Completed project
Project | Learning analytics
31 January 2023
About Learning analytics
University learning analytics systems collate data on student engagement, for example attendance, and use of virtual learning and library facilities. This data can be used to identify students with low or no engagement, and so who might be at risk of lower attainment or even of withdrawing from their studies.
Some universities use this information to flag at-risk students who can be targeted for an intervention such as an email or a support call. A review by TASO has found that evidence suggests that interventions that are prompted by learning analytics systems can be effective but the impact is highly dependent on the context and design. There is no comprehensive model supported by a strong evidence base to guide universities, and there is little evidence from a UK setting.
To contribute the required evidence, we appointed Nottingham Trent University and Sheffield Hallam University to evaluate the effectiveness of interventions prompted by learning analytics – through two randomised controlled trials.
The Behavioural Insights Team has been appointed as an independent evaluator for the work.
Related outputs
Background
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.
The existing evidence suggests that using learning analytics data can be beneficial for students. However, there is currently no comprehensive model supported by a strong evidence base, and there are also a number of challenges and limitations to the implementation of learning analytics.