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Technology, Knowledge and Learning

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03.08.2021 | Original research

Learning Analytics for Programme Review: Evidence, Analysis, and Action to Improve Student Learning Outcomes

verfasst von: Christine Armatas, Theresa Kwong, Cecilia Chun, Christine Spratt, Dick Chan, Joanna Kwan

Erschienen in: Technology, Knowledge and Learning | Ausgabe 2/2022

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Abstract

The application of learning analytics (LA) to research and practice in higher education is expanding. Researchers and practitioners are using LA to provide an evidentiary basis across higher education to investigate student learning, to drive institutional quality improvement strategies, to determine at-risk behaviours and develop intervention strategies, to measure attrition more effectively and to improve curriculum design and evaluation in both on-campus and e-learning settings. This paper is a case study report of the novel application of LA to programme curriculum review from a major cross-institutional project in Hong Kong. The paper describes the rationale for the project, the conceptual model that led the approach and the development of a software tool that allowed the automation of statistical analyses specifically relevant to programme review. In addition, the paper addresses a major challenge that the project faced in relation to data governance. The paper concludes by proposing the potential benefits of LA for programme curriculum review.

Vorheriger Artikel Learning Analytics Intervention Improves Students’ Engagement in Online Learning

Nächster Artikel Implementation of Learning Analytics Indicators for Increasing Learners' Final Performance

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Titel: Learning Analytics for Programme Review: Evidence, Analysis, and Action to Improve Student Learning Outcomes
verfasst von: Christine Armatas
Theresa Kwong
Cecilia Chun
Christine Spratt
Dick Chan
Joanna Kwan
Publikationsdatum: 03.08.2021
Verlag: Springer Netherlands
Erschienen in: Technology, Knowledge and Learning / Ausgabe 2/2022
Print ISSN: 2211-1662
Elektronische ISSN: 2211-1670
DOI: https://doi.org/10.1007/s10758-021-09559-6

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