First author 

• Sato, S., Cutumisu, M., & Nagashima, T. (2026). A systematic review of empirical studies on Intelligent Tutoring System feedback in K-12 Classrooms. In Proceedings of the International Conference on Artificial Intelligence in Education (AIED2026), Seoul, South Korea [acceptance rate: 28.6%] [link]　

• Sato, S. & Nagashima, T. (2026). Understanding teachers’ feedback strategies in classrooms with an intelligent tutor: A survey study. In Proceedings of the Annual Meeting for the International Society of the Learning Sciences (ISLS2026), Irvine, CA. [link]

• Sato, S., Zheng, Q., Su, M., & Nagashima, T. (2025). Towards developing a guideline for optimizing interface design of intelligent tutoring software. In Proceedings of the 20th European Conference on Technology Enhanced Learning (EC-TEL2025). (Poster) [Paper]

• Sato, S., Platz, M., & Nagashima, T. (2024). Which leads to more effective learning in intelligent tutoring software, effort-based or performance-based feedback? In Proceedings of the 64th Annual Meeting of the Cognitive Science Society, Rotterdam, Netherlands. Cognitive Science Society. [link]
  
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• Sato, S., & Kubo, M. (2019). Status and issues of ICT use in health education classes: Questionnaire survey for teachers in T Prefecture. Kitakanto Journal of Physical Education, Health and Sports Sciences, 4, 19-29.

Co author 

• Nagashima, T., Siegrist, L., Scholz, N., Sato, S., Vincoli, M., & Su, M. (2026). Identifying alignments and misalignments between teachers’ and students’ views on AI use in the school classroom. In Proceedings of the ACM on Human-Computer Interaction (PACMHCI). CSCW2026.

• Nagashima, T., Sato, S., Hladký, M., Scholz, N., & Siegrist, L. (2026). Teachers’ perspectives on decision-making in AI-supported classrooms: A cross-cultural study of Germany and Japan. International Conference on Artificial Intelligence in Education (AIED2026), Seoul, South Korea. [acceptance rate: 16.7%].