TY - GEN
T1 - Visualizing Studying Activities for a Learning Dashboard Supporting Meta-cognition for Students
AU - Lu, Min
AU - Chen, Li
AU - Goda, Yoshiko
AU - Shimada, Atsushi
AU - Yamada, Masanori
N1 - Funding Information:
This research is supported by a JST AIP Grant No. JPMJCR19U1, Japan.
Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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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U2 - 10.1007/978-3-030-50344-4_41
DO - 10.1007/978-3-030-50344-4_41
M3 - Conference contribution
AN - SCOPUS:85088742555
SN - 9783030503437
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 569
EP - 580
BT - Distributed, Ambient and Pervasive Interactions - 8th International Conference, DAPI 2020, Held as Part of the 22nd HCI International Conference, HCII 2020, Proceedings
A2 - Streitz, Norbert
A2 - Konomi, Shin’ichi
PB - Springer
T2 - 8th International Conference on Distributed, Ambient and Pervasive Interactions, DAPI 2020, held as part of the 22nd International Conference on Human-Computer Interaction, HCII 2020
Y2 - 19 July 2020 through 24 July 2020
ER -