2026

• 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.
• Vincoli, M., Scholz, N., & Nagashima, T. (2026). “I think I would rather decide what to do”: Students’ perception of control in an AI-infused classroom. In Proceedings of the 21st European Conference on Technology Enhanced Learning (EC-TEL2026), Valencia, Spain. [acceptance rate: 26.0%].
• Rief, V., Hladký, M., Yoo, M., Heel, S., Sato, S., & Nagashima, T. (2026). Conversational AI meets mindfulness: Exploring LLMs as a socio‑emotional layer in a math intelligent tutoring system. In Proceedings of the 21st European Conference on Technology Enhanced Learning (EC-TEL2026), Valencia, Spain.
• Nagashima, T., Hladký, M., & Rief, V. (2026). Warning about AI fallibility increases help-seeking in a math intelligent tutor. In Proceedings of the 21st European Conference on Technology Enhanced Learning (EC-TEL2026), Valencia, Spain. [link]
• Borchers, C., Zhang, L., Yang, K., & Nagashima, T., & Dominigue, B. (2026). Understanding student effort using reaction time propensities during problem solving at scale. In Proceedings of the ACM Conference on Learning at Scale (L@S2026), Seoul, South Korea. [acceptance rate: 22.0%].[link]
• 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. In Proceedings of the International Conference on Artificial Intelligence in Education (AIED2026), Seoul, South Korea. [acceptance rate: 16.7%]. [link]
• 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]
• Nair, A., Su, M., & Nagashima, T. (2026). Investigating human-AI agency in interactive simulations for complex systems education: The effects of questioning and content agency on student learning. In Proceedings of the Annual Meeting for the International Society of the Learning Sciences (ISLS2026), Irvine, CA.
• 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.
• Han, B., Coghlan, S., Buchanan, G., & McKay, D. (2026). Ethical gaps and power dynamics in decision-making about AI adoption: The case of AI for monitoring student learning in education. International Journal of Human-Computer Studies, 103810. (*work conducted prior to joining the group) [link] 
• Han, B., Coghlan, S., Buchanan, G., & McKay, D. (2026). The values of academic integrity in the era of monitoring AI in classrooms. In Artificial Intelligence and Academic Integrity: Navigating Ethical Challenges of AI in Education (pp. 141-157). Singapore: Springer Nature Singapore. (*work conducted prior to joining the group) [link] 
• Han, B., Ma, Y., Coghlan, S., McKay, D., Buchanan, G., & Smith, W. (2026). AI sensing and intervention in higher education: Student perceptions of learning impacts, affective responses, and ethical priorities. In Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (pp. 1-21). Best Paper Award (*work conducted prior to joining the group) [link] 
• Reinwarth, A. L., Balzert, E., Hilpert, B., Hladký, M., Gebhard, P., & Schneeberger, T. (2026). TACSIA: A Framework for Passenger Expectations on Trust in Autonomous Cars with Socially Interactive Agents. In Proceedings of the Extended Abstracts of the 2026 CHI Conference on Human Factors in Computing Systems (pp. 1-6). [link] 
• Su, M., Chi, M. T., & Nagashima, T. (2026). Applying the PAIR-C Framework to foster deep understanding and address misconceptions in science education. Journal of the Learning Sciences, 35(1), 130–175. [link] 

2025

• Hladký, M., Han, B., Gratch, J., Gebhard, P., & Schneeberger, T. (2025). Steal and smile: Impact of emotion regulation and social values on smiles in social conflicts. In 13th International Conference on Affective Computing and Intelligent Interaction (ACII). IEEE. Best Paper Award.
• Wen, C., Phung, T., Mehrotra, P., Gulwani, S., Nagashima, T., & Singla, A. (2025). Exploration vs. fixation: Scaffolding divergent and convergent thinking for human-AI co-creation with generative models. arXiv. [link]
• Su, M., Dang, B., Nguyen, A., & Nagashima, T. (2025). Choice-making in an adaptive learning system: The role of motivational pedagogical agents and prior knowledge. npj Science of Learning, 10(77). [link] 
• Borchers, C., Nagashima, T., Liu, P., Alibali, M. W., & Aleven, V. (2025). Is more gamification better? Evaluating playful interactions and narratives for algebra learning. In Proceedings of the 20th European Conference on Technology Enhanced Learning (EC-TEL2025). [link] 
• Scholz, N., Nguyen, M. H., Singla, A., & Nagashima, T. (2025). Partnering with AI: A pedagogical feedback system for LLM integration into programming education. In Proceedings of the 20th European Conference on Technology Enhanced Learning (EC-TEL2025). [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). [link]
• Su, M., Bonaventura, K., & Nagashima, T. (2025). Investigating the effects of motivational pedagogical agents on student learning and choice making in an adaptive learning system. In Proceedings of the 20th European Conference on Technology Enhanced Learning (EC-TEL2025). [link]
• Nagashima, T., Kilger, H., & Aleven, V. (2025). When less is more: Students’ use of diagrams and their perception of diagram use in an AI tutor for algebra learning. In Proceedings of the 65th Annual Meeting of the Cognitive Science Society, San Francisco, CA. Cognitive Science Society. [link]
• Vincoli, M., Scholz, N., & Nagashima, T. (2025). Multidimensional student agency in learning with AI: A conceptual framework and design implications. In Proceedings of the International Conference on Artificial Intelligence in Education (AIED2025), Palermo, Italy. Best Paper Nominee. [link]
• Nagashima, T., Vincoli, M., Scholz, N., & Su, M. (2025). Understanding students’ nuanced views on AI-supported classroom learning through perspective taking. In Proceedings of the International Conference on Artificial Intelligence in Education (AIED2025), Palermo, Italy.[link]
• Shamamyan, N., Su, M., & Nagashima, T., (2025). Co-designing a trustworthy peer agent with middle-school students for learning math. In Proceedings of the ACM Interaction Design and Children Conference (IDC’25), Reykjavik, Iceland. [link]
• Nagashima, T. & Su, M. (2025). Towards better understanding students’ choices in advanced learning technology. In Proceedings of the Annual Meeting for the International Society of the Learning Sciences (ISLS2025), Helsinki, Finland. [pdf]
• Su, M., Bonaventura, K., & Nagashima, T. (2025). Fostering strategic choice-making through motivational pedagogical agents in an adaptive learning system. In Proceedings of the Annual Meeting for the International Society of the Learning Sciences (ISLS2025), Helsinki, Finland. [pdf]
• Hladký, M., Silber, M., & Nagashima, T. (2025). The MindfulMath Tutor: A mindfulness-infused learning environment to battle math anxiety. In Proceedings of the Extended Abstracts of the ACM CHI Conference on Human Factors in Computing Systems (CHI EA’25), Yokohama, Japan.
• Aleven, V., Borchers, C., Huang, Y., Nagashima, T., McLaren, B., Carvalho, P., Popescu, O., Sewall, J., & Koedinger, K. (2025). An integrated platform for studying learning with intelligent tutoring systems: CTAT+TutorShop. arXiv. [link]

2024

• Nagashima, T., Bonaventura, K., & Su, M. (2024). Parallel design: Achieving both researchers’ and practitioners’ goals in the design of an interactive learning system for mathematics. In Proceedings of the Learning, Design and Technology (LDT ’24), Delft, Netherlands. ACM. [link] 

• Kilger, H., Su, M., & Nagashima, T. (2024). Guiding children’s choice making in an Intelligent Tutoring System. In Proceedings of the Learning, Design and Technology (LDT ’24), Delft, Netherlands. ACM. [link] 

• 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] 

• Su, M., Chi, M. T., Nagashima, T., Gole, J., Xin, Y., & Ha, J. (2024). Exploration of cognitive engagement patterns in online environments with multiple external representations. In Proceedings of the Annual Meeting for the International Society of the Learning Sciences (ISLS2024), Buffalo, NY. [link] [pdf]

• Sabnis, N. & Nagashima, T. (2024). Empowering learners: Chatbot-mediated learning-by-teaching. In Proceedings of the ACM CHI Conference on Human Factors in Computing Systems (CHI EA’ 24), Honolulu, Hawai’i [link]

2023

• Chan, J. Y.-C., Nagashima, T., & Closser, A. H. (in press). Participatory design for Cognitive Science: Examples from the Learning Sciences and Human-Computer Interaction. Cognitive Science, 47(10). [link]
• Sha, H., Sugiura, M., Nagashima, T., & Shigeta, K. (2023). Relations between participation in collaborative learning and learning outcomes in online learning. Information and Technology in Education and Learning, 3(1), 1-5. [link] [pdf]
• Nagashima, T., Zheng, B., Tseng, S., Ling, E., & Aleven, V. (2023). Promoting students’ self-regulated choices in learning with visual representations in intelligent tutoring software. In Proceedings of the Annual Meeting for the International Society of the Learning Sciences (ISLS2023), Montreal, Canada. [pdf]
• Karumbaiah, S., Borchers, C., Shou, T., Falhs, A., Liu, C., Nagashima, T., Rummel, N., & Aleven, V. (2023). A spatiotemporal analysis of teacher practices in supporting student learning and engagement in an AI-enabled classroom. In Proceedings of the International Conference on Artificial Intelligence in Education (AIED2023), Tokyo, Japan. [pdf]
• Nagashima, T., Yadav, G., & Aleven, V. (2023). Remote classroom research toward equity during COVID-19. In K. Stamatis & J. Polman (Co-Chairs), Designing to disrupt and encountering disruption: Engaging with the unexpected in educational research [Symposium]. In Proceedings of the Annual Meeting for the International Society of the Learning Sciences (ISLS2023), Montreal, Canada. [pdf]

2022

• Nagashima, T., Britti, J., Wang, X., Zheng, B., Turri, V., Tseng, S., & Aleven, V. (2022). Designing playful intelligent tutoring software to support engaging and effective algebra learning. In Proceedings of the 17th European Conference on Technology Enhanced Learning (EC-TEL2022) [link] 
• Aleven, V., Blankestijn, J., Lawrence, L., Nagashima, T., & Taatgen, N. (2022, to appear). A dashboard to support teachers during students’ self-paced AI-supported problem-solving practice. In Proceedings of the 17th European Conference on Technology Enhanced Learning (EC-TEL2022) [link] 
• Hou, X., Nagashima, T., & Aleven, V. (2022). Design a dashboard for secondary-school learners to support mastery learning in a gamified learning environment. In Proceedings of the 17th European Conference on Technology Enhanced Learning (EC-TEL2022) [link] 
• Nagashima, T., Ling, E., Zheng, B., Bartel, A. N., Silla, E. M., Vest, N. A., Alibali, M. W., & Aleven, V. (2022). How does sustaining and interleaving visual scaffolding help learners? A classroom study with an Intelligent Tutoring System. In Proceedings of the 44th Annual Meeting of the Cognitive Science Society. Cognitive Science Society [link] 
• Vest., N., Silla, E. M., Bartel, A. N., Nagashima, T., Aleven, V., & Alibali, M. W. (2022). Self-explanation of worked examples integrated in an Intelligent Tutoring System enhances problem solving and efficiency in algebra. In Proceedings of the 44th Annual Meeting of the Cognitive Science Society. Cognitive Science Society [link] 
• Nagashima, T., Tseng, S., Ling, E., Bartel, A. N., Vest, N. A., Silla, E. M., Alibali, M. W., & Aleven, V. (2022). Students’ self-regulated use of diagrams in a Choice-based Intelligent Tutoring System. In Proceedings of the Annual Meeting for the International Society of the Learning Sciences (ISLS2022), Hiroshima, Japan. [pdf] 
• Shigeta, K., Takeda, T., Kaneko, D., Yagi, H., & Nagashima, T. (2022). Development of a Moodle plugin to track OER improvements. In Proceedings of the Annual Conference for Japan Society for Educational Technology, Kanagawa (in Japanese).

2021

• Nagashima, T. & Hrach, S. (2021). Motivating factors among university faculty for adopting Open Educational Resources: Incentives matter. Journal of Interactive Media in Education, 1(19), 1-10. [pdf] 
• Nagashima, T. (2021). Towards fostering metacognitive use of diagrams through diagrammatic self-explanation. In Proceedings of the 12th International Conference on the Theory and Application of Diagrams (Diagrams 2021).
• Nagashima, T., Yadav, G., & Aleven, V. (2021). A framework to guide technology-based educational studies in the evolving classroom environment. In Proceedings of the Sixteenth European Conference on Technology Enhanced Learning (EC-TEL2021). [link]
• Yang, K., Nagashima, T., Yao, J., Williams, J.J., Holstein, K., & Aleven, V. (2021). Can crowds make a good thing better, with minimal expert guidance? A step-by-step analysis of a teacher-guided crowd revision pipeline. ACM Conference on Computer-Supported Collaborative Work and Social Computing (CSCW2021). [link]
• Nagashima, T., Bartel, A. N., Tseng, S., Vest, N.A., Silla, E. M., Alibali, M. W., & Aleven, V. (2021). Scaffolded self-explanation with visual representations promotes efficient learning in early algebra. In Proceedings of the Annual Meeting of the Cognitive Science Society (CogSci2021). [link]
• Nagashima, T., Bartel, A. N., Yadav, G., Tseng, S., Vest, N. A., Silla, E. M., Alibali, M. W., & Aleven, V. (2021). Using anticipatory diagrammatic self-explanation to support learning and performance in early algebra. In Proceedings of the Annual Meeting of the International Society of the Learning Sciences (ISLS2021), Bochum, Germany. Best Design Paper Nominee. [pdf]
• Nagashima, T., Yadav, G., & Aleven, V. (2021). Rethinking technology-based educational studies in the evolving classroom environment: An interview study with US teachers. In Proceedings of the Annual Meeting of the International Society of the Learning Sciences (ISLS2021), Bochum, Germany.
• Bartel, A. N., Silla, E. M., Vest, N.A., Nagashima, T., Aleven, V., & Alibali, M. W. (2021). Reasoning about equations with tape diagrams: insights from math teachers and college students. In Proceedings of the Annual Meeting of the International Society of the Learning Sciences (ISLS2021), Bochum, Germany. [link]

2020

• Bartel, A. N., Silla, E. M., Vest, N. A., Nagashima, T., Aleven, V., & Alibali, M. W. (2020). Reasoning about equations with tape diagrams: Do differing visual features matter? Submitted to the 42nd Annual Meeting of the Cognitive Science Society, Toronto, Canada
• Nagashima, T., Bartel, A. N., Silla, E. M., Vest, N. A., Alibali, M. W., & Aleven, V. (2020). Enhancing conceptual knowledge in early algebra through scaffolding diagrammatic self-explanation. In Proceedings of the International Conferences of the Learning Sciences (ICLS2020), Nashville, TN. [pdf]
• Nagashima, T., Yang, K., Bartel, A. N., Silla, E. M., Vest, N. A., Alibali, M. W., & Aleven, V. (2020). Pedagogical Affordance Analysis: Leveraging teachers’ pedagogical knowledge for eliciting pedagogical affordances and constraints of instructional tools. In Proceedings of the International Conferences of the Learning Sciences (ICLS2020). Nashville, TN. [pdf]

2019

• Shigeta, K., Takeda, T., Mori, H., Yagi, H., Nagashima, T., Kaneko, D., & Hayashi, Y. (2019). A practice of group-based learning support in online learning based on learner motivation and goal setting. Workshop paper, Information Processing Society of Japan (in Japanese) [link].
• Nagashima, T. (2019). Towards enhancing conceptual knowledge in algebra through diagrammatic self-explanation. In Companion Proceedings of the 9th International Learning Analytics and Knowledge Conference (LAK19). Tempe, AZ. [pdf]

2018

• Nagashima, T. (2018). Contextualized instruction in data science and its effect on transfer of learning. In Proceedings of the 13th European Conference on Technology Enhanced Learning (EC-TEL). Leeds, UK. [pdf]
• Takeda, T., Hayashi, Y., Shigeta, K., Mori, H., Kaneko, D., Yagi, H., & Nagashima, T. (2018). Visualizing relationships among content topics and learning activities of online courses. In Proceedings of EdMedia: World Conference on Educational Media and Technology. Amsterdam, Netherlands: Association for the Advancement of Computing in Education (AACE). [link]

2013~2017

• Shigeta, K., Yagi, H., Takeda, T., Mori, H., Hayashi, Y., Kaneko, D., & Nagashima, T. (2017). A study on improving learning materials utilizing comments on MOOC discussion boards. In Proceedings of the Annual Conference for Japan Society for Educational Technology, Shimane. (in Japanese)
• Hayashi, Y., Takeda, T., Nagashima, T., Yagi, H., Mori, H., Kaneko, D., & Shigeta, K. (2016). Development of the dashboard system for teachers to perform effective indication of the learning data analysis. In Proceedings of the 5th International Conference on Knowledge Creation and Intelligent Computing. Manado, Indonesia. [link]
• Nagashima, T., Yagi, H., & Shigeta, K. (2015). The value of delivering MOOC as OER. In Proceedings of the Annual Conference for Japan Association for Educational Media, Tokyo. (in Japanese) 
• Yagi, H. Nagashima, T., & Shigeta, K. (2015). Improvement model of lectures and teaching materials developed by OER and MOOC. In Proceedings of the Annual Conference for Japan Association for Educational Media, Tokyo. (in Japanese)
• Yagi, H., Nagashima, T., Hamada, M., Shima, M., Kobayashi, K., & Shigeta K. (2015). Flipped classroom using interactive distance learning system: An experimental class in liberal arts education among national universities in Hokkaido. In Proceedings of the Annual Conference for Japan Society for Educational Technology, Tokyo. (in Japanese)
• Yagi, H., Nagashima, T., Hamada, M., Shima, M., Kobayashi, K., & Shigeta K. (2015). Development of educational videos for liberal arts education among national universities in Hokkaido: How instructional designers and video content specialists can develop a collaborative workflow in a small team. In Proceedings of the Annual Conference for Japan Society for Information and Systems in Education, Tokyo. (in Japanese)
• Shigeta, K., Yagi, H., Nagashima, T., Hamada, M., Miyazaki, T., Kobayashi, K., and Shima, M. (2015). Cooperative liberal arts education and flipped classroom implementation using MOOC. Journal of Digital Practices 6(2), 89-96. (in Japanese) [pdf]
• Nagashima, T. (2014). What makes open education thrive? Examination of factors contributing to the success of open education initiatives. International Journal for Innovation and Quality in Learning 2(3), 10-21. [pdf]
• Nagashima, T. (2013). Open educational resources in higher education: A global perspective. In Proceedings of the International Conference for Media in Education, Aichi.