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利用LLM增強代理人模擬課堂教育

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

大型語言模型(LLMs)已被應用於各種智能教育任務以協助教學。儘管初步探索專注於獨立的LLM增強代理人用於特定教育任務,但在多代理人協作框架中利用LLMs來模擬具有真實用戶參與的課堂的潛力尚未被探索。在這項工作中,我們提出SimClass,一個涉及用戶參與的多代理人課堂模擬框架。我們確認了代表性的課堂角色,並引入了一種新穎的課堂控制機制用於自動課堂教學,並在兩個現實課程中進行用戶實驗。利用教育分析中的Flanders互動分析系統和社群探究理論框架,我們證明LLMs能夠有效模擬傳統課堂互動模式,同時增強用戶體驗。我們還觀察到SimClass中代理人之間出現的新興群體行為,代理人合作創造活躍的課堂互動,以改善用戶的學習過程。我們希望這項工作能開創LLM增強的多代理人系統應用於虛擬課堂教學的先河。
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.
PDF3214November 29, 2024