Starting this year, the national conference has been split into two sessions, autumn and spring, and the autumn conference was held at the Nagoya Congress Center. I would like to thank everyone on the Autumn Conference Planning Committee and the Executive Committee. I am sure there were many challenges, including coordinating with the conference management contractors. Thank you very much for your hard work. (The photo was taken by Prof. Fujimoto from the University of Tokyo. Thank you for listening to my presentation as well.)

Next is the spring conference. During this session, I had various discussions with Prof. Horita (Tohoku University), Prof. Higashihara, Prof. Muramatsu, Prof. Morishita, and Prof. Tsukuka (Shinshu University), Prof. Inagaki (Tohoku Gakuin University), Prof. Yamauchi (University of Tokyo), and Prof. Matsukawa (Tohoku University), and also held meetings with the spring conference committee members to finalize the details for the spring conference. As this is the first time the conference has been split into two, I would like to make it a great event for our members and participants with everyone’s cooperation, while keeping in mind the future development of the research field of Educational Technology. Thank you for your support.

Personally, it was my first poster presentation in a while, so I was nervous. As for the topic, I introduced our ongoing Learning Analytics research at Kyushu University and Kyoto University, which is being conducted in high schools, specifically focusing on what we are doing to support lesson design based on Learning Analytics. In Learning Analytics research, the mainstream approach involves developing adaptive learning environments based on learning log analysis, estimating grades or dropout rates for early warning or learning support, and developing dashboards.

However, in Learning Analytics within schools, especially in primary and secondary education, teachers act as “mediators” in various senses, and I believe it is necessary to consider their teaching experience, educational philosophy, and teaching style. I presented an overview of our research, which has started focusing on lesson design support, lesson design research, and intervention research based on Learning Analytics, taking into account not only students’ learning activities but also the teachers’ perspectives. Thank you to everyone who was interested and came to listen.

Masakazu Yamada, Keishi Shimada, Li Chen, Satomi Hamada, Xuewang Geng, Toshishi Baba, Tsuyoshi Furukawa, Komon Nanri, Kohei Kuroiwa, Satoru Yoshimoto, Brendan Flanagan, Gökhan Akçapınar, Rwitajit Majumdar, Hiroaki Ogata (2019). Towards Evidence-Based Lesson Design using Learning Analytics: A Case Study in High Schools, Proceedings of the 2019 Autumn Conference of the Japan Society for Educational Technology, 31-32

My students also did a great job. I was worried, so I went to check on them. They gave their presentations and handled the Q&A sessions well. Since this was the debut at JSET for all three of them, I was anxious, but I am very grateful that many people came to see them. I hope to continue to improve our research. The presentation details are as follows.

Xuanqi Feng, Masakazu Yamada (2019). A Visualization Approach for Learning Game Logs in Informal Learning, Proceedings of the 2019 Autumn Conference of the Japan Society for Educational Technology, 107-108

Feng-kun’s research presented a method and visualization for categorizing players in a completely online learning game without face-to-face interaction, using collected logs to distinguish between players who are playing effectively and those who are not, based on factors such as grades. His follow-up research will be presented at ICCE 2019 this year.

Xuewang Geng, Masakazu Yamada (2019). Design of a Learning Support System for Compound Verbs using Augmented Reality, Proceedings of the 2019 Autumn Conference of the Japan Society for Educational Technology, 151-152

Geng-kun’s research involves developing a learning environment using AR to learn Japanese compound verbs (verbs such as “hiroiageru” (pick up) or “utsurikomu” (reflect/be captured in)). Specifically, it involves combining paper cards with regular Japanese verbs written on them to form compound verbs, and when a smartphone app developed by Geng-kun is held over them, the image represented by the compound verb is displayed via AR. At the time of the presentation, development was actually already finished, and we will proceed with concrete evaluations.

Satomi Hamada, Masakazu Yamada (2019). Visualization of Learning Logs in a Web System Supporting Structural Understanding of Congruence Proofs, Proceedings of the 2019 Autumn Conference of the Japan Society for Educational Technology, 541-542

Hamada-san’s research is on the development of a learning support system for junior high school congruence proof problems. It is said that even when students answer free-form proof problems, the correct answer rate is around 30%. As a preliminary support step before students can write free-form answers, she is developing a system to support the structural understanding of proof problems. We conducted an evaluation last year, and while it showed that the system was effective, we need to consider how teachers should develop lessons on proof problems after students have used this system. This research introduced a prototype of a function that visualizes learning logs from the congruence proof problem learning support system and provides feedback to teachers. The further development of this project will be presented at CELDA 2019.

Thank you to everyone who listened to my students’ presentations. We will continue to conduct research that can contribute to educational and learning settings, and we appreciate your continued guidance and support.