I was working with a colleague the other day and overheard a discussion between students on a nearby table, they couldn’t work out how well they were doing on their course and if they were doing enough work. They were able to access their assignment feedback, and their tutors provided opportunities for formative assessment, but it still wasn’t enough to alleviate their worries. They wanted more information.

So how can we put information in the hands of the students? The answer could be a data analytics, something that is gaining traction in the education sector, where it is normally called learning analytics. Learning analytics can be defined as ‘the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimising learning and the environments in which it occurs’ (Siemens, 2011 in: LACE, 2015). As an institution we already capture and store lots of information about our students, but the learning analytics movement focuses on the actions that comes out the analysis of that data. Analyses move from descriptive to predictive, and maybe to prescriptive.

Empty lecture hallThese analyses can be quite simple, for example: if attendance monitoring indicates that students don’t turn up to Thursday 9am lectures, then it would make sense to reschedule the lecture for another time. Comparing student attainment with library resource access may throw up interesting patterns; this may help tutors target students for support. With all the interest from the sector, Jisc have commissioned a project to develop a learning analytics solution for UK FE and HE institutions.

Using this data to predict or generalise raises a number of ethical and legal issues. A group of interested parties are working to define and find solutions for these issues, led by Jisc, LACE and the Apereo Foundation. In November 2014, Jisc published a Code of Practice for learning analytics detailing the key ethical and legal considerations for institutions. Since then, they have hosted a number of events where colleagues from institutions across Europe have been able to discuss them in more detail, leading to the publishing of A taxonomy of ethical, legal and logistical issues of learning analytics v1.0.

The Jisc learning analytics project has 5 strands:

    Learning analytics architecture

  • the ethical and legal issues,
  • institutional infrastructure,
  • choosing suitable analytics tools,
  • a staff dashboard, and
  • a student app.

I have been lucky to be involved with the Jisc learning analytics project since last summer and was invited to attend a scoping meeting for the student app project in London at the end of February. It became clear that the scope of such an app was unlimited, so it initially focussed on delivering the key information a student needs to their devices in a way they can intuitively understand when they need it. With an ambitious time-scale to get a beta version in students’ hands by October 2015 for a pilots, soon students will have access to pertinent information about their academic performance.

That overheard conversation will be changed dramatically. The students will know their progress and engagement in their own education at-a-glance. Learning analytics really puts the student at the centre of education.

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