; they should receive attention and assistance in transferring.
Third, institutional administrators at four-year institutions have an
ambiguous view about enrolling transfer students from other four-year
LI / Four-Year to Four-Year Transfers
209
institutions. Transfer students have been used to fill vacancies in upperlevel courses created by high attrition rates or departmental enrollment
imbalances (Cheslock, 2005). Institutions may save educational resources
by enrolling transfer students because transfers fill vacancies that would
otherwise go unused (Dowd, Cheslock, & Melguizo, 2008). However, for
the same reason, transferring students may also incur high costs of instruction. If transfers spend a much longer time completing the degree than
freshman entrants, their attendance at upper-level courses, which are more
expensive than lower-level courses, may raise the cost of instruction. Given
such mixed consequences, transfers from four-year institutions, who are
not guaranteed articulation or are eligible for financial aid in transferring,
are less attractive to four-year institutions and receive low priority from
institutional administrators.
This study examines the timely attainment of the bachelor’s degree among
students who transfer from four-year to four-year institutions and discusses
possible policies to improve four-to-four transfer efficiency. Additionally,
this study compares the probability of bachelor’s degree attainment among
students who start from four-year institutions and thereafter (a) stay in their
original institutions until graduation, (b) stop out but return to their original institution, (c) leave their original institution for a time but eventually
enroll in other four-year institutions, and (d) leave original institutions and
promptly enroll in other four-year institutions without stopping out.
I include only four-year institutions because students at community colleges must transfer to four-year institutions to attain a bachelor’s degree.
Much previous research has examined bachelor’s degree attainment among
students who transfer from community colleges. The current study focuses
on an area that has received little attention—the timely attainment of a
bachelor’s degree among students transferring from four-year to four-year
institutions.
CONCEPTUAL FRAMEWORK
The conceptual framework of this study is empirical analyses of students’
retention theories and the policy discussion on the efficiency of two-to-four
transfer. Students’ decisions to follow different educational pathways can be
viewed as an extension of their withdrawal from their original institution
(Hillman, Lum, & Hossler, 2008). Accordingly, the literature that guides
this study draws on student retention theories and degree attainment. The
reasons that motivate students to voluntarily withdraw from an institution
have long been a focal topic in higher education. Academic performance,
financial factors, and institutional attributes play well-documented roles in
students’ departure choices.
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Academic Performance
As early as the mid-1970s, Cope and Hannah (1975) pointed out that
academic underachievement and other academic issues are the most commonly reported reasons for students’ voluntary departure. Bean (1980,
1983) and Eaton (Bean & Eaton, 2002) synthesized the industrial turnover
model and the framework of student involvement and found that students’
academic achievement measured by grade point average (GPA) was the
most obvious indicator of intention to withdraw from college. Moreover,
academic underachievement can also be a result of students’ intention to
depart (Stage & Hossler, 2002). Students who intend to leave their institutions may not be motivated to perform well and may therefore receive less
attention and encouragement than students who want to stay. The resulting
spiral of poor performance and lack of encouragement may well result in
the decision (or the requirement) to withdraw.
Although academic preparation in high school is closely related to academic achievement in college, researchers have found that it has a complex
influence on students’ decisions to leave college. Campus-based studies have
found that college GPA has a direct effect on student persistence, while high
school GPA and other measures of ability do not (Benin, Brandt-Williams, &
Okun, 1996; Nora & Cabrera, 1996). Yet broader national studies have presented the contradictory finding that high school academic performance is a
reliable predictor of college persistence (Astin, 1975; Williamson & Creamer,
1988). Despite these inconsistent findings, students’ academic capability, as
indicated by both precollege and at-college performance, can be regarded as
significant factors in decisions to withdraw from an institution.
Financial Factors
Along with the substantial increase in tuition and fees, concern about
college affordability has initiated much research on the economic perspective of student persistence for more than three decades (St. John, 1994).
In the 1970s, college costs barely increased, but tuition and fees began to
grow much more rapidly than consumer prices in the following decades
(College Board, 2004). Under growing financial pressure, financial factors
have become a major consideration in students’ decision about continued
enrollment at their initial institution.
Most studies have shown that tuition and fees are inversely associated
with persistence (Paulsen & St. John, 1997; St. John, Andrieu, Oescher, &
Starkey, 1994; St. John, Oescher, & Andrieu, 1992; St. John, Paulsen, & Starkey, 1996), but the effects have varied across institutional types and student
groups. Increased tuition shows a greater negative effect on persistence for
students enrolled in public four-year institutions than on their counterparts
in the private sector (Paulsen & St. John, 1997). Students from lower-income
LI / Four-Year to Four-Year Transfers
211
families are more sensitive to the increased tuition than students from
affluent families (Heller, 1997). Drawing enrollment data from 50 states
from 1976 to 1994, Heller compared the price-sensitivity of first-time enrollees and continuing students to changes in tuition and state grants. He
employed cross-sectional and time-series methods and found that students
who had already been in higher education showed stronger price elasticity
than newcomers.
The effects of financial aid on student persistence varies across the type
and amount of aid, and the financial need of a recipient group. Institutional
research on the campus of the University of Nevada, Reno, calls into question
prior beliefs about the correlation of financial aid and students’ sensitivity
to the cost of higher education. Herzog (2008) found that, controlling for
an array of indicators of student characteristics, institutional attributes,
and students’ college experience, financial aid exhibited a larger impact on
middle- and high-income students than it did on low-income students. In
addition, he also found that academic achievement in the freshman year
was the most important factor in predicting the persistence of low-income
students.
Institutional Attributes
Students who leave institutions because of the institutional environment
may find themselves forced out by matters beyond their control. Accordingly to Tinto’s (1993) interactionalist model, students who cannot adjust
and integrate into the institutional environment may end up withdrawing.
Following Tinto’s model, a large number of studies have emphasized the
importance of student fit, efforts, and integration and engagement in different components of the institutional environment on student persistence
(Pascarella & Terenzini, 1991, 2005). Strauss and Volkwein (2004) compared the influences of academic and social integration on institutional
commitment and concluded that academic integration, especially student
experience in the classroom with faculty, has a more important influence
on student persistence.
The institutional attributes that are frequently found to influence persistence include type (public versus private), quality, and size. Pascarella
and Terenzini’s (2005) meta-analysis indicated that the average unadjusted
rates of student persistence into the second year were lower in public institutions than in private institutions. The difference varied depending on
the definition of the population, the census period, and the highest degree
an institution offers. Research results have consistently shown that, ceteris
paribus, the more selective the institution, the more likely that students will
continuously attend and achieve their degrees within six years (Adelman,
1999; Dey & Astin, 1989; Ethington, 1997).
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In the 1990s, the literature regarding the indirect influence of institutional
size on persistence offered a mixed conclusion (Astin, 1993; Astin, Tsui, &
Avalos, 1996; Pascarella & Terenzini, 1991; Stoecker & Pascarella, 1991). Astin
(1993) found that institutional size was the strongest institutional factor
that negatively affected persistence and degree completion. However, Astin,
Tsui, and Avalos (1996) argued in a later study that the negative and indirect
influence from size could be small, possibly trivial. Ethington (1997) and
Stoecker and Pascarella (1991) further pointed out that size was inversely
associated with student social integration into the institutional environment.
The larger the student body, the less likely that students are involved in the
institutional social environment.
Based on the prior literature, the constructs of academic performance,
financial factors, and institutional attributes constitute the key reasons why
students leave an institution. Yet students who choose different educational
pathways present more specific reasons. The transfer and stop-out participants from four-year institutions of the Beginning Postsecondary Students
Longitudinal Study (BPS: 96/01) were asked to select among 13 different
reasons in academic year 2001 to describe their reason for transferring or
stopping out.
Table 1 shows the reasons reported by transfer students who started at and
transferred to four-year institutions. The most frequently identified reason
is that the destination institution offered desired programs or coursework.
Sixty-nine students (18%) earned a degree or certificate at their original fouryear institution, then transferred to another institution. The less significant
reasons were logistics, personal interest, etc. Only 8% of the students gave
financial reasons as their top reason for transferring. Low satisfaction with
the school’s reputation, quality, and other academic concerns about the
original institution were also mentioned as the top motivation to transfer.
Table 2 shows the reasons reported by stop-out students who originally
attended four-year institutions. The most frequently chosen reason (24%)
for stopping out was the need to work, with financial reasons as the third
(12%) most frequently mentioned motivation. Only five students stopped
out because they wanted a different academic program, and three reported
other academic reasons.
Even though transfer and stop-out students were given distinct lists of
reasons to explain their departure from original institutions, transfer and
stop-out students chose perceptibly different causes as their top reasons.
Generally, the academic-related reasons were more important in students’
decision to transfer, while the financial and personal reasons ranked higher
in stop-out decisions. Such differences may imply that the top reasons not
only motivate students to leave, but also influence students’ decisions about
educational pathways after they leave. In addition, students who leave for
LI / Four-Year to Four-Year Transfers
213
TABLE 1
THE TOP REPORTED REASONS OF TRANSFER STUDENTS
No. of Transfers
Total:
82
69
64
42
40
31
27
19
6
1
381
Percentage (%)
22
18
17
11
10
8
7
5
2
0
100
Reasons
Offered desired program/coursework
Earn degree/certificate
Logistics
Personal interest/enrichment
Other
Affordable/other financial reasons
Reputation of program/faculty/school
Prepare for new career/degree
Academic problems elsewhere
Advance in current job
Source: U.S. Department of Education, National Center for Education Statistics, Beginning Postsecondary Students (BPS:96/2001).
TABLE 2
THE TOP REPORTED REASONS OF STOPOUT STUDENTS
No. of Stopouts
Total:
18
10
9
7
7
6
5
5
5
3
1
76
Percentage (%)
24
13
12
9
9
8
7
7
7
4
1
100
Reasons
Needed to work
Taking time off from studies
Other financial reasons
Change in family status
Other
Conflicts with demands at home
Deciding on different program
Conflicts with job/military
To pursue other interests
Academic problems
Participated in co-op/internship
Source: U.S. Department of Education, National Center for Education Statistics, Beginning Postsecondary Students (BPS:96/2001).
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academic-related reasons may have higher degree aspiration than students
who leave for other reasons and may therefore be more likely to complete
the bachelor’s degree. Thus, students’ experience with and their perceptions
of their original institution are important indicators of their choice of educational pathways and the possibility of bachelor’s degree completion.
DEGREE ATTAINMENT OF TRANSFER STUDENTS
The bachelor’s degree attainment of transfer students is an important
research subject of institutional research; however, it has attracted only a
few researchers making national studies. Given the nature of the institutional study, institutional researchers usually compare the bachelor’s degree
attainment of incoming transfer students with native students at the same
institution, while researchers doing national studies investigate the degree
attainment of outgoing transfer students with those staying at their original
institutions. Accordingly, to combine the research results at both institutional
and national levels may present a comprehensive view of degree attainment
of transfers.
Institutional Research
The natural controls over the effects of the institutional environment
make institutional research a good means for comparing the academic
success of transfer students with that of native students in the destination
institutions. The University of Missouri system analyzed academic success in
terms of one-year persistence, graduation rate within six years, and cumulative GPAs of transfer and native students (Eimers & Mullen, 1997; Mullen
& Eimers, 2002; Saupe & Long, 1996). In 1996, the University of MissouriColumbia admitted transfer students (who transferred from both two-year
colleges and four-year universities) in good academic standing whose overall
GPA for all college-level courses at previous institutions was at least 2.0
(on a 4.0 scale). Comparing 10,312 degree-seeking transfers with 14,351
native students who entered between fall 1983 and 1991, Saupe and Long
regressed persistence and graduation rates on a dummy variable of transfers
with the number of transfer credits, transfer GPA, and type of previous institutions controlled. They found that one-year persistence and graduation
rates within six years of native students were consistently higher than those
for transfers. Even though the differences were moderate, persistence and
graduation rates for transfers from four-year institutions were significantly
higher than those from two-year colleges; and the rates for students from
public institutions were higher than those from private institutions. Eimers
and Mullen (1997) replicated Saupe and Long’s study and found consistent
results in the persistence and graduation rate. In addition, they found that,
LI / Four-Year to Four-Year Transfers
215
when credit hours and GPAs were constant, transfer minority students were
less likely to graduate than White or Asian American students.
Porter (1999) analyzed the academic performance of transfers at the
University of Maryland and asserted that some confusing results of performance differences between transfers and native students might come
from an inappropriate comparison. He argued that, because transfers had
a taste of college life before they entered the University of Maryland, their
previous college experience might have had shadow effects on their social
and academic integration into a new college climate. On the other hand,
transfers, like new students, also experience the need to adapt to the new
climate (Dougherty, 1992). Therefore, Porter believed that to sample returning transfers (both from two-year colleges and four-year universities)
with returning natives offered a more promising method because a fair
comparison between placed transfers and natives was allowed. Controlling
student characteristics and academic and social experience at Maryland
University, Porter found that transfers appeared to be 1% to 9% less likely
to be retained within one year, were 2% to 8% less likely to graduate within
six years, and earned 0.1 to 0.2 lower GPAs than natives.
The research results of institutional studies provide important insights
for the current study on academic success of transfer students, especially the
consideration of transfer students’ experience in their original institutions.
Researchers of national studies who compared outgoing transfer students
with those staying in their original institutions also included transfer students’ experience in their original institutions, more or less. Yet the national
studies, for the lack of the control over students’ experience at destination
institutions, did not present the same results as institutional studies.
National Research
Adelman (1999, 2006) thoroughly examined how multi-institutional attendance patterns influence the academic success of transfers at the national
level. Drawing data from the High School and Beyond/Sophomore cohort
longitudinal study (HS&B: 80/92) and the National Education Longitudinal
Study of 1988 (NELS: 88/00), Adelman concluded that academic resources
indicated by high school curriculum, test scores, and class rank contributed
most to long-term bachelor’s degree completion. Adelman (1999) also
claimed that students who attended more than one school and did not return to their first institution were less likely than transfers who did return
to complete a bachelor’s degree within 11 years.
Rab (2004) used the same data sample as Adelman (2006) to comprehensively examine how attending more than one institution influences educational trajectories and degree completion for transfer students. She focused
only on transfers who started at four-year institutions. Rab demonstrated
that economically disadvantaged students were more likely to show multi-
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THE REVIEW OF HIGHER EDUCATION WINTER 2010
institutional attendance patterns—which has been documented as less efficient in terms of degree completion. More importantly, Rab observed that
engaging low socioeconomic students in a multi-institutional attendance
pattern might result in a new stratification in higher education. As she said,
“Clearly, swirling represents a less successful route to degree completion for
poor students, and they are disproportionately likely to follow it. Therefore,
swirling assists in the continuing reproduction of class inequalities and helps
create new forms of stratification within higher education” (p. 8).
Adelman (1999, 2006) and Rab (2004) offer valuable information on the
empirical analysis and policy implications for this study on the academic success of students who attend more than one institution. Consistent research
results found that attending multiple institutions decreased the probability of
obtaining the bachelor’s degree and increased the amount of time required to
attain the degree for those who were successful. Students, especially students
from lower-income families, who attend multiple institutions, spend more
on higher education and take longer to earn their degree. As the results, the
socioeconomic hierarchy in higher education can be further widened.
POLICY DISCUSSION OF TRANSFER EFFICIENCY
To help students receive their bachelor’s degree in a timely fashion is certainly a goal of policymakers. The longer students stay in higher education,
the higher the cost to both their families and to the government. As a result,
many state governments adopt various policies to help students move from
community colleges to four-year institutions effectively and efficiently. The
common elements for successful transfer policies typically include articulation agreements, core curricula, a common course numbering system, and
statewide transfer guides (Wellman, 2002). These policies and agreements
have the goals of (a) eliminating delays in degree completion caused by the
unnecessary repetition of course work, (b) providing clear information for
students to use in moving from community colleges to four-year institutions,
and (c) assuring students that the credits they earn toward their associate’s
degree at a community college will apply toward completion of the bachelor’s
degree at four-year institutions (Creech, Lord, & Cornett, 2007).
In addition, a few states (Arizona, Maryland, Massachusetts, Texas, and
Virginia) have adopted financial aid policies specially designed for twoto-four transfer students. Despite the different aims of these financial aid
policies, the policies generally encourage behaviors that improve the rate
of attaining a bachelor’s degree at four-year institutions, and penalize parttime study and broken enrollment, which decrease the probability of timely
degree attainment (Long, 2005). Moreover, the financial aid policies also
provide incentives for four-year institutions to enroll more transfer students
(Wellman, 2002). For example, the New Mexico Commission of Higher
LI / Four-Year to Four-Year Transfers
217
Education created a system of performance-based funding to financially
reward institutions for each Pell Grant-eligible student who persists from
first to second year at an in-state community college, receives an associate’s
degree or certificate, and then transfers to an in-state four-year institution
(Long, 2005). The Bundy Aid Program is a direct institutional aid policy
in New York that unrestrictedly pays independent colleges based on the
number of degrees that each confers. Because of this policy, many private
colleges establish partnership relations with community colleges and foster
two-to-four transfers on an institutional level.
The primary purpose of statewide transfer policies is to help two-to-four
transfer students complete their bachelor’s degree efficiently. When states
lack such policies on four-to-four transfer, individual receiving institutions
make decisions about accepting transfer students and the number of credits.
The receiving four-year institutions usually consider the sending institutions’
accreditation and the comparability of coursework in determining how many
credits can be transferred (Enzi, Boehner, & McKeon, 2005). Some institutions may decide the number of transfer credits when offering admission;
others make such decisions after students are enrolled.
Additionally, two groups of officials review and decide the number of
accepted transfer credits: (a) admission officials determine credits applied
toward general education, and (b) faculty members decide if the courses
meet the department requirements for degree completion. Thus, credits
that can be accepted in one four-year institution may not be transferrable
to the one university a student wishes to attend. The lack of statewide coordination and the complicated transferring process make the four-to-four
transfer much less efficient than two-to-four transfer in terms of timely
degree completion.
METHODOLOGY
Heckman (1979) first proposed a two-step procedure, which has been
known as a standard econometric method to correct the sample selection
bias (Greene, 2002). Such bias may be due to the endogenous sampling
method by which individuals are segmented from the available sample
based on their decision or choice that in part contains information on the
dependent variable (Cameron & Trivedi, 2005). In such cases, the probability
distribution of the endogenous variables is correlated with the dependent
variable, and the parameter estimates of interest may be inconsistent unless corrective measures are taken. For example, in a study of the effect of
drinking wine on health, individuals with serious health problems may
quit drinking under their doctor’s advice. However, the positive effects of
drinking wine on health may be upwardly biased because individuals with
a serious health problem do not drink. In this study, transfer students may
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THE REVIEW OF HIGHER EDUCATION WINTER 2010
be observed to be less likely to obtain a bachelor’s degree, because students
who are less likely to obtain the degree in their original institutions tend to
transfer to other institutions. Thus, I employ Heckman’s two-step model to
correct this sample selection bias.
In the first step, the students’ likelihood of leaving their original institutions is regressed by their personal characteristics, pre-college academic
performance, within-college experience, financial concerns, and attributes
of their original institutions. Based on a first-step regression, an inverse
Mills ratio is calculated to measure the “departure hazard” of each student
as an indicator of the selection bias. The first-step logistic regression is
represented as:
eF1(x1 ’β1)
(1) Pr[y1 | x1] =
+ σ1,
y1 = { 1 if departed }
F (x ’β )
0 if stayed
1+ e 1 1 1
y1 = 1 if the student’s departed from the original institution, and y1 = 0 if
the student’s stayed. F1(x1’β1) = f1 (C, S, A, E, T, I), where
C = the student’s characteristics, indicated by age, gender, and ethnicity;
S = the student’s socioeconomic background, indicated by family annual
income in 1995 and the higher educational level of the parents;
A = the student’s pre-college academic performance indicated by SAT
score and the highest degree to which he or she aspires;
E = the student’s at-college experience indicated by GPAs in the academic
year 1995–1996, part-time attendance in the academic year 1995–1996, and
academic and social integration to their original institutions;
T = the student’s financial concerns indicated by net tuition and fees in
the academic year 1995–1996;
I = the attributes of the original institutions indicated by type, size, selectivity, and location;
σ1 = the error term
By obtaining the parameters in the first step, the inverse Mills ratio denoted as λ is calculated. Specifically, λ = f(-x1’β1)/[1-F(-x1’β1)], where f(·)
and F(·) are the probability density function and cumulative distribution
function of the standard normal distribution, respectively. This ratio is
used in the second-step regression as a regressor to control the correlation
between the errors in the first- and second-step regressions. The secondstep regression that predicts the student’s bachelor’s degree attainment is
represented as:
(2) Pr[y2 | x2]=
e[F2(x2 ’β2) +σ12 λ(x1’β1)]
1+ e
[F (x ’β ) +σ λ(x ’β )]
2 2 2
12
1 1
+ σ2,
y2= { 1 if graduated
0 if not graduated
}
LI / Four-Year to Four-Year Transfers
219
y2 = 1 if the students graduated, and y2 = 0 if not. F2(x2’β2) = f2(C, S, A,
E´,T´, I), where:
C = the student’s characteristics indicated by age, gender, and ethnicity;
S = the student’s socioeconomic backgrounds indicated by family annual
income in 1995 and the higher educational level of the parents;
A = the student’s pre-college academic performance indicated by SAT
scores and the highest degree to which he or she aspires;
E´ = the student’s at-college experience indicated by part-time attendance in the academic year 1995–1996 and accumulative GPAs in the last
academic term;
T´ = the student’s financial concerns indicated by net tuition and fees in
the academic year 1995–1996, and the total amount of Pell Grants received
from academic year 1995–1996 to 2001–2002;
I = the attributes of the original institutions indicated by type, size, selectivity, and location;
σ2 = the error term
With the selectivity bias controlled by the inverse Mills ratio, the probability of bachelor’s degree attainment can be accurately estimated in the
second-step regression.
DATA
The analytical sample for this study is drawn from the national longitudinal data set of the Beginning Postsecondary Students Longitudinal
Study (BPS: 96/01). The BPS is designed specifically to collect data related
to students’ lives following college enrollment and graduation and thus
contains information on their college experience, persistence in school,
degree completion, and employment following enrollment. The BPS surveys
students who are enrolled in a postsecondary institution for the first time
and follows the same students two and five years after their first enrollment.
The current study uses the BPS data collected for students enrolled in the
academic year 1995–1996 and their follow-up data in the academic year
2000–2001. In addition, institutional data such as institution size, type, and
selectivity are drawn from the Integrated Postsecondary Education Data
System (IPEDs) of 1995.
This study includes only the first-time degree-seeking traditional students
who originally attended a four-year institution. Because students at twoyear community colleges have to move to a four-year institution to receive a
bachelor’s degree, there is not much heterogeneity in these students’ transfer
behavior, and the effect of transfer on bachelor’s degree attainment is positive
for them. Furthermore, the study selects students who transferred only once,
and does not include students who transferred to other two-year colleges at
any point of their educational pathways. Additionally, for the purposes of
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THE REVIEW OF HIGHER EDUCATION WINTER 2010
this study, attending summer school is not counted as enrollment. Therefore,
the analytical sample of the study is composed of students who stayed in the
original four-year institution, those who left and came back to the original
institution, and those who transferred to other four-year institutions. Both
the descriptive and regression results are weighted by the number of students
who responded to surveys in 1996 and 2001.
Variables
Table 3 shows the definitions and measures of the dependent and independent variables of this study. The dependent variable is bachelor’s degree
attainment within six years. Students’ educational pathways are the explanatory independent variables, which consist of four categories: (a) staying at
the original institution for six years or until degree completion (stayed);
(b) leaving the original institution but returning to it until the sixth year
or degree completion (stop-out); (c) leaving the original institution for a
period but eventually enrolling in another four-year institution (interrupted
transfer); and (d) leaving the original institution and promptly enrolling in
other four-year institution (continuous transfer).
Table 4 presents the weighted means for continuous variables and the
number of cases for categorical variables of this study. Table 5 presents the
percentages of degree attainment within six years among the students by
different educational pathways. Four types of educational pathways are
shown in the table: stayed, stop-out, interrupted transfer, and continuous
transfer. Table 5 shows that 91.3% of the students who stayed in the original
institution obtained a bachelor’s degree within six years, while only 19.6%
of the stop-out students did. Among transfer students, interrupted transfers
show a much lower probability of obtaining a degree within six years than
continuous transfers. The interrupted students (n = 19), who comprise only
24.7% of the sample, obtained the degree, while 272 continuous transfers
(59.5%) obtained degrees within six years. The graduation rate of all students
in the sample is 82.4%.
Table 6 shows the students’ characteristics and family backgrounds by
educational pathways. Except for the students’ age, the average family income,
SAT scores, academic aspirations, and parents’ educational level are significantly different across the educational groups. The average family income in
1996 for staying students is $70,590, which is the highest among all groups.
The average family income of the continuous students is the second highest,
and that of stop-out students is the lowest among all the groups. The staying
students obtained the highest average SAT score, while the SAT score of the
continuous students is the lowest among all the groups.
Because all the students originally attended four-year institutions, the
majority aspire to obtain post-baccalaureate degrees. The difference in academic aspirations is small but significant across the groups. Once again, the
LI / Four-Year to Four-Year Transfers
221
TABLE 3
DEFINITION AND CODING OF VARIABLES
Variables
Definition and Coding
Stay
A stay refers to a student who continuously enrolls in the original
institution without taking a break for more than four months
Stop-out
A stop-out is defined as a break in enrollment in the original
institution of five or more consecutive months, but the student
comes back to the original institution.
Continuous transfer
A continuous transfer occurs when a student leaves the original institution, enrolls at a destination institution within four
months, and stays there for four or more months.
Interrupted transfer
An interrupted transfer occurs when a student leaves the original
institution for more than four months and then enrolls at a destination institution for four or more months.
Degree attainment
Dichotomous indicator, coded “1” if a student received a bachelor’s degree by AY 2000-2001, otherwise “0”
Male
Dichotomous indicator of gender, coded “1” if a student is male
Age
Continuous measure of a student’s age (by December 31, 1995)
Race
Continuous measure of an ethnic group that a student belongs to,
coded from 1=White, non-Hispanic to 4=Asian/Pacific Islander
SAT (in hundreds)
Continuous measure of derived combined SAT score
Aspiration
Continuous measure indicating the highest degree expected by AY
1995–1996, coded from 1=less than four-year degree or no degree
to 6=doctoral degree or first professional degree
Parent’s highest
ed. level
Continuous measure indicating the higher educational
attainment of parent, coded from 1=did not complete high school
to 3=some college education or more
Family income in
1996 (in thousands)
Continuous measure indicating parents’ income for students
under 30 for 1995 calendar year
GPA in AY 1995-1996
Continuous measure indicating the grade point average in
1995–1996, standardized to a 4.00 point scale
Cumulative GPA
when last enrolled
Continuous measure indicating the actual or estimated GPA in
the last term as an undergraduate, coded as 1=most Ds or below
(below 1.24) to 7=most As (3.75 or above)
Ever attended
part-time
Dichotomous indicator of pattern of enrollment intensity for
months enrolled during AY 1995-1996, coded “1” if a student
attended as a part-time student.
Academic integration
Continuous measure indicating the overall level of academic
integration students experience in original institutions during
the academic year 1995-1996. It is based on the average of the
students indicating how often they had done the following items:
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THE REVIEW OF HIGHER EDUCATION WINTER 2010
Table 3, cont.
Variables
Definition and Coding
participated in study groups, had social contact with faculty, met
with an academic advisor, or talked with faculty about academic
matters outside of class. Non-missing values for these items were
averaged and the average multiplied by 100, and then coded as
1=barely integrated (below 150) to 4=very actively integrated
(250 and above)
Social integration
Continuous measure indicating the overall level of social integration students experience in original institutions during the academic year 1995–1996. It is based on the average of the responses
indicating how often they had done the following items: attended
fine arts activities, participated in intramural or nonvarsity sports,
participated in varsity or intercollegiate sports, participated in
school clubs, or gone places with friends from school. Non-missing values for these items were averaged and the average multiplied by 100, and then coded as 1=barely integrated (below 150)
to 4=actively integrated (250 and above)
Net tuition and fees
in AY 1995-1996
(in thousands)
Continuous measure indicating tuition and fees minus all grants
received during the academic year 1995–1996. Negative values
recoded to zero.
Cumulative Pell
grants (in thousands)
Continuous measure indicating cumulative Pell grant amount
from academic year 1994–1995 through 2001–2002.
Public school
Dichotomous indicator of type of original institution that a student attended, coded “1” as a public institution
Size (in hundreds)
Continuous measure of the total number of students enrolled for
credits in 1995
Selectivity
Continuous measure derived from two variables: the category of
“very selective” identifies institution in which the 25th percentile
of SAT I and ACT scores of freshmen entering in Fall 1997 was
greater than 1000. The remaining institutions were divided into
“selective” and “least selective” categories based on selective Carnegie classifications (1994 classification): coded as 1=least selective
to 3=very selective
Distance to home
(in hundreds)
Continuous measure indicating distance in miles from the
original school to a student’ permanent home 1995–1996
1
2
3
Parent’s highest ed. level
Did not complete high school
Completed high school or equivalent
Some college or more
2990
42
591
2357
2990
3
9
495
1585
898
1
2
3
4
5
2990
2391
199
222
178
Aspiration
Certificate
Associate’s degree
Bachelor’s degree
Master’s degree
Doctoral or first-professional degree
1
2
3
4
Race
White, non-Hispanic
Black, non-Hispanic
Hispanic
Asian/Pacific Islander
2990
2990
1334
1656
2990
1
0
Age
Gender
Male
Female
Obs
SAT
Code
Variable
2.8
4.1
987
1.4
18.3
0.5
Mean
0.4
0.7
203
0.8
0.7
0.5
Std. Dev.
1
1
430
1
16
0
Min
TABLE 4
DESCRIPTIVE STATISTICS OF INDEPENDENT VARIABLES
3
5
1550
4
24
1
Max
1.4
19.8
78.8
0.1
0.3
16.6
53.0
30.0
80.0
6.7
7.4
6.0
44.6
55.3
Percent %
LI / Four-Year to Four-Year Transfers
223
2990
1407
566
1017
1
2
3
1
2
3
4
Selectivity
Least selective
Selective
Very selective
Academic integration in original institution
Barely integrated
Integrated
Actively integrated
Very actively integrated
2990
156
960
1289
585
2990
Size 96
2990
1771
1219
Public school
Public institutions
Private institutions
1
0
2990
Net tuition and fees
2990
380
2610
Ever part-time 96
Attended part-time
Not attended part-time
1
0
2990
GPA 96
Obs
2990
Code
Family income 96
Variable
Table 4, cont.
2.8
1.8
14,002
0.6
7,277
0.1
2.9
69,288
Mean
0.8
0.9
11,867
0.5
5,907
0.3
0.7
63,816
Std. Dev.
1
1
133
0
50
0
0.2
100
Min
4
3
51,445
1
34,040
1
4
100,000
Max
5.2
32.1
43.1
9.6
47.1
18.9
34.0
59.2
40.7
12.7
87.3
Percent %
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THE REVIEW OF HIGHER EDUCATION WINTER 2010
2990
Cumulative Pell grants 2002
1,144
5.4
268
2.4
Mean
2,361
1.0
567
0.8
Std. Dev.
0
1
1
1
Min
13,489
7
6,300
4
Max
16.8
36.0
41.4
5.8
Percent %
Note: Means are weighted by the students who were respondents in both BPS:1996 and BPS:2001.
Source: U.S. Department of Education, National Center for Education Statistics, Beginning Postsecondary Students (BPS:96/2001), and Integrated Postsecondary
Education Data System (IPEDS: 1995).
2990
GPA when last enrolled
2990
502
1075
1243
173
Obs
2990
1
2
3
4
Code
Distance to home
Social integration in original institution
Barely integrated
Integrated
Actively integrated
Very actively integrated
Variable
Table 4, cont.
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225
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THE REVIEW OF HIGHER EDUCATION WINTER 2010
TABLE 5
THE NUMBER OF DEGREE ATTAINMENT WITHIN SIX YEARS
BY ATTENDANCE PATTERNS
# Obs
Attained
Not attained
% of attainment
Stay
Stop-Out
Interrupted
Transfer
2359
2153
206
91.3
97
19
78
19.6
77
19
58
24.7
Continuous
Transfer
457
272
185
59.5
Total
2990
2463
527
82.4
Source: U.S. Department of Education, National Center for Education Statistics, Beginning Postsecondary Students (BPS:96/2001).
TABLE 6
AVERAGES BY EDUCATIONAL PATHWAYS
Stay
Age
Family income 96**
SAT ***
Aspiration ***
Parent’s highest ed. level **
18.3
70,590
1003
5.1
2.8
Stop-Out
Interrupted
Transfer
18.6
49,729
938
4.8
2.6
18.4
60,437
927
4.9
2.7
Continuous
Transfer
18.4
68,474
925
5.0
2.8
Note: Means are weighted by the students who were respondents in both BPS:1996 and BPS:2001.
The group differences are tested, *** p<0.01, ** p<0.05, * p<0.1
Source: U.S. Department of Education, National Center for Education Statistics, Beginning Postsecondary Students (BPS:96/2001).
average aspiration of staying students is the highest. The majority of staying
students want to obtain post-master’s degrees. Moreover, the parents of
staying students also achieved a higher educational level than the parents of
stop-out and interrupted transfer students. Therefore, the staying students
are likely to come from better socioeconomic backgrounds and show higher
academic capability and aspirations than the students who followed other
educational pathways.
Table 7 shows the numbers of students by gender and race across educational pathways. Female students are more likely to stay in the original
LI / Four-Year to Four-Year Transfers
227
TABLE 7
NUMBERS OF OBSERVATIONS BY EDUCATIONAL PATHWAYS
Male
Female
White
Black
Hispanic
Asian
Stay
Stop-Out
Interrupted
Transfer
1,059
1,300
1,879
154
178
148
50
47
75
7
10
5
41
36
65
3
6
3
Continuous
Transfer
184
273
372
35
28
22
Source: U.S. Department of Education, National Center for Education Statistics, Beginning Postsecondary Students (BPS:96/2001).
institution or continuously transfer to other institutions than male students.
Because only 20% of the total students in the sample are minorities, the
number of White students engaged in each educational pathway is much
higher than other ethnic groups. Thus, 1,879 White students, and only 154
Black, 178 Hispanic, and 148 Asian students remained in their original
institution. Three hundred and seventy-two White students, and only 35
Black, 28 Hispanic, and 22 Asian students continuously enrolled in other
four-year institutions. The number of Asian students engaged in each educational pathway is the lowest among all the ethnic groups.
Limitations
Even though the BPS is an appropriate data source for examining college
students’ transfer behavior, it limits the analysis of this study in two ways.
First, the BPS tracks interviewees for only six years from AY 1995–1996 to AY
2000–2001. This relatively short time frame raises concern about accurately
identifying graduates among transfer and stop-out students. Because of attending multiple institutions and taking time off from higher education, it is
predictable that transfer and stop-out students typically would need longer
to complete bachelor’s degrees than staying students. In the current study,
transfer and stop-out students who have not attained the degree within six
years are coded as “not graduated,” regardless of whether or when they may
attain their degree. The short BPS time frame thus limits the examination of
graduation-rate timeliness among students following different educational
pathways. Nonetheless, graduation within six years is a standard cutting
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point when researchers examine bachelor’s degree attainment. Educational
pathways that do not encourage students to graduate within six years can be
considered inefficient. Moreover, students who take longer to graduate pay
more and require more educational resources from institutional and state
systems. The case becomes worse if these students are less likely to graduate
than their staying peers. Rab (2004) found that economically disadvantaged
students were more likely to attend multiple institutions, thus increasing
the likelihood of greater stratification in higher education. Therefore, timely
graduation is an important concern not only for students and parents, but
also for institutional administrators and policymakers. The topic thus merits
close examination.
Second, the BPS does not provide adequate information after students
leave their original institutions. As a result, information about the experience of transfer students in destination institutions and stop-outs outside
higher education are not available. This limitation could be addressed in
future studies, in which researchers use other primary data. Researchers
may control the confounding effects from students’ experiences at multiple
institutions and outside higher education to further examine the effects
from educational pathways.
RESULTS
Table 8 presents the results of the second step of Heckman’s two-step
model of degree attainment within six years among students who follow
different educational pathways. The results are weighted by the number
of students who responded to surveys in 1996 and 2001. Model 1 includes
attendance patterns and student characteristics. The results show that, compared with the staying students, the stop-out students are 71.2% less likely
to attain a degree within six years; interrupted transfer students are 70%
less likely; and the continuous transfers are 31.9% less likely. In addition
to attendance patterns, other significant influences on degree attainment
are student age, gender, and race. With other variables being equal, older
students are 2.5% less likely to complete a degree than younger students.
Male students are 5.4% less likely to attain a degree than their female counterparts. Hispanic students appear to be 11% less likely to obtain a degree
than White students.
Student socioeconomic backgrounds and academic preparation are added
to the regression in Model 2. A gap in degree attainment between staying
students and students involved in other educational pathways remains
significant, and the magnitude of the difference stays almost the same. The
younger students still have 2.4% higher likelihood of degree completion than
older students, whereas female students are 5.5% more likely to attain a de-
LI / Four-Year to Four-Year Transfers
229
TABLE 8
RESULTS OF HECKMAN’S TWO-STEP TEST OF
DEGREE ATTAINMENT AMONG STUDENTS INVOLVED
IN DIFFERENT EDUCATIONAL PATHWAYS
(Delta-p Shown)
Degree Attainment
(1)
Omitted group = stay
Stop-out
Interrupted transfer
Continuous transfer
Age
Male
Omitted group = White students
Black
Hispanic
Asian
(2)
(3)
(4)
-0.712***
(0.044)
-0.700***
(0.055)
-0.319***
(0.034)
-0.025**
(0.012)
-0.054**
(0.017)
-0.712***
(0.046)
-0.700***
(0.055)
-0.318***
(0.034)
-0.024*
(0.012)
-0.055**
(0.017)
-0.706***
(0.047)
-0.700***
(0.058)
-0.328***
(0.035)
-0.022*
(0.012)
-0.057**
(0.016)
-0.711***
(0.047)
-0.710***
(0.060)
-0.326***
(0.037)
-0.019
(0.013)
-0.040*
(0.017)
-0.030
(0.041)
-0.110***
(0.042)
0.040
(0.050)
-0.022
(0.041)
-0.090**
(0.041)
0.033
(0.048)
0.002
(0.007)
-0.017
(0.012)
0.025
(0.020)
0.0003
(0.0002)
0.021
(0.040)
-0.082**
(0.040)
0.029
(0.048)
0.006
(0.006)
-0.016
(0.012)
0.022
(0.020)
0.0001
(0.0001)
0.025
(0.028)
0.002
(0.003)
0.014
(0.04)
-0.050
(0.040)
-0.044
(0.041)
-0.005
SAT
(0.006)
Aspiration
(0.012)
Parent’s highest ed. level
(0.021)
Family income in 1995
(0.0001)
GPA in AY 1995–1996
(0.027)
Net tuition and fees in AY 1995–1996
(0.003)
Ever attended part-time in AY 1995–1996
-0.023
(0.025)
Omitted group = Barely integrated into academic environment
Integrated
(0.045)
Actively integrated
(0.054)
Very actively integrated
(0.081)
-0.008
0.015
0.0001
0.010
0.002
-0.015
(0.026)
-0.026
(0.046)
-0.065
(0.055)
-0.060
(0.055)
-0.043
-0.093
-0.107
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THE REVIEW OF HIGHER EDUCATION WINTER 2010
Table 8, cont.
Degree Attainment
(1)
(2)
Omitted group = Barely integrated into social environment
Integrated
(0.025)
Actively integrated
(0.030)
Very actively integrated
(3)
0.052**
(0.024)
0.042
(0.029)
0.070**
(0.027)
-0.005
(0.031)
-0.0004***
(0.0001)
0.022
(0.015)
0.0006
(0.002)
(4)
0.048*
0.033
0.054
(0.030)
Public school
-0.003
(0.030)
School size
-0.0003***
(0.0001)
Selectivity
0.024
(0.014)
Distance to home
0.0006
(0.002)
Cumulative GPA in the last term
0.055***
(0.010)
Cumulative Pell grants AY 2001-2002
-0.010***
(0.0004)
Mills
-0.427***
-0.431***
-0.339**
-0.328**
(0.061)
(0.070)
(0.147)
(0.149)
Observations
2990
2990
2990
2990
Pseudo R2
0.274
0.276
0.300
0.324
Note: Robust standard errors in parentheses; regressions are weighted by the number of students who
were respondents in both BPS:1996 and BPS:2001, and standard errors are adjusted for design effects.
Moreover, the interaction effects of students’ gender, ethnicity, and family income have been tested;
no effects found.
Source: U.S. Department of Education, National Center for Education Statistics, Beginning Postsecondary Students (BPS:96/2001), and Integrated Postsecondary Education Data System (IPEDS:
1995).
*** p<0.01, ** p<0.05, * p<0.1
gree than male students. The gap in degree attainment between Hispanic and
White students slightly decreases when their socioeconomic backgrounds
and pre-college academic performance are added to the model. When the
socioeconomic backgrounds and pre-college academic performance are
held equal, White students are 9% more likely than Hispanic students to
complete their degree. Even though Rab (2004) found that economically
disadvantaged students were less likely to complete the bachelor’s degree, the
findings of Model 2 in this study do not support Rab’s results. The variables
LI / Four-Year to Four-Year Transfers
231
of the students’ socioeconomic backgrounds and academic preparation do
not show any significant influence on degree completion.
Model 3 includes students’ experience in original institutions. Students
involved in educational pathways other than staying show a much lower
probability of degree completion within six years, especially for stop-out and
interrupted transfer students. Both the stop-out and interrupted transfers
are 70% less likely to attain a degree, while the continuous transfers are
32.8% less likely than staying students. The younger students still have a
slightly (2.2%) higher probability of completing a degree. The difference
in degree attainment between male and female students remains a little
lower than 6%. Hispanic students are 8.2% less likely than White students
to obtain a degree.
Students’ socioeconomic backgrounds, academic preparation, net tuition
and fees, attendance, and GPA in the first academic year show no significant
influence on their degree attainment. Students’ academic integration to
institutional environment has no effect on degree completion, while their
social integration is positively associated with degree completion. Compared
to the students who barely integrated to the social environment of original
institutions, students who integrated to the social environment are 5.2%
more likely to obtain the bachelor’s degree within six years, and students
who very actively integrated are 7% more likely. The size of the original institution is the only variable among institutional attributes that significantly
influences degree completion; however, the magnitude of the influence
is quite trivial. When school size increases by one thousand students, the
probability of degree completion decreases by 0.4%.
The final model adds the GPA and the amount of Pell Grants that students
receive by the academic year 2001–2002 (or the last academic term) to the
regression. Model 4 shows that the probability gap of degree attainment
among students involved in different attendance patterns remains the same
as in prior models. In this model, stop-out students appear to be 71.1% less
likely than staying students to obtain a degree; the interrupted transfers
are 71% less likely, and the continuous transfers are 32.6% less likely. The
influence of age on degree attainment disappears when the final GPA and
total Pell grant are added, but the gender influence remains. Male students
have a 4% lower likelihood of degree completion than their female peers. In
addition, Hispanic students no longer appear less likely than White students
to obtain a bachelor’s degree when the final GPA and the amount of Pell
grants are controlled.
The effects of students’ social experience in original institutions on the
degree completion is lowered in Model 4, but students who achieve social
integration at their original institutions still have 4.8% higher probability of
obtaining their bachelor’s degree than barely integrated students. Therefore,
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THE REVIEW OF HIGHER EDUCATION WINTER 2010
to a certain extent, the results of Model 3 are inconsistent with the findings
of Adelman (1999, 2006) that students’ experiences in original institutions
have no effect on their degree attainment. Moreover, the cumulative GPA
unsurprisingly shows significant positive effects on students’ degree attainment. Students with a better GPA in the last academic term have 5.5%
higher likelihood of obtaining the degree. However, the amount of total Pell
grants that students received during their college years or until academic
year 2001–2002 appears to negatively affect the probability of degree attainment. Such a finding may not lead to the conclusion that the more
money through Pell grants that a student receives, the less likely he or she
is to graduate within six years. One may consider that students who receive
a higher amount through Pell grants are likely to be from the low-income
families. Earlier studies have documented that these students have lower
probabilities of degree attainment.1
CONCLUSIONS AND IMPLICATIONS
Adelman (1999) claimed that attendance at a four-year institution is one
of the most reliable predictors of students’ attainment of a bachelor’s degree.
Students who originally enroll at four-year institutions have high academic
aspirations and good academic preparation. They want to pursue at least a
bachelor’s degree. If these students stay in their original four-year institutions, over 90% of them may be able to complete their bachelor’s degree
within six years. (See Table 5.) However, some of them need to attend other
four-year institutions at some point. The complicated and random process
of enrolling transfer students in four-year institutions may discourage them
and delay their progress toward a bachelor’s degree.
The statewide policies that streamline the transfer from community
colleges to four-year institutions provide a clear path for transfer students
(Creech, Lord, & Cornett, 2007), enhance transfer rates (Anderson, Sun, &
Alfonso, 2006), facilitate the transfer process (Long, 2005), and prevent the
loss of credits (Roksa & Keith, 2008). However, while the efforts of policymakers and researchers assist an increasing number of community college
students to attend four-year institutions, four-to-four transfer students
are negotiating with institutional officials at destination institutions on an
individual basis and repeating coursework at the new institution. The fourto-four transfer students are often assumed capable of returning to their
original institution and completing their bachelor’s degree. By contrast, this
The interaction effects of students’ socioeconomic status with age, gender, and ethnicity
have been tested and show no influence on the likelihood of degree completion; they are
therefore not presented in Table 8.
1
LI / Four-Year to Four-Year Transfers
233
study shows that not all of these students return to their original institutions
nor are they able to receive their bachelor’s degrees within six years.
The most important result of this study is the discrepancy in the probabilities of timely graduation for students following different educational
pathways. Students staying in their original four-year institution have the
highest probability of obtaining a bachelor’s degree within six years. The
probability for students who continuously enroll in another four-year institution is second. Students who leave their original institutions and stay
out for some time before reenrolling at a four-year institution have the
lowest probability of degree attainment, whether they return to the original
institution or attend another four-year institution.
The large discrepancy in the degree completion between students who
continuously enroll in four-year institutions and those who break their
enrollment echoes Adelman (2006), who concluded: “Post-matriculation
behaviors and attendance patterns that were strongly and positively associated with bachelor’s degree attainment [included] continuous enrollment”
(p. 9). This study shows that students who break their enrollment are 70%
less likely to complete their degrees within six years than students who stay.
The policymakers may therefore want to provide incentives for students to
continuously enroll or discourage those who break their enrollment. Similar
methods have been used in the two-to-four transfer policy in Texas. The
Towards Excellence, Access, and Success (TEXAS) Grant awards two-to-four
transfer students the tuition and required fees based on the amount charged
by the public university (Long, 2005). To be eligible, students must enroll in
a four-year institution for at least three-quarters time within 12 months of
receiving their associate’s degree. Recipients who earn a minimum 2.5 GPA
can renew the grant for up to four years or until they complete the degree.
Policymakers who want to help four-to-four transfer students graduation
in a timely manner may consider adopting similar financial incentives for
needy students who continuously enroll. Long (2005) pointed out that the
TEXAS grant may exclude two-to-four transfers who need to interrupt
their enrollment to deal with family-related issues. However, this consideration may not be significant for four-to-four transfer students, since they
reported enrolling in a desired major as their top reason for transferring.
(See Table 1.)
Moreover, putting a limit on grant renewal negatively sanctions those
who take “too long” to complete the degree. National statistics show that
four-to-four transfer students on average take eight to nine more months to
attain their bachelor’s degrees (Enzi, Boehner, & McKeon, 2005). The needy
four-to-four transfer students may also be required to present proof of the
unmet financial needs (such as tax documents and an enrollment letter)
from which the amount of financial aid can be calculated. They must also
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complete the degree at their destination institution within four years to be
eligible for the transfer grant and its renewal.
This study also found that the continuous transfers who simply change
institutions still have a 33.4% lower probability of attaining their bachelor’s
degree than students who stay at their original four-year institution. Because
of the BPS’s short time frame, this study cannot determine whether the
transfer students receive the degree in destination institutions after they
took the BPS survey. But Porter (1999) found a one-digit percentage gap in
graduate rates between transfers and staying native students after six years
for his University of Maryland sample. The reason could be the loss of credit
caused by changing majors or repeating courses.
If four-to-four students transfer within their state, they can benefit from
a statewide core curriculum and common numbering system. The core curriculum identifies the general education courses (Creech, Lord, & Cornett,
2007). Even though students change majors, the courses they take from the
core curriculum can be transferred to destination institutions within the
same state. The common course numbering system ensures that comparable
courses at public community colleges and four-year institutions within the
state have common titles and numbers (Creech, Lord, & Cornett, 2007). The
core curriculum and common numbering system are designed primarily
to help two-to-four transfers, but these statewide transfer policies can also
conveniently assist institutional officials and students in facilitating fourto-four transfer students.
This study also shows that Hispanic students are 11% less likely to obtain their bachelor’s degree within six years, regardless of their educational
pathways (Model 1 of Table 8). Rab (2004) also observed that minority and
economically disadvantaged students are more likely to engage in multiinstitutional attendance patterns. The needy minority students who leave
original institutions because of financial concerns may need transfer policies
that target them for assistance throughout their college years. The Virginia
Transfer Grant is a financial aid policy that helps two-to-four minority
students transfer within the state. It provides grants of up to full tuition
and fees to minority students enrolled in the state’s traditionally White
institutions and to all transfer students at historically Black institutions
(Long, 2005). Similarly, policymakers may consider designing a financial
aid policy to assist needy minority students who transfer among four-year
institutions as well. States that have already launched such policies to aid
two-to-four transfer could expand their programs to include four-to-fouryear transfer students.
Unlike transfers from community colleges to four-year institutions,
students starting at four-year institutions need not transfer to other fouryear institutions to obtain a bachelor’s degree. Would transfer policies that
LI / Four-Year to Four-Year Transfers
235
facilitate four-to-four transfer encourage students to engage in unnecessary
multi-institutional enrollment? Roksa and Keith (2008) may provide an answer in their recent study of articulation policies and success after transfer.
They found that articulation policies do not induce students to transfer from
community college to four-year institutions nor increase the probability of
timely bachelor’s degree completion. What most articulation policies do is
to assure students inclined to move from one segment of state higher education system to another that they will not be punished by losing credits.
Similarly, creating transfer policies that help students move from one state
four-year institution to another may not encourage students to leave their
original institution. Instead, such policies may coordinate transfers among
state four-year institutions, improve the efficiency of such transfers, and
help more students obtain bachelor’s degree in a timely fashion.
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