Simulating Classroom Education with LLM-Empowered Agents
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arXiv
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| Auteurs principaux: | , , , , , , , , , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866917849359974400 |
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| author | Zhang, Zheyuan Zhang-Li, Daniel Yu, Jifan Gong, Linlu Zhou, Jinchang Hao, Zhanxin Jiang, Jianxiao Cao, Jie Liu, Huiqin Liu, Zhiyuan Hou, Lei Li, Juanzi |
| author_facet | Zhang, Zheyuan Zhang-Li, Daniel Yu, Jifan Gong, Linlu Zhou, Jinchang Hao, Zhanxin Jiang, Jianxiao Cao, Jie Liu, Huiqin Liu, Zhiyuan Hou, Lei Li, Juanzi |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_19226 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Simulating Classroom Education with LLM-Empowered Agents Zhang, Zheyuan Zhang-Li, Daniel Yu, Jifan Gong, Linlu Zhou, Jinchang Hao, Zhanxin Jiang, Jianxiao Cao, Jie Liu, Huiqin Liu, Zhiyuan Hou, Lei Li, Juanzi Computation and Language Human-Computer Interaction 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. |
| title | Simulating Classroom Education with LLM-Empowered Agents |
| topic | Computation and Language Human-Computer Interaction |
| url | https://arxiv.org/abs/2406.19226 |