Leveraging learning analytics
Niall Sclater, consultant and director at Sclater Digital, discusses leveraging learning analytics to enhance the student experience
Over the last few years ‘analytics’ has moved from a buzzword to a prominent feature across many areas of university practice, as institutions try to better understand and act on trends in the data they’re accumulating.
Learning analytics – which builds on data collected about students’ learning activities – can help universities improve the student experience, but doing this effectively has been highlighted as one of the biggest challenges facing the sector in a Jisc co-design consultation.
In an attempt to understand what’s happening in the sector, I have been speaking to people at a number of UK universities and colleges that are known to be pioneering the use of learning analytics.
Where to start
The first thing to note is that there is no simple, one-size-fits-all method to gathering learning analytics. The institutions I spoke to varied hugely in their organisational structures and approaches, from the University of Edinburgh operating a variety of analytics projects across its schools and departments, to the more centralised student support system used at Bridgwater College. While there’s much to be learnt from the experience of others, organisations clearly need to start by identifying their own specific strategic and educational requirements.
Motivations for using learning analytics also varied widely across the institutions. For some, increasing retention was seen as vital while others, which perhaps didn’t have huge problems with drop-out, felt that improving the student experience was a bigger priority, or increasing their National Student Survey scores. When undertaking your own analytics programme you need to be clear what the aims and objectives are, and then set out how you’ll go about achieving them.
Also think about the most appropriate data sources. Student information systems and virtual learning environments (VLEs) typically provide most of the data, but you might want to look into other sources and how these can be used, such as swipe or proximity cards for monitoring attendance, which has been shown to correlate strongly with achievement.
For example, we know that students who fail to engage with library services can be at higher risk of drop-out. There are some excellent cases of institutions tapping into this, such as the University of Bedfordshire, where students are required to swipe a card when using the library helpdesk, thus providing a source of engagement data.
A question of ethics
One thing that’s causing some nervousness around learning analytics is ensuring that the use of student data is ethical and legal.
As analytics involves sharing data between multiple software systems, departments and even other universities, respecting privacy is essential. In my conversations there were concerns with how information is being used for learning analytics, although interestingly these often came from staff, rather than the students themselves.
While ethical implications hadn’t actually proved too problematic for the institutions I spoke with, many had taken specific actions to abate potential issues. For example, The Open University worked with its student association to develop a policy on the ethical use of student data for learning analytics.
What comes next?
It’s important to emphasise that the UK is at a very early stage of understanding and deploying learning analytics. Many institutions are only starting to consider how they can best utilise the large datasets they are accumulating. Even the people I spoke to with the most experience felt that they were just beginning to understand how to develop effective metrics and interventions, and as such were reluctant to claim any significant outcomes to date.
But don’t let that deter you. All of the institutions I engaged felt that learning analytics was increasingly necessary to help them work out how to improve the experience for their learners. Jisc is also helping here, working with sector partners to develop basic tools for tracking and intervention, as well as a code of practice to deal with concerns around privacy. To find out more visit the Effective Learning Analytics blog or contact Paul Bailey, Jisc senior co-design manager.