Simulating Classroom Education with LLM-Empowered Agents
Authors: name: Zheyuan Zhang, name: Daniel Zhang-Li, name: Jifan Yu, name: Linlu Gong, name: Jinchang Zhou, name: Zhiyuan Liu, name: Lei Hou, name: Juanzi Li

Large language models (LLMs) have been employed in various intelligent
educational tasks to assist teaching. While preliminary explorations have
focused on independent LLM-empowered agents for specific educational tasks, the
potential for LLMs within a multi-agent collaborative framework to simulate a
classroom with real user participation remains unexplored. In this work, we
propose SimClass, a multi-agent classroom simulation framework involving user
participation. We recognize representative class roles and introduce a novel
class control mechanism for automatic classroom teaching, and conduct user
experiments in two real-world courses. Utilizing the Flanders Interactive
Analysis System and Community of Inquiry theoretical frame works from
educational analysis, we demonstrate that LLMs can simulate traditional
classroom interaction patterns effectively while enhancing user's experience.
We also observe emergent group behaviors among agents in SimClass, where agents
collaborate to create enlivening interactions in classrooms to improve user
learning process. We hope this work pioneers the application of LLM-empowered
multi-agent systems in virtual classroom teaching.