Mind the Gap

Abstract

The issue of student attrition is a complex one and has been an area of research interest among education researchers. Recently, education researchers are proposing to tap into the large amount of student data that are housed within the institution's data warehouse. This big student data of demography, learning journey, and their interactions with the institution presents a rich source of insights that can be discovered using advanced analytics. Consequently, education researchers have put forward predictive models, suggest the use of data triggers and dashboards aimed at improving student retention. This however has been met with limited success to date. From experience, there remains a gap between the analytics and the operationalization of the analytics. Consequently, this gap needs to be addressed to achieve student retention. The authors propose a dual framework to close this gap. While this framework was developed in the context of creating a solution for student attrition, it is sufficiently generalizable to analytical solutions for problems around student learning.