Analysis of Evidence-based Course of Study Predictors for Improving the Post-school Outcomes of Post-secondary Education and Employment for Students With Autism
Year: 2015
Type: article
Abstract: The purpose of this study was to conduct a secondary data analysis in order to examine the relationship of three evidence-based high school course of study predictors: (a) inclusion, (b) career and technical education, and (c) work-study experience, on the post-school outcomes for post-secondary education and employment, for a population of students with autism.Participants were selected from a sample of 5,919 students with disabilities in the state of Ohio.All students identified in the disability category of autism were included (N = 136).Results established three predictor variables for improving outcomes for post-secondary education and employment for students with autism.First, inclusion in the general education classes for at least 80% of the time was highly associated with post-school outcomes for post-secondary education.Second, academic proficiency, defined as passing all five of the Ohio graduation tests, was highly associated with post-school outcomes for post-secondary education.Finally, a work-study program was associated with positive employment outcomes.Implications for transition planning include: use of evidence-based predictors to improve post-school goals; and post-school goals should reflect a course of study that improves the odds of meeting that goal.Predictors such as inclusion or work-study programs can positively contribute to better transition planning that can improve opportunities for post-secondary education and employment.I would like to thank my committee for their guidance and support throughout this journey.Dr. Barton, I thank you for your patient guidance and gentle editing that helped me clarify my statistical jargon.Dr. Kritzer, I thank you for encouraging me to finish the dissertation journey, and Dr. Schenker, I thank you for helping me polish my statistical analysis.Dr. McMahan-Queen, I thank you for your insight, guidance, words of wisdom, and support.You have been a terrific teacher and coach throughout this process and I have learned so much from you.To Dr. Baer, thank you for helping me understand the epidemiological approach to the logistic regression.Finally, I want to
Author: Carol Feldman-Sparber
Institution: Kent State University
Language: English
Subfield: Education
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W2522616454