Study Progression, Success and Program Component Selection

Abstract

This article evaluates some of the underlying assumptions of a data analytics initiative being undertaken at an Australian university, which provide student support staff with lists of students who have enrolled in program components (classes) different from the plan prescribed in the curriculum (e.g., out of sequence, not on the plan). This study was undertaken with the assumption that these ‘inappropriate’ enrolments might negatively impact student progression and success. The analysis suggests that student progression is significant negatively affected; in particular, students can be prevented from studying full-time, extending the time needed to complete their program. However, the impact on student success was found to be minimal. The findings help to demonstrate the impact of the data initiative, and the value of continuing and expanding its use into the future.