@inproceedings{zhang-etal-2025-simulating,
    title = "Simulating Classroom Education with {LLM}-Empowered Agents",
    author = "Zhang, Zheyuan  and
      Zhang-Li, Daniel  and
      Yu, Jifan  and
      Gong, Linlu  and
      Zhou, Jinchang  and
      Hao, Zhanxin  and
      Jiang, Jianxiao  and
      Cao, Jie  and
      Liu, Huiqin  and
      Liu, Zhiyuan  and
      Hou, Lei  and
      Li, Juanzi",
    editor = "Chiruzzo, Luis  and
      Ritter, Alan  and
      Wang, Lu",
    booktitle = "Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)",
    month = apr,
    year = "2025",
    address = "Albuquerque, New Mexico",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2025.naacl-long.520/",
    pages = "10364--10379",
    ISBN = "979-8-89176-189-6",
    abstract = "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. Our implementation and service can be found at https://github.com/THU-MAIC/SimClass."
}