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Data-Driven Predictions of Academic Success among College Students in Saudi Arabia


Omar J. El-Moussa
Runna Alghazo
Maura A.E. Pilotti
Maura A.E. Pilotti

Abstract

Predictors of college performance are markers of learners' characteristics that can be used to optimize admission, advising, counseling, and instruction. The present study focused on female and male graduates of a Saudi Arabian university that follows a USA general education curriculum. Saudi Arabia exemplifies a society in transition from a rigid patriarchal system to one that is more gender equitable. The study investigated the extent to which gender, high-school Grade Point Average (hs-GPA), and the GAT (equivalent to the SAT I) can predict GPA at graduation, as well as verbal, analytical, and quantitative competencies of graduates in Business, Engineering, and Law. In our study, females outperformed males on most measures except on the GAT. Gender differences in the choice of major were also found. For all, hs-GPA and GAT were poor predictors of academic success. Alternative measures were proposed along with the use of a data-driven approach for predicting students' performance at a given institution.


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eISSN: 2310-7103