Reconstructing Vocational Teacher Capacity in AI-Enabled Industry-Education Integration: A Policy and Institutional Analysis of Liaoning Province - Tang, Chi; Rozaini Binti Rosli (Asia Pacific Economic and Management Review, 2026)
The digital transformation of vocational education has moved beyond the question of whether teachers should use digital tools. In regions where industrial renewal and vocational reform overlap, the more difficult question is how teachers' professional capacity should be rebuilt when artificial intelligence, data-based training resources and school-enterprise co-development become part of everyday institutional work. Taking Liaoning Province as the analytical setting, this paper examines how vocational teachers' roles are being reorganised under three connected pressures: the spread of AI-enabled pedagogy, the demand for deeper industry-education integration and the regional need to support industrial upgrading. The study adopts qualitative document analysis of international frameworks, Chinese national policy documents, Liaoning provincial education documents and recent empirical studies on TVET teacher digital competence. The findings suggest that teacher role change is better understood as capacity reconstruction than as simple role replacement. Four dimensions are identified: curriculum translation between occupational tasks and learning outcomes, AI-assisted instructional design and verification, boundary work in school-enterprise cooperation, and ethical stewardship of digital assessment and learner data. The paper argues that AI application strengthens vocational education only when it is embedded in industry-linked curriculum renewal and supported by organisational arrangements for teacher development. For vocational colleges in Liaoning, the practical priority is not to train teachers to operate isolated tools, but to build collaborative mechanisms through which teachers, enterprises and digital platforms jointly update curriculum, assessment and workplace learning. The paper offers a regional policy-informed framework for managing vocational teacher development in AI-enabled vocational education.