The University of Derby has been scoping early indicators (engagement analytics) for spotting students at risk of withdrawing in their SETL (Student Experience Traffic Lighting) project.
Challenges
Institutions generally hold a vast array of data about students, often in different systems which are not always interoperable. The data challenges experienced in this project include:
- predisposing factors, such as responsibility as a carer, means that students are more likely to withdraw from their studies, however it’s not always possible to capture this type of data as it’s not generally held in any IT system
- there is little interoperability between different data systems; for example, the data required to populate an engagement dashboard is held in at least seven different systems at the University
- each student is an individual who brings with them individual challenges to succeeding at and engaging with higher education
Benefits
Scoping out the type of data to be included in a dashboard of core engagement data:
- means that staff would be able to view a student’s level of engagement with the institution; for example, linking data on absences, access to the library and the VLE (Virtual Learning Environment) could help a tutor see if the student was still engaging in the course, even if they were absent due to illness
- has produced a change of thinking in the way students at risk of withdrawing will be supported at the University; i.e. it will be more proactive than reactive
- has helped staff identify key points in the student lifecycle where students are most likely to be at risk of withdrawal.
Recommendations
Engagement analytics goes beyond the hard data recorded in learning analytics, because:
- it’s dangerous to make decisions about student engagement based solely on a set of data, as understanding the context of the data is important and developing the relationship between the tutor and student is essential
- both staff and students find it useful to have their own customisable engagement dashboards
- soft data that can’t always be found on institutional systems should also be recorded and considered.
Further Information
If you would like to find out more about this project, the following resources may help: