title: From MOOC to MAIC: Reshaping Online Teaching and Learning through
    LLM-driven Agents
summary: Since the first instances of online education, where courses were uploaded to
  accessible and shared online platforms, this form of scaling the dissemination
  of human knowledge to reach a broader audience has sparked extensive discussion
  and widespread adoption. Recognizing that personalized learning still holds
  significant potential for improvement, new AI technologies have been
  continuously integrated into this learning format, resulting in a variety of
  educational AI applications such as educational recommendation and intelligent
  tutoring. The emergence of intelligence in large language models (LLMs) has
  allowed for these educational enhancements to be built upon a unified
  foundational model, enabling deeper integration. In this context, we propose
  MAIC (Massive AI-empowered Course), a new form of online education that
  leverages LLM-driven multi-agent systems to construct an AI-augmented
  classroom, balancing scalability with adaptivity. Beyond exploring the
  conceptual framework and technical innovations, we conduct preliminary
  experiments at Tsinghua University, one of China's leading universities.
  Drawing from over 100,000 learning records of more than 500 students, we obtain
  a series of valuable observations and initial analyses. This project will
  continue to evolve, ultimately aiming to establish a comprehensive open
  platform that supports and unifies research, technology, and applications in
  exploring the possibilities of online education in the era of large model AI.
  We envision this platform as a collaborative hub, bringing together educators,
  researchers, and innovators to collectively explore the future of AI-driven
  online education.
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paper_authors.name: Daniel Zhang-li
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paper_authors.name: Shangqing Tu
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paper_authors.name: Zhanxin Hao
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paper_authors.name: Rui Miao Li
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paper_authors.name: Haoxuan Li
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paper_authors.name: Yuanchun Wang
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paper_authors.name: Hanming Li
paper_authors._id: 66da878e54209e91013cd371
paper_authors.name: Linlu Gong
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paper_authors.name: Jie Cao
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paper_authors.fullname: Jie Cao
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paper_authors.user: Jieastro
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paper_authors.name: Jiayin Lin
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paper_authors.fullname: Jiayin Lin
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paper_authors.user: Lin-23457
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paper_authors.name: Jinchang Zhou
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paper_authors.name: Fei Qin
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paper_authors.name: Haohua Wang
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paper_authors.name: Jianxiao Jiang
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paper_authors.name: Lijun Deng
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paper_authors.name: Yisi Zhan
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paper_authors.name: Chaojun Xiao
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paper_authors.name: Xusheng Dai
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paper_authors.name: Xuan Yan
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paper_authors.name: Nianyi Lin
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paper_authors.name: Nan Zhang
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paper_authors.name: Ruixin Ni
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paper_authors.name: Yang Dang
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paper_authors.name: Lei Hou
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paper_authors.name: Yu Zhang
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paper_authors.name: Xu Han
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paper_authors.name: Manli Li
paper_authors._id: 66da878e54209e91013cd385
paper_authors.name: Juanzi Li
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paper_authors.fullname: Juanzi Li
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paper_authors.name: Zhiyuan Liu
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paper_authors.fullname: Zhiyuan Liu
paper_authors.type: user
paper_authors.user: zibuyu9
paper_authors._id: 66da878e54209e91013cd387
paper_authors.name: Huiqin Liu
paper_authors._id: 66da878e54209e91013cd388
paper_authors.name: Maosong Sun
paper_title: From MOOC to MAIC: Reshaping Online Teaching and Learning through
    LLM-driven Agents
paper_summary: Since the first instances of online education, where courses were uploaded to
  accessible and shared online platforms, this form of scaling the dissemination
  of human knowledge to reach a broader audience has sparked extensive discussion
  and widespread adoption. Recognizing that personalized learning still holds
  significant potential for improvement, new AI technologies have been
  continuously integrated into this learning format, resulting in a variety of
  educational AI applications such as educational recommendation and intelligent
  tutoring. The emergence of intelligence in large language models (LLMs) has
  allowed for these educational enhancements to be built upon a unified
  foundational model, enabling deeper integration. In this context, we propose
  MAIC (Massive AI-empowered Course), a new form of online education that
  leverages LLM-driven multi-agent systems to construct an AI-augmented
  classroom, balancing scalability with adaptivity. Beyond exploring the
  conceptual framework and technical innovations, we conduct preliminary
  experiments at Tsinghua University, one of China's leading universities.
  Drawing from over 100,000 learning records of more than 500 students, we obtain
  a series of valuable observations and initial analyses. This project will
  continue to evolve, ultimately aiming to establish a comprehensive open
  platform that supports and unifies research, technology, and applications in
  exploring the possibilities of online education in the era of large model AI.
  We envision this platform as a collaborative hub, bringing together educators,
  researchers, and innovators to collectively explore the future of AI-driven
  online education.
paper_ai_keywords: large language models (LLMs) multi-agent systems MAIC (Annotative AI-empowered Course) educational recommendation intelligent tutoring AI-augmented classroom scalability adaptivity preliminary experiments learning records open platform collaborative hub