Post-High School Outcomes of Adolescents with Learning Disabilities: Using Annual State Administrative Data and Predictive Analytics

Abstract

This study involved the analyses of extant data from two U.S. states of post-school outcomes (PSO) for students with a specific learning disability (SLD) one year after they had exited high school. The purpose of this study was to fill two gaps in the literature. The first gap was to understand what happened to these exiters in the first year after high school related to employment and further education or training at a state level. The second gap was to demonstrate the necessity of local and state education professionals to use PSO data, which is collected annually, by applying predictive analytics (PA) to support their decision making. The data analyses produced two main findings. One, the strongest predictors of PSO were students graduating from high school and their high school classroom placement. Two, PA was reasonably accurate in predicting PSO and demonstrated robust capabilities for reliable use on an annual basis to support policies, programs, and practices. Limitations of this study related to the data and number of predictors. The study concludes with implications of administrative state data use and PA for state and local education professionals and for researchers.