This study explored the academic outcomes of two-year college students who were reinstated following an academic suspension at a small, Midwestern technical college. Binary logistic regression was used to identify factors that were predictive of student reinstatement outcomes (reinstatement success or reinstatement nonsuccess). The analysis included independent variables of age, gender, cumulative quality point status, term of dismissal quality point status, and evidence of a mental health concern. As an independent variable, evidence of a mental health concern was dichotomous (yes or no) and a qualitative review of suspension appeal paperwork submitted by students was used to identify any self-reported or documented evidence of a mental health concern. The overall model, which included all independent variables, was found to be statistically significant and correctly predicted 65.7% of all cases. A significant relationship was also identified between student reinstatement outcomes and the independent variables of age and cumulative quality point status. In accordance with the findings of this study, limitations, recommendations for future research, and implications for future practice are discussed.
Date of Degree
Doctor of Education (EdD)
Counseling and Student Personnel
Stene Winkler, E. E. (2020). Predicting academic outcomes of reinstated technical college students following an academic suspension [Doctoral dissertation, Minnesota State University, Mankato]. Cornerstone: A Collection of Scholarly and Creative Works for Minnesota State University, Mankato. https://cornerstone.lib.mnsu.edu/etds/1038
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