This study focuses on the research of AIGC (Artificial Intelligence Generated Content)-empowered collaborative learning, analyzing the evolutionary process of collaborative learning paradigms from traditional collaborative learning, computer-supported collaborative learning to AIGC-driven generative collaborative learning. It elaborates on the core elements of the AIGC-driven generative collaborative learning paradigm, including the role reconstruction of teacher-student agents, the supporting system of environmental agents, and in-depth interactions under agent collaboration. The study proposes its implementation path, which forms a technical supporting system through four mechanisms: self-guidance, collaborative creation, path evolution, and swarm intelligence. Meanwhile, it points out the structural breakthroughs of AIGC-driven generative collaborative learning, such as developing learners' meta-collaboration abilities, constructing a collaborative knowledge co-creation network and cross-domain collaboration ecosystem, and promoting the intelligent evolution of collaborative roles and dynamic optimization of group decision-making. The research indicates that AIGC propels collaborative learning towards the stage of smart education, providing a practical blueprint for the transformation of educational paradigms and pointing out the direction for the application and innovative development of educational technology, which is conducive to cultivating innovative and collaborative talents.
Key words
Generative Artificial Intelligence /
collaborative learning /
educational paradigm /
agent /
smart education
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