J. COLLEGE STUDENT RETENTION, Vol. 15(3) 347-365, 2013-2014
HITTING THE BOOKS AGAIN: FACTORS
INFLUENCING THE INTENTIONS OF YOUNG
ADULTS TO REENROLL IN COLLEGE
KIM SCHATZEL, PH.D.
THOMAS CALLAHAN, PH.D.
TIMOTHY DAVIS, MBA, MUP, MSF
The University of Michigan–Dearborn
ABSTRACT
Results from the analyses of data from 463 former college students between
the ages of 25 and 34 years old identify those most likely to reenroll in
higher education in the near future. Those who intend to reenroll are more
likely to be members of minority groups, younger, single, and recently
laid-off, have earned more credits, and hold strong beliefs about the value
of education. Specific recommendations for strategies and policies through
which colleges could motiviate former students to reenroll and facilitate
their transitions back into the educational system are offered. Among these,
programs that include techniques for updating technology skills, improving
time management and goal setting practices, and reinforcing study habits
appear to be particularly appropriate to the needs of this subpopulation.
Suggestions for future research on stopouts, as well as stayouts, conclude
the study.
INTRODUCTION
In addition to facing harsh economic times, institutions of higher learning are
also facing a shrinking pool of traditional students. The projected number of
high-school graduates is not expected to equal its 2008 peak until after 2018
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Ó 2013, Baywood Publishing Co., Inc.
doi: http://dx.doi.org/10.2190/CS.15.3.c
http://baywood.com
348 / SCHATZEL, CALLAHAN AND DAVIS
(National Center for Education Statistics, 2009). However, about eight million
adults, an estimated 21% of 25 to 34 year olds in the United States, have
attended college and withdrawn without completing a degree (U.S. Census
Bureau, 2007). Some of these individuals do not intend to return to college at
any time in the future, whereas others intend to reenroll. Those who choose to
reenroll after an absence of one or more semesters are referred to as stopouts
(Carnegie Commission on Higher Education, 1973). This group of nontraditional
former college students represents a large and unique pool of potential students
for colleges and universities.
To our knowledge, no previous research has specifically examined the demographic, psychographic, and situational factors that affect nontraditional students’
intentions to reenroll. For that reason, the purpose of this study is to specifically
identify the demographic and psychographic factors that influence the intention
to reenroll among young adult stopouts.
CONCEPTUAL FRAMEWORK
Because stopout behaviors encompass many factors associated with the attraction to and withdrawal from higher education, hypotheses for this study have been
developed relying on multiple streams of research, including those associated
with the initial entry, retention, withdrawal, and reenrollment of adult learners.
The existing literature on stopout and stayout behaviors has relied on theoretical
models of college retention and withdrawal behaviors. Models that have guided
significant research in the study of stopouts are Tinto’s (1975, 1993) explanations
of student retention. In these models, students enter higher education with specific
family backgrounds and individual characteristics. They begin with a commitment
to the concept of higher education, and later develop a commitment to a specific
institution. These commitments influence their academic performance and intellectual development, leading to academic integration into the system. Social
systems also affect their commitments to an institution and, more generally,
higher education. The quality of interactions with faculty and fellow students leads
to corresponding levels of social integration. Levels of academic and social
integration define the fit between students and academic institutions, which in
turn determine the choice to stay or leave.
Influenced by the employee turnover models developed in the organizational
sciences, Bean (1990) proposed a model of student attrition that emphasized
attitudes and intentions, and most importantly, the intentions to stay or withdraw.
Bean and Eaton (2000) later proposed that behaviors, cognitions, and attitudes
determine levels of both academic and social integration. Psychological concepts
such as self-efficacy, approach-avoidance, and locus of control help explain
withdrawal behaviors in this extension of models of attraction and retention. Expanding research to include nontraditional students, Bean and Metzner
(1985) emphasized factors external to the institutional environment, including
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employment opportunities, family responsibilities, financial resources, and opportunities to transfer to another institution.
Student withdrawal and retention behaviors also have been studied from the
economic perspective associated with human factors theory (Becker, 1964). In
this instance, St. John, Cabrera, Nora, and Asker (2000) have developed the
college choice nexus model to include the influences of economic and financial
variables in student choice. In this three-step model, socioeconomic factors and
academic abilities lead potential students to form dispositions toward an educational institution. Next, students perform cost-benefit analyses associated with
the decision to choose a particular academic institution. After enrollment, students
assess the congruence of their previous expectations with actual experiences.
In this third stage, factors such as low grades or negative social interactions
create conflicts with earlier predictions. The college choice nexus model represents a rational process relying on self-assessed probabilities of success and failure
for the student at an institution. According to Cabrera et al. (2000), the overall
process explains decisions to remain enrolled in or withdraw from an institution.
Relying on guidance from the above perspectives, together with previous research
on stopouts and stayouts, our overall research goal is to identify predictors of
reenrollment intentions for young adults with previous college experiences.
QA: Need Ref
DEPENDENT VARIABLE
Intentions are important variables in the student retention literature. Bean
(1990) and Bean and Eaton (2000) have identified intentions to stay as the
strongest predictors of student retention. Regardless, intentions represent cognitive variables, rather than behavioral variables. Although intentions have
been shown to predict behaviors in the retention literature, one might question
the role of intentions as a surrogate for reenrollment among stopouts. Combining elements from the Tinto (1993) and Bean (1990) models, Cabrera,
Nora, and Castaneda (1993) have shown that intentions directly affect retention behaviors.
Empirical evidence for the relationship between intentions and reenrollment
has been provided by Stokes and Zusman (1992) and Woosley (2004). At the
university Woosley (2004) studied, 54% of stopouts stated intentions to
reenroll. Of those, 34% actually reenrolled in that university within 1 year.
Arguably, this relationship is higher than her results indicate. Her data do not
include reenrollment at any other institution and tracked students for only a
period of 1 year following their withdrawals.
The funding agency for this research required the examination of a specific
group of former college students: those 25-34 years old, with previous college
experiences, but no degree. For the purposes of the hypotheses, we refer to this
group as YAPEENDs, young adults, with previous educational experiences,
but no degrees.
QA: Need Ref
QA: Need Ref
350 / SCHATZEL, CALLAHAN AND DAVIS
MINORITY STATUS
Tinto (1993) posits that minorities may face additional social and academic
integration difficulties when pursuing higher education. Astone, Shoen,
Ensminger, and Rothert (2000) describe costs of enrollment, utility of education
for the individual, and likelihood of success as factors affecting African
Americans’ decisions to reenroll. Among studies assessing the effects of minority
status on stopouts, Pascarella, Duby, Miller, and Rasher (1981), DesJardins,
Ahlburg, and McCall (2006), and Johnson (2006) have found that African
Americans are more likely to stopout of college than are majority group members,
although DesJardins et al. (2006) demonstrate that these effects disappear when
factors such as income and age are controlled. Moreover, Johnson (2006) has
reported that minority students are less likely to reenroll in college than are
Caucasians. In empirical research that has included both intentions and behaviors,
Woosley et al. (2005) have shown that minority groups are less likely to state the
intention to reenroll in college, but do not differ in their actual reenrollment.
Minority students at racially diverse institutions are more likely to stopout
(Oseguera & Rhee, 2009). Interestingly, Bynum and Thompson (1983) present
evidence that minority status itself explains withdrawal behaviors. In their
study of four universities, minority students are more likely to stopout or stayout,
even in the instances in which Caucasians represented the minority group.
The research in this area is mixed, but in light of the research showing minorities
are more likely to stop out, we predict that minorities will be less likely to state
the intention to return.
Hypothesis I: YAPEEND majority group members will be more likely to
express intentions to reenroll in higher education than will YAPEEND
minority group members.
GENDER
In most cases, previous research has shown that women express more motivation to enroll and do participate in higher education in greater percentages
than do men (Diprete & Buchmann, 2006; Horn, Peter, & Rooney, 2002).
Johnson (2006) demonstrates that female students are less likely to reenroll
than are male students. Woosley et al. (2005) have shown that males are more
likely to state the intention to reenroll, but are not more likely to reenroll than
are females. Stratton et al. (2008) report that women’s withdrawal behavior is
often related to their decisions to temporarily stopout of education, whereas
men are more likely to stayout. Stimpson and Janosik (2008) report that after
disciplinary suspensions, men are three times more likely to reenroll than are
women. Because the Stratton et al. (2008) study represents a large sample,
multi-institution sample, we predict that young adult women will be more likely
to express an intention to reenroll.
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Hypothesis II: YAPEEND women will be more likely to express intentions
to reenroll in higher education than will be YAPEEND men.
AGE
QA: Need Ref
The influence of age on adult learners’ intentions to pursue higher education
has been researched extensively. For example, Thomas (2001) summarizes the
literature that describes barriers faced by older students (e.g., Bean & Metzner,
1985; Benshoff, 1991; Klein, 1990; Richter-Antion, 1986; Spanard, 1990).
Barriers preventing older individuals from socially integrating back into college
are related to limited social support systems, a lack of peers, and the presence
of the financial, family, and work obligations (Bean & Metzner, 1985).
Related to withdrawal behaviors, Hoyt and Winn (2004), DesJardins et al.
(2006), and Grossett (1993) indicate that stopouts are more likely to be older
than continuing students. Horn (1998), Burley, Butner, and Cejda (2001), and
Berkovitz and O’Quin (2007) present evidence that older students are more
likely to be stayouts than stopouts after withdrawal. A summary of this research
indicates that the majority of studies indicate that age has a negative relationship
with the intention to pursue higher education.
Hypothesis III: Younger YAPEENDs will be more likely to express intentions to reenroll in higher education than will be older YAPEENDs.
FULL-TIME EMPLOYMENT STATUS
QA: Need Ref
Woosley (2004) and Gentemann, Ahson, and Phelps (1998) have shown that
those students who did not reenroll reported greater conflicts between work and
school before their withdrawals. The conclusions from these studies highlight
the significant difficulties students face when attempting to maintain employment and reenroll in education.
Hypothesis IV: Unemployed or part-time YAPEEND workers will be more
likely to express intentions to reenroll in higher education than will
be YAPEEND full-time workers.
DISPLACED WORKER STATUS
Specifically describing stopouts, Light (1995) has established that high
local unemployment rates significantly predict students’ intentions to reenroll.
Women who have more concerns about the stability of their jobs are more
likely to state the intention to reenroll in college (Smart & Pascarella, 1987).
Regardless of the extent to which education leads to a comparably salaried job,
most evidence indicates that many displaced workers choose education following
lay-offs (Ghilani, 2008; Knapp & Harms, 2002).
352 / SCHATZEL, CALLAHAN AND DAVIS
Hypothesis V: YAPEEND displaced workers will be more likely to express
intentions to reenroll in higher education than will be YAPEEND
workers who have not been displaced.
INCOME
DesJardins et al. (2006) estimate that about three-quarters of high income
students attend college continuously until graduation, whereas about threequarters of both middle and low incomes students stopout at some point.
Furthermore, Johnson (2006) has shown that first generation college students,
often from lower socioeconomic strata, are less likely to reenroll after a stopout
incidence. From an economic perspective, education is often not a realistic
choice for those in lower economic strata. According to the human capital
(Becker, 1964) and choice nexus models (St. John et al., 2000), for poor individuals the costs of education often outweigh perceived benefits. The above
review indicates that low incomes are often associated with fewer or truncated
educational experiences.
Hypothesis VI: YAPEENDs with greater incomes will be more likely to express
intentions to reenroll in higher education than will be YAPEENDs
with lesser incomes.
FINANCES
St. John et al. (2000) have emphasized the importance of costs as determinants
of the decision to withdraw from and reenroll in college. They report that the
costs of college have a substantial negative influence on college persistence
behaviors. Hoyt and Wynn (2004) report stopouts are more concerned about
financial problems than are those who stay out. Horn (1998) and Tumen and
Shulruf (2008) hypothesize that reenrollment may represent a means of delaying
repayment of student loans. Regardless, all forms of financial aid increase the
probability of remaining in college (DesJardins et al. 2006). Support from loans
increases the likelihood of withdrawal (DesJardins, Ahlburg, & McCall, 2002).
Previous research leaves little doubt that the costs associated with higher education act as barriers to adults’ interests in and plans to attend higher education.
Hypothesis VII: YAPEENDs who state fewer concerns about costs will be
more likely to express intentions to reenroll in higher education than
will be YAPEENDs who state more concerns about costs.
TIME
Silva, Cahalan, Lacierno-Paquet, and Stowe (1998) believe that time creates
the strongest barrier of all for adult learners. From an economic perspective,
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Stratton et al. (2007) point out that time spent in education after reenrollment itself
represents an opportunity cost. Time for education must be weighed against
other uses of time, such as opportunities for leisure activities or additional
immediate earnings.
Hypothesis VIII: YAPEENDs who state fewer concerns about time conflicts will be more likely to express intentions to reenroll than will be
YAPEENDs who state more concerns about time conflicts.
FAMILY RESPONSIBILITIES
Students who have young children are more likely to stay out than stop out of
college when compared to students who do not have young children (Gentemann
et al., 1998; Horn, 1998; Hoyt & Winn, 2004; Stratton et al., 2008). Pompper
(2006) reports that stopouts who later reenrolled identified child care and
family responsibilities as significant reasons for their previous withdrawals.
From an economic perspective, marriage increases an individual’s household
responsibilities and increases the likelihood of stopping out (Stratton et al., 2008).
Women with children under the age of 6 also are more likely to stop out (Stratton
et al., 2008). Based on this evidence, family responsibilities do appear to create
barriers for adult learners to reenroll in college.
Hypothesis IXa: YAPEENDs who are single will be more likely to express
intentions to reenroll in higher education than will be YAPEENDs who
are married or partnered.
Hypothesis IXb: YAPEENDs with fewer children will be more likely to
express intentions to reenroll than will be YAPEENDs who have more
children.
IMPORTANCE OF EDUCATION
From a theoretical perspective, Tinto (1993) emphasizes the importance of
educational goals and a commitment to education in students’ intentions to
remain in or withdraw from college. For stopouts specifically, Woosley et al.
(2005) have indicated that commitment to education is a strong predictor of the
intention to reenroll.
Hypothesis X: YAPEENDs who agree that a college education is important will be more likely to express intentions to reenroll in higher
education than will be YAPEENDs who do not perceive education as
being important.
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PREVIOUS EDUCATIONAL SUCCESS
QA: Need Ref
QA: Need Ref
Tinto (1993) posits that students begin higher education with skills and
abilities that influence their decisions and behaviors throughout their college
experiences. Among the most important of these are cognitive skills, abilities,
and strategies for success. In support of the importance of these variables
among stopouts, studies by Johnson (2006), Berkovitz and O’Quin (2006), and
DesJardins et al. (2006) have established that academic performance does affect
adults’ probabilities of reenrolling in college. Johnson (2006) and Wilson (2007)
describe GPA as the most significant explanation for a broad category of student
persistence behaviors, including reenrollment. Emphasizing the importance of
previous preparation and success, Daubman et al. (1985) have established that
among students who reenroll the semester after withdrawal on academic probation, only 9% successfully complete the next semester. Burley et al. (2001) report
that over three-quarters of students who stopout from community college after
only one semester had started with identifiable learning deficiencies.
Similarly, Woosley (2004), Johnson (2006), and DesJardins et al. (2006)
maintain that SAT/ACT scores differentiate those who reenroll from those who
do not. Previous academic success and satisfaction with academic achievement
were strong predictors of actual reenrollment in the Woosley et al. (2005) study.
Hypothesis XI: YAPEENDs who report successful educational experiences
will be more likely to express intentions to reenroll in higher education than will be YAPEENDs who report less successful educational
experiences.
PREVIOUS EDUCATIONAL ATTAINMENT
QA: Need Ref
It has been established that actual reenrollment in higher education is
explained by the level of previous educational attainment (Gentemann et al.
1998; Berkovitz & O’Quin, 2007; Hammer, 2003; Woosley et al., 2005). Research
appears to clearly indicate that higher levels of education are associated with
higher levels of participation in adult education.
Hypothesis XII: YAPEENDs with higher levels of educational attainment
will be more likely to express intentions to reenroll than will YAPEENDs
with lower levels of educational attainment.
METHOD
Respondents
Respondents, identified from current census data, voter registration lists, and
warranty card registrations, were selected to participate in telephone interviews
if they had some previous college experience but no degree, were not currently
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enrolled in college, and were between the ages of 25 and 34. A total of 599
telephone interviews were completed. The mean age for the sample was just under
30 years old. Females comprised about 52% of the sample. More than 80% of
the sample described their race/ethnicity as Caucasian, whereas almost 13%
of the sample described their race/ethnicity as African American. All respondents
were residents of Detroit, Michigan or its suburbs, a metropolitan statistical area
of over four million individuals. The percentages of minorities in this sample was
roughly equivalent to those reported in census data (U.S. Census Bureau, 2006).
The dependent variable, intention to return, was measured using a 5-point scale.
Respondents who chose the midpoint choice were dropped from the analysis.
Therefore, the final sample for analyses included 208 respondents who definitely
stated intentions to return, and 255 who stated they did not intend to return.
Of the 9,269 individuals who agreed to participate in the interview, 646 met
all criteria for the survey. Of those respondents, 599 answered all relevant items
on the survey.
Instrument
The survey contained both demographic and psychographic items that previous
research had established were related to intentions to return to college. Two
versions of the survey were administered, one designed for adults who stated
an intention to return to college and the other designed for those who did not
intend to return. Verb tense constituted the only difference between these surveys.
Before administering the survey, summative scales were developed to represent
perceptions about barriers faced including finances (FINANCE), time (TIME),
as well as motivators associated with perceptions of the importance of education
(IMPORTANT), and an estimate of previous success in college (SUCCESS).
Items measuring demographic variables included marital status (PARTNERED), number of children (CHILD), layoff history (LAYOFF), minority
status (MINORITY), full-time employment status (FULL-TIME), previous
credits earned (CREDITS), AGE, INCOME, and GENDER.
Procedure
A commercial survey company administered interviews by telephone. Potential
respondents were asked their ages, whether they had attended college without
completing a degree, and whether they were currently enrolled in college. Each
of these items served as filters for the selection of respondents. Interviews
stopped for respondents who indicated that they were not between 25 and 34
years of age, had not attended college, were currently enrolled in college, or had
completed a degree.
Binary logistic regression tested the hypotheses. Binary logistic regression is
recommended in analyses in which a binary dependent variable is to be predicted
from independent variables, regardless of whether they are continuous, discrete, or
356 / SCHATZEL, CALLAHAN AND DAVIS
a combination of both (Hosmer & Lemeshow, 2000). With 13 independent
variables, heuristics for minimal sample size called for at least 130 cases of the
rarer of the levels of the dependent variable (Garson, 2009). In this instance,
the rarer of the two levels contained 208 cases.
Data Analysis
Independent variables were centered for the analyses. As evidence of an
absence of multi-collinearity, no variance inflation factor (VIF) for any variable
was greater than two. Confirmatory factor analysis indicated acceptable levels
of convergent and discriminant validity for the model. The CFI was 93.9 and the
RMSEA was .056. Both of these indices indicate a reasonable, but not strong
fit of the model to the data (Browne & Cudeck, 1993; Hu & Bentler, 1999).
Average variances extracted (AVE) (Fornell & Larcker, 1981) measure the
variance explained by a latent construct taking into account the variance due to
random measurement error. These ranged from .58 to .78, all above the minimum
value of .50 considered adequate measures of discriminant validity (Bagozzi,
Yi, & Phillips, 1991). Composite reliabilities measure scale reliabilities and
assess the internal consistency of the latent constructs (Fornell & Larcker, 1981).
These ranged from .70 to .80, all equal to or greater than the recommended minimum value of .70 for these measures (Bagozzi & Phillips, 1991).
As suggested by Bagozzi and Phillips (1991), nested models of the correlations among pairs of variables were compared to further test discriminant
validity. A chi-square difference test determined whether the constrained-to-unity
pairs of constructs and unconstrained pairs of constructs significantly differed
(Anderson & Gerbing, 1988). For all pairs, the chi-square test between the two
pairs was at least 3.84, indicating discriminant validities for all pairs (Anderson
& Gerbing, 1988).
Table 1 presents the variables and their measures, as well as average variances
extracted and composite reliabilities for the four latent constructs.
RESULTS
The omnibus tests of model coefficients were significant, c2 (13, N = 443) =
119.34, p < .001, indicating that the predictive ability of the proposed model was
greater than that of the model described by the intercept alone. The Hosmer and
Lemeshow c2 statistic was not significant, c2 (8, N = 443) = 13.53, p > .05. This
statistic tests the hypothesis that the difference between observed and expected
events in the data is simultaneously zero for subgroups of 10 observations
(Hosmer & Lemeshow, 2000). The lack of significance for this statistic indicates
adequate fit of our model to the data.
The classification table indicated that 73% of the cases were correctly classified. The proportional-by-chance-accuracy rate for this classification was 62%.
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Table 1. Latent Constructs (with Average Variances Extracted;
Composite Reliabilities) and Demographic Measures
FINANCE: (AVE; .78; CR; .70)
You left college for financial reasons. (Reverse)
Family finances prevent you from returning to college. (Reverse)
You do not believe you could receive financial aid to return to college. (Reverse)
TIME: (AVE; .62; CR; .73)
You could not fit college classes around your work schedule. (Reverse)
You do not have the time to return to college. (Reverse)
IMPORTANT: (AVE; .72; CR; .80)
A college education is important for a person’s success.
To make a good living you need a college education.
SUCCESS: (AVE; .51; CR; .74)
You performed as well academically as you had expected.
You were academically successful at the last college you attended.
You left college because you did not have to study skills necessary for college.
(Reverse)
MINORITY:
You would best identify your race or ethnicity as? Majority = 0
GENDER:
Your gender is? Female = 0
AGE:
Your age in years is?
FULL-TIME:
You are employed full-time? No = 0
LAYOFF:
Have you experienced a layoff in the last two years? No = 0
INCOME:
Five ranges of income levels.
MARRIED:
What is your partnered status? Single = 0
CHILD:
Number of children under 10 years.
CREDITS:
Five ranges of credits earned.
Intention:
Likelihood of returning to college in the near future? No = 0
358 / SCHATZEL, CALLAHAN AND DAVIS
This percentage represents the accuracy rate attributable to chance multiplied
by 1.25. It is considered to be the minimum predictive percentage for meaningful
classification results (Garson, 2009).
Seven variables were associated with a greater likelihood that respondents
would state the intention to reenroll in higher education: minority status (odds
ratio [OR] = 2.75, 95% confidence interval [CI] = 1.57 to 4.81); being younger
(OR = .89, CI = .82 to .97); working full-time (OR = 1.79, CI = 1.02 to 3.14);
having been laid-off (OR = .28, CI = .14 to .57); being single (OR = .50, CI = .30
to .84); believing education is important (OR = 2.00, CI = 1.56 to 2.58); and
credits earned (OR = 1.37, CI = 1.10 to 1.72). Table 2 presents the results from
the logistic regression model.
Table 2. Logistic Regression Analysis for Variables
Predicting Intention to Reenroll
95% C.I. for OR
Variable
B
S.E.
OR
Lower
Upper
Minority
1.01***
0.29
2.75
1.57
4.81
Gender
0.01
0.24
1.1
0.69
1.76
–0.12**
0.04
0.89
0.82
0.97
0.58*
0.29
1.79
1.02
3.14
1.26***
Age
Full-time
0.36
0.28
0.14
0.57
Income
–0.18
0.11
0.83
0.68
1.03
Finance
0.03
0.12
1.03
0.81
1.31
Time
0.11
0.11
1.12
0.9
1.4
–0.69**
Layoff
0.26
0.5
0.3
0.84
Child
0.0
0.12
0.99
0.79
1.26
Important
0.69***
0.12
2
1.56
2.58
0.17
0.93
0.67
1.3
0.11
1.37
1.1
1.72
0.11
0.82
Partnered
Success
Credits
Constant
–0.07
0.32**
–0.20
Notes: c2 (13, N = 443) = 119.34; p < .001.
*p < .05; **p < .01; ***p < .001.
Intention: No = 0.
Minority: Majority = 0.
Gender: Female = 0.
Layoff: No = 0.
Partnered: No = 0.
Full-time: No = 0.
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DISCUSSION
In our study, minorities are more likely to state the intention to reenroll than
are majority group members. This finding conflicts with conclusions from
previous research (DesJardins et al., 2006; Johnson, 2006; Woosley et al., 2005).
Kimmel and McNeese (2006) have noted that minority students express more
motivations and commitments to learning. That may provide some explanation
for our findings. Regardless of what may be driving minority stopouts’ intentions
to reenroll, minorities are attending college in record numbers. The percentage of
minority students in higher education is now more than 32% and growing (U.S.
Department of Education, 2008).
Even among 25 to 34 year olds, younger individuals are more likely to intend
to reenroll in college. As the models of student retention predict, maturity may
imply more family responsibilities and job constraints (Bean & Metzner, 1985).
Likewise, from an economic perspective, students approaching middle age
may believe that lifetime payoffs from education are outweighed by the costs
(Becker, 1964).
Counter to our hypothesis, full-time workers were more likely to intend to
reenroll. Pressures from jobs to improve knowledge, skills, and abilities may
be motivating full-time workers to return to school. Not surprisingly, workers
experiencing a recent layoff were more likely to intend to reenroll in school.
This trend has been identified nationally, but may have been amplified in a sample
of young adults residing in the state with the highest unemployment rate in
the nation at the time of the study. As found by most previous research, former
students who are single are more likely to state an intention to reenroll. Supporting
the importance of Tinto’s (1993) concept of goal commitment, respondents who
believe education is important are more likely to intend to reenroll. Previous
credits earned, a measure of academic integration and an input into an economic
costs-benefits analysis, also predict reenrollment.
Other hypotheses, based on relatively robust previous findings, failed to be
supported, including those predicting negative effects from time constraints,
financial constraints, lower incomes, number of children, and previous success in
college. These factors did not differentiate stopouts who intended to reenroll
from those who did not. Finances, time constraints, and academic success may
have been significant determinants of stopout behaviors in studies of populations
other than young adults, but our research indicates these factors do not predict
differences between the intentions of stopouts and stayouts.
Some previous research has indicated significant interactions. We included
interaction terms for gender with marital status and children and minority
status with gender, income, and financial difficulties in early runs of the
model, but these were not significant predictors of intentions to reenroll. They
also worsened the fit of the model to the data, and they were not included in the
final analysis.
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Policy Implications
QA: Need Ref
The United States has lost its position as the country with the highest percentage of young adults with college attainment. It has fallen from first to
twelfth, and the administration in Washington continues to urge Americans
to seek more education (de Vise, 2010). Job prospects, including better pay
and benefits, are connected to postsecondary educational attainment, and those
benefits open the door to additional training and access to technology (Carnevale,
Smith, & Strohl, 2010).
Our research has identified traits of young adults who want to return to
college and complete postsecondary education. This identification has important
implications for recruitment. As an estimate of the size of the population of
former students who might reenroll, Grimes and Antworth (1993) report that
57% of those who withdrew from one community college intended to reenroll
at the same college. Bonham and Luckie (1993) report a higher percentage, with
more than 70% indicating intentions to return.
Younger adults who have completed more credits toward a degree are more
likely to state the intention to return. They are also more likely to be single and
displaced from a job. Because they agree that college is important for success,
they require less information about the need for education. This frees policymakers and universities to invest in the tools and mechanisms to help connect
college into the lives of these motivated adults.
Young adult learners are more likely to have experienced career changes,
such as layoffs or obsolescence of skill and knowledge sets. More importantly,
this group has experienced college education previously. From this perspective,
they are less naïve about the realities of higher education. They understand
that educational institutions differ significantly in their affordability, academic
requirements, rigors, and social norms. Given these differences, traditional
admissions processes and other campus structures are not the most efficient
mechanism to convert them to enrolled students. First-year freshmen and their
high-school counselors spend considerable effort assembling application data,
thinking about majors, ordering standardized test scores, and providing academic
transcripts. Previously enrolled students may not need these services or may
need modified versions of these services.
In general, stopouts do not have similar infrastructures to assist them with
their unique needs. Among recommendations to support returning adult learners
would be to develop resources and tools for this subpopulation, such as one-stop
centers that provide support for administrative tasks to expedite the return to
college. In addition, these adult learners need assistance to reintegrate into the
college mindset, through seminars or orientation programs that include updating
technology skills, time management practices, goal setting, and study habits.
Service programs, such as those already established for veterans, might serve as
models for young adult students returning to college.
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361
Specifically, laid-off workers must deal with the fact that many educational
programs take longer than the time required to find a new job. This group, as
well as full-time workers, would benefit from online classes and flexible class
schedules in order to reduce time to complete degree requirements while providing
outcomes that provide easy transition either back into the workplace or career
advancements. As community colleges and trade schools have shown, the needs
of these groups might be better served by emphasis on targeted certificate programs, rather than 2- or 4-year degrees.
Similarly, Wilson (2007) argues that minority students are more successful
if there is adequate social support and networking specifically established for
that population. Single and laid-off workers should benefit from similar programs
as they reintegrate into the educational environment.
These same subgroups are market segments for targeted advertising and
outreach. In particular, targeting minorities, full-time workers, recently laid-off
workers, and those who have significant numbers of credits would be efficient and
costs effective.
Limitations and Suggestions for Future Research
QA: Need Ref
Among limitations of our research, we examined stopouts and stayouts in
one metropolitan area. Admittedly, our findings may not be generalizable to other
areas of the country. At the time of this study, the Detroit metropolitan area
was experiencing serious economic pain. We cannot estimate how these high
unemployment rates and multiple plant closures may have influenced the results.
Furthermore, although the study was specifically directed toward identifying
stopouts and their intentions, the sponsoring agencies required information that
increased the length of the instrument and limited the number of items per
construct. Assumedly, more observed items for each latent construct would
have created stronger scales.
As pointed out before, explaining reenrollment in higher education is represented by a relatively small stream of research. Work in this area (e.g., Horn, 1998;
Johnson, 2006; Stratton et al., 2008; Woosley, 2004; Woosley et al., 2005) has
provided the groundwork for future research of reenrollment as separate and
distinct from withdrawal and persistence behaviors. We recommend a redirection
of studies toward research for which the study of stopouts is the main objective.
We also recommend further research attempting to replicate or refute findings
from this study that contradicted or do not confirm previous research findings
(i.e., minority status, income, and gender).
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