Abstract
Background of study: The advance of Industry 4.0, artificial intelligence (AI), and digital transformation has reshaped Technical and Vocational Education and Training (TVET) and requires vocational teachers to develop adaptive capacities aligned with twenty-first-century learning demands, yet the knowledge structure and research direction in this area have not been comprehensively mapped. Aims and scope of paper: This study analyzes the intellectual structure, developmental trends, and thematic clusters of research on vocational teacher adaptation. Methods: A total of 315 Scopus-indexed documents, exported in RIS format on 19 July 2026, were examined through performance analysis and science mapping using VOSviewer version 1.6.18. Result: Publication output increased sharply, with more than half of the documents (163 publications) issued in 2025–2026. China, Indonesia, and Malaysia were the most productive countries, although international collaboration remained relatively low at 18.4%. Co-occurrence analysis of 91 keywords identified six clusters within a densely connected network (1,506 links; total link strength = 4,908), covering skills transformation in the Industry 4.0 era, digital competence and literacy, machine learning in engineering education, employability and AI-supported training, adaptive learning and professional development, and digital learning delivery technologies. Research attention remains dominated by learners such as students and apprentices, whereas vocational teachers, the principal actors of technological adaptation, receive limited attention. Conclusion: The field is growing rapidly but remains thematically imbalanced; future research should prioritize the adaptive capacity of vocational teachers, particularly in the Indonesian context, and strengthen international collaboration to enrich scholarly development in TVET.