Research on the Dual-Driven Teaching Reform of "AI + Industry-Education Integration" for Intelligent Manufacturing Professional Groups in Higher Vocational Colleges

Abstract

Against the dual strategic backdrop of the accelerated cultivation of new quality productive forces and the digital transformation of vocational education, the intelligent manufacturing industry has achieved comprehensive iterative upgrading relying on cutting-edge technologies such as artificial intelligence, digital twins, and industrial big data. Subversive changes have taken place in the industrial post structure, technical standards, and talent competency system, forcing higher vocational colleges to carry out systematic and in-depth teaching reforms for intelligent manufacturing professional groups. The two-way linkage of AI empowerment and in-depth industry-education integrationhasbecome acoreapproachforintelligent manufacturingprofessional groupsin highervocationalcolleges tosolvepracticaldilemmasincludingthesupply-demandmismatchintalenttraining,thelagofteachingcontentbehind industrial development, and the formalization of school-enterprise collaborative education. It also serves as a key support for constructing a digital, intelligent and modern vocational education system. Adopting the literature review method, comparative analysis method and inductive deductive method, this paper systematically sorts out the research context and practical progress of the teaching reform of "AI + industry-education integration" for domestic intelligent manufacturing professional groups in higher vocational colleges, and defines the core connotation and coupling mechanism of the dual-driven model. By constructing two groups of comparative analysis tables, this paper quantitatively compares the differentiated characteristics between the traditional teaching model and the AI-enabled dual-driven teaching model, and analyzes the advantages, disadvantages and applicable scenarios of three mainstream domestic reform paradigms. On this basis, it summarizes common problems existing in current teaching reforms, including superficial integration of AI technology, fragmented industry-education collaboration mechanisms, delayed iteration of curriculum systems, insufficient integration of virtual and physical training, weak digital and intelligent competencies of teachers, and the absence of intelligent evaluation systems. Combined with academic research achievements and industrial practical experience, this paper sorts out systematic reform paths from six dimensions: technological integration, curriculum restructuring, training upgrading, mechanism innovation, teacher training, and evaluation optimization, and prospects the future development trends of relevant reforms. This study aims to enrich the theoreticalsystemofdigitaleducationforintelligentmanufacturingprofessionalgroups,andprovidetheoreticalsupport and practical