TH E O OH HI IO O L LO ON NG GI IT TU UD DI IN NA AL L T TR RA AN NS SI IT TI IO ON N S ST TU UD DY Y: : T HE PH AS SE E I II I – – E EX XI IT T A AN ND D F FO OL LL LO OW WU UP P P HA THIRD DRAFT OF STATE REPORT Robert M. Baer, Principal Investigator. Al Daviso, Project Director, Kent State University Lawrence Dennis, Liaison, Office for Exceptional Children Robert Flexer, Consultant, Kent State University Margo Izzo, Consultant, The Ohio State University This study was funded by the Office for Exceptional Children at the Ohio Department of Education and the Office of Special Education and Rehabilitation Services #
Page 1 of 36 The Ohio Longitudinal Transition Study The No Child Left Behind Act (NCLB) of 2001 has emphasized the need for accountability and evidenced­based instruction in the education of all students, and the Individuals with Disabilities Education Act (IDEA) has held schools accountable for the progress of students with disabilities in the general curriculum since 1997. However, the focus of the IDEA has always been twofold—progress in the general curriculum and preparation for productive adult roles (Turnbull, Turnbull, Wehmeyer, & Park, 2003). Consequently, the IDEA amendments of 2004 have emphasized the need for schools to be accountable for student post­ school as well as in­school outcomes (IDEIA of 2004). These recent amendments demonstrate a commitment by advocates and policy­makers to improve access to the general curriculum, goal­ oriented transition planning, and post­school results for students with disabilities. . In order to determine how well students with disabilities were performing following completion of secondary education, the Office for Exceptional Children (OEC) at the Ohio Department of Education (ODE) developed a strategic plan that included the goal that: “By June 2004 [OEC] will develop a longitudinal tracking system for students with disabilities after K­12 departure” (Ohio Department of Education, 2000). This goal was implemented in 2004, when the OEC provided funding to five Special Education Regional Resource Centers (SERRCs) and Kent State University to begin collecting, coding, and analyzing information on transition­age students with disabilities prior to and after graduation (Cohort I). Eight more SERRCs were funded to collect longitudinal data in 2005 and 2006 (Cohorts II and III), and three more SERRC regions are slated to begin collecting data in 2007 (Cohort IV) thereby covering all of Ohio’s sixteen SERRC regions (Dennis, 2005). The Ohio Longitudinal Transition Study (OLTS) originated from the OEC state plan, but was based on earlier pilot studies at the Miami Valley SERRC, the Cuyahoga Valley SERRC, and Project LIFE (Ohio’s system change project for transition). Piloting led to the decision to adopt a longitudinal tracking system for the OLTS (Baer et al., 2003). A longitudinal tracking system follows groups of randomly selected students from their final year of graduation to five years after graduation. A longitudinal tracking design was chosen for the OLTS because it has been shown to provide more reliable information than simply surveying a group of students after
Page 2 of 36 graduation and secondly, because it provides information about the transition process as well as outcomes (Halpern, 1990). Method Instrument Two surveys were designed for the OLTS—an exit survey conducted just prior to graduation and a followup survey conducted one, three, and five years after graduation or aging out of high school. The exit survey used in the OLTS included information from school records and from interviews of graduating students with disabilities. Survey questions were initially drawn from the literature on postschool research (Mooney, Phelps, & Anctil, 2002; Kohler, 1993; Rabren & Chambers, 2002; Stodden, Jones, & Chang, 2002) and from early postschool outcome studies including the National Longitudinal Transition Study (Blackorby & Wagner, 1996). The validity of survey questions was examined by a state team of transition advocates and policy­makers and by pilot surveyors at the Cuyahoga and Miami Valley SERRCs who checked survey responses against what they knew about their students (Baer et al., 2003). Survey questions were further examined by the surveyors who examined the results of the survey for Cohort I and provided recommendations for improvements. The exit surveys were numbered and contained no student identifiable information. They were divided in two sections. The first section of the exit survey was drawn from student records and included eleven questions that provided background information about the student’s ethnicity, disability, school setting, type of school, academic placement, career and technical education, and proficiency test (now graduation test) scores. The second section of the exit survey was conducted by interview and included ten questions that were designed to obtain specific information about: (a) student postschool goals, (b) student perceptions of secondary services received, (c) student financial plans, and (d) coursework that they needed but were not able to take. The followup surveys included a number for matching with the exit surveys and used no student identifiable information. The followup survey was designed to be conducted by phone interview and included sixteen questions which asked graduates whether they attained the postschool goals that were recorded in the exit survey, how satisfied they were with these outcomes, and how they would rate school services retrospectively. The followup survey
Page 3 of 36 included questions about postschool work, education, independent living, community participation, financial supports, and satisfaction. The followup survey also contained questions about student earnings and work hours and, if students’ postsecondary goals were not attained, the reasons for not attaining them. Local Education Agency (LEA) Recruitment The Office for Exceptional Children (OEC) staff held meetings with Special Education Regional Resource Center (SERRC) directors to identify cohorts (or groups) of SERRCs for participation in the OLTS each year. The ultimate goal of this yearly recruitment effort was to enlist all sixteen of Ohio’s SERRCs into one of four cohorts. Four SERRCs were identified for Cohort I (exit 2004) and an additional SERRC was added to this cohort upon request of the SERRC director. SERRC recruitment was repeated annually with four SERRCs recruited for Cohort II (exit 2005) and four more recruited for Cohort III (exit 2006). Three more SERRCs are to be recruited for Cohort IV (exit 2007) and at that time all SERRC regions will have been included (Dennis, 2005). At each participating regional SERRC, LEAs were recruited to represent rural, suburban, and urban schools in the region. Kent State University and OEC staff held fall meetings in 2003 and spring meetings in 2004 at each of the five Cohort I SERRCs to go over the purpose of the OLTS and to request participation of rural, suburban, and urban schools. Kent State and OEC staff provided a brochure and surveys about the OLTS and presented a PowerPoint presentation about the costs and benefits of following up with students with disabilities after graduation. Participation was voluntary, but certain types of schools were vigorously recruited (i.e. urban schools) to obtain as representative sample of Ohio schools as possible. This process was repeated yearly for each cohort. It is anticipated that after each SERRC cohort has been followed for five years, new cohorts of LEAs will to be recruited for each region creating a new six­year cycle for each SERRC region. In addition to the mandatory six­year cycle of recruitment of LEAs in each SERRC region, individual LEAs may choose to start following up with their students for any year. In this case, these “non­recruited” LEAs would participate as part of the cohort identified to collect exit data for that year. Participating SERRCs were provided funding from OEC for hosting the meetings, and additional funding was provided to provide an incentive for local education agencies (LEAs) to
Page 4 of 36 participate in the first round of data collection at each SERRC. The OEC contracted with Kent State University to support the SERRCs and their participating LEAs. Kent State staff met with each cohort about four times a year. After collection of followup data at each SERRC, staff from participating LEAs and Kent State staff presented to SERRC governing boards regarding the OLTS findings for that region and statewide. In 2003­2004, project staff held spring meetings at each of the five Cohort I SERRCs to prepare the participating LEAs to conduct phone interviews with students they had conducted exit interviews with the prior year. In 2005, followup surveys were conducted for graduates of Cohort I who were one year out from graduation from high school. Surveyors were instructed to attempt to contact students at least four times. Surveyors were instructed to conduct followup interviews with the same respondent that was used in the student’s exit survey. In 2004­2005, project staff held meetings with four additional SERRCs who were designated as Cohort II to prepare the interested LEAs to conduct surveys of exiting students with disabilities. Cohort II surveyors were instructed to interview the student whenever possible and, secondarily, parents or other persons who knew the student well if the student could not answer the survey questions. To aid student participation, surveyors were instructed to paraphrase questions on the survey as needed, and to conduct surveys individually. . Coding and Analysis Coding consisted of a two­part process: (a) machine coding and (b) manual coding. Manual coding was used to enter answers to open­ended questions and comments. Surveys were received as late as September because several of the school surveyors were unable to conduct their surveys until after the IEP season in April, May, and June. In October, project staff at Kent State University printed out descriptive statistics to spot errors in coding and to generate a preliminary report. This report was presented to schools at the participating SERRCs for comments and corrections. Project staff conducted initial analyses to compare the sample to the population of students with disabilities who exited special education using state data derived from the Twenty­ Fourth Annual Report to Congress (U.S. Department of Education, 2003) and national data from the NLTS2 (Wagner & Marder, 2003). They then conducted correlational analyses to identify variables with strong correlations to planned and actual postschool outcomes. Promising variables were entered into linear and logistic regression SPSS programs to identify variables
Page 5 of 36 that best predicted postschool outcomes for students. These models generally included a combination of student characteristics, school programs, and in­school outcomes (Baer et al., 2003; McMahan & Baer, 2001). The OLTS Sample During the first year of the study (2004), educators from 52 schools in five SERRC regions collected data on a total of 741 exiting students with disabilities who were designated as Cohort 1. In the second year (2005), 52 additional schools collected data on an additional 601 students with disabilities who were designated as Cohort 2. A total of 1,342 exit surveys were conducted, 94% with students, 2.7% with parents, and 3.3% from other. Figure 1 shows the percentage of surveys collected from each SERRC region. Participating LEAs were primarily high schools (74%), followed by joint vocational schools (21%) with suburban school making up 47% of the sample followed by urban and large city schools (31.8%), rural schools (13.3%), and small city schools (5.4%). Figure 1 ­ Ohio Regions Sampled Cuyahoga 12% Northern 12% Northwest 12% North Central 12% Mid­East Ohio 6% Lincoln Way 16% Miami Valley 9% Central Ohio 7% Southwest 14% The 1,342 surveys that were collected on students with disabilities exiting high school were compared to demographic data reported for graduating students in Ohio in the Twenty­ Fourth Annual Report to Congress (U.S. Department of Education, 2003) and to the Second National Longitudinal Study of Transition (Wagner & Marder, 2003) . The percentage of males
Page 6 of 36 in special education for the combined Cohort I­II exit sample was 59.3% compared to 57.5% nationally (Javits & Wagner, 2003). The gender for the Ohio followup sample was 57.5% male. (No data was available regarding gender for states in the Twenty­Fourth Annual Report to Congress.) Figure 2 shows how the disability characteristics of the sample compared to Ohio students with disabilities graduating with diplomas or who aged out of special education as reported in the Twenty­Fourth Annual Report to Congress (U.S. Department of Education, 2003). The disabilities of students in the exit samples (N=1342) were very closely aligned with the Ohio population with the exception of students with emotional disabilities. This was partly due to the fact that these students were more likely to refuse to participate in the Ohio study. More variation was seen in the smaller followup sample (N=205) which underrepresented graduates with learning disabilities and emotional impairments. Figure 2 –Exit and Followup Sample Disabilities vs. Ohio 60 Exit Sample Followup Sample Ohio* 50 percent 40 30 20 10 0 f
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Page 7 of 36 students with disabilities who exited special education as reported in the Twenty­Fourth Annual Report to Congress (U.S. Department of Education, 2003). This figure shows that African­ American students were somewhat overrepresented in the exit sample as compared to Ohio (23.4% compared to 16.8% for Ohio). White students were underrepresented (72% vs. 81.3% for Ohio). The smaller followup sample (N=205) reversed this bias by over representing white students (85.3% vs. 81.3% for Ohio) and under representing African­American students.(10.7% vs. 16.8% for Ohio). Figure 3 ­ Exit/ Followup Ethnicity vs. Ohio and gender vs. U.S. 100 Percent 80 60 40 20 0 al
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Exit Sample Ohio* *Special education students who graduated or aged out as reported in the 24th Annual Report to Congress General Observations Regarding Sampling The exit samples corresponded well to the population of students with disabilities exiting high school with a diploma or certificate. More significant bias was noted in the sample of students who were contacted one year past graduation. This was reportedly due to the greater difficulty in reaching certain kinds of students after graduation. Students who were less mobile were generally easier to contact after graduation (i.e. white students and students with cognitive disabilities). However, the advantage of a longitudinal study was that the exit sample could be matched to the followup sample (Halpern, 1990).
Page 8 of 36 Results Transition Planning The ratings of transition planning for Cohort I and Cohort II could not be aggregated because of a change in the wording of the question. Of the 467 students who had any postsecondary education goals in Cohort I, 77% indicated that they were addressed by their transition plan. Of the 341 students who had any postsecondary goals in Cohort II, 67% indicated that they were addressed “well” or “very well” in their transition plan. Of the 597 students who planned to work full or part­time in Cohort I, 86% indicated that they were addressed by their transition plan. Of the 466 students who planned to work full or part­time in Cohort II, 80% reported that they were addressed “well” or “very well” in their transition plan. Of the 741 students in Cohort I who rated their transition plan in relation to their independent living goals, 63% reported they were addressed in their transition plan. Of the 531 students in Cohort II who rated their transition plan in relation to their independent living goals, 70% % indicated they were addressed “well” or “very well” in their transition plan. Of the 741 students in Cohort I who rated their transition plan in relation to their community and leisure goals, 52% reported they were addressed in their transition plan. Of the 511 students in Cohort II who rated their transition plan in relation to their leisure and community participation goals, 66% indicated they were addressed “well” or “very well” in their transition plan. Secondary Programs Cohort I – School Programs Due to changes in EMIS reporting guidelines, the secondary programs for Cohort I and Cohort II were reported separately in Figures 4 and 5. Figure 4 shows the major secondary programs for the students in Cohort I (N=741) where 30% of students were reported to be participating in partial mainstream classes and only 2% were in self­contained classrooms. Nearly 45% of the students who were surveyed were reported by Ohio’s Education Management Information System (EMIS) to have participated in work study and 7.3% reported participating in community­based job training (Option 4) programs.
Page 9 of 36 Figure 4­ Secondary programs for Cohort I 100 percent 80 60 40 20 0 Academic Mainstream Career/Tech Mainstream Partial Mainstream Self­Contained Classes Work Study Program Option 4/Job Training Cohort II – School Programs Figure 5 shows that about 30% of the students in Cohort II were designated as participating in special education 21­59% of the time and 24% designated as participating in special education 60% or more. Vocational special needs (VOSE) participation was indicated for 37% of students surveyed, career assessment for 41%, transition specialist for 26%, special needs career and technical education (Option IV) for about 8%, and assistive technology for 3.3%. Figure 5 ­ Secondary Programs of Students in Cohort II. 50 percent 40 30 20 10 0 SPED (less than 21%) SPED (21%­60%) SPED (60% or more) VOSE Special Needs CTE Transition Specialist Career Assessment Assitive Technology Career and Technical Education Figure 6 shows both cohorts’ participation in career and technical education in semesters. More than 43% of students reported four or more semesters of career and technical education
Page 10 of 36 and would be considered vocational concentrators, while 39.1% reported no career technical education. percent Figure 6 –Semesters of Career and Technical Education 45 40 35 30 25 20 15 10 5 0 0 1 2 3 Semesters 4 5 6 or more Due to changes in the Ohio Educational Management Information System (EMIS) it was not possible to aggregate the specific academic programs and transition services for both of these cohorts. Participation in mainstream academics and transition services was reported at significantly higher rates for Cohort I than for Cohort II which used the new EMIS codings. While mainstream career technical education was reported for 50% of students in Cohort I, students who indicated either enrollment at a career/technical school, taking any vocational classes, or taking any semesters of career technical education totaled 815 of 1342 students surveyed or 61% for Cohort I and Cohort II combined. These rates compared to the national rate reported in the NLTS2 which was also 61%. Transition services (VOSE, Option IV, Transition Specialist, or Work Study) and//or some type of vocational education were reported for 83% of students in Cohort I and over 90% of the students in Cohort II. Of students not receiving any transition services or career/technical education, nearly 25% were African­American. Student Ratings of Secondary Programs Students rated the secondary programs they participated in on a 4 point scale with 4 equaling very helpful, 3 equaling helpful, 2 equaling somewhat helpful, and 1 equaling not helpful at all. Career and technical education was rated by half of the students and received the highest average score of 3.40. Paid work on own was rated by 70% of the students for an average of 3.26. School supervised work was rated by 40% of the students for an average of
Page 11 of 36 3.01. A total of 76% of the students rated proficiency testing which came in with the lowest average score of 1.93. Figure 6 shows both cohorts’ average ratings of school services. 4 point scale rating Figure 6 – Student Ratings of Secondary Services and Programs 3.5 3 2.5 2 1.5 Proficiency Tests Job Shadowing IEP Meetings Work on Own Supervised Work Classes at College In­School Job Career/Tech Ed Extracurricular Prepare ACT/SAT Vocational Rehab MR/DD Services Anticipated Postschool Outcomes Work and Education Goals Figure 7 shows students’ work and education goals reported in the exit surveys for Cohort 1 and Cohort II. The most commonly reported work and postsecondary education outcomes for both cohorts were full­time work, two­year college, part­time work, four­year college, technical school, and the military. Only a small proportion of students anticipated receiving vocational rehabilitation services or other non­college training or employment services. percent Figure 7 – Anticipated Postschool Work and Education Outcomes 60 Work Full­time 50 Work Part­time 40 4­Yr College 30 2­Yr College 20 Technical School 10 Military 0 Cohort 1 Cohort 2 Other Figure 8 shows that the types of work anticipated by both cohorts were fairly evenly distributed across the major job sectors; though clerical work, custodial work, and agricultural
Page 12 of 36 work were less commonly chosen. Many of the students chose “other” which included accounting, acting, art, biology, interior design, engineering, broadcasting, fashion design, forestry, law enforcement, massage therapy, movie directing, photography, and entrepreneurship Figure 8 – Anticipated Fields of Work 35 Food Service 30 Computers Auto Construction 25 Industry 20 Marketing 15 Custodial Clerical Agriculture 10 Child Care Cosmetology 5 Health Care 0 Human Services 1 year 2 Year Other
Independent Living and Leisure Goals Figure 9 shows student independent living, community, and leisure goals. Nearly half of the students in this sample reported that they would be continuing to live with their parents after graduation. Students indicated that driving, voting, going to the mall, outdoor activities, and hobbies were important to most of the students. Religious activities and playing sports were also popular categories. Only 14% of the students anticipated using public transportation. Figure 9 – Independent Living and Leisure Goals percent 80 60 40 20 0 Cohort I Live Parents Own a Car Play Sports Mall and Movies Voting Public Transp. Hobbies Outdoor Activities Cohort II Driver's License Use a Computer Religious Activities Other Page 13 of 36 Anticipated Financial Support Figure 10 shows the anticipated sources of income for students from Cohort II only. More than 85% of the students planned to obtain income through employment (not shown on this slide). The second most important source of income was reported to be family members, followed by student loans, scholarships, Medicaid, and disability (SSI/SSA) benefits. Figure 10 also shows what sources of income Cohort II students had applied for prior to graduation. The greatest discrepancy between income that was anticipated and that had been applied for was in the areas of student loans and scholarships. Figure 10 – Financial Support Goals 50 percent 40 30 20 10 0 Plan to Sheltered Work Food Stamps Scholarships Have applied for Family Members ODJFS Student Loans Disability Benefits Rent Subsidies Medicaid Postschool Outcomes for Cohort I In reading data regarding graduate outcomes, the reader should be cautioned that due to the size of the followup sample (N=205), that chance variations could not be ruled out in evaluating sub groups that were smaller than 30 (i.e. about 15% of the followup sample). Consequently, the findings of this round of followup data should be considered tentative until additional followup surveys are conducted in 2006­2007. Additionally, it should be noted that the exit data reported in this section only represented students who were successfully contacted after graduation and therefore the reader will note some discrepancies between the exit data reported in the previous section and the exit data reported for the sample that was successfully followed up.
Page 14 of 36 Planned vs. Actual Work Outcomes and VR Support – Cohort I Figure 11 shows how the students’ planned outcomes compared to their actual outcomes in the areas of employment and vocational rehabilitation. (It should be noted that exit data in these charts is only for students who were successfully followed up.) Of the exit sample that was successfully followed up, nearly 49% anticipated entering full­time employment, 45% worked full time in the past year, and 36% reported full­time employment at the time of their followup phone interview. While 33% of these graduates anticipated part­time employment, 42% reported this outcome for the past year and 32% were employed part­time at the time of their interview. Vocational rehabilitation services were anticipated by 25% of the sample that was successfully followed up, 14% reported receiving services from VR in the past year, and only 6% reported that they were receiving VR services at the time of their interview. percent
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The average hourly wage reported by graduates was $7.31 per hour and the average work week was 31 hours. Urban graduates reported wages of $5.91 per hour and 29 hour work weeks. Suburban graduates reported average wages of $7.90 per hour and 33 hour work weeks. Rural graduates reported $6.83 per hour and 30 hour work weeks. Males earned $7.54 per hour and averaged 33 hour work weeks. Females earned $7.08 per hours and averaged 30 hour work weeks. Only 13% of graduates reported being “very dissatisfied” or “dissatisfied” with their work. Satisfaction with adult services was lower with 24% reporting being “very dissatisfied” or dissatisfied” with adult services.
Page 15 of 36 Figure 12 shows the planned vs. the actual fields of employment that graduates entered. Many more graduates entered food service and industry jobs than anticipated while none found jobs working with computers, as planned. Figure 12 – Planned vs. Current Fields of Employment for Cohort I 40 35 percent 30 25 20 15 10 5 0 Planned Current Food Service Auto Computers Construction Industry Marketing Clerical Custodial Agriculture Child Care Cosmetology Health Care Human Services Other Graduates who were unemployed attributed their unemployment to a number of factors. Approximately 36% reported they went into postsecondary education, 16% reported they could not find a job that matched their interests, 11% cited transportation problems, 7% reported not wanting to lose their benefits, 7% reported not having the required skills, 5% reported not being able to find any job, and 5% reported not wanting to work at all. Planned vs. Actual Outcomes in Postsecondary Education – Cohort I Figure 13 shows planned, past year, and current outcomes in postsecondary education for graduates who were successfully followed up one year after graduation. Four year colleges were most frequently planned for with 21% of students listing this goal. After one year out, only 13.7% had attended any classes and only 9.8% were still enrolled at the time of the followup phone survey. Graduates were more likely to successfully enroll in two­year colleges were more likely to succeed with 20.4% of the followup sample listing this goal, 17.6% reporting having attended classes in the past year. However graduates entering two­year colleges also experienced a high attrition rate with only 13.2% reporting continued enrollment in classes at the time of their followup phone interview. Graduates did not enroll in technical schools or military options at the rates planned, but retention in these programs was higher. However, as previously noted the sample sizes of these groups were probably too small to rule out chance variations.
Page 16 of 36 Figure 15 – Planned, Past Year, and Current Outcomes in Postsecondary Education
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The types of educational supports reported by these graduates (N=69) were primarily tutoring (41%) followed by extra time for tests (36%), and remedial classes (29%). The remaining accommodations included tour of disability services (13%), reduced schedule loads 12%, tapes of books and lectures (10%), and note­taking services (9%). The two major reasons that graduates gave for not attending postsecondary education as planned was lack of money (22%) and change in plans (16%). Postschool Engagement Levels – Cohort I Figure 16 shows the overall engagement levels of graduates one year after graduation. These engagement rates were calculated by adding the work load (which was figured at 50% for part­time work and 100% for full­time work) to postsecondary education (which was figured as 100%). This yielded five postschool engagement scores of: (a) 0% for no work or postsecondary education, (b) 50% for part­time work, (c) 100% for full­time work or any college enrollment, (d) 150% for part­time work and college, and (e) 200% for full­time work and college.
Page 17 of 36 percent of graduates Figure 16 – Engagement Outcomes of Graduates 51.5 41.5 31.5 21.5 11.5 1.5 0% 50% 100% 150% 200% Outcomes for Seven Clusters of Students Engagement outcomes were examined for seven clusters of students that were identified using an SPSS two­step cluster analysis (Aldenderfer & Blashfield, 1984; SPSS, 2003). After clustering, an analysis of variance (ANOVA) and a Tamhane’s T2 post hoc analysis were used to identify variables in each cluster that were significantly different from the other clusters. The following groups of students were identified. 1. Cluster 1 focused on students planning to enter employment after graduation that had cognitive disabilities or multiple disabilities and did not pass their ninth grade proficiency tests. 2. Cluster 2 focused on students planning to enter two­year colleges who had cognitive disabilities and did not pass their ninth grade proficiency tests. This cluster had a high proportion of urban female students. 3. Cluster 3 focused on students planning to enter employment after graduation that had learning disabilities and passed their ninth grade proficiency tests. This cluster had few urban students. 4. Cluster 4 focused on students with both employment and college goals who had learning disabilities and did not pass their ninth grade proficiency tests. This cluster had a higher proportion of urban students.
Page 18 of 36 5. Cluster 5 focused on students with a two­year college goal that had learning and other disabilities and who generally passed their ninth grade proficiency tests. This cluster was also distinguished by a relatively low number of urban students. 6. Cluster 6 focused on students with a four­year college goal who had learning and other disabilities who passed their ninth grade proficiency tests and few students who planned to work full­time after leaving high school, 7. Cluster 7 focused on students with a technical school goal who had learning and other disabilities and that passed the ninth grade proficiency test. This cluster had a high proportion of male students. Table 1 shows the engagement outcomes for students in these seven clusters. Graduates with cognitive and multiple disabilities in Cluster 1 had the highest proportion not engaged in work or postsecondary education (38%), followed by graduates with two­year college goals cognitive disabilities in Cluster 2 that had 33% of its graduates in this category. Proficient graduates with two­year college goals in Cluster 5 had the highest engagement rates with no graduates reporting not being engaged and only 15% reported as being engaged in part­time work only. Table 1 also shows specific student work and education outcomes. Full­time work outcomes were similar for graduates with learning disabilities who were proficient (Cluster 3) and graduates who were non­proficient (Cluster 4). Postsecondary education outcomes were obtained for only 17% of non­proficient graduates with cognitive disabilities. Only 50% of graduates with the goal of four year college achieved this goal, but 9% went into two­year colleges. About 52% of students with the goal of a two­year college achieved this goal, but 4% went into four­year colleges. Only 19% of students with technical school goals achieved this goal, but 13% went into two­year college programs.
Page 19 of 36 Table 1. Engagement, Work, and Education Outcomes by Clusters of Graduates in Percent Cluster Group 1. Work goal, cognitive/multiple disabilities, non­prof. 2. 2 year college goal, cognitive disabilities, non­prof. 3. Work goal, learning disabilities, proficient 4. Work and college goals, learning disabilities, non­prof. 5. 2 year college goal, learning/other disabilities, proficient 6. 4 year college goal, learning/other disabilities, proficient 7. Technical school goal, learning/other disabilities, proficient Level of Engagement Work & Education Outcomes (In percent) (In percent) Not 50% 100% FT 2 year 4 year Tech Engaged Engaged Engaged work college college school 38% 35% 27% 27% 0% 0% 0% 33% 0% 67% 58% 17% 0% 0% 24% 12% 64% 53% 6% 0% 0% 15% 19% 65% 58% 8% 0% 4% 0% 15% 85% 26% 52% 4% 0% 16% 13% 71% 25% 9% 50% 0% 19% % 75% 50% 13% 0% 19% Predictors of Postschool Engagement – Cohort I The ultimate question that directed the Ohio Longitudinal Transition Study was, “What services and in school outcomes best predicted the graduate outcomes. To answer this question, postschool engagement rates were used as the dependent variable and a number of key variables were included as independent variables or predictors. A linear regression model was used to identify which variables best predicted the postschool engagement rates of students after graduation. A linear regression model looks at the dependent variable and determines (after controlling for the other variables in the model) how much of the variance (in this case engagement levels) can be accounted for by each independent variable (or predictor). Figure 17 shows the SPSS printout that was obtained using a model that included the following independent variables or predictors: (a) gender, (b) level of disability, (c) academic program, (d) work study participation, (e) vocational education, (d) school setting, (e) adult
Page 20 of 36 services received, (f) whether the student eld a job upon graduation, and (g) whether the student passed most or all of their proficiency tests. This regression analysis showed that variables “f” and “g” were the only significant predictors of postschool engagement for this sample (p<.05). The standardized coefficients for these two variables were .290 and .274. This meant that these variables accounted for 29% and 27.4% respectively of the standardized variations in engagement levels. Table 2 – Predictors of Postschool Engagement for Cohort I Model Unstandardized Standardized Coefficients Coefficients B Std Error t Sig. Beta Constant .150 .205 Had paying job when left high school* .330 .082 .290 4.039 .000* Male gender .119 .076 .107 1.568 .119 Non­minority .143 .105 .096 1.361 .175 Milder disability .249 .133 .131 1.865 .064 Partial mainstream classes .041 .087 .038 .472 .637 Work study ­.140 .092 ­.126 ­1.531 .128 Vocational education ­.119 .083 ­.103 ­1.440 .152 Urban school setting .042 .096 .031 .488 .662 Receiving vocational rehabilitation ­.127 .163 ­.059 ­.781 .436 Receiving MR/DD services ­.127 .151 .070 ­.844 .400 .345 .099 .274 3.492 .001* Number of proficiency tests passed* .729 .467 Dependent variable = percent of time engaged in school or work *p<.05 Discussion This study includes three major samples of students with disabilities: (a) Cohort 1 which consisted of 741 students with disabilities who exited or aged out of high school in 2004 from five SERRC regions and 52 schools in Ohio, (b) Cohort II which consisted of 601 students with disabilities who exited or aged out of high school in 2005 from four additional SERRC regions and 52 schools in Ohio, and (c) Cohort I – Followup which consisted of 205 graduates or students who aged out of special education from five SERRC regions and 20 schools. These
Page 21 of 36 data are presented together in this report to provide the fullest picture of postschool outcomes available to date. Procedural Findings Sampling The combined exit samples for Cohort I and Cohort II were highly comparable in terms of disability and ethnicity to Ohio’s population of students with disabilities who exited or graduated from high school in the Year 2000 as reported in the Twenty­Fourth Annual Report to Congress. The Cohort I—Followup sample showed three weaknesses that will need to be addressed to be generalized to Ohio as a whole. First, the size of the Cohort I—Followup sample was too small to allow for analysis of subgroups. Second, only 20 of the 52 schools who conducted exit interviews conducted any followup interviews. Third, the teachers conducting followup interviews reported lower response rates for African American students, students with learning disabilities, and students with emotional disabilities. These findings suggest that teachers at the LEAs had a much easier time conducting exit interviews than in conducting followup interviews. Teachers reported that while exit interviews could be conducted as part of their current exit meetings with students, followup interviews required additional time outside of their current responsibilities. They noted that trying to conduct followup interviews in the April­June window fell right in the middle of the IEP season, which was their busiest time. Teachers generally agreed that the window for conducting followup interviews needed to be extended into July and August to conduct this research with current staffing levels. The loss of African­American students, students with learning disabilities, and students with emotional disabilities was attributed to high mobility for these students. Even though teachers collected phone numbers for several family members, these phones were often out of service by one year post­exit. This problem is likely to become more pronounced when Ohio starts conducting followup on students who have dropped out. Ohio may need to take steps to allow the OLTS to interface with the databases of the Rehabilitation Services Commission and with other schools and alternative programs that are often recipients of these students. Currently, Ohio law does not permit the use of student identification numbers that allow tracking across systems and schools. Even with this approach, followup samples may need to be weighted using
Page 22 of 36 approaches similar to that employed by the National Longitudinal Transition Study to assure that the OLTS followup sample is representative of Ohio as a whole (Javits & Wagner, 2003). Instrument The combination of EMIS and interview data in the exit survey provided a flexible and efficient way of obtaining data. The EMIS data yielded demographic information and information about students’ disabilities, ethnicity, and academic programs. Additionally, the use of EMIS allowed greater comparability across school districts. However, the surveyors reported that some of the EMIS data was unreliable in giving a true picture of services that students received in high school. One area of particular concern was the coding for work study which actually represented a number of services including: (a) school supervised work experiences, (b) employability skills training, (c) career development, and (d) students who obtained needed credits toward graduation by working in the community. To deal with this issue some of the EMIS data was triangulated with data obtained through the student exit interview. The postschool phone survey was reported to be easy to administer taking only about 10­ 20 minutes of phone time. Most of the time spent in doing this survey was in contacting the students. The teachers conducting the survey reported that graduates were generally pleased to hear from them, and that the survey often identified areas that the graduates needed additional support. A computerized version of the postschool phone survey is being developed for piloting in 2006. Coding and Analysis The 2005 survey was developed in conjunction with NCS Pearson which made machine coding faster. The exit surveys were coded first by machine and then manually for open­ended questions and comments. Exit surveys were coded and analyzed without problem, but 12% of the followup surveys could not be matched to student numbers used on exit surveys. Some of the schools reported that they had lost the numbers assigned to the students. To address this problem, the 2006 surveys will be sent to school as a packet with the permission form, exit, and followup surveys pre­numbered. As surveys are used they will be torn out of the packet. Packets will also be sent out with a few pre­addressed return envelopes to make mailing easier.
Page 23 of 36 Secondary Programs Transition planning was reported to be strongest in the area of student work goals with more than four in five students reporting positive ratings in this area. Ratings for how well transition plans addressed college goals were somewhat lower and dropped even further for independent living and community participation and leisure goals. When this was discussed with the teachers and surveyors who conducted the study, they noted that often the transition page was filled out by the work study coordinator or work­focused transition specialists who were strongest in this area. It was noted that schools are somewhat ambivalent about addressing independent living and community and leisure goals for students, typically leaving the bulk of the responsibility for these goals to the students and the parents. The secondary transition programs in this sample closely resembled the NLTS2 findings for students taking vocational education (i.e. 61%) (Levine, Marder, & Wagner, 2004; Wagner, 2003;). Ohio’s provision of additional transition services through work study, Option IV, VOSE, and work study meant that the vast majority of students with disabilities in Ohio had access to transition services and/or vocational education. The finding that more than 43% of the students sampled completed four or more semesters of career/technical education while only about 17% took 1­3 semesters indicated that about 3 of 4 students in career/technical education were vocational concentrators. This finding can be interpreted as an indicator of success for students entering career/technical education, or as an indicator that CTE programs have been successfully screening out students who cannot complete the vocational training. Graduation from CTE was substantially lower for students with cognitive disabilities in Cohort I than for students with learning disabilities, although overall there was no significant difference between the proficiency scores of students exiting from joint vocational schools compared to students exiting from high school. This would suggest that high schools served students with both the least and the greatest disabilities, overall, though these findings are still somewhat tentative. . The finding that African­American students were 25% of the students who did not receive either vocational education or transition services is a concern, but may also be related to the finding that many of these students were focusing on four­year college outcomes. When these results were discussed with the teachers and parent mentors who conducted the surveys, they noted that low vocational education and transition participation rates for African­American
Page 24 of 36 students may be related to lack of parental or postschool role models who had pursued advanced career and technical education. Participation in mainstream academics was harder to assess from the findings of OLTS Cohort and Cohort II. Eighty percent of OLTS Cohort I indicated participation in mainstream academics and OLTS Cohort II showed about 75% of students sampled as having participated in 40% or more of their classes in regular academics. NLTS2 showed that 70% of students sampled nationally took any academic mainstream courses, but it also encountered difficulties in quantifying the extent of participation in regular education. The NLTS2 figures indicate that only 2% of students nationally took no courses outside of special education, comparable to Ohio’s findings of 2% for students in self­contained classrooms. . Student ratings of secondary services were consistent across OLTS Cohort I and Cohort II. Generally, students’ rated: (a) work on their own and (b) career and technical education as the two services that were most helpful in their transition. Both cohorts found proficiency testing to be significantly less helpful than other parts of their high school experience, even for students who were able to pass most or all of their testing areas. Whether this rating actually related to the helpfulness of proficiency testing or to the general onerousness of testing was unclear. Students in both cohorts generally appreciated special education and transition services rating IEP meetings, supervised work experiences, and in­school work experiences more highly. One caution in interpreting this data was that special education staff conducted the surveys and could have biased these ratings. Anticipated Postschool Outcomes Anticipated postschool outcomes were highly consistent across both of the OLTS cohorts. About 50% of students interviewed in Cohort I and II anticipated working full­time after graduation and about 30% anticipated working part­time. More than 62% anticipated attending a four­year college, two­year college, or technical school. These findings were somewhat higher than NLTS2 data which found that 68% of their national sample of students with disabilities planned to work competitively and about 60% anticipated some type of postsecondary education. When these findings were discussed with the teachers and parent mentors who conducted the survey, it was noted that academic mainstreaming had brought the aspirations of these students in line with those of their non­disabled peers, 80% of whom were anticipating postsecondary education.
Page 25 of 36 One concern that was noted in the area of postsecondary education goals was that these goals often did not relate to student performance in regard to academics. Significant numbers of African­American females with mental retardation anticipated postsecondary education despite passing none of their proficiency tests. Another concern was the gap between transition services provided by special education and guidance counselors. The special educators who conducted the survey indicated that they did not have much contact with totally mainstreamed special education students and depended on guidance counselors to assure that appropriate courses were being taken. Additionally, several of them noted that the focus of transition specialists was still on transition to work rather than postsecondary education and that they needed additional training in postsecondary options and collaboration with high school guidance counselors to address the skyrocketing postsecondary education goals of students with disabilities. The areas of employment anticipated by both OLTS cohorts were generally consistent with non­traditional (or other) areas of employment indicated for 20­30% of students surveyed. Healthcare, food service, auto mechanics, computers, and construction were leading areas for students possibly due to the number of CTE programs in these areas. The large proportion of “other” postschool employment goals were in areas that would require postsecondary education such as engineering, broadcasting, fashion design, forestry, and law enforcement. Postschool community participation and independent living goals underscored the importance of involving the families in transition planning. Nearly half of the students in both cohorts reported that they would be continuing to live with their family after graduation. Many of the students planning to live on their own planned to enter full­time employment. Student community goals also indicated the importance of a drivers’ license and a car with only about 1 in 7 students indicating that they planned to use public transportation after graduation. Aside from the usual goals of going to the mall and movies for youth, 40% of the students with disabilities who were sampled indicated that religious activities would be important after graduation. This finding suggested that religious organizations may represent a relatively large and untapped resource in establishing support networks for graduating students with disabilities. Anticipated sources of financial support shown in Figure 10 also underscored the importance of involving family members in transition planning as they were listed as the most common financial support (other than employment) for students with disabilities after graduation. The persons who conducted the surveys reported that two of the biggest problems in
Page 26 of 36 getting students to apply for scholarships and student loans related to parents being either unwilling or unable to provide the required financial documentation. They reported that they helped as much as possible, but they could not fill in for the parents in regard to this responsibility. Actual Postschool Outcomes for Cohort I As previously noted, only 205 usable followup surveys were obtained for Cohort I. This was related to the fact that only 20 of the 52 schools that collected exit data for Cohort I were also able to collect followup data. Additionally, 24 surveys were unusable due to inability to match numbers with the students’ corresponding exit data. In Ohio, approximately 68% of graduates with disabilities who were one year from leaving school were reported to be working for pay at the time of their interview and 36% were working full­time (32 or more hours per week). These outcomes compared to 40% full­time employment rates (35 or more hours per week) for NLTS2 students who were out of school for up to two years and 55% for 2003 high school graduates from the general population. The average hourly wage reported for Ohio graduates one year from leaving school was $7.31 per hour compared to the national average for school completers of $7.20. The average hours per week for Ohio graduates was 31 hours compared to a national rate of 29 hours. Job satisfaction for Ohio graduates was nearly identical to NLTS2 satisfaction rating of 43% “very satisfied” and 18% “dissatisfied” or “very dissatisfied.” These data suggested that employment outcomes in Ohio were roughly comparable to national findings, and that special education graduates continued to lag behind their typical peers in employment outcomes. Utilization of vocational rehabilitation (VR) services from the Rehabilitation Services Commission (RSC) was considerably lower than anticipated with only about 50% of graduates receiving services as anticipated. Adult services were rated the lowest in satisfaction ratings with 24% of students indicating they were “dissatisfied” or “very dissatisfied.” At the time of the interview, less than one graduate in ten was reported to be receiving services from RSC. This underscored the importance of involving schools and natural supports in the transition to adulthood. The types of employment reported by Ohio graduates were 22% in food service compared to about 19% nationally. Some of the categories used by NLTS2 were not comparable to Ohio, but certain similarities were noted. These included the finding that: (a) very few
Page 27 of 36 graduates in Ohio and nationally went into clerical jobs (less than 1%), and (b) a large proportion of Ohio and national graduates went into other fields (about 25­35%). When these findings were discussed with teachers and the surveyors conducting the survey, they noted that clerical fields were generally a poor match for the majority of special education graduates because of their reading and writing disabilities. The relatively high proportion of graduates who entered food service suggested that one year from graduation, many of the jobs were not related to students’ career paths. In Ohio, only one graduate in three that worked in food service had anticipated entering that field. Conversely, graduate employment in fields such as automotive, computers, health care, and human services were much lower than anticipated one year from graduation. However, NLTS2 findings suggest that employment outcomes improve over time and the findings of three­ year followup will give a much clearer picture of this situation. Graduate satisfaction with employment The reasons for not entering employment as anticipated were first and foremost a result of graduates entering postsecondary education instead of seeking employment as planned. This would suggest that career goals for many students were not finalized by graduation. The major problems that graduates with disabilities encountered in finding and maintaining employment were not being able to find a job, transportation problems, and not having the necessary skills. Loss of benefits and not wanting to work were reported for slightly over 10% of the unemployed graduates. These findings suggested that assistance in job placement, transportation, vocational training, and benefits counseling would be the primary intervention points for improving employment outcomes for graduates with disabilities. The postsecondary education outcomes for Ohio graduates with disabilities showed a considerable gap between expectations and outcomes. About 21% of students anticipated entering four­year colleges, with only 14% enrolling, and 10% still in a four­year college at the end of one year. This compared to NLTS2 findings of 9% four­year college enrollment and 6% retention at the end of one­year. Better outcomes were noted in relation to two­year colleges with 20% anticipating entering a two­year college, 18% reporting enrollment, and 13% reporting being enrolled at the time of the interview at the end of one year after graduation. NLTS2 reported 20% two­year college enrollment and 10% retention. Typical retention rates for students without disabilities were 28% at the end of one­year for four­year colleges and 12% for two­year colleges. These findings suggested that graduates with disabilities fared considerably
Page 28 of 36 better in achieving two­year than four­year college goals and that enrollment and retention in four­year colleges showed the largest gap between graduates with and without disabilities. The primary educational supports reported by graduates who entered postsecondary education were tutoring, extra time for tests, and remedial classes. Only 13% reported having had a tour of student disability services, and while this response may have been lowered by the phrasing of the question in the OLTS survey, it was consistent with NLTS2 findings that more than 52% of national graduates with disabilities did not consider themselves as having a disability and 65% nationally who were not receiving any accommodations or services. These findings highlighted the need for additional efforts in the areas of self­determination and self­ advocacy training, as well as efforts to help students with disabilities feel more comfortable in disclosing their disability. The reasons for not attending postsecondary education as planned fell primarily in the area of financial need. One major discrepancy that was identified for Cohort II was the difference between plans to use scholarships and student loans, and the number of students who had applied for these supports at the time of graduation. The teachers and surveyors who conducted the study noted that they had observed a number of reasons for this. The strongest concern they voiced was lack of parental follow­through on providing information about their income and assets. Some parents were reported to have lacked the ability to fill out the necessary forms, while others simply refused to divulge the information. This finding underscored the importance of providing some type of parental support in this process. The engagement, work, and postsecondary education outcomes showed that proficient graduates who focused on two­year colleges were more likely to be fully engaged after graduation. Conversely, graduates who did not pass their ninth grade proficiencies were largely unsuccessful in achieving their postsecondary education goals. Interestingly, proficiency scores did not appear to make a difference in employment outcomes one year after graduation for students who had learning and other disabilities. This finding mirrored a similar finding in NLTS2 which found no initial differences in the early postschool employment rates of school completers and school dropouts. The overall engagement of graduates with disabilities in Ohio indicated that about one­ fifth were unemployed and one­fifth underemployed at the time of the interview. NLTS2 found nationally that 21% of out of school youth were unemployed. Eighteen percent of Ohio’s
Page 29 of 36 graduates were employed and attending postsecondary education compared to 21% nationally. Only two predictors emerged as significant in relation to the postschool engagement of Ohio graduates with disabilities: (a) having a paying job before leaving high school and (b) passage of proficiency tests. These predictors held even after controlling for gender, ethnicity, level of disability, secondary programs, school setting, adult agency involvement, and vocational education. This suggested that an focusing on in­school outcomes rather than programs or disability status should be the guiding principle for schools. General Recommendations A few common themes emerged from an examination of the data and from followup meetings with the teachers and parent mentors who conducted the survey. These can be summarized as follows: 1. The need to bolster supports for postsecondary education of students with disabilities. While students with disabilities in Ohio and nationally are planning to enter postsecondary education at unprecedented rates, many are not able to enroll for financial reasons and more are lost in the first year of schooling. This is true both nationally and in Ohio. Some possible points of intervention include: (a) training for students related to self­determination and self­advocacy, (b) training and supports for parents and students in regard to applying for financial aid and student loans, and (c) training for transition specialists related to postsecondary education preparation issues, (d) promotion of collaboration between special education transition planners and guidance counselors, and (e) assuring that students are successful relative to Ohio’s proficiency testing and college entrance examinations. 2. The need to assure that students entering employment after graduation have a job by graduation. Progress in the general curriculum was only one of two predictors of postschool engagement. Schools need to assure that students that want to work after graduation are provided the needed vocational training, job placement, and transportation supports as part of their transition plans. This was particularly important for students with disabilities in urban areas who had far fewer resources in regard to employment. Some possible points of intervention would include: (a) greater access to vocational training, (b) job search skills training, (c) job clubs, and (d) parent training in regard to use of community contacts to find jobs. 3. The need to focus on special education outcomes rather than programs. This study suggested that the way that special education services were delivered was less important than a focus on
Page 30 of 36 particular student outcomes. This would suggest that program decisions should ultimately be guided by whether a particular program will result in a critical outcome for a student with a disability. Participation in regular academics should be seen as a means for a student to achieve academic proficiency, not as an end in itself. This is true for participation in work study and other transitional programs. This study indicated that these programs have little value if they do not result in the outcome of student employment at the time of graduation. Some possible intervention points include: (a) identifying in­school and academic outcomes of students with disabilities with disabilities who participate in given school programs, (b) using these outcomes to guide IEP and transition planning, and (c) allocating more resources to programs that provide either of these outcomes or both. 4. The need for articulation agreements between secondary and postsecondary education programs. This study suggested that a large proportion of special education graduates were attending remedial classes after graduation and that many were dropping out in the first year of postsecondary education. This finding suggested that secondary education programs are sending students into postsecondary education programs without the necessary skills to succeed. Some possible intervention points might include: (a) greater collaboration between high schools and postsecondary programs in identifying and addressing remedial education needs and (b) provision of high school funded remedial programs in postsecondary education settings to enhance enrollment and decrease the financial burden on special education graduates.
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Page 35 of 36 Table of Contents Method .......................................................................................................................................3 Instrument ...............................................................................................................................3 Local Education Agency (LEA) Recruitment ..........................................................................4 Coding and Analysis ...............................................................................................................5 The OLTS Sample...................................................................................................................6 General Observations Regarding Sampling..........................................................................8 Results ........................................................................................................................................9 Transition Planning .................................................................................................................9 Secondary Programs................................................................................................................9 Cohort I – School Programs.................................................................................................9 Career and Technical Education ........................................................................................10 Student Ratings of Secondary Programs ............................................................................11 Anticipated Postschool Outcomes .........................................................................................12 Work and Education Goals ................................................................................................12 Independent Living and Leisure Goals...............................................................................13 Anticipated Financial Support ...........................................................................................14 Postschool Outcomes for Cohort I .........................................................................................14 Planned vs. Actual Work Outcomes and VR Support – Cohort I........................................15 Planned vs. Actual Outcomes in Postsecondary Education – Cohort I................................16 Postschool Engagement Levels – Cohort I.........................................................................17 Predictors of Postschool Engagement – Cohort I ...............................................................20 Discussion.................................................................................................................................21 Procedural Findings...............................................................................................................22 Sampling ...........................................................................................................................22 Instrument .........................................................................................................................23 Coding and Analysis..........................................................................................................23 Secondary Programs..............................................................................................................24 Anticipated Postschool Outcomes .........................................................................................25 Actual Postschool Outcomes for Cohort I..............................................................................27 General Recommendations....................................................................................................30
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