Session 73: Engagement analytics to support student engagement and continuation

Abstract

As the amount of data being created by universities increases Learning Analytics is, in turn, becoming more multifaceted and complex. How we define engagement and disengagement by students is complex, though important to understand if we are to help support student continuation. This presentation will outline the results of a staff consultation and survey, combined with large scale predictive analytics from several systems in order to establish which factors can most reliably predict a student is beginning to disengage from their studies and are at risk of discontinuing.

As important as using data in this manner is ensuring that any insights are actionable, and the data is made available to the most appropriate people to support students to arrest any further slippage in engagement. We will demonstrate a dashboard of the data and suggest possible interventions for staff to put in place for students to be supported to remain a member of their community of learning. In addition to this we will provide support around the data fluency for those engaging with the analytics insights.

This project is a collaboration between the LJMU academic community, Teaching and Learning Academy, Strategy Support Office, Academic Registry, and Senior Strategic Project Manager Student Experience, and reflects an institution wide approach in the use of data to support student continuation and the student experience.