Simulating Classroom Education with LLM-Empowered Agents
This work pioneers the application of LLM-empowered multi-agent systems in virtual classroom teaching, addressing the need for collaborative educational simulations with real user participation.
The authors tackled the problem of simulating classroom education by proposing SimClass, a multi-agent framework using LLMs, and demonstrated through user experiments in two real-world courses that it can create dynamic learning environments with active interactions, improving the user learning process.
Large language models (LLMs) have been applied across various intelligent educational tasks to assist teaching. While preliminary studies have focused on task-specific, independent LLM-empowered agents, the potential of LLMs within a multi-agent collaborative framework for classroom simulation with real user participation remains unexplored. In this work, we propose SimClass, a multi-agent classroom simulation teaching framework. 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. Using the Flanders Interactive Analysis System and Community of Inquiry theoretical frameworks from educational analysis, we demonstrate that LLMs can simulate a dynamic learning environment for users with active teacher-student and student-student interactions. We also observe 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.