About Learning Analytics

Interest in the field of learner analytics has been growing over the last few years, with influential publications such as the New Media Consortium’s “Horizon Reports” having identified them as important new technologies for the last four successive years. This section gives a short overview to this emerging field.

Learning analytics has been recently been 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” (LAK 11, https://tekri.athabascau.ca/analytics/).

Another widely cited working definition is that “Analytics is the process of developing actionable insights through problem definition and the application of statistical models against existing and/or simulated future data” (Cooper 2012:3, MacNeil et al 2014)

In its broadest sense  then it entails collecting and interpreting data about learner’s activities so as to improve the learning experience.

The concept of analytics in education is not new. Educational establishments have been collecting all sorts of data for years, ranging from exam results to the popularity of specific library books on course reading lists. However there have been a few changes in approaches to this kind of data in recent years.

One component of this can be seen in the general emergence of “league tables” and other metrics ranking Institutions’ performance, and a requirement for Institutions to publish Key Informations Sets. Part of this interest is also cultural, as people have an increased expectation that they can access data held about themselves, and an increased interest in the use of technology to quantify aspects of their own lives.

In conjunction with this, so much more of our learners’ activities are mediated via the use of technology. As a result, more of these activities leave a digital footprint. This can range from very formalised sets of institutional data on one hand, such as exam performance, through to very informal types of engagement with social networking channels on the other. As more of this data is generated, we also now have better technologies to store, analyse and visualise it. It seems obvious perhaps that with access to this data, and the means to interpret it, that we might want to harness this to improve the educational experience for our learners, whilst equally making it more effective at Institutional and sector level.

See also:

Learning Analytics: Levels of Analytics

Learning Analytics: Critical Factors

Learning Analytics: Useful Resources and References