Following on from last month’s Mental Health and Wellbeing Week, this extra post sees Chris Sheridan, eLearning coordinator for the Clinical Trials programme with the Usher Institute, exploring how monitoring online activity using learning analytics can help staff spot at-risk students…

It’s the start of term. Staff and students begin to flit around their courses, logging in often, navigating their way around, dipping into the forums and functions of their VLE, and generally finding their groove for the semester.

When induction time is over, the buzz dies down and the routine business of teaching and learning begins. This is when monitoring student activity becomes crucial. However, for staff, this is when other pressing tasks in the academic calendar take over. Who has time to watch individual student activity – making sure students are logging in regularly and participating in discussions, etc?

As student numbers grow there just aren’t the resources to keep a check on individuals in large cohorts of online courses, but this is where being online can actually help. Using learning analytic techniques to spot potential issues at a glance within the VLE can highlight students who may “vanish” further down the line.

Learning analytics can benefit staff and students in many ways, including:

• Improving future teaching methods and materials
• Creating personalised/tailored learning
• Showing students how their own learning is developing
• Highlighting students at risk

This last point is an important indicator to aid student retention. The benefit for staff is that the student can be contacted, and plans put in place to support them through any difficulties. The benefit for the student is they can go onto achieve academic success.

But it can also highlight much more in a student’s life. Issues otherwise left unknown can be uncovered and addressed. This Guardian article explains how using analytics can provide markers for the increasingly important matter of health and wellbeing. As pointed out, data and ethics should be considered and technology doesn’t replace the personalised touch of a real life support team, but can act as a “human optimisation system”. Anything that improves not only the student experience but the human experience, is priceless.

For our needs, big data isn’t necessary, and analytics don’t have to be as sophisticated as giant users such as Facebook might use. Google Analytics can be overkill with details like click and bounce rates, page views, and visitor frequency and recency. Really all that’s needed for meaningful results is the data already contained within the VLE. Let’s keep it simple – we just need something to trigger an alert for situations like the following:

• Student hasn’t logged in for a while
• Successful student begins to fail
• Student doesn’t participate in group work
• Student misses live sessions or appointments

Without reasonable explanation, these can all be warning signs of potential issues lurking in the student’s immediate outlook, which can worsen rapidly without intervention. If the red flags can be waved to the teaching and support team through the VLE, then despite rocky roads many academic journeys could continue, keeping students turned on and tuned in.