Hello! I am a PhD Candidate in the Human-Computer Interaction Institute (HCII) at Carnegie Mellon University, where I am advised by Professor Vincent Aleven. Before joining CMU, I completed my Master’s degree in Learning, Design, and Technology at Stanford Graduate School of Education, working with Professor Candace Thille on Open Learning Initiative at Stanford.
My work lies at the intersection of the learning sciences, human-computer interaction, and cognitive science. I co-design intelligent technologies with educators and learners and use them as a platform to understand and support human learning. My research has looked at topics such as:
- Co-designing novel instructional and interaction strategies with teachers to help children reason with, and learn from, visual representations in an intelligent system
- Designing an educational game to support engaging and effective learning in math
- Re-conceptualizing classroom research as a mutual, equitable learning opportunity between researchers and practitioners
- Supporting learners’ autonomous, self-regulated choice making in an intelligent system
I work with stakeholders to find real-world problems, design and evaluate tools, strategies, and digital technologies in a variety of learning environments. I am also an activist working in the area of open education as a member at Creative Commons Japan and as an OER Research Fellow at Open Education Group.
Prior to coming to the US, I spent two years working at the Center for Open Education at Hokkaido University (Japan) as an instructional designer, following my graduation from International Christian University in Tokyo where I received my bachelor’s degree in Education.
I am on the job market looking for TT faculty, industry, and non-profit positions (UX, HCI, or learning research role) inside and outside US! Feel free to get in touch – I can be reached at tnagashi[at]cs.cmu.edu.
- 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). (New!) [paper]
- 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. (New!) Best Design Paper Nominee. [paper]
- 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. [paper]
- 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. [paper]