Session Details
[SL]Engineering Education Salon
Thu. Sep 3, 2026 10:00 AM - 12:00 PM JST
Thu. Sep 3, 2026 1:00 AM - 3:00 AM UTC
Thu. Sep 3, 2026 1:00 AM - 3:00 AM UTC
F room(Lecture room 106)
Moderator: Harunori Nagata(Editor/Publication Committee/Hokkaido University)
“Our Trusted AI Partner! Does the Committee Really Need to Go That Far!? — An Honest Discussion on the ‘Gray Areas’ Hidden Behind Convenience and the ‘Unresolved Frustrations’ on the Front Lines”
Generative AI is rapidly becoming integrated into engineering education practices—such as student-led inquiry-based learning and efforts to enhance faculty teaching skills—but this salon is not merely a forum for discussing use cases and challenges.
This initiative is a new endeavor that also serves as an open editorial planning committee for the journal of JSEE. Starting with presentations and discussions at the annual conference, participants will bring their insights and concerns to the table to explore key issues. Through the transcription of these discussions and the use of generative AI to turn them into articles, the project aims to identify authors for a special feature. It is not merely a discussion of generative AI as a topic; by incorporating generative AI into the planning, recording, and editing processes themselves and organically linking the annual conference with the journal, this project also anticipates the future of editing.
Centered on the presentations of the 2026 Engineering Education Award-winning papers, we invite you to join us in this process of collectively shaping the next special issue. Through dialogue among participants regarding practice, challenges, ethics, and editorial practices, we will identify key issues to explore further and potential authors.
We hope this will serve as a forum for exchanging insights across disciplines and perspectives, while keeping in mind both the expectations and concerns surrounding generative AI.
This initiative is a new endeavor that also serves as an open editorial planning committee for the journal of JSEE. Starting with presentations and discussions at the annual conference, participants will bring their insights and concerns to the table to explore key issues. Through the transcription of these discussions and the use of generative AI to turn them into articles, the project aims to identify authors for a special feature. It is not merely a discussion of generative AI as a topic; by incorporating generative AI into the planning, recording, and editing processes themselves and organically linking the annual conference with the journal, this project also anticipates the future of editing.
Centered on the presentations of the 2026 Engineering Education Award-winning papers, we invite you to join us in this process of collectively shaping the next special issue. Through dialogue among participants regarding practice, challenges, ethics, and editorial practices, we will identify key issues to explore further and potential authors.
We hope this will serve as a forum for exchanging insights across disciplines and perspectives, while keeping in mind both the expectations and concerns surrounding generative AI.
[2F000]Greeting
Yukihiko Sato (Editor/Publication Committee/Chiba University))
[2F001]Panel Discussion
Panelists
Jun Mada, Professor, Nihon University
Hiroyoshi Miwa, Professor, Kwansei Gakuin University
Atsushi Fujiki, Professor, Kansai University
Hideaki Aburatani, Professor, National Institute of Technology (KOSEN), Kitakyushu College
Jun Mada, Professor, Nihon University
Hiroyoshi Miwa, Professor, Kwansei Gakuin University
Atsushi Fujiki, Professor, Kansai University
Hideaki Aburatani, Professor, National Institute of Technology (KOSEN), Kitakyushu College
Discussion Topics:
1) Examples of Generative AI Applications in Engineering Education
2) Ethics and Guidelines for Generative AI in Education, Research, and Assessment
3) How to Design Engineering Education in the Age of Generative AI
4) What to Develop into Articles Based on Discussions About Generative AI
1) Examples of Generative AI Applications in Engineering Education
2) Ethics and Guidelines for Generative AI in Education, Research, and Assessment
3) How to Design Engineering Education in the Age of Generative AI
4) What to Develop into Articles Based on Discussions About Generative AI