Learning Analytics in Open and Distance Higher Education: The Case of the Open University UK

Boroowa, A. and Herodotou, C. (2022). Learning Analytics in Open and Distance Higher Education: The Case of the Open University UK. In: Prinsloo, P.; Slade, S. and Khalil, M. eds. Learning Analytics in Open and Distributed Learning. SpringerBriefs in Education. Singapore: Springer, pp. 46–62.

DOI: https://doi.org/10.1007/978-981-19-0786-9_4

Abstract

This chapter reflects on two major learning analytics initiatives which took place at the Open University (OU) in recent years and which facilitated the adoption of analytics across the university. Analytics for Action (A4A) focused on the use of learning analytics to inform the learning design of online courses and Early Alert Indicators (EAI) examined the use of predictive learning analytics in online teaching and their potential to identify students at risk and inform teachers who can proactively intervene. The authors showcase how each initiative raised differing and shared challenges and highlight lessons learnt from their implementation. The OU has achieved significant progress in testing, implementing and widely adopting an evidence-based approach to learning analytics that help to inform practices in other open and distance higher education institutions. Yet, a number of challenges remain such as the scalability in the implementation of approaches, such as predictive learning analytics, especially when there are limited resources to employ teachers to communicate with students and moderate timely interventions. This chapter concludes by noting the importance of human interaction to facilitate and achieve learning outcomes. Learning analytics is not the panacea, rather how it is adopted and used determines the outcome.

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