Abstract
Learning analytics dashboards (LADs) are emerging tools that convert abstract, complex information with visualizations to facilitate teachers’ data-driven pedagogical decision-making. While many LADs have been designed, teachers’ capacities for using such LADs are not well articulated in the literature. To fill the gap, this study provided a conceptual definition highlighting data visualization literacy and integrating abilities as two critical components in LAD capacities. Moreover, this study assessed teachers’ LAD capacities through a knowledge test and examined the combined effect of teachers’ self-regulation, emotions, perceptions of LAD usefulness and ease of use, and online teaching experience on teachers’ achievements of the LAD capacity knowledge test. The results of a Bayesian path analysis based on the sample of 150 teachers show that (1) teachers’ self-regulation and perceived LAD usefulness were the two main factors that made significant impacts on their LAD capacities, (2) the factors of negative emotions and perceived ease of use had effects on teachers’ LAD capacities, but such effects were mediated by self-regulation and perceived usefulness, and (3) online teaching experience had little effect on LAD capacities. This is the first study that conceptually researches teachers’ capacities for LAD uses. The findings offer novel perspectives into the complexity of LAD using process and demonstrate the importance of teachers’ self-regulation, emotions, and perceptions of usefulness in enhancing teachers’ abilities to use LADs for pedagogical decisions and actions.
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Data availability
The raw datasets used in the current study are not publicly available due to ethics requirements, but the anonymized data are available from the corresponding author upon reasonable request.
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Appendices
Appendix 1
Suppose that you are teaching an online course with a learning management system (LMS). A learning dashboard is supplied for you to track students' study trajectories and evaluate performance. The dashboard contains several visualizations with different functions. Based on your previous knowledge and experience, please answer the following questions.
LAD capacities assessment
Appendix 2
Figure
Trace plots for the direct effects
Appendix 3
Figure 7
Autocorrelation plots for the direct effects
Appendix 4
Figure 8
Bayesian posterior distribution plots for the direct effects
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Liu, Y., Huang, L. & Doleck, T. How teachers’ self-regulation, emotions, perceptions, and experiences predict their capacities for learning analytics dashboard: A Bayesian approach. Educ Inf Technol (2023). https://doi.org/10.1007/s10639-023-12163-z
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DOI: https://doi.org/10.1007/s10639-023-12163-z