The engagement of university teachers with predictive learning analytics

Herodotou, Christothea; Maguire, Claire; McDowell, Nicola D.; Hlosta, Martin and Boroowa, Avinash (2021). The engagement of university teachers with predictive learning analytics. Computers & Education, 173, article no. 104285.

DOI: https://doi.org/10.1016/j.compedu.2021.104285

Abstract

Predictive learning analytics (PLA) is an educational innovation that has the potential to enhance the teaching practice and facilitate students' learning and success. Yet, the degree of adoption of PLA across educational institutions remains limited, while teachers who make use of PLA do not engage with it in a systematic manner. Informed by the Unified Theory of Acceptance and Use of Technology (UTAUT), we conducted eleven in-depth interviews with university teachers and examined their engagement patterns with PLA for the duration of a 37-week undergraduate course. We aimed to identify (a) factors that explain the degree of using PLA in the teaching practice, and (b) the impact of an intervention - sending email reminders to teachers - on facilitating systematic engagement with PLA. Findings suggested that, amongst the factors facilitating engagement with PLA were performance expectancy, effort expectancy, and social influence. Amongst the factors inhibiting engagement with PLA were performance expectancy and facilitated conditions related to training and a lack of understanding of predictive data. Implications for the adoption and use of PLA in higher education are discussed.

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