Generative AI Driving the Paradigm Shift in Smart Education: Technology Layering, Application Scenarios, and Collaborative Governance
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Keywords
artificial intelligence, smart education, large language models (LLMS), personalized learning, human-AI collaboration
Abstract
The explosive development of generative artificial intelligence is profoundly reshaping the technological pathways and application forms of smart education. Employing a narrative review methodology, this paper systematically examines the technological evolution and application trajectory of AI-empowered smart education. The study finds that the layering of technological capabilities determines the depth boundaries of application scenarios—from traditional Intelligent tutoring systems to large language models, each technological leap corresponds to a paradigm shift in educational applications, progressing from “automation” towards “generation” and “personalization.” Based on this framework, the paper identifies five core application directions: personalized learning, intelligent assessment, teacher empowerment, content generation, and educational equity. Furthermore, it recognizes three key challenges: technological adaptability, human-AI collaboration models, and ethical governance. Finally, a collaborative evolutionary research framework encompassing “Technology—Pedagogy—Governance” is proposed to provide a reference for the practical implementation of AI in education.
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