The Integration of Artificial Intelligence and Practical Teaching in Vocational Education: Mechanism and Framework
Abstract
cultivation and industrial demand. However, it currently faces widespread structural dilemmas including limited situational boundaries, insufficient personalized guidance, lack of process-oriented evaluation systems, and inadequate integration between industry and education.
The iterative upgrading of artificial intelligence (AI) offers new possibilities to solve these problems. Nevertheless, existing studies mostly
focus on scenario-based explorations of technical applications, lack systematic explanations of the internal mechanism of integrating AI
and practical teaching in vocational education, and have not yet formed a theoretical framework that conforms to the law of vocational
skill formation and possesses both universality and operability. Supported by vocational skill formation theory, constructivist learning
theory, the Technological Pedagogical Content Knowledge (TPACK) framework, and empowerment theory, this study clarifies the core
connotation of integrating AI and practical teaching in vocational education, systematically deconstructs the internal operation mechanism
of their integration, reveals the hierarchical evolution law of the integration process, and further constructs a systematic integration framework covering core objectives, main modules, implementation links and guarantee systems. This study not only enriches the theoretical
system of digital transformation of vocational education, but also provides an implementable blueprint for vocational colleges to promote
the reform of AI-enabled practical teaching.
Keywords
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DOI: http://dx.doi.org/10.70711/neet.v4i6.9530
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