Reframing Vocational Teachers’ Roles in the Digital Turn: School–Enterprise Partnership and AI-Enabled Pedagogy in Liaoning Province

Abstract

Digital transformation in vocational education is often discussed in terms of platforms, infrastructure, or curricular modernization. Less attention has been paid to the redistribution of pedagogical and organizational work that accompanies these changes. This article examines how vocational teachers’ professional roles are being reshaped at the intersection of school–enterprise partnership and AI-enabled pedagogy. The study adopts an integrative review of scholarship on vocational education digitalization, teacher professionalism, work-based learning, and artificial intelligence in education, combined with a policy-text analysis of national Chinese and Liaoning provincial documents. The analysis shows that digital transformation does not simply add new tools to existing routines. It expands teachers’ work in five directions: learning design, boundary-spanning coordination with industry, data-informed mentoring, curriculum and resource curation, and ethical governance of AI use. School–enterprise partnership functions as an organizational mechanism because it redistributes curriculum development, assessment, and practice supervision across institutional boundaries. AI-enabled pedagogy functions as a pedagogical mechanism because it changes how teachers diagnose learner needs, organize practice, provide feedback, and monitor progression. In Liaoning Province, where digital campus construction and industrial upgrading are advancing together, the coupling of these two mechanisms is especially visible. The article argues that the future vocational teacher is neither a traditional lecturer nor a mere platform operator, but a professional who connects occupational standards, digital resources, and student development. On this basis, the paper proposes practical pathways for vocational colleges, including teacher industry residency, discipline-specific AI professional development, workload recognition for partnership work, and human-centered governance of educational data and AI applications.