Through advancements of Technology-Enhanced Learning an opportunity has emerged to provide students with timely feedback using Learning Analytics in the form of visualizations. To afford actual impact on learning, such tools have to be informed by theories of education. Particularly, educational research shows that individual differences play a significant role in explaining students’ learning process. However, limited empirical research has investigated the role of theoretical constructs such as motivational factors that are underlying the observed differences between individuals. In this work, we conducted a field experiment to examine the effect of three designed Learning Analytics Visualizations on students’ participation in online discussions in authentic course settings. Using hierarchical linear mixed models, our results revealed different effects of visualizations on the quantity and quality of messages posted by students with different Achievement Goal Orientations. Findings highlight the methodological importance of considering individual differences and pose important implications for future design of Learning Analytics Visualizations.
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Thesis advisor: Hatala, Marek
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