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Innovation and Practice of a Talent Cultivation Model for AI Technical Skills in Higher Vocational Education Based on "Four-Stage Progression, Dual Integration, and Virtual-Physical Symbiosis"

Author(s)

Zhengrong Luo1,2,*, Bo Hu1, Jinyang Jiang1, Huajie Zhou1, Yunbo Li1, Chongquan Fang1

Affiliation(s)

1Guang’an Vocational & Technical College, Guangan, China 2Guang'an City Artificial Intelligence Technology Innovation Center, Guangan, China *Corresponding Author

Abstract

The exponential iteration of artificial intelligence technology has posed three structural challenges to talent cultivation in higher vocational education: the widening technological generation gap, increasingly fragmented student profiles, and deepening superficiality in industry-education collaboration. This study constructs a theoretical model of "Four-Stage Progression, Dual Integration, and Virtual-Physical Symbiosis," achieving a paradigm breakthrough through a three-dimensional governance framework. A dynamic stratification mechanism based on competency models resolves the contradiction between student heterogeneity and teaching homogeneity; a curriculum transformation path relying on decomposed industrial work orders establishes a rapid translation channel from technical knowledge to educational elements; and a certification closed-loop ecosystem is built to form a value feedback chain between teaching and work driven by competency certification. This model provides innovative theoretical contributions in reconstructing educational governance structures, mechanisms for translating technical knowledge, and the evolution of industry-education integration ecosystems. Its scaling requires overcoming challenges such as gradient dependence on regional industrial innovation capacity, high-level technology reliance in virtual training platforms, and institutional rigidity constraints. Future development paths must deconstruct institutional barriers through flexible academic system reforms, leverage cross-regional vocational education communities to dilute resource disparities, and innovate digital education infrastructure supply models via public-private partnership paradigms.

Keywords

Artificial Intelligence Technology; Talent Cultivation Model; Higher Vocational Education; Industry-Education Integration; Educational Governance

References

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