TEACHER READINESS FOR AI-DRIVEN DIGITAL TRANSFORMATION IN CHINESE TVET INSTITUTIONS: A CONCEPTUAL FRAMEWORK FOR EDUCATIONAL ADMINISTRATION

Abstract

Artificial intelligence (AI) is changing the content, delivery, assessment, and governance of technical and vocational education and training (TVET). In China, revised professional teaching standards now integrate digitalization and AI, yet institutional adoption produces educational value only when teachers can exercise informed professional judgment. This conceptual review examines teacher readiness for AI-driven digital transformation in Chinese TVET institutions from an educational administration perspective, synthesizing research on organizational readiness, AI literacy, digital competence, intelligent technological pedagogical content knowledge, and whole-institution TVET development. Teacher readiness is defined as a dynamic, multilevel state in which educators are willing and collectively able to use, evaluate, adapt, and govern AI for occupationally authentic, pedagogically sound, ethical, and inclusive learning. The framework connects nine teacher-level dimensions—human-centred orientation, change commitment, AI literacy, technical and data competence, pedagogical integration, occupational relevance, assessment capability, ethical judgment, and collaborative professional learning—with six institutional conditions: strategic leadership, infrastructure and support, job-embedded professional development, workload and incentives, school-enterprise collaboration, and data and quality governance. A staged administrative process from diagnosis through capability building, protected experimentation, scaling, institutionalization, and renewal is outlined. The article argues that readiness must be demonstrated through authentic artifacts, observed practice, and learner outcomes rather than inferred from access or self-reported confidence, so administrators should govern AI transformation as a sociotechnical change process developing teacher agency, institutional capacity, and continuous evidence together.