Predicting Secondary School Drop-Out Rates for Students with a Primary Diagnosis of a Specific Learning Disability

Emily Bruce, Tennessee State University

Abstract

The purpose of this study was to predict secondary school drop-out for students with a primary diagnosis of a Specific Learning Disability (SLD). Specifically, this study investigated the direct effects of socioeconomic status (SES), gender, achievement, adaptive measures, and SLD in a hierarchical logistic regression. Data from the National Longitudinal Transitional Study II (NLTS2) was used in the analysis (N = 2,370). The results from the final logistic regression model indicated direct effects for predicted drop-out from SES, SLD, self-care, social skills, and classroom behavior. However, an interaction between SLD and social skills predicted that students with SLD and better social skills had a 14% decreased likelihood of secondary school drop-out (B = -.15; Exp(B) = .86; p < .01). The outcomes of this study may be helpful in identifying areas for interventions to decrease drop-out.^

Subject Area

Educational psychology|Psychology

Recommended Citation

Emily Bruce, "Predicting Secondary School Drop-Out Rates for Students with a Primary Diagnosis of a Specific Learning Disability" (2016). ETD Collection for Tennessee State University. Paper AAI10119069.
http://digitalscholarship.tnstate.edu/dissertations/AAI10119069

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