PERSISTENCE IN POSTSECONDARY EDUCATION
Postsecondary Education Persistence of Adolescents with Specific Learning Disabilities or
Emotional-Behavior Disorders
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Abstract
While experiences of students with disabilities transitioning from high school to college have
been well documented, the influence exerted by selected factors on these experiences is less well
understood. Using data from the Education Longitudinal Study of 2002, the influence of selected
risk and resilience factors on the short-term postsecondary educational outcomes, i.e., persistence,
of adolescents with specific learning disabilities or emotional-behavior disorders was examined.
A logistic model revealed group differences between individuals with disabilities and peers
without disabilities. All selected risk and resilience factors significantly predicted educational
persistence. No significant differences were observed between adolescents with specific learning
disabilities or emotional-behavior disorders, but three factors—grade point average,
socioeconomic status, and number of friends having plans to attend a 4-year college—were
significant predictors of educational persistence for adolescents with disabilities. Implications of
these findings are discussed.
Keywords: postsecondary educational outcomes, risk and resilience framework, highincidence disabilities
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Postsecondary Education Persistence of Adolescents with Specific Learning Disabilities or
Emotional-Behavior Disorders
An increasing number of adolescents with disabilities have pursued postsecondary education
in recent years (Getzel, 2008; Newman, Wagner, Cameto, & Knokey, 2009). However,
individuals with specific learning disabilities or emotional-behavior disorders enroll in college
and postsecondary training at rates far below those of the general population without disabilities
(Wagner, Newman, Cameto, Garza, & Levine, 2005). Moreover, students with disabilities are
less likely to maintain full-time status resulting in longer periods needed to complete a degree
(Wessel, Jones, Markle, & Westfall, 2009), and more likely to drop out of postsecondary
education (Murray, Goldstein, Nourse, & Edgar, 2000). Although a few comprehensive studies
have been conducted on the transition of adolescents with disabilities from school to
postsecondary education and work (e.g., Blackorby & Wagner, 1996; Newman et al., 2009;
Wagner et al., 2005), relatively little is known about how risk and resilience factors contribute to
the persistence of students with disabilities in postsecondary education.
Our study focused on adolescents with specific learning disabilities or emotional-behavior
disorders because of the many similarities these adolescents share, including overlap among the
impact of disability on academic performance, work preparation, and career attainment (Dietz &
Montague, 2006; Kaplan, Dewey, Crawford, & Wilson, 2001; Hallahan, Kauffman, & Pullen,
2012). Even so, Sabornie (Sabornie, Cullinan, Osborne, & Brock, 2005; Sabornie, Evans, &
Cullinan, 2006) identified important differences in the cognitive and behavioral characteristics of
these groups. For example, adolescents with specific learning disabilities exhibit higher cognitive
abilities and higher academic achievement. Adolescents with emotional-behavioral disorders
were more likely to face arrest, incarceration, or probation-parole violation (Newman et al.,
PERSISTENCE IN POSTSECONDARY EDUCATION
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2009).
The decision to examine adolescents with these disabilities in the same analysis was based
on the similarity in characteristics and the common challenges faced as they prepare for and
transition from school to postsecondary education and work (Gregg, 2009). Examining how
adolescents with disabilities experience and cope with academic- and career-related issues can
facilitate a better understanding of how career theories and interventions might be used to
explain and promote career behavior, choice, and attainment for these individuals.
Persistence in Postsecondary Education
Postsecondary education plays a significant role for individuals with disabilities aspiring to
career opportunities that cannot be attained with a high school degree (Lindstrom, Doren, &
Miesch, 2011). Employment projections in the United States provide compelling evidence on the
increasing importance of postsecondary education. Occupations requiring at least some type of
postsecondary education for entry are expected to grow at quicker rates than other aspects of the
workforce, while occupations requiring a high school degree or less will grow more slow
(Lockard & Wolf, 2012). While a majority of jobs held by individuals with disabilities are
semiskilled and part-time (Barkley, 2006), individuals with disabilities who earn postsecondary
degrees show comparable work outcomes (e.g., employment status, benefits, income) to
individuals without disabilities (Madaus, 2006).
One positive indicator used to represent success in pursuing a postsecondary education
degree is the concept of persistence. Berger and Lyon (2005) defined persistence as “the desire
and action of a student to stay within the system of higher education” (p. 7). Students are more
likely to enroll and persist in their degree program when engaged in the institution both
academically and socially. Much of the work on persistence of students in postsecondary
PERSISTENCE IN POSTSECONDARY EDUCATION
education has focused on individual and college factors (Tinto, 1987, 1992). Mamiseishvili and
Koch (2011) found that women and African American college students were more likely than
men and White students to persist. Students who held positive outcome expectations about
attaining a higher degree were also more likely to persist.
Seo, Abbott, and Hawkins (2008) reported that adolescents with learning disabilities had
significantly lower postsecondary school enrollments at age 21 than those without disabilities.
Adolescents with disabilities from middle or high socioeconomic status (SES) families had
higher postsecondary education enrollments than those with disabilities from low SES families
(Wagner et al., 2005). Kortering, Braziel, and McClannon (2010) reported that students with
learning disabilities were more likely to have lower educational and occupational aspirations
than those without disabilities. Factors influencing these lowered rates of enrollment and
persistence of students with disabilities in college are not clear.
Conceptual Considerations for Risk and Resilience Factors
Use of a risk-resilience framework offers researchers a balanced approach to understanding
the outcomes of individuals with disabilities by stressing individual strengths and limitations,
rather than an emphasis on limitations imposed by the presence of disability. Risk factors
increase the likelihood that barriers or constraints exist that limit individual plans or activity,
while resilience factors are those processes that reduce the risk or increase the probability of
successful outcomes (Gregg, 2009; Murray, 2003). The presence of disability increases the
possibility that adolescents will experience risk (Morrison & Cosden, 1997), while the nature of
disability presents both common and unique career needs, experiences, and potential, as well as
susceptibility to career-related risks. Career-related barriers associated with disability include
social stigma, employment discrimination, inadequate vocational training and preparation, poor
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self-efficacy, and lower or restricted occupational aspirations (Fabian & Liesener, 2005).
Resilience factors can be divided into internal and external influences. Internal resilience
factors include positive temperament, recognition of one’s disability, accommodation strategies,
and knowledge of ways to be proactive and advocate for one’s self (Gregg, 2009; Murray, 2003).
Disability identity may have a bearing on the career behavior of adolescents with disabilities by
decreasing engagement with others (Mpofu & Harley, 2006). Other internal factors pertinent to
educational persistence include an individual’s educational expectations and academic
achievement (Murray, 2003). Family factors such as SES, family composition, parent-child
discussions about work and education, and parents' educational expectations may also influence
educational persistence.
External resilience factors support individuals in their education- and work-related decisionmaking. The presence of a supportive adult appears to be one of the strongest resilience factors
for individuals with learning disabilities (Goldberg, Higgins, Raskind, & Herman, 2003).
Connections to supportive and helpful people (Reiff, Gerber, & Ginsberg, 1997), sustained
emotional support from parents (Cosden, Brown, & Elliott, 2002), and positive parent-child
interactions (Wong, 2003) also appear related to the potential of success for individuals with
disabilities. It is critical that high school students with disabilities are knowledgeable of the
Americans with Disabilities Act, realities of the workplace, and importance of self-determination
(Madaus, Gerber, & Price, 2008). Outcomes for individuals with learning disabilities “reflect a
combination of protective and risk factors, some of which are internal, whereas others are
external to the individual” (Morrison & Cosden, 1997, p. 56).
Since risk and resilience factors may influence the career behavior and postsecondary
educational outcomes of adolescents with specific learning disabilities or emotional-behavior
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disorders, our understanding incorporated the work of both career theorists (e.g., Lent, Brown, &
Hackett, 1994) and disability researchers (e.g., Murray, 2003; Wong, 2003). Another aspect to
consider was the issue of outcomes. The unique interplay of risk and reliance factors will result
in widely varied outcomes ranging from successful employment or unemployment, enrollment in
a postsecondary academic or vocational programs, dropping out of school or successful
completion of a postsecondary degree, job difficulties, job (dis)satisfaction, and life
(dis)satisfaction (Barkley, 2006; Reiff, Gerber, & Ginsberg, 1997). The question of how to
incorporate risk-resilience factors to understand the persistence of young people with specific
learning disabilities or emotional-behavior disorders in postsecondary education deserves
attention.
Purpose
Our analysis examined the influence of selected risk-resilience factors on college persistence
for adolescents with (or without) specific learning disabilities or emotional-behavior disorders.
The outcome, persistence, was a conceptualized as a dichotomous variable based on the pursuit
or lack of pursuit of postsecondary education measured two years after high school completion.
Educational persisters included those individuals who (a) had successfully completed or were
enrolled in a two-year postsecondary education institution (e.g., technical education, community
college) or (b) were enrolled in a four-year postsecondary education program at the time of data
collection. Educational persisters were compared to a second group who (a) had never enrolled
in postsecondary education or (b) had enrolled in a two- or four-year program but left before
completion. Two research questions guided the analysis: (a) Do differences exist in short-term
postsecondary educational outcomes between students with learning disabilities or behavior
disorders, and individuals without disabilities? (b) What risk-resilience factors influenced short-
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term postsecondary educational outcomes for groups with or without disabilities?
Method
Educational Longitudinal Study of 2002 (ELS:2002)
Data from the Education Longitudinal Study of 2002 (ELS:2002), administered by the
National Center for Education Statistics, was selected because of its focus on the transition of
adolescents from high school to postsecondary education and work. The ELS:2002 contains a
base-year sample comprised of 15,362 10th-graders drawn from 752 public and private school
during the 2001-2002 school year. Subsequent administrations were conducted in 2004 and 2006.
Our analysis included data from the first and second follow-up surveys as we focused on the
transition period from 12th grade through two years after high school (Ingels et al., 2007). The
initial sample was 10,760 and included 9,990 adolescents without disabilities (92.84%) and 770
adolescents with either specific learning disabilities or emotional-behavior disorders (7.16%).
Identification of Students with Disabilities
We used two methods to identify individuals with specific learning disabilities or emotionalbehavior disorders. The first method examined students’ base year status (grade 10) on two
variables, provision of Special Education services through an Individualized Education Program
(IEP) and indication of diagnosed disability using school transcript data. Drawing on previous
studies (Hodapp & Krasner, 1994-1995; Reschly & Christenson, 2006), we also used a base-year
question that asked parents about the presence and type of disability for their child. Transcript
data identified students who received school credit in one or more of three types of special
education-related coursework, including general special education (F1R54_C), special
education-vocational (F1R55_C), and special education-resource curriculum (F1R56_C). We
excluded students with other types of disabilities and those with multiple disabilities from our
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analysis. This approach was used in prior studies of NELS:88 data (Hodapp & Krasner, 19941995; Ingels & Scott, 1993).
The final sample included all individuals without disabilities who participated in all three
data collection points (n=9,990) and individuals who met established disability criteria in the
base year and participated in all three data collection points, including 670 (6.23%) participants
who reported a learning disability and received one or more disability-related services, and 100
(0.93%) reporting an emotional-behavioral disorder and receiving at least one disability-related
service. The nondisabled group did not include other types of students with disabilities. Our
sample compared favorably to percentages of students with specific learning disabilities and
emotional-behavior disorder who received federally supported programs in 2002 and 2003 (5.9%
and 1.0%, respectively; Snyder & Dillow, 2012). Over one-half of non-disabled adolescents were
women (52.4%), while only 37.2% of the disability group was women (see Table 1).
[Insert Table 1 about here]
Measures
Persistence in postsecondary education was constructed from second follow-up data using
both postsecondary enrollment and completion status. Public high school graduates in 2004 who
either enrolled in a postsecondary institution or completed a degree (or certificate) by 2006 were
classified as persistent in postsecondary education, whereas those who had never enrolled or had
enrolled and dropped out of postsecondary education were classified as not persistent.
Individual risk-resilience factors included gender, occupational aspirations in grade 12,
educational expectations in grade 12, and academic achievement scores including high school
grade point average (GPA; M=2.667), reading achievement (M=50.661), and math achievement
(M=49.723). Gender was coded “0” for adolescent men and “1” for adolescent women.
PERSISTENCE IN POSTSECONDARY EDUCATION
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Educational expectations were assigned the following values: less than college graduate=0, more
than college graduate=1, uncertain/don’t know=2. Occupational aspirations were grouped
according to level of job status: high prestige=0, medium prestige=1, and low prestige=2, and
uncertain/don’t know=3. High school GPA was used to reflect participants’ general academic
achievement (Bozick et al., 2006).
Family risk-resilience factors were represented by SES, family composition (0=others,
1=two parents), parental communication about college attendance, and parents’ educational
expectations. A standardized SES composite indicator (M= .00) was constructed by ELS:2002
researchers using five variables, including father’s and mother’s education, father’s and mother’s
occupations, and family income (Bozick et al., 2006). Parental communication was measured
with items asking how often respondents discussed going to college with their parents (never=0,
sometimes=1, often=2). Parental educational expectation for their children was conceptualized as
a dichotomous variable, either less than a 4-year college degree or 4-year college degree or more.
School and peer risk-resilience factors were represented by the number of friends who had
dropped out of high school and the number of friends planning to attend a four-year college.
Both variables consist of four options including none=0, a few=1, some=2, and most/all=3.
Community risk-resilience factor was measured using one item that asked respondents how
often they performed community service. The variable consisted of four options; none=0, less
than once a week=1, once a twice a week=2, and (almost) every day=3.
Control variables were used to describe the sample and included English as native language
and race/ethnicity. English as a native language was coded 0 for other than use of English and 1
for use of English. Race/ethnicity was coded 0 for White; 1 for Asian; 2 for Black; 3 for
Hispanic, no race specified; 4 for Hispanic, race specified; 5 for more than one race; and 6 for
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Native American. Additional information on variables is found in Appendix.
Data Analyses
To investigate any existing differences in college persistence among students with learning
disabilities, emotional-behavior disorders, and students without disabilities, we used a logistic
regression model using a forced entry approach, which is generally employed for modeling the
probability of an occurrence of an event through the use of associated covariates. The model can
be written as
logit Pr(𝑦𝑖𝑗 = 1| 𝐗 𝑖𝑗 ) = 𝛽0 + 𝐗 ′𝑖𝑗 𝛽, i = 1,…,C; j = 1,…,ni
𝑝
logit 𝑝 = log 1−𝑝
(1)
(2)
where 𝑦𝑖𝑗 denotes the outcome variable (1=persistent, 0=nonpersistent), C is the number of
clusters (schools), ni is the number of individuals in cluster (school) i, 𝐗 𝑖𝑗 denotes the vector of
covariates, and 𝛽 stands for the effects of covariates. The covariate vector 𝐗 𝑖𝑗 was composed of
variables measured to represent risk-resilience factors and several control variables.
To adjust for school effects we incorporated the cluster (school) effect as a random effect in
the logistic model, and a pseudo maximum likelihood estimation approach was adopted to
estimate model parameters. We generated 20 multiply imputed data sets using a multiple
imputation by the chained equations approach to handle missing values.
Results
Descriptive Results
Table 1 summarizes descriptive statistics from the multiply imputed data sets used for
analysis. Only 6.7% of the sample was composed of individuals with disabilities (87.5% specific
learning disabilities, 12.5% emotional-behavior disorders). Approximately two-thirds of
adolescents with disabilities were not persistent in postsecondary education, almost twice the rate
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of the nondisabled group. There were no observable differences between adolescents in the
learning disabilities or emotional-behavior disorders groups.
The proportion of adolescents with disabilities expressing uncertain occupational aspirations
was 19.0%, while the rate for adolescents without disabilities was 42.1%. In terms of educational
expectations, the proportion of adolescents expecting less than a 4-year college degree was
almost double for adolescents with disabilities (48.9%) compared to the nondisabled group
(23.5%). Corresponding proportions of adolescents with educational expectations for more than
a 4-year college degree were much lower among the group with disabilities (35.0%) than the
group without disabilities (69.1%). The GPA of adolescents with disabilities (M=2.167) was
lower than adolescents without disabilities (M=2.703). The reading achievement scores of
adolescents with disabilities (M=40.841) were lower than adolescents without disabilities
(M=50.661). Math achievement scores of adolescents with disabilities (M=38.44) were also
lower than those without disabilities (M=49.723).
The SES of the nondisabled group was near zero (M=0.002), reflecting the standardized
mean. The group with disabilities showed a significantly negative SES (M=-0.205), indicating
that adolescents with disabilities were from lower SES families. Adolescents with disabilities
indicated that their friends were less likely to go to a 4-year college than students without
disabilities. Although 51.9% of individuals without disabilities indicated that friends planned to
go to college, only 28.7% of individuals with disabilities did so. A large difference existed in the
outcome, persistence in college, between adolescents with disabilities (32.4%) and nondisabled
peers (63.0%).
Comparison by Disability Type
The base model revealed that after holding native language and race/ethnicity constant, the
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persistence of adolescents without disabilities was significantly different from those with
disabilities. The estimated odds ratio for individuals with emotional-behavior disorders and
college persistence was 0.305 (coefficient = -1.185, 95% confidence intervals [CI] for odds ratio
[OR] = 0.156-0.598), whereas the odds ratio estimate for persons with learning disabilities and
college persistence was 0.295 (coefficient = -1.221, 95% CI for OR = 0.239-0.363). Adolescents
with emotional-behavior disorders were approximately 70% [=(1-0.305)×100] less likely to
enroll or persist in college than adolescents without disabilities. Adolescents with learning
disabilities were approximately 71% [=(1-0.295)×100] less likely to enroll or persist in college
than nondisabled peers. Design-adjusted Wald tests determined that disability status was a
significant predictor of college persistence [F(2, 379) =71.68, p <.001].
Risk-Resilience Factors for Persistence in Postsecondary Education
Risk-resilience factors were included in the base model to determine their influence on
college persistence (see Table 2). The Hosmer-Lemeshow Goodness-of-Fit test suggested no
evidence of lack of fit (𝐶̂ =10.87, df=8, p=.21). Estimated coefficients of disability type revealed
that while individuals with emotional-behavior disorders were not statistically different from
peers without disabilities in persistence after holding risks-resilience factors constant, individuals
with learning disabilities experienced a significant deficiency in the odds of persisting when
compared to persons without disabilities (coefficient=-0.300, OR=0.741, 95% CI for OR=0.5740.956). The odds of not persisting were 25.9% higher for adolescents with learning disabilities
than for peers without disabilities when controlling for other covariates. Educational expectations,
high school GPA, and math achievement showed positive effects on persistence. Individuals who
expected to attain more than a college degree had almost two times greater odds (coefficient
=0.708, OR =2.029, 95% CI for OR=1.735-2.373) of persisting in college than those expecting
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less than a college degree. The odds ratio for high school GPA was 2.346 (95% CI for
OR=2.107-2.613), meaning that adolescents with higher high school GPAs were more likely to
persist in postsecondary education. Adolescents with higher math achievement scores were also
more likely to persist in postsecondary education (coefficient=.024, OR=1.024, 95% CI for
OR=1.014-1.036).
Unlike individual factors, all, as opposed to some, family factors proved to be important for
college persistence. SES was significantly favorable to persistence (coefficient=0.514, OR=1.672,
95% CI for OR=1.515-1.845), individuals with higher family SES were more likely to persist in
college than their peers with low SES (see “All Participants v Disabilities model” in Table 2).
The group of adolescents indicating two-parent family composition had an odds ratio of 1.166
(coefficient=0.154, 95% CI for OR=1.033-1.317), indicating that adolescents who live with both
parents were 17% more likely to persist in postsecondary education than their peers who lived
with a single parent. Compared with those who had never discussed college with a parent, those
who had discussed college with a parent were more likely to be involved and persist in college
(sometimes: coefficient=0.330, OR=1.391, 95% CI=1.018=1.901; often: coefficient =0.757, odds
ratio =2.132, 95% CI=1.594-2.853). In other words, the more often parents and children
discussed college, the more likely children were to be enrolled and persistent in postsecondary
education. Similarly, parents’ educational expectations were also important. Compared to the
less-than-college group, the higher expectation group was 25% more likely to persist in
postsecondary education (coefficient=0.223, 95% CI for OR=1.040-1.503).
[Insert Table 2 about here]
School-peer and community factors had significant impact on college persistence,
specifically pertaining to adolescents who had observed friends dropping out of school.
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Compared to those who did not have any friends dropping out of school, individuals with some
friends dropping out of school (coefficient = -0.410, OR=0.664, CI for OR=0.542-0,813) were
less likely to be persistent in postsecondary education. Although degraded persistence levels of
the few and most/all friends had dropped out groups seem insignificant, the negative effects of
experiencing friends leaving high school cannot be disregarded. More important, the designadjusted Wald test demonstrated that the parameters associated with the student drop out factor
were significantly different from zero, suggesting that the peer factor was an important predictor
of college persistence. Friends’ plans for attending a four-year college also proved to be
important. All estimates were positive at all levels with the none group as a reference group,
which suggests that friends’ plans for college were likely to be corollary to persistence. In
particular, the most/all friends going to college group was more likely to persist in postsecondary
education than the none of friends going to college group (coefficient=0.413,OR=1.511, 95% CI
for OR=1.154-1.980). Moreover, significant results of the design-adjusted Wald test suggest that
the peer factor was an important predictor. Students who participated in community service less
than once a week during high school were more likely to persist in postsecondary education than
peers who did not serve. The design-adjusted Wald test indicated that the parameters associated
with community service were significantly different from zero.
Influential Risk-Resilience Factors for Persistence of Individuals with Disabilities
Since no statistically significant differences in persistence existed between disability types,
this factor was disregarded while fitting the logistic regression model. Table 2 (disabilities model)
depicts the logistic regression model applied only to individuals with disabilities (𝐶̂ =8.92, df=8,
p=.34). High school GPA (OR=1.772, 95% CI for OR=1.241-2.529), and SES (OR=2.465, 95%
CI for OR=1.685-3.605) were of particular importance for understanding the persistence
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dynamic. Adolescents with higher GPAs and higher SES families were more likely to persist in
college than peers with lower GPAs and lower SES families.
Friends’ plans for college also favorably affected persistence (coefficient =0.837, OR=2.309,
95% CI=1.104-4.831). The few friends going to college group was more likely to persist than the
none of friends going to college group. However, the design-adjusted Wald test suggested that a
friend’s plans for college might not be a significant predictor of college persistence when
controlling for the associations between other variables with college persistence.
Discussion
This study investigated the usefulness of selected factors in explaining educational
outcomes for young adults with and without disabilities. When the model containing all
participants regardless of disability status was examined, all risk-resilience covariates, except for
occupational aspirations and reading achievement, were significantly associated with the
likelihood of persisting in postsecondary education. However, only a few variables—high school
GPA, SES, and peers’ plans to attend a 4-year college—were significantly associated with the
model of college persistence when only examining students with disabilities. This result
indicated an important and noteworthy difference for adolescents with disabilities. It is possible
that these three salient factors contribute more meaningfully to the college persistence of
students with disabilities compared with students without disabilities. In this section, we discuss
how these risk-resilience factors contribute to an understanding of postsecondary education
persistence of adolescents with specific learning disabilities or emotional-behavior disorders, and
we provide limitations of the study and implications for practice and future research.
Impact of Risk-Resilience Factors on Educational Persistence
Influence of disability status. Results of our base model (control variables only) supported
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previous research findings on the association between disability status and college persistence
(e.g., DaDeppo, 2009; Murray et al., 2000; Wagner et al., 2005). The adolescents with
disabilities in our analysis persisted in postsecondary education at lower rates than students
without disabilities. Disability status is an important, albeit indirect, risk factor in explaining
college persistence. The presence of a disability may pose barriers because of self-perceptions.
Students might experience failure in academics based on their disability status, perceived
disability-related failure, or overly positive self-perception; the disability label itself, implying a
difficulty in learning or actual difficulty with learning, contributes to a lowered chance of
enrolling in or completing postsecondary programs or of not receiving the academic or emotional
support necessary to be successful in a competitive academic environment (Cosden &
McNamara, 1997; Heath, Roberts, & Toste, 2011; May & Stone, 2010).
Influence of high school GPA. Among individual risk-resilience factors, students with higher
GPAs were more likely to persist in postsecondary education. Although the importance of
academic achievement for success in postsecondary education for students with disabilities has
been downplayed (e.g., DaDeppo, 2009), our results reflect its importance, and these outcomes
coincide with studies that have demonstrated the consistent (and primary) role of academic
achievement in postsecondary education (e.g., Bozick et al., 2006; Mamiseishvili & Koch, 2011).
The importance of the high school GPA on college persistence can be further supported by the
Social Cognitive Career Theory persistence model, highlighting a significant indirect effect of
high school GPAs on college persistence via academic self-efficacy and goals (Brown et al.,
2008).
Role of occupational aspirations. The uncertainty in occupational aspirations expressed by
adolescents with disabilities was considerably less than the uncertainty of adolescents without
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disabilities. Despite this difference, occupational aspirations did not help explain college
persistence, suggesting that persistence is more sensitive to shorter-term anticipation or
experience than by perceived longer-term benefits or goals. In contrast, research on short-term
work outcomes and work-bound adolescents with disabilities revealed that occupational
aspirations significantly predicted the number of hours worked per week for work-bound
adolescents with specific learning disabilities or emotional-behavior disorders (Rojewski, Lee, &
Gregg, in press). It is likely that educational expectations and attainment may play significant
roles as mediators of occupational aspirations (i.e., indirect influence of occupational aspirations
on college persistence through educational expectations) in understanding our results because
persistence and attainment in postsecondary education are considered to be more important
short-term goals for college-bound adolescents with disabilities, compared to work-bound
adolescents with disabilities.
Influence of SES. One of the most consistent findings on college persistence is the pervasive
influence of SES. A recent study by Chen and St. John (2011) found that individuals from high
SES families have 55% higher odds of persisting in college than adolescents from low SES
families. Similar to past studies, in our analysis, SES played an important role in the persistence
of students with disabilities. It is important to note that although all family risk-resilience factors
were significantly associated with the college persistence of nondisabled adolescents, only SES
was significantly associated with persistence for adolescents with disabilities. This finding
suggests that SES-related differences in parenting or opportunities to access academic resources
may contribute to college persistence.
Peer influence on college persistence. The literature provides limited information about the
influence of high school friends or peers on postsecondary education outcomes. However, the
PERSISTENCE IN POSTSECONDARY EDUCATION
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importance of social networking and support influences social resources available to individuals
in learning situations (Scott, 2000). In our study, only one social factor, friends’ plans to attend
college, had a significant association with college persistence for adolescents with disabilities.
Although the model containing all participants showed that students with most or all of their
friends planning to attend a four-year college were more likely to persist in postsecondary
education than were students with few friends planning to attend, results of the logistic model for
disabilities showed that even a few friends planning to attend college contributed to a greater
persistence for adolescents with disabilities. These findings suggest that students with specific
learning disabilities or emotional-behavior disorders are more likely to be influenced by a few
close friends, who may provide them with the academic or emotional support necessary for
college persistence, than those without disabilities. However, caution is warranted in interpreting
this finding because of a statistically insignificant result of the design-adjusted Wald test.
Limitations of the Study
This study contains several limitations. Although the ELS:2002 database provided an
excellent opportunity to examine our research questions, it is not specifically designed to
examine disability issues. Fortunately, unlike previous national longitudinal databases, e.g.,
NELS:88, in which some students with disabilities were excluded from the base year sampling,
this was not the case with the ELS:2002 sampling scheme (Ingels et al., 2007). Even so, reliance
on a school-based diagnosis to identify students with disabilities likely resulted in our sample
being less homogeneous than might have been expected. Therefore, we exercised caution in
identifying individuals with disabilities, and relied on several different criteria depending on
availability.
Our study was delimited by the time between high school completion and two years after
PERSISTENCE IN POSTSECONDARY EDUCATION
20
high school graduation. Since students with disabilities are both less likely to go on to
postsecondary education and, when they do, are more likely to make a delayed entry into higher
education, the two-year window for studying persistence in postsecondary education provides a
limited, albeit important, picture of persistence behaviors in postsecondary education. This
delimitation can be addressed in the near future with the scheduled release of the ELS:2002 third
follow-up data in 2014. This data will provide information on outcomes eight years after high
school. Although a full understanding of the transition process requires longer periods of
assessment, it is important to acknowledge and understand this shorter period of time, especially
as many adolescents, regardless of disability status, experience prolonged periods of floundering
in the first few years after high school (Blackorby & Wagner, 1996). Because our results apply
only to individuals with disabilities graduating on time with same-age peers, our results could be
strengthened by future studies that analyze students who fall behind the modal sequence in high
school.
Implications for Practice and Future Research
It is important for parents, school teachers, and counselors to continuously interact and
engage with adolescents with specific learning disabilities or emotional-behavior disorders by
recognizing that these factors are important indicators of short-term postsecondary education
outcomes. In particular, existing school programs may strengthen the relationship with parents to
encourage their involvement at home in helping, motivating, and encouraging students to
succeed academically (e.g., McDonnall, Cavenaugh, & Giesen, 2012) and to provide relevant
resources and information for students, especially from low SES families, to moderate the
influence of SES. Moreover, school teachers can develop peer mentoring programs to support
peer interactions that may influence students’ study strategies or short-term postsecondary plans
PERSISTENCE IN POSTSECONDARY EDUCATION
21
and outcomes. Future study is needed to examine how policy-related strategies or interventions
(e.g., federal Pell Grants) may reduce the effect of SES on educational persistence for
adolescents with disabilities and how school-parent partnerships and peer mentoring programs
can increase students’ academic achievement and postsecondary outcomes.
Future research may take several directions. First, it may prove worthwhile to examine the
combined influence of the 16 in-school predictors identified by Test et al. (2009), along with the
risk-resilience factors we examined in this study on college persistence of other disability types
using the either the National Longitudinal Transition Study-2 (NLTS-2) or ELS:2002 database.
A second avenue for research may be to incorporate aspects of Tinto's (1987, 1992) theory of
students’ departure/persistence, developed for students without disabilities, to students with
specific learning disabilities or emotional-behavior disorders. To date, a specific application of
this theory to adolescents with disabilities is lacking. It is possible that all or part of Tinto’s work
may transfer to adolescents with disabilities and help to explain why students with disabilities do
or do not persist in postsecondary education environments. Third, the mediation effect of
interactions between individuals’ attitudes and institutional experience, along with indirect
influences of risk-resilience factors on college persistence via academic self-efficacy and goals
for youths with disabilities, is worth pursuing.
Finally, we should not disregard the contribution of non-significant risk-resilience factors on
college persistence. Indeed, risk-resilience variable coefficients in the disabled group model were
higher than those for the nondisabled group model. We speculate that a relatively high number of
variations might explain the lack of significance for most factors in the disabled group model.
Future studies using relatively homogenous data such as NLTS-2 are necessary to determine
whether other risk-resilience factors may contribute to college persistence.
PERSISTENCE IN POSTSECONDARY EDUCATION
22
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Table 1.
Multiply Imputed Descriptive Data of Sample Used to Investigate Postsecondary Education Outcomes of Young
Adults with High-Incidence Disabilities
Disability
(n=770)
Estimated
SE
proportion
Variable
Individual factors
Disability type
Genderc
Occupational aspirations
High
Medium
Low
Uncertain/Don’t know
Educational expectations
Less than a 4-year college degree
More than a 4-year college graduate
Don’t know
GPAd
Reading achievementd
Math achievementd
Family factors
SESd
Family compositione
Parent discussion: college
Never
Sometimes
Often
Parents’ educational expectationsf
School and peer factors
Friends dropped out
None
A few
Some
Most/All
Friends’ plan to go to 4-yr college
None
A few
Some
Most/All
Community factors
Community service
None
Less than once a week
Once or twice a week
(Almost) Every day
Control variables
Native languageg
Race
Asian
Black
Hispanic, no race specified
Hispanic, race specified
More than one race
American Indian
White
Outcome variable
Persistence in collegeh
a
f
b
No disability
(n=9,990)
Estimated
SE
proportion
All participants
(n=10,760)
Estimated
SE
proportion
0.875a
0.372
0.018
0.021
—
0.524
—
0.006
0.067b
0.514
0.003
0.006
0.378
0.232
0.200
0.190
0.024
0.020
0.020
0.017
0.285
0.118
0.176
0.421
0.006
0.004
0.005
0.007
0.291
0.125
0.178
0.406
0.006
0.004
0.005
0.006
0.489
0.350
0.161
2.167
40.841
38.438
0.022
0.021
0.017
0.032
0.402
0.389
0.235
0.691
0.074
2.703
51.365
50.531
0.006
0.007
0.004
0.016
0.189
0.198
0.252
0.668
0.079
2.667
50.661
49.723
0.006
0.007
0.004
0.016
0.187
0.195
-0.205
0.500
0.034
0.023
0.002
0.585
0.015
0.007
-0.011
0.580
0.015
0.007
0.155
0.362
0.483
0.646
0.018
0.022
0.023
0.022
0.048
0.264
0.688
0.892
0.003
0.006
0.007
0.004
0.055
0.271
0.674
0.876
0.003
0.006
0.007
0.005
0.427
0.400
0.121
0.052
0.021
0.021
0.015
0.010
0.519
0.363
0.085
0.032
0.008
0.007
0.004
0.002
0.513
0.366
0.087
0.034
0.008
0.007
0.003
0.002
0.199
0.230
0.283
0.287
0.020
0.020
0.021
0.022
0.059
0.171
0.250
0.519
0.003
0.005
0.006
0.008
0.069
0.175
0.252
0.504
0.003
0.005
0.006
0.008
0.705
0.121
0.125
0.049
0.020
0.015
0.015
0.009
0.587
0.227
0.153
0.032
0.007
0.005
0.004
0.002
0.595
0.220
0.151
0.033
0.006
0.005
0.004
0.002
0.880
0.014
0.860
0.006
0.861
0.006
0.017
0.160
0.048
0.094
0.067
0.014
0.600
0.004
0.019
0.009
0.013
0.012
0.005
0.023
0.045
0.142
0.075
0.085
0.041
0.009
0.602
0.003
0.007
0.006
0.006
0.003
0.002
0.011
0.044
0.143
0.073
0.086
0.043
0.010
0.602
0.003
0.007
0.006
0.006
0.003
0.002
0.011
0.324
0.021
0.630
0.008
0.610
c
d
0.008
e
Behavioral disorders is reference. Non-high-incidence disabilities is reference. Male is reference. Indicates mean scores. Other is reference.
Less than college is reference. gOther than use of English is reference. hNon-persistence in college is reference.
Note. Hispanic, race specified means that specific ethnicity such as Mexican, Puerto Rican, Central American, South American, etc was identified.
PERSISTENCE IN POSTSECONDARY EDUCATION
29
Table 2.
Logistic Regression Models for Risk-Resilience Factors Predicting Postsecondary Work Outcome
Variable
Individual factors
Disability typea
Behavioral disorders
Learning disabilities
Genderb
Occupational aspirationsc
Medium
Low
Don’t know
Educational expectationsd
More than college graduate
Don’t know
GPA
Reading achievement
Math achievement
Family factors
SES
Family compositione
Parent discussion: collegef
Sometimes
Often
Parents’ educational expectationsg
School and peer factors
Friends dropped outh
A few
Some
Most/All
Friends’ plan to go to 4-yr collegeh
A few
Some
Most/All
Community factors
Community serviceh
Less than once a week
Once or twice a week
(Almost) Every day
Control variables
Native languagei
Race/Ethnicityj
Asian
Black
Hispanic, no race
Hispanic, race
More than one race
American Indian
All Participants
(n=10,760)
Coefficient SE
Odds Ratio
Disabilities
(n=770)
Coefficient SE
Odds Ratio
0.019
-0.300*
0.153*
0.352
0.129
0.069
1.019
0.741
1.165
—
—
0.411
0.234
1.508
0.052
0.130
0.037
0.099
0.091
0.079
1.053
1.139
1.038
-0.095
0.522
-0.099
0.303
0.324
0.330
0.909
1.685
0.906
0.708***
0.052
0.853***
-0.001
.024***
0.079
0.105
0.055
0.005
0.005
2.030
1.053
2.347
0.999
1.024
0.376
0.523
0.572***
-0.006
0.035
0.271
0.313
0.180
0.017
0.021
1.456
1.687
1.772
0.994
1.036
0.514***
0.154*
0.050
0.062
1.672
1.166
0.902***
0.330
0.193
0.220
2.465
1.391
0.330*
0.757***
0.223*
0.158
0.148
0.093
1.391
2.132
1.250
-0.153
0.276
-0.052
0.389
0.361
0.249
0.858
1.318
0.949
-0.125
-0.410***
-0.316
0.065
0.103
0.176
0.882
0.664
0.729
0.113
-0.333
-0.933
0.233
0.372
0.553
1.120
0.717
0.393
0.125
0.168
0.413**
0.136
0.134
0.137
1.133
1.183
1.511
0.837*
0.467
0.549
0.375
0.361
0.370
2.309
1.595
1.732
0.292***
0.133
0.268
0.079
0.095
0.170
1.339
1.142
1.307
-0.143
-0.322
0.563
0.366
0.346
0.491
0.867
0.725
1.756
-0.229*
0.103
0.795
-0.211
0.379
0.810
0.350**
0.230*
0.205
0.074
-0.410**
-0.166
0.135
0.086
0.130
0.130
0.154
0.285
1.419
1.259
1.228
1.077
0.664
0.847
-0.208
0.247
0.484
0.132
-0.020
-0.173
0.765
0.329
0.530
0.424
0.447
1.072
0.812
1.280
1.623
1.141
0.980
0.841
—
—
Note. Adjusted Wald test for all parameters and McFadden’s R2 in All participants model: F(30, 377.7) = 65.49, p <.001 and .269, Adjusted
Wald test for all parameters and McFadden’s R2 in Disabilities model: F(28, 255.6) =3.70, p<.001 and .165.
a
The reference group is nondisabled. bThe reference group is male. cThe reference group is high. dThe reference group is less than college graduate.
The reference group is other. fThe reference group is never. gThe reference group is less than college. hThe reference group is none. iThe
reference group is use of English. jThe reference group is White.
e
*p < .05, **p < .01, ***p < .001
PERSISTENCE IN POSTSECONDARY EDUCATION
30
Appendix
Definition and Measurement of Covariates and Outcomes from ELS:2002 Database
Variable
ELS:2002 variables
Variable labels
Outcome variable
Persistence in college
Individual factors
Gender
Occupational aspirations
Educational expectations
GPA
Reading achievement
Math achievement
F2RTYPE;
F2EDLEVL
F2 respondent type;
Highest level of education attempted
F2SEX
F1OCC30
Sex-composite;
F1 occupation at age 30-coded; The occupation the
respondent expects/plans to have at age 30 was assigned
to one of seventeen categories.
F1 how far in school student thinks will get
GPA for all academic courses, honors weighted
Reading IRT estimated number right
F1 math IRT estimated number right for F1 scores
F1RAGPH
BYTXRIRR
F1TXM1IR
Family factors
SES
Family composition
Parent discussion: college
Parents’ educational expectations
F1SES1R
F1FCOMP
F1S64H
BYPARASP
F1 socio-economic status composite, v.1 (restricted)
F1 Family composition
How often discussed going to college with parents
How far in school parent wants 10th grader to gocomposite
School and peer factors
Friends dropped out
F1S65A
How many friends dropped out of high school
F1S65D
How many friends plan to attend 4-year
college/university
F1S39C
How often performs community services
F1STLANG
F1 whether English is student’s native languagecomposite
F1 student’s race/ethnicity-composite
Friends’ plan to go to 4-yr college
Community factors
Community service
Control variables
Native language
Race
F1RACE
Note. F1 refers to data collected during the first follow-up. F2 refers to data collected during the second follow-up.