Description
Abstract: The recent rapid integration of AI in education has sparked a critical question: where do human cognition and machine intelligence converge? In this talk, I will share our latest explorations into the mutual inspiration between human and machine learning processes, and the effort to find their common ground. I will discuss how understanding human learner’s status, such as tracking their cognitive load via EEG or moderating textual aids for reading, can inform more empathetic education technology design, and how Large Language Models (LLMs) can be used to simulate human learners to provide teachers with novel pedagogical insights. Meanwhile, I will demonstrate how machine-centric knowledge structures can be translated back to humans through interactive visualization technologies. By examining these intersections across various real-world educational scenarios, I will show the possibility to align machine logic with human mental models and thus move further than streamline information transfer. Our ultimate goal is create a productive feedback loop that improves both human learning and model training.| Period | 17 Apr 2026 → 19 Apr 2026 |
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| Event title | 2026 14th International Conference on Information and Education Technology |
| Event type | Conference |
| Location | Koriyama, JapanShow on map |
| Degree of Recognition | International |