What is it? Learning analytics is an umbrella term for the measurement, collection, analysis, and reporting of data about learners, for the purpose of understanding and optimising their learning and the environments in which it occurs.

Learner analytics is an area of learning analytics which focuses solely on the learners and attempts to identify targeted interventions that help mitigate the risks individual learners may experience while studying.

Evidence? Since the early 2010s, interest in learning analytics has increased rapidly and prompted the publication of many papers documenting small-scale experiments in the areas of education, psychology, computing and data science. Yet, much of what has been published lacks empirical rigour or peer review. Most literature reviews do not reflect upon the research design or theory of change of the studies included.

The existing evidence base suggests that well-designed learning analytics interventions tend to improve students’ outcomes. Whilst we can assume that students’ aspirations/attitudes are also positively affected, more causal research is needed to confirm this assumption.

Should HEPs adopt learning analytics? The existing evidence suggests that learning analytics can be beneficial for students. However, currently, there is no comprehensive model supported by a strong evidence base for instructors to make effective learning analytics interventions. There are also a number of challenges and limitations to the implementation of learning analytics that should be addressed in each context.