My primary research interest is to advance a transformative theory of effective learning technology and its applications in order to advance a cognitive theory of learning and teaching. I am particularly interested in innovating an artificial-intelligence technology for education that helps students learn, teachers teach, and researchers understand how people learn and fail to learn. My scholarly expertise thus spans education, learning science, cognitive science, and computer science.
To advance the transformative theory of effective learning technology, I apply data-driven, iterative design engineering techniques. I start from understanding students’ and teachers’ needs and challenges, using user-centered methods commonly used in the field of human-computer interaction (e.g., contextual inquiry, cognitive task analysis, storyboarding, and multi-level rapid prototyping). I then evaluate the developed learning technology in authentic classroom settings, i.e., in-vivo studies. I analyze the data collected from the in-vivo studies and identify strengths and weaknesses of the technology innovation.
To advance the cognitive theory of learning and teaching, I apply empirical methods used in the fields of learning analytics and educational data mining to the data collected from the in-vivo studies. In particular, I have demonstrated the advantage of combining process data (that show detailed interactions between students and the technology) and outcome data (e.g., test scores and questionnaire responses) to understand how and why students learn and fail to learn.
Spring 2023 Office Hours
Upon request by email
- Advanced Learning Technologies
- Artificial Intelligence and Intelligent Agents
- Data Sciences and Analytics
- Graphics, Human Computer Interaction, & User Experience
- Ph.D. in Intelligent Systems, University of Pittsburgh (2004)
- M.S. in Mathematics Education, Tokyo Gakugei Unversity (Tokyo, Japan)
- B.A. in Mathematics Education, Tokyo Gakugei Unversity (Tokyo, Japan)
CSC Spring Courses
- CSC 116-003 LEC Intro Comp - Java MW 12:50pm-2:40pm Room: 200 111 Lampe Drive
- Most Receptive Graduate Professor Outside of Class Award (CSC, NCSU) - 2019
- Finalist of the Best Paper Award. International Conference on Digital Game and Intelligent Toy Enhanced Learning (DIGITEL2012) - 2012
- Finalist of the Best Paper Award. International Conference on Intelligent Tutoring Systems (ITS2012) - 2012
- Best Demo Award. International Conference on User Modeling and Adaptive Personalization (UMAP2010) - 2010
See my personal web: https://go.ncsu.edu/matsuda