Hung-Chun Chang

Biography

Hi, I am Hung-Chun (Jonathan) Chang, a Master’s student in Psychology at National Taiwan University (NTU), advised by Prof. Hsiu-Ping Yueh in the Social Lab and co-advised by Prof. Feng-Ming Tsao and Prof. Hiroaki Ogata (Kyoto University).

I am drawn to a broad question: how do we learn, both as learners and as researchers trying to understand learning? I approach it by asking whether computational models of learners hold up against real learning data. My current work treats LLM-based simulated students as measurement instruments and asks what they actually capture: how closely their behavior matches real learners in DataShop data, what their internal representations encode, and whether anything they learn persists beyond the context window. Part of this work was done during a research residency with Prof. Hiroaki Ogata at Kyoto University and was accepted at the ReLEAF workshop at ICCE 2026.

I also build the systems I study. I was the sole developer of ECRobot, a robot tutor used in a between-subjects learning study, and of a web-based end-user programming platform for authoring social robot behavior. I have deployed social robots with real users in a museum, a library, and with older adults.

Previously, I earned two bachelor’s degrees at NTU: a B.S. in Interdisciplinary Studies of Human-Computer Interaction through the University Interdisciplinary Bachelor’s Program, and a B.S. in Agriculture from the Department of Forestry and Resource Conservation, with a minor in Psychology.

Outside research, I run long distances and cycle; I finished two half marathons and several road races in 2025.

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Research Interests

• Human learning: how people — scientists included — form concepts, and how the concepts we hold shape what we measure and notice.
• Learner modeling: simulated students, construct validity, and comparing model and human learning.
• Human-computer interaction: tutoring systems and social robots for education and older adults, built both as tools and as testbeds for learning research.