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|Title:||Examining the Effectiveness of Self-Referenced and Peer-Referenced Learning Analytics Dashboards in Enhancing Students’ Self-Efficacy: Taking Individual Differences Into Account|
Tan, Jennifer Pei-Ling
|Publisher:||International Society of the Learning Sciences|
|Citation:||Jonathan, C., Koh, E., & Tan, J. P. (2022). Examining the effectiveness of self-referenced and peer-referenced learning analytics dashboards in enhancing students’ self-efficacy: Taking individual differences into account. In Weinberger, A. Chen, W., Hernández-Leo, D., & Chen, B. (Eds.), Proceedings of the 15th International Conference on Computer-Supported Collaborative Learning - CSCL 2022 (pp. 250-257). International Society of the Learning Sciences.|
|Abstract:||This study examined the effectiveness of self-referenced and peer-referenced learning analytics (LA) dashboards in enhancing students’ self-efficacy in critical reading, taking individual differences into account. A quasi-experiment with an embedded mixed methods approach was used, with 209 Grade 9 students who participated in critical reading online discussions in the English Language (EL) subject during a nine-week trial. Multiple regression analysis revealed that individual differences, namely, learning goals, performance goals, and gender, were significant predictors of critical reading self-efficacy, whereas dashboard type and initial achievement levels were not. Epistemic network analysis highlighted the importance of students’ perceptions of how helpful and motivating they found the dashboards to be. Put together, the results highlight the theoretical and methodological importance of taking individual differences into account and have practical implications for designing more purposeful formative LA dashboards for enhancing students’ self-efficacy.|
|Appears in Collections:||ISLS Annual Meeting 2022|
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