From MOOC to MAIC: Reshaping Online Teaching and Learning through LLM-driven Agents
Jifan Yu, Zheyuan Zhang, Daniel Zhang-li, Shangqing Tu, Zhanxin Hao,, Rui Miao Li, Haoxuan Li, Yuanchun Wang, Hanming Li, Linlu Gong, Jie Cao,, Jiayin Lin, Jinchang Zhou, Fei Qin, Haohua Wang, Jianxiao Jiang, Lijun Deng,, Yisi Zhan, Chaojun Xiao, Xusheng Dai, Xuan Yan

TL;DR
This paper introduces MAIC, a novel online education framework utilizing LLM-driven multi-agent systems to enhance scalability and personalization, supported by preliminary university experiments and aiming for a collaborative research platform.
Contribution
It proposes a new AI-augmented online education model using multi-agent LLM systems, integrating technical innovations and initial empirical analysis.
Findings
Preliminary experiments with 100,000+ learning records from 500+ students.
Initial observations on AI-driven personalized learning.
Foundation laid for a collaborative open platform for AI in online education.
Abstract
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…
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Taxonomy
TopicsOpen Education and E-Learning
