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The effectiveness of learning analytics for identifying at risk students in higher education – Summary

Ed Foster & Rebecca Siddle (2019) The effectiveness of learning analytics for identifying at-risk students in higher education, Assessment & Evaluation in Higher Education, DOI: 10.1080/02602938.2019.1682118 
Ed Foster and Rebecca Siddle, Centre for Student & Community Engagement, Nottingham Trent University

The UK higher education sector is increasingly facing up the challenges of reducing disparities of attainment between socially disadvantaged students and their more advantaged peers. Pressures from the Office for Students’ Access and Participation plans will only place more pressure on institutions to develop clear and effective strategies for improving student outcomes.

One of the challenges faced by all institutions is how to effectively target support or interventions at the students that require it most. Foster & Siddle (2019) explore the effectiveness of using learning analytics to identify students in need and contrast it with using student background, specifically widening participation status. The paper discusses the accuracy of this approach and, perhaps more importantly, the efficiency of using learning analytics compared to the strategy of targeting support based on student background.

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The paper can be accessed via DOI: 10.1080/02602938.2019.1682118

If, for whatever reason you are unable to access the paper this way, the authors have agreed to share a small number of their personal copies with us. Please contact hello@solutionpath.co.uk

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