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Empowering learners with personalised learning approaches? Agency, equity and transparency in the context of learning analytics

Research output: Contribution to journalArticle

Original languageEnglish
Pages (from-to)554-567
Number of pages23
JournalAssessment & Evaluation in Higher Education
Issue number4
Early online date25 Nov 2019
Publication statusPublished - 2020


The emergence of personalised data technologies, such as learning analytics is framed as a solution to manage the needs of higher education student populations that are growing ever more diverse and larger in size. However, the current approach to learning analytics presents tensions between increasing student agency in making learning-related decisions and ‘datafying’ students in the process of collecting, analysing and interpreting data. This paper presents a study that explores staff and student experience of agency, equity, and transparency in existing data practices and expectations towards learning analytics in a UK university. The results show a number of intertwined factors that have contributed to the tensions between enhancing a learner’s control of their studies and, at the same time, diminishing their autonomy as an active agent in the process of learning analytics. This paper argues that learner empowerment should not be automatically assumed to have taken place as part of the adoption of learning analytics. Instead, the interwoven power relationships in a complex educational system and the interactions between humans and machines need to be taken into consideration when presenting learning analytics as an equitable process to enhance student agency and educational equity.

    Research areas

  • learning analytics, transparency, agency, equity

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