Teacher Role Reconfiguration in AI-Enabled TVET: Linking Institutional Digital Transformation and Teacher AI Application

Abstract

This study develops a mediation framework explaining how institutional digital This article develops a conceptual framework explaining how institutional digital transformation may be translated into teacher role reconfiguration in technical and vocational education and training (TVET). Drawing on sociotechnical systems theory, role theory and human-AI collaboration research, the article argues that digital transformation does not alter teacher roles simply by providing platforms, data systems or smart training environments. Its professional significance depends on teacher AI application as an enacted pedagogical practice. The framework specifies a mediation pathway from perceived institutional digital transformation to teacher AI application and then to teacher role reconfiguration. Teacher role reconfiguration is conceptualised as five-dimensional professional expansion: learning designer, data-informed mentor, smart skills coach, industry-education broker and AI ethics steward. Using Liaoning, China, as an illustrative industrial-region context, the article outlines a three-wave empirical validation protocol involving second-order construct modelling and structural equation modelling. The contribution is twofold: it shifts TVET digitalisation research from technology provision to teacher enactment, and it offers a measurable role-centred framework for studying AI-enabled professional change in vocational education.