Our students presented in the Practitioner section at Learning Analytics and Knowledge 2020, the premier international conference in the field of Learning Analytics. While we would have liked to challenge ourselves in the Research section, given the nature of the topic, it was positioned as practical research. We decided to start with the Practitioner section, and if things go well, we would like to challenge the Research section next time.

This conference was originally scheduled to be held in Frankfurt, but due to the global spread of the novel coronavirus, it was held online via Zoom, following the JSET Spring National Conference. This situation seems likely to continue for a while. Online conferences might continue throughout this year…

I was wondering if Germany would be okay, and before the virus spread to Europe, I had received emails from Professor Ifenthaler at the University of Mannheim about the situation in Germany. It seemed like there would be no problem, and I was fully prepared to go. However, the speed of the infection was terrifying, and it is a pity that it ended up like this.

The presentation topics were as follows:

Chen, L., Goda, Y., Shimada, A., and Yamada, M.(2020). Effects of In-class and Out-of-class Learning Behaviors on Learning Performance and Self-regulated Learning Awareness, Companion Proceedings 10th International Conference on Learning Analytics & Knowledge (LAK20), pp.104-106. Link to this proceedings

In one of our university courses, we verified which learning behaviors in the eBook viewer “BookRoll,” both inside and outside of class, contribute to academic performance and Self-Regulated Learning awareness. We used the MSLQ for Self-Regulated Learning awareness.

Hamada, S., Xu, Y., Geng, X., Chen, L., Ogata, H., Shimada, A., and Yamada, M. (2020). For Evidence-Based Class Design with Learning Analytics: A Proposal of Preliminary Practice Flow Model in High School, Companion Proceedings of Learning Analytics and Knowledge 2020, pp.13-16. Link to this proceedings

This is a result of the SIP/AIP acceleration research. We are conducting classroom practices in high schools using Moodle, BookRoll, and a dashboard, and this paper organizes the perspectives and flows that should be considered to deploy Learning Analytics into practice. Simply using a system does not automatically improve grades; there are stakeholders involved. We have organized how to get those people involved in the practice. It is still preliminary, but I hope to organize various things in the future.

Although not a student, I manage one team, and we also presented a poster as a result of the AIP acceleration research.

Lu, M., Chen, L.,Goda, Y., Shimada, A., and Yamada, M. (2020). Development of a Learning Dashboard Prototype Supporting Meta-cognition for Students, Companion Proceedings 10th International Conference on Learning Analytics & Knowledge (LAK20), pp.104-106, Link to this proceedings

This introduces the development of “Metaboard,” a dashboard being developed under the AIP acceleration research that is expected to activate meta-cognition and have an effect on changing learning behaviors. Our student, Ms. Chen, designed it, and Professor Lu from the Faculty of Arts and Science developed it.

Although it was not held this time, the manuscripts accepted for the Data Challenge@LAK2020 were also published as Proceedings. In addition to my student, Mr. Xu, manuscripts by students from the Taniguchi and Shimada Laboratory (Graduate School of Information Science and Electrical Engineering) were also published.

In our high school practice, we are conducting research based on the hypothesis that it is not the number of markers, but the area marked that affects students’ grades. We are also researching the evaluation of a system that aggregates logs from the knowledge map tool “BR-Map” linked with BookRoll to generate learners’ knowledge maps and automatically cluster similar maps, as well as the evaluation of a system that recommends summarized teaching materials based on the timing and situation of the learner’s study. I am involved from the perspective of evaluation.

Xu,Y., Geng, X., Chen, L., Hamada, S., Taniguchi, Y., Ogata, H., Shimada, A., and Yamada, M. (2020). Can the Area marked in eBook Readers Specify Learning Performance? Companion Proceedings 10th International Conference on Learning Analytics & Knowledge (LAK20), pp.638-648, Link to this proceedings

Onoue, A., Yamada, M., Shimada, A., Minematsu, T., and Taniguchi, R. (2020). Social Knowledge Mapping Tool for Interactive Visualization of Learners’ Knowledge, Companion Proceedings 10th International Conference on Learning Analytics & Knowledge (LAK20), pp.632-637, Link to this proceedings

Nakayama, K., Shimada, A., Minematsu, T., Yamada, M., and Taniguchi, R. (2020). Recommendation of Personalized Learning Materials based on Learning History and Campus Life Sensing, Companion Proceedings 10th International Conference on Learning Analytics & Knowledge (LAK20), pp.649-654, Link to this proceedings

If you are interested, please take a look. We will continue to advance our research on system development to make students’ learning even better. Thank you for your continued support.