From MOOC to MAIC: Reshaping Online Teaching and Learning through LLM-driven Agents
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866913492208975872 |
|---|---|
| author | Yu, Jifan Zhang, Zheyuan Zhang-li, Daniel Tu, Shangqing Hao, Zhanxin Li, Rui Miao Li, Haoxuan Wang, Yuanchun Li, Hanming Gong, Linlu Cao, Jie Lin, Jiayin Zhou, Jinchang Qin, Fei Wang, Haohua Jiang, Jianxiao Deng, Lijun Zhan, Yisi Xiao, Chaojun Dai, Xusheng Yan, Xuan Lin, Nianyi Zhang, Nan Ni, Ruixin Dang, Yang Hou, Lei Zhang, Yu Han, Xu Li, Manli Li, Juanzi Liu, Zhiyuan Liu, Huiqin Sun, Maosong |
| author_facet | Yu, Jifan Zhang, Zheyuan Zhang-li, Daniel Tu, Shangqing Hao, Zhanxin Li, Rui Miao Li, Haoxuan Wang, Yuanchun Li, Hanming Gong, Linlu Cao, Jie Lin, Jiayin Zhou, Jinchang Qin, Fei Wang, Haohua Jiang, Jianxiao Deng, Lijun Zhan, Yisi Xiao, Chaojun Dai, Xusheng Yan, Xuan Lin, Nianyi Zhang, Nan Ni, Ruixin Dang, Yang Hou, Lei Zhang, Yu Han, Xu Li, Manli Li, Juanzi Liu, Zhiyuan Liu, Huiqin Sun, Maosong |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_03512 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | From MOOC to MAIC: Reshaping Online Teaching and Learning through LLM-driven Agents Yu, Jifan Zhang, Zheyuan Zhang-li, Daniel Tu, Shangqing Hao, Zhanxin Li, Rui Miao Li, Haoxuan Wang, Yuanchun Li, Hanming Gong, Linlu Cao, Jie Lin, Jiayin Zhou, Jinchang Qin, Fei Wang, Haohua Jiang, Jianxiao Deng, Lijun Zhan, Yisi Xiao, Chaojun Dai, Xusheng Yan, Xuan Lin, Nianyi Zhang, Nan Ni, Ruixin Dang, Yang Hou, Lei Zhang, Yu Han, Xu Li, Manli Li, Juanzi Liu, Zhiyuan Liu, Huiqin Sun, Maosong Computers and Society Computation and Language 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. |
| title | From MOOC to MAIC: Reshaping Online Teaching and Learning through LLM-driven Agents |
| topic | Computers and Society Computation and Language |
| url | https://arxiv.org/abs/2409.03512 |