Testing and exploring the predictors of faculty motivation to use learning analytics to enhance teaching effectiveness

Journal of Computing in Higher Education(2022)

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Abstract
The purpose of this mixed-methods study was to explore factors affecting faculty members’ motivation to use learning analytics (LA) to improve their teaching. In the quantitative phase, 107 faculty members completed an online survey about their motivation to use LA. The results showed that cost, utility, attainment value, and competence all predicted intrinsic motivation to use LA; then, in turn, positive introjected motivation and amotivation predicted faculty LA usage. In the qualitative phase, ten faculty participated in three focus groups, and seven themes emerged as key factors that affected their motivation to use LA. The themes involving motivating factors included tracking and monitoring learning activities, early alert, improve teaching effectiveness, institutional training, and support. Alternatively, demotivating factors included the cost in terms of time, lack of data competence, and the ‘un-structuredness’ of the dataset. The paper also discussed the mechanisms for increasing LA usage among faculty members to improve their teaching.
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Key words
Faculty, Learning analytics, Motivation, Self-determination, Expectancy-value, Teaching effectiveness
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