The basics of learner analytics

Each time a student logs into your institutions Virtual Learning Environment (VLE), a new session is logged in its database. The summary of login information can be helpful to assess student engagement over time. Three metrics are beneficial:

  1. Average session duration: The average time students are active on the VLE for each login.
  2. Frequency: how often a student logs in over a given period, such as a week or month.
  3. Recency: The duration since the last session on the VLE.

You can use the average session duration to assess if students are engaging longer with their online learning. This metric requires your VLE to accurately measure when the student is active and does not just have the VLE open in a tab while watching Average session duration is beneficial at the course or module level to track the time students are on the VLE against the expected time and at the institution level to track progress from year to year.

The average frequency of sessions is a good marker for how engaged students are on a course. You may set expectations of how often a full-time student is supposed to log in, at least once per working day, for instance, and then you can track against this. 

Identifying students at risk of dropping out of a course is crucial as they may need support. Tracking students who have not logged into the system for a set number of days, say five during term-time on a full-time course, will allow you to identify students who might need academic or pastoral help. The recency table will help you determine how long it has been since students last logged in and show the number that falls outside your expectations. 

For these three metrics to be valid, you need to have trust in their accuracy; this includes the technical accuracy of how they are tracked and how it captures all the online activity a student might complete. Other metrics can help, but these are a great starting point.