Abstract
The existing researches and developments of dashboard visualizing results from learning analytics mainly serve the instructors instead of learners in a direct manner. Effective visualizations extracted from learning log data can help the students to reflect and compare studying activities and access their metacognition to improve their self-regulated learning. For such purposes, we designed a reading path graph for visualizing the studying activities on slide pages used as teaching materials in classes intuitively, as one of the key functions of the learning dashboard. By providing the comparisons between the user’s own situation and the class overview, the visualization is expected to motivate the further actions of using other tools of the learning dashboard and reflecting studies. This paper introduces our exploration of the data process flows of extracting necessary data from a large number of operational logs for the visualization, and the techniques and strategies applied for rendering the graphics effectively. We implemented the data processing module with Python3 and the web-based visualization module of the reading path graph with JavaScript based on D3.js considering the extensibilities. The issues engaged in the development of prototypes are discussed, which will lead to the improvement of future prototypes and better designs of user experiments for formative evaluations as the next step of this research.
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Acknowledgments
This research is supported by a JST AIP Grant No. JPMJCR19U1, Japan.
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Lu, M., Chen, L., Goda, Y., Shimada, A., Yamada, M. (2020). Visualizing Studying Activities for a Learning Dashboard Supporting Meta-cognition for Students. In: Streitz, N., Konomi, S. (eds) Distributed, Ambient and Pervasive Interactions. HCII 2020. Lecture Notes in Computer Science(), vol 12203. Springer, Cham. https://doi.org/10.1007/978-3-030-50344-4_41
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DOI: https://doi.org/10.1007/978-3-030-50344-4_41
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