Examining Postsecondary Education Predictors and Participation for Students With Learning Disabilities.

572894

research-article2015

LDXXXX10.1177/0022219415572894Journal of Learning DisabilitiesJoshi and Bouck

Article

Examining Postsecondary Education Predictors and Participation for Students With Learning Disabilities

Journal of Learning Disabilities 1–11 © Hammill Institute on Disabilities 2015 Reprints and permissions: sagepub.com/journalsPermissions.nav DOI: 10.1177/0022219415572894 journaloflearningdisabilities.sagepub.com

Gauri S. Joshi, PhD1 and Emily C. Bouck, PhD2

Abstract Given the history of poor postschool outcomes for students with disabilities, researchers repeatedly sought to demonstrate the links between predictor variables and postschool outcomes for students with disabilities. This secondary data analysis used the National Longitudinal Transition Study–2 to examine the relationship between postsecondary education–related transition services and postsecondary education participation for students with learning disabilities. Logistic regression analyses indicated receiving core content area instruction in the general education classroom was positively related to postsecondary education participation. Frequency distributions indicated students with learning disabilities attended 2-year college at higher rates than other postsecondary education programs. The results suggest educators should consider inclusion in general education classroom for core content area instruction for students with learning disabilities with postsecondary education goals to the extent permitted by their least restrictive environment. Keywords transition, postsecondary education, postschool outcomes Postsecondary education—whether 2- or 4-year college or a vocational/technical program—is an important gateway to successful adult life (Fleming & Fairweather, 2012; Shaw & Dukes, 2013; Test, Aspel, & Everson, 2006). Attending and completing any form of postsecondary education assists an individual in obtaining a meaningful and fulfilling vocation as well as securing monetary independence (Shaw & Dukes, 2013). Financial independence, in turn, positively affects other areas of adult life, such as independent living. Individuals who complete postsecondary education tend to be more confident, experience better career opportunities, and demonstrate better problem-solving and interpersonal skills as compared to their peers who did not graduate (Test et al., 2006). Students with disabilities who attend postsecondary education experience benefits like improved career options, greater earning potential, higher job satisfaction, and more secure employment—similar to their peers without disabilities (Fleming & Fairweather, 2012). Despite the benefits associated with participation, historically few students with disabilities attended postsecondary education as compared to their peers without disabilities (Blackorby & Wagner, 1996; Wagner, Newman, Cameto, Garza, & Levine, 2005). The poor rate of participation includes not only the aggregate of students with disabilities but also specific disability populations, including the highincidence population of students with learning disabilities. Blackorby and Wagner (1996) analyzed data from the

original National Longitudinal Transition Study and found 30.5% of students with learning disabilities as compared to 68.0% of their peers without disabilities reported being engaged in postsecondary education 3 to 5 years after school. More recently, Wagner, Newman, Cameto, Garza, et al. (2005) analyzed data from the National Longitudinal Transition Study–2 (NLTS2) and reported 32.7% of students with learning disabilities attended any postsecondary education as compared to 61.8% of peers without disabilities who left school around the same time frame (i.e., 2001; National Center for Education Statistics, 2009). Other reports from the NLTS2 also consistently indicated students with learning disabilities participate in postsecondary education at a lower rate than their peers without disabilities (e.g., Newman, Wagner, Cameto, & Knokey, 2009; Newman, Wagner, Cameto, Knokey, & Shaver, 2010). However, other recent data paint a conflicted picture. Using later data from the NLTS2, Sanford, Newman, Wagner, Cameto, Knokey, and Shaver (2011) reported a comparable percentage of students without disabilities and 1

Portland State University, OR, USA Michigan State University, East Lansing, USA

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Corresponding Author: Gauri S. Joshi, Portland State University, Department of Special Education, P.O. Box 751, Portland, OR 97207–0751, USA. Email: [email protected]

Downloaded from ldx.sagepub.com at CMU Libraries - library.cmich.edu on October 28, 2015

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Journal of Learning Disabilities

students with learning disabilities attended postsecondary education (62.1% vs. 60.9%, respectively). Also using NLTS2 data, Newman and colleagues (2011) found an almost equivalent percentage of individuals in the general population (67.4%) and those with learning disabilities ever attended any type of postsecondary education (66.8%). While the postsecondary education attendance gap between students with learning disabilities and their peers without disabilities appears to have closed, a more in-depth examination of the recent studies shows qualitative differences. Across different data sets and time, the story remains consist: Students with learning disabilities attend vocational, technical, or business school as well as 2-year or community college at higher rates than their peers without disabilities but attend 4-year college at lower rates (Murray, Goldstein, Nourse, & Edgar, 2000; Newman et al., 2011; Sanford et al., 2011). For Sanford and colleagues (2011), twice as many students with learning disabilities attended 2-year or community college and vocational, business, or technical school compared to students without disabilities (41% vs. 21.2% and 31.5% vs.16.7%, respectively). Conversely, students without disabilities attended 4-year colleges at double the frequency of students with learning disabilities (i.e., 37.4% vs. 15.5%, respectively). Newman and colleagues (2011) reported similar results: Students with learning disabilities attended 4-year colleges at a much lower frequency than their peers without disabilities (21.2% vs. 40.2%, respectively) but participated in 2-year or community college and vocational, technical, or business schools at higher frequencies than their peers without disabilities (49.9% vs. 20.6% and 35.8% vs. 20.3%, respectively). Given the benefits of participation in postsecondary education experiences, previous researchers analyzed factors that predict the increased likelihood of participation in postsecondary education for students with disabilities. While not specific for the students with learning disabilities, multiple studies—across states and time—reported inclusion in general education academic content area instruction as a positive predictor of engagement in postsecondary education (Baer et al., 2003; Flexer, Daviso, Baer, Queen, & Meindl, 2011; Test et al. 2009). Halpern, Yovanoff, Doren, and Benz (1995) found receiving and completing instruction in reading, writing, and mathematics—along with demonstrated competence in these academic areas—was a positive predictor of postsecondary education attendance. Baer and colleagues (2003) also determined that after accounting for student-related variables such as gender or ethnicity, participation in general education remained the only significant predictor for postsecondary education participation, indicating a focus on academics is important for students with disabilities with postsecondary education goals. More recently, Flexer and colleagues (2011) reported inclusion in the general education classroom for more than

80% of the time significantly improved the odds of students with disabilities attending postsecondary education fulltime. Students included in the general education classroom were two to four times more likely to participate in postsecondary education than students who were not included. Similarly, Lombardi, Doren, Gau, and Lindstrom (2013), from a secondary analysis of the NLTS2, reported students with disabilities who received language arts and mathematics instruction in an inclusive setting were almost twice as likely to attend or graduate from 2-year programs. Students who received mathematics instruction in an inclusive environment were twice as likely to attend and graduate from 4-year programs. Most recently, Rojewski, Lee, and Gregg (2013) analyzed the NLTS2 data to evaluate the causal effects of inclusion on postsecondary education outcomes of students with high-incidence disabilities (i.e., learning disabilities and emotional-behavior disorders). Rojewksi et al. found students who received 80% or more of their academic credits in general education environments were two times more likely to participate in postsecondary education compared to their peers who received fewer credits in such settings. Outside of academic instruction, some researchers also found career technical education—typically considered to be a predictor of postschool employment—positively related to postsecondary education participation (Baer et al., 2003). In a systematic review of transition literature, Test and colleagues (2009) reported career technical education as a predictor of postsecondary education with a moderate effect size ranging from 0.21 (small) to 0.53 (large), with a median effect size of 0.47 (medium). The findings from previous studies are consistent in terms of the relationship between participation in general education classes and postsecondary education attendance. To understand whether the variables associated with postsecondary participation for students with disabilities in general predict participation for students with learning disabilities, researchers analyzed the NLTS2 database. Students with learning disabilities constitute the largest disability population—4.8% of students in general and 36.7% of students with disabilities (U.S. Department of Education, 2013). When compared to their peers with other high-incidence disabilities, students with learning disabilities are more likely to attend some form of postsecondary education (Newman et al., 2011; Sanford et al., 2011) and are often the population included in general education courses (Baer et al., 2003). Through their secondary analysis of the NLTS2, the researchers explored the postsecondary education outcomes of students with learning disabilities as well as the relationship between these outcomes and postsecondary education– related transition services received (i.e., extent to which students received core content area instruction in the general education classroom and career technical education). The specific research questions included the following: (a) What postsecondary education–related transition services


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Joshi and Bouck do students with learning disabilities participate in while in high school? (b) What are the immediate and long-term postsecondary education outcomes (aggregated and disaggregated by type of postsecondary institution) for students with learning disabilities? (c) To what degree do participation rates relative to type of postsecondary education differ for students with learning disabilities? and (d) To what extent is the receipt of postsecondary education–related transition services predictive of postsecondary education outcomes for students with learning disabilities?

Method The present study is a part of a larger study that used the NLTS2 data to investigate the relationship between transition services received by students with high-incidence disabilities and their postschool outcomes. Specifically, the larger study examined transition services and postschool outcomes aggregated and disaggregated—when possible— by disability for students with learning disabilities, emotional disabilities, mild intellectual disability, ADHD, and speech-language impairments. This current study focused on assessing the postsecondary education–related transition services received by students with learning disabilities and their postsecondary education outcomes.

Participants The original NLTS2 used a two-stage stratified random sampling to select participants (SRI International, 2000a; Wagner, Newman, Cameto, & Levine, 2005). In the first stage, local educational agencies (LEAs) and state special schools (i.e., schools for students with hearing and visual impairments and multiple disabilities) were randomly selected to participate based on geographic area, LEA size based on student enrollment for students in Grades 7 through 12, and district/community wealth (Wagner, Newman, Cameto, & Levine, 2005). In the second stage, students aged 13 to 16 who were at least in the seventh grade and who received special education services in 1 of 12 disability categories (i.e., learning disabilities, speech impairment, intellectual disability, serious emotional disturbance, other health impairment, multiple disabilities, hearing impairments, visual impairments, orthopedic impairments, autism, traumatic brain injury, and deaf-blindness) were randomly selected to participate (SRI International, 2000a). Since the NLTS2 was designed to document students’ postschool outcomes, at the beginning of the study more students aged 16 rather than 13 to 15 were included in the sample (SRI International, 2000a). In addition, sampling of students was done to ensure a 3.6% standard error rate in the most prevalent disability categories (i.e., learning disabilities, speech impairments, emotional/behavior disorders, intellectual disability,

hearing impairments, and other health impairments) (SRI International, 2000a). Sample size was computed to ensure a sufficient number of students in each disability category participated in data collection such that by the end of the study—after accounting for attrition and survey response rates—findings could still be generalized and represent most disability categories (Newman et al., 2009). The NLTS2 described the secondary and postsecondary experiences of students with disabilities across the country and allowed for national population estimates to be reported via SPSS Complex Samples instead of focusing only on the students who participated in the study (i.e., the sample; Newman et al., 2009; Wagner, Newman, Cameto, Garza, et al. 2005). National population estimates were provided by weighting each participating student’s response to represent students from his or her disability category who were educated in a similar LEA—based on geographic region, student enrollment, and wealth—or special school (Newman et al., 2009; Wagner, Newman, Cameto, Garza, et al., 2005). Participant responses were also weighted to represent estimates of race/ethnicity (Newman et al., 2009; Wagner, Newman, Cameto, Garza, et al., 2005). Using the weighted design, the NLTS2 study represented a total of 19,899,621 students receiving special education services from 12,435 LEAs (SRI International, 2000a). In this secondary data analysis of the NLTS2, researchers limited inclusion criteria to the following: (a) identified with a learning disability as the primary disability on the individualized education program (IEP), (b) received special education while in school (i.e., had an IEP or a 504 plan), and (c) enrolled in Grades 9 through 13 (13 is ungraded and the only option past 12th grade). Using the above criteria, a total of 289,720 students with learning disabilities were represented in this study. Of these, the 77.5% (SE 4.5) were male. The majority also identified as Caucasian (65.4%, SE 6.2), followed by Hispanic (18.5%, SE 4.6), African American (12.8%, SE 3.6), Asian (1.7%, SE 1.6), and multiracial (1.6%, SE 1.2). With respect to socioeconomic status, 38.6% (SE 6.4) reported a family income of more than $50,000, 33.3% (SE 7.3) reported a family income less than $25,000, and 28.1% (SE 5.8) reported a family income between $25,000 and $50,000. In terms of geographical location, most of the participating students were educated in suburban schools (48.6%, SE 8.5), followed by urban (39.9%, SE 8.4) and rural (11.5%, SE 3.8). The majority of students reported being in 12th grade at the time of their in-school data collection (86.1%, SE 3.9). Finally, the most frequently reported in-school age was 17 (54.3%, SE 6.9), followed by 16 (20.7%, SE 5.2) and then 18 (13.4%, SE 3.3). The average age of the students with learning disabilities in school was 17.1 (SE 0.15); the average age of the students during their immediate postschool outcomes was 19.04 (SE 0.14), and the average age was 21.24 (SE 0.17) for long-term outcomes.


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Procedures The NLTS2 used six data collection mechanisms to obtain information about the secondary school experiences, transition, and postschool outcomes of students with disabilities: parent/youth interviews, teacher survey, school program survey, school background or characteristics survey, direct assessments and in-person interviews, and student transcripts (SRI International, 2000b). The NLTS2 data collection occurred over 10 years and was conducted across five waves; each wave consisted of a 2-year period. While some surveys—such as the parent/youth survey— were conducted for every wave, others were conducted only once or twice (e.g., the school characteristics or the school program survey). For the purposes of this secondary data analysis, variables from the parent/youth survey (Waves 1, 2, 3, and 4), and school program survey (Waves 1 and 2) were extracted. The parent/youth survey was conducted across all five waves of data collection. While parents responded to a telephone interview or a mail survey in Wave 1, students responded in the subsequent Waves 2, 3, and 4 (SRI International, 2000b). If a student was unable to answer the questions, the researchers collected parents’ responses. The parent/youth survey included questions such as age when disability was identified, family involvement, services student received, and their postschool outcomes (i.e., whether an individual had ever engaged in postsecondary education or attended any postsecondary institution at the time of data collection; SRI International, 2000b). Additionally, demographic information related to student’s ethnicity, gender, family income, and age was identified from the parent/ youth survey. The school program survey provided information about students’ overall school programs, their IEP goals, and their educational and vocational experiences and was a selfadministered mail survey completed by each student’s special education teacher (SRI International, 2000b). Information about students’ primary disability listed on their IEP whether they received special education services in school, and their grade levels were identified from the school program survey. In addition, variables related to whether students were educated in the general education classroom for language arts, mathematics, science, and social studies and if they received career technical education came from the school program survey. To conduct statistical analyses, the researchers needed one database with relevant variables from multiple waves of NLTS2 data. In particular, students who were in high school when data were collected in Wave 1, out of school in Wave 2, and out of school for more than 2 years in Wave 3 were included. Similarly, students who were in high school in Wave 2 but out of school in Wave 3 and out of school for more than 2 years in Wave 4 were included. To construct the

database, the researchers first identified all the in-school variables required for the secondary data analysis from the school program and parent/youth survey (please see Table 1 for a description of variables included in this study). Starting with the school program survey Wave 1 and 2, the researchers included only those students who met the aforementioned inclusion criteria. The researchers deleted any nonrelevant variables; relevant variables included whether the student received core academic content in the general education classroom and participated in career technical education. The researchers also deleted any variables not focused on the in-school experiences of students with learning disabilities (i.e., not relevant for this secondary analysis) from the parent/youth survey databases from Waves 1 and 2. Next, variables from Wave 1 of the parent/youth survey were merged with Wave 1 of the school program survey, and variables from Wave 2 of the parent/youth survey were merged with Wave 2 of the school program survey. To reflect the postschool experiences, the researchers reduced subsequent waves (i.e., when included students were out of school) of the parent/youth database to the desired variables. First, the researchers identified individuals who were out of school in Waves 2 and 3—for the immediate postschool outcomes, by using the variable related to whether respondents received instruction in secondary school (npXD1a). Only respondents who indicated they did not receive instruction were considered to be out of school. Next, each wave (2 and 3) was reduced to only the relevant postschool experiences variables (refer to Table 1). Finally, the Wave 2 parent/youth survey consisting of only the relevant postschool variables was merged with the researcher-created in-school Wave 1 database containing the Wave 1 school program survey and Wave 1 of the parent/youth survey. Similarly, the researchers merged Wave 3 of the parent/youth survey with the database that included the merger of in-school data from Wave 2 of school program survey and Wave 2 of the parent/youth survey. As before, the researchers used the merge variables feature in SPSS (Version 18.0) and merged via respondent’s specific identification number. The researchers repeated the same procedures to identify students’ long-term postschool outcomes (i.e., 2 to 4 years after exiting school), using Waves 3 and 4 of the parent/youth survey, respectively. The researchers reduced Waves 3 and 4 down to the same variables as the immediate postschool outcomes and then merged each with its respective database (i.e., Wave 3 into the in Wave 1 and out Wave 2 database and Wave 4 into the in Wave 2 and out Wave 3 database). Thus, the researchers constructed two databases that reflected the in-school and postschool outcomes of students with learning disabilities. Since researchers required one database for data analyses, all variables in both databases were renamed to be consistent and to ensure a successful merger of cases. Finally, using the merge cases feature of


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Joshi and Bouck Table 1. Description of Variables Used by Survey Instrument and Data Collection Wave. Variable name School program survey Disability of the student Received special education or had a 504 plan Grade Received occupational career technical education or vocational education instruction Received language arts, mathematics, science, and social studies in the general education classroom Parent/youth survey Ethnicity Gender Family income Age Individual received instruction in secondary school Ever attended PSE since high school Currently attends PSE at the time of data collection Ever attended 2-year college since high school Currently attends 2-year college at time of data collection Ever attended vocational education since high school Currently attends vocational education at time of data collection Ever attended 4-year college since high school Currently attends 4-year college at time of data collection

NLTS2 variable ID

Data collection wave

nprXd2b nprXD1a nprXA1 nprXA3k

1 and 2 1 and 2 1 and 2 1 and 2

nprXA3[a-d_1]

1 and 2

wX_EthHdr2001 wX_GendHdr2001 wX_IncomeHdr2001 wX_Age2001 npXD1a npXS3a_S4a_S5a_D4a1_D4a2_D4a3 npXS3c_S4c_S5c_D4b1_D4b2_D4b3 npXS3a_D4a1 npXS3c_D4b1 npXS4a_D4a2 npXS4c_D4b2

1 and 2 1 and 2 1 and 2 1–4 2 and 3 2–4 2–4 2–4 2–4 2–4 2–4

npXS5a_D4a3 npXS5c_D4b3

2–4 2–4

Note. There may be slight changes in the variable IDs from one wave to the next. In IDs, X indicates the wave year (i.e., 2, 3, or 4). NLTS2 = National Longitudinal Transition Study–2; PSE = postsecondary education.

SPSS 18.0 Complex Samples, researchers merged the two databases—containing in-school data from the school program and parent/youth survey in Wave 1 and out-of-school data from Waves 2 and 3 as well as in-school data from Wave 2 and out-of-school data from Waves 3 and 4—into one large database.

Data Analysis To answer the four research questions, researchers used frequency distributions, the F test included with the NLTS2 data, and logistic regressions. To answer Research Question 1—regarding receipt of transition services related to postsecondary education—the researchers conducted frequency counts for whether students received instruction in the core content areas of language arts, mathematics, science, and social studies in the general education classroom (Baer et al., 2003; Corcoran & Silander, 2009) and participated in career technical education (Test et al., 2009). The second research question—students’ immediate and long-term postsecondary education outcomes—was also addressed via frequency distributions. The researchers analyzed postsecondary education outcomes—operationally defined as attending vocational or technical education and 2- or 4-year college—relative to ever attending or currently attending at the time of data collection, and did so for both immediate

(i.e., within 2 years of school exit) and long-term (i.e., occurring 2 to 4 years after exiting school) outcomes. Along with the aggregated postsecondary education attendance, researchers conducted frequency distributions to assess student participation in three types of postsecondary education: 2-year college, 4-year college, and vocational/technical education. To assess Research Question 3—whether participation rates relative to type of postsecondary education differed for students with learning disabilities—researchers used the F test included with the NLTS2 datasets. According to Newman et al. (2011), the F test can be used to understand whether differences between two independent groups are statistically significant by evaluating whether differences in their reported frequencies are greater than would occur by chance. In this study, researchers used the F test to determine whether the reported percentage of students with learning disabilities who attended 2-year college, 4-year college, or vocational/technical school were statistically significantly different from each other. Finally, logistic regression analyses were conducted to address Research Question 4—understanding the relationship between postsecondary education–related transition services (i.e., academic instruction and career/technical education) and postschool outcomes (i.e., ever attended and currently attending postsecondary education) both immediately


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after school exit (within 2 years) and long term (2 to 4 years after school exit). Since the postschool outcome variables— currently attending and ever attending postsecondary education—used in this study were dichotomous in nature (0 = no and 1 = yes), logistic regression was considered to be appropriate for this analysis (Peng, Lee, & Ingersoll, 2002). The following two independent variables were included in each of the two logistic regression models: (a) whether students received career technical education (0 = no and 1 = yes) and (b) general education summation variable (on a scale of 0 to 4). The general education summation variable was created for the purposes of analyses by combining four variables (extent to which students with learning disabilities received core academic content area instruction in the general education classroom—language arts, mathematics, science, and social studies) into one that ranged from 0—received no core academic content areas in general education setting—to 4—received all four content areas in the general education setting.

Results The results reported in this secondary analysis are weighted to reflect population data (SRI International, 2000a). Reported data are based on the responses of the individuals who answered the survey questions rather than the total number of individuals included in the secondary analysis. Individuals may not have been asked a specific question due to skip logic within a survey, may have chosen not to answer a question, or may have dropped out of the study.

Receipt of Postsecondary Education Transition Services Out of the 289,720 students with learning disabilities who responded, less than half received academic content instruction in the general education classroom, with the exception of social studies (50.3%, SE 7.2): science (47.3%, SE 7.3), language arts education (44.9%, SE 6.9), and mathematics (40.4%, SE 7.1). Of the 289,572 students with learning disabilities who responded, 60.1% (SE 6.1) indicated receiving career technical education instruction in school. In terms of the general education summation variable—used in the logistic regression models that reflected the number of core content area classes students received in the general education setting—the most frequent number was 0 (41.3%, SE 6.0), followed by 4 (24.5%, SE 5.4), 2 (16.1%, SE 3.2), 3 (9.8%, SE 2.6), and then 1 (8.3%, SE 2.4).

Postschool Outcomes Within 2 years of exiting school, a little more than one third of students with learning disabilities reported ever attending postsecondary education (36.9%, SE 5.1; see Table 2). At

the time of data collection, however, slightly less than one fourth (24%, SE 4.3) of the students with learning disabilities reported currently attending postsecondary education. Within 2 to 4 years of exiting high school, 43.8% (SE 7.0) of students with learning disabilities reported ever attending postsecondary education, yet only 18.8% (SE 4.6) reported currently attending postsecondary education at the time of data collection. Broken down by type of postsecondary education, the highest percentage of students with learning disabilities reported currently and ever attending 2-year college, as opposed to vocational education or 4-year college (refer to Table 2). The percentage of students with learning disabilities currently attending 2-year college immediately after exiting high school was statistically significantly different from the percentage attending vocational education (p < .05). In terms of ever attending, the percentage of students with learning disabilities ever attending a 2-year college was statistically significantly different from the percentage of those who ever attended vocational education (p < .001 and p < .05) as well as 4-year college (p < .01 and p < .01), both for immediate and long-term outcomes, respectively.

Relationship Between Transition Services and Postschool Outcomes Within 2 years of leaving school, inclusion in the general education classroom for instruction in core content areas was statistically significantly related to whether students with learning disabilities ever engaged in postsecondary education as well as currently engaged in postsecondary education at the time of data collection, with odds ratios of 1.588 and 1.545, respectively. The odds ratio of roughly 1.6 for each dependent variable indicated that for each additional core content area students received in a general education environment, they were 1.6 times more likely to participate in postsecondary education (see Table 3). The results for the long-term outcomes (i.e., 2 to 4 years after exiting school) mirrored the immediate outcome of receiving postsecondary education at the time of data collection, t(104) = 3.592, p < .001, with an odds ratio of 1.910. However, the relationship between ever attending postsecondary education after more than 2 years of school exit and receiving instruction in the general education classroom was not statistically significant. Participation in career technical education was not related to whether students with learning disabilities ever engaged in any postsecondary education or were currently doing so at the time of data collection.

Discussion The present study examined postsecondary education– related transition services received by students with learning


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Joshi and Bouck Table 2. Immediate and Long-Term Postsecondary Education Outcomes for Students With Learning Disabilities. Immediate outcomes Postschool outcomes Ever attended PSE Vocational education 2-year college 4-year college Currently attending PSE Vocational education 2-year college 4-year college

Long-term outcomes

n

%

SE

n

%

SE

288,798 286,908 289,720 286,908 288,798 289,720 289,720 289,720

36.9 7.5 29.0 11.5 24.0 5.5 16.1 9.1

5.1 2.3 4.9 3.3 4.3 2.1 3.8 2.9

217,510 217,510 217,510 217,510 217,510 217,510 217,428 217,510

43.8 18.3 35.5 11.4 18.8 4.6 10.5 7.8

7.0 5.0 6.8 3.9 4.6 2.7 3.6 3.3

Note. PSE = postsecondary education.

Table 3. Relationship Between Participation in Transition Services and Postsecondary Education. Transition services

β

Immediate ever attended postsecondary Inclusion in general education .463 Career technical education .448 Immediate currently attend postsecondary Inclusion in general education .435 Career technical education .617 Long-term ever attended postsecondary Inclusion in general education .288 Career technical education .253 Long-term currently attend postsecondary Inclusion in general education .647 Career technical education .645

SE

Exp(β)

0.165 0.436

1.588* 1.565

0.145 0.527

1.545* 1.854

0.163 0.618

1.333 1.288

0.180 0.674

1.910* 1.906

*p ≤ .05.

disabilities, their postsecondary education outcomes, and the relationship between the two using data from the NLTS2. Three main findings emerged from data analyses. First, receiving core content area instruction in the general education classroom was related to whether students with learning disabilities ever attended or were currently attending any postsecondary education. Second, students with learning disabilities participated in 2-year programs with a higher frequency than other postsecondary education programs. Third, receiving career technical education instruction was not related to any postsecondary education participation (i.e., ever attended or currently attending). The finding that receipt of core content area instruction in general education classes is positively related to attending postsecondary education mirrors previous research demonstrating a relationship between inclusion in general education classroom and participation in postsecondary education for students with disabilities in general (Baer et al., 2003; Flexer et al., 2011; Lombardi et al., 2013; Rojewski et al., 2013). However, in this study, the relationship lessened the

longer students were out of school; there was no relationship between students’ receiving their core content area instruction in general education settings and ever attending postsecondary education 2 to 4 years after exiting high school. The lessening of the relationship is not surprising as one might expect postschool variables to become more impactful on postschool outcomes the longer one is out of school. Regardless, transition planning teams—including teachers as well as parents and students—should consider core content area instruction in the general education settings for students with learning disabilities who plan—or would like the opportunity—to participate in postsecondary education, including vocational training, 2-year college programs, or 4-year college programs. Despite the positive relationship observed between inclusion in the general education classroom for core content areas and postsecondary education attendance, this finding needs to be interpreted with three caveats: (a) the correlational nature of this study, (b) the large sample size, and (c) the issues of educational placement. The correlational rather than causal nature of this study implies receiving core content area instruction in the general education classroom is associated with postsecondary education participation for students with learning disabilities. Previous research suggests several other factors—such as high school grade point average, socioeconomic status, peers’ plans to attend 4-year college, and even receiving accommodations at the postsecondary level—factor into the extent to which students with and without learning disabilities participate and successfully complete postsecondary education and should be examined in future research (Cameto, Knokey, & Sanford, 2011; Lee, Rojewski, Gregg, & Jeong, 2014). Based on the nature of the study, we cannot conclude that participation in general education courses causes students with learning disabilities to attend postsecondary education. Second, findings from this study need to be interpreted in the context of obtaining statistical significance due to the large sample size (Carver, 1978). The statistically significant relationship between inclusion in the general education


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classroom and postsecondary education participation may be a result of the large sample size in this study (Carver, 1978). The odds ratio of additional core content area received in general education settings for participating in postsecondary education do question the practical importance. We found for each additional core content area received in a general education, odds of students with learning disabilities attending postsecondary education were roughly 1.6 and 1.9, for the short term and long term, respectively. While 1.6 and 1.9 indicate the odds of participating increase as the amount of general education courses increases, the odds are not extremely large, suggesting other factors may also influence postsecondary education attendance for students with learning disabilities not examined in this secondary analysis (Field, 2009). Third, the positive relationship between inclusion in general education and postsecondary education participation needs to be examined within the broader context of educational placement. In other words, are these findings reflective of educational placement decisions favoring brighter and more academically motivated students, or does inclusion in general education classrooms with peers without disabilities influence the likelihood of postsecondary education participation? Previous research suggested academic performance of students with learning disabilities educated in inclusive settings is not different from that of their peers educated in noninclusive settings (Fore, Hagan-Burke, Burke, Boon, & Smith, 2008). On the other hand, Rojewski et al. (2013) found being educated in an inclusive setting for the majority of high school credits had a positive effect on postsecondary education participation for students with high-incidence disabilities, indicating exposure to higher academic standards may have increased the educational ambitions of these students. It appears not merely inclusion but its nuances— amount of time students spend in the general education classroom—may play an important role in helping students achieve their postsecondary goals and should be examined in future research. A final point regarding the relationship between general education participation and postsecondary education involves the study’s focus on participation rather than completion. Although inclusion in core content areas is related to participation in postsecondary education, it may not by itself ensure that students with learning disabilities successfully complete postsecondary education (Flexer et al., 2011), and completion—rather than just attendance— should be the goal for students with and without disabilities. However, the analysis with the NLTS2 with regard to completion would require additional waves of data, such as extending to Wave 5 for those in school in Year 2 but out in Years 3, 4, and 5. Given that Wave 4 data for those in school during Wave 2 reflects students who are out between 2 and 4 years, the additional wave of data would grant students

time to perhaps successfully complete a longer program, such as a 4-year college degree (Cameto et al., 2011). The second main finding is consistent with previous research: Students with learning disabilities attended 2-year college at a higher frequency than vocational/technical education or 4-year college (Newman et al., 2011; Sanford et al., 2011). In fact, with the exception of whether students with learning disabilities attending postsecondary education at the time of data collection 2 to 4 years after school exit, results of the F test demonstrated statistically significant differences between students who attended 2-year college and vocational/technical schools or 4-year college. Students with learning disabilities may participate in 2-year programs with greater frequency for several reasons, including open enrollment policies, shorter duration of the program, location, smaller class sizes, the option of attending part-time, and a less threatening environment (Cameto et al., 2011; Test et al., 2006). Future research should examine whether qualitative differences exist between students with learning disabilities who choose to participate in 2-year college as opposed to vocational/technical school or 4-year college. In addition, future research should examine a longer duration postschool to explore (a) if students with learning disabilities matriculate from a 2-year college program to a 4-year college program, (b) the relationships between attendance at different postsecondary education institutions and employment-related postschool outcomes (e.g., working, wage) for students with learning disabilities, and (c) of course, completion of postsecondary programs as well as those programs disaggregated by type (i.e., 2-year program, 4-year program, technical/vocational program). The third main finding indicated a lack of statistically significant relationship between receipt of career technical education instruction in high school and participation in any postsecondary education any time after school exit—contradicting previous research depicting career technical education as a predictor of postsecondary education attendance with a moderate level of evidence (Test et al., 2009). One potential interpretation for the lack of significance involves the well-documented relationship between receipt of career technical education in high school and postschool employment (Baer et al., 2003). Applied to these findings, perhaps students with learning disabilities who received career technical education instruction in high school chose not to attend any postsecondary education but joined the workforce immediately after school exit. Postschool employment data from the larger secondary analysis—of which this study is a subset—suggested immediately after school exit and in the long term, the majority of students with learning disabilities ever engaged in employment (90.8%, SE 2.6 and 88.7%, SE 5.7, respectively) and were currently engaged in employment (58%, SE 7.3 and 73.5%, SE 6.6, respectively; Joshi, 2012). In contrast, less than half of the students who responded ever engaged in or currently attended any type of postsecondary


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Joshi and Bouck education (refer to Table 2). A final explanation for the lack of statistical significance for career technical education could be the correlation between receipt of career technical education and participation in general education; collinearity among independent variables can result in high but non–statistically significant coefficients (Menard, 2002). Another element in the discussion of career technical education is related to terminology. Specifically, in this study the authors used the more current term, career technical education, as stipulated in the Carl D. Perkins Career and Technical Education Improvement Act of 2006. The NLTS2 school program survey, however, used the term occupational vocational education (SRI International, n.d.). Although the difference in terminology may be viewed as merely semantic, the NLTS2 survey instrument distinguished between prevocational and occupational vocational education (SRI International, n.d.). Given the self-reported nature of NLTS2 data, the findings obtained in this study could have varied depending on how participating teachers defined occupational vocational education. In other words, perhaps the responding teachers had a narrow understanding or interpretation of career technical education, which may have influenced the lack of statistical significance observed. Future researchers should examine how service providers understand and implement career technical education in their classrooms and whether there is a difference in student outcomes based on implementation.

Limitations and Future Directions The results of this study need to be considered in light of several limitations. Given the design of the original NLTS2, the self-reported nature of the surveys is a limitation. Individuals who participated in the original NLTS2 may have chosen not to respond to a question or may not have been asked a question due to skip logic, which resulted in missing data. In addition, data analysis was limited to the survey questions used in the original NLTS2. Specifically, the nature of data collection in the original NLTS2 (e.g., whether students received a specific service [0 = no and 1 = yes]) did not provide for a more in-depth exploration of the extent or frequency with which students with learning disabilities received transition services and how the differences in the degree of receipt of services—or the quality of those services—may have affected their postschool outcomes. In this study, the authors limited postsecondary education– related transition services to instruction in core content areas in general education classrooms and receipt of career technical education—documented as predictor variables in previous research. These variables were included as researchers were interested in assessing how services—training and instruction received in high school as opposed to individual factors—were related to postsecondary education outcomes of students with learning disabilities. However,

other transition services related to postsecondary participation can include attendance, achievement, and supplemental instruction in mathematics, reading, and writing. Future research should examine how these services may be related to the postsecondary education outcomes of students with learning disabilities. However, we employed Cohen’s (1990) philosophy in this study that fewer variables are better. In light of the findings suggesting receiving core content area instruction in a general education setting is positively related to postsecondary education, future research should examine which factors influence core content area instruction in the general education classroom for students with learning disabilities. Although the higher postsecondary education participation rates are encouraging, statistically significant differences among percentage of students with learning disabilities who attended 2-year college and percentage of their peers who attended either vocational/technical education or 4-year college warrant further examination of why students choose to participate more in 2-year programs over other postsecondary education options. Finally, future researchers need to assess the supports required by students with learning disabilities to systematically prepare them to not only attend but also complete the postsecondary education of their choice. Authors’ Note The first author volunteers at the Department of Special Education, Portland State University through a courtesy faculty appointment. This research was conducted while the first author was a doctoral candidate at Purdue University. The first author received a Purdue University Bilsland doctoral dissertation fellowship for this project.

Declaration of Conflicting Interests The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research project was supported in part by a Purdue University Bilsland Dissertation Fellowship to the first author.

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