Construction of a Project-Based Learning Model under the Generative Artificial Intelligence Multi-Agent Collaborative Framework

Abstract

The breakthrough development of generative artificial intelligence provides technical possibilities for its integration into project-based learning. However, how to organically integrate the content generation capability of generative artificial intelligence with the distributed collaboration capability of multi-agent systems to construct an adaptive project-based learning support framework remains a core issue in the current field of educational technology research. This study focuses on the construction of a project-based learning model under the generative artificial intelligence multi-agent collaborative framework, and it elaborates on the topic from three dimensions: theoretical foundation, architectural design, and process regulation. At the level of theoretical foundation, this study explains the educational application logic of generative artificial intelligence and the architectural principles of the multi-agent collaborative mechanism. At the level of architectural design, this study constructs a learning support framework that encompasses intelligent task decomposition, multi-agent role configuration, and generative resource organization. At the level of process regulation, this study explores the intelligent perception of the learning process, the emergent characteristics of group knowledge construction, and the closed-loop feedback mechanism for outcomes. This research aims to provide a theoretical reference for the deep integration of generative artificial intelligence in the educational field and to offer framework support for the intelligent transformation of project-based learning.