利用LLM增强代理模拟课堂教育

Simulating Classroom Education with LLM-Empowered Agents

June 27, 2024

作者: Zheyuan Zhang, Daniel Zhang-Li, Jifan Yu, Linlu Gong, Jinchang Zhou, Zhiyuan Liu, Lei Hou, Juanzi Li

cs.AI

摘要

大型语言模型（LLMs）已被应用于各种智能教育任务以协助教学。虽然初步探索集中在针对特定教育任务的独立LLM增强代理，但LLMs在多代理协作框架中模拟具有真实用户参与的课堂的潜力尚未被探索。在这项工作中，我们提出SimClass，一个涉及用户参与的多代理课堂模拟框架。我们确定了代表性的班级角色，并引入了一种新颖的班级控制机制用于自动课堂教学，并在两门真实课程中进行用户实验。利用弗兰德斯互动分析系统和社区探究理论框架从教育分析中，我们展示了LLMs可以有效模拟传统课堂互动模式，同时提升用户体验。我们还观察到SimClass中代理之间出现的新兴群体行为，代理合作创造活跃的课堂互动，以改善用户学习过程。我们希望这项工作开创了LLM增强的多代理系统在虚拟课堂教学中的应用。

English

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.