Pham Cong Hiep, Pham Khanh Duy

Main Article Content

Abstract

Early detection of student performance factors is essential for universities to develop supportive academic initiatives that suit individual students.  This study examines four academic factors, including Grade Point Average (GPA) from Grade 12, GPA of courses taken from the university, course load, and previous course failure in the university, to ascertain the relationship between these factors and course performance. Academic study records of 9048 semesterly student performance in 2021 from an English-speaking international university in Vietnam were quantitatively examined to test the developed theoretical model. The results found a significant correlation between all factors except current course load and student performance. Though such data has been commonly stored in institutional student record systems, the developed academically-based predictive system can provide value to student-support activities and decision-making to enhance student performance early.

Keywords: Academic performance, early performance detection, academic predictive analytics.

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