Date of Award

2015

Document Type

Open Access Dissertation

Department

Educational Leadership and Policies

Sub-Department

Educational Administration

First Advisor

Katherine Chaddock

Abstract

This quantitative study explored students’ self-reported, pre-college academic self-concept and students’ self-reported, pre-college social self-concept and the likelihood of student withdrawal prior to their second year. Additionally, the interaction between academic self-concept and social self-concept and first-year academic performance were examined. Using data from the University of South Carolina, three binary logistic regression models were run to determine whether academic self-concept and social self-concept were significant predictors of student withdrawal and/or whether or not the self-concept variables moderated the relationship between students’ first-year academic performance and student withdrawal. Additional academic, financial, and demographic pre-college attributes were selected as control variables and included in each logistic regression model. The variables selected for this study reflect each of the three categories (family background, individual attributes, and pre-college schooling) of pre-entry characteristics in Tinto’s (1993) Student Integration Model, the theoretical framework for this study. As researchers have cited the need to include a psychological component to Tinto’s model (Berger & Lyon, 2005; Braxton, 2000; Pascarella & Terenzini, 1991; Robbins & Noeth, 2004), this research sought to advance the literature by determining whether academic self-concept and social self-concept were variables to include as additional pre-college characteristics in the Student Integration Model. The results from the study revealed there is not a statistically significant relationship between academic self-concept and student withdrawal or between social self-concept and student withdrawal. Additionally, neither self-concept variable moderates the relationship between students’ first-year academic performance and student withdrawal. However, there were several significant findings outside the scope of the research questions. Of the ten control variables used in this study, four were statistically significant predictors of student withdrawal, after controlling for the other variables in the model. As expected, first-year academic performance was a significant predictor of student withdrawal. Additionally, major declaration, student residency, and completion of the FAFSA were also significant predictors of student withdrawal.

Rights

© 2015, Elizabeth Orehovec

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