Dear Colleagues,

Call for Papers: Artificial Intelligence, Emerging Technologies and the Future of Vocational Education and Training

Artificial intelligence (AI) and emerging digital technologies are transforming vocational education and training (VET) at an unprecedented pace. From generative AI and intelligent tutoring systems to learning analytics, educational datafication, extended reality (XR), digital twins, robotics, wearable technologies and agentic AI, these developments are reshaping how vocational knowledge is created, delivered, assessed and applied. At the same time, they raise important questions about the purpose of education, the future of skilled work, equity, governance, professional practice and human–AI collaboration within the transition from Education 4.0 towards Education 5.0.

This Topical Collection invites Entry and Review manuscripts that synthesise established knowledge, critically examine current developments, and provide authoritative overviews of AI and emerging technologies in vocational education and training. Contributions should present scientifically sound, evidence-informed accounts of mature topics or provide comprehensive reviews of the existing literature, identifying emerging trends, unresolved challenges and priorities for future research. Rather than presenting new empirical findings, submissions should consolidate existing knowledge, clarify concepts, evaluate current evidence, and provide accessible reference resources for researchers, educators, policymakers and practitioners.

Indicative topics include, but are not limited to, the following:

• Artificial intelligence in vocational education and training;
• Education 4.0 and Education 5.0;
• Generative AI and foundation models;
• Agentic AI and human–AI collaboration;
• Learning analytics and educational datafication;
• AI-supported assessment and feedback;
• Extended reality (VR/AR/MR/XR) and immersive learning;
• Digital twins and simulation-based vocational training;
• Robotics, automation and intelligent manufacturing education;
• Internet of Things and smart learning environments;
• Wearable technologies for vocational learning;
• Adaptive and personalised learning systems;
• AI literacy for vocational educators and learners;
• Ethics, governance and trustworthy AI;
• Algorithmic bias, transparency and accountability;
• Digital inclusion and equity in AI-enabled vocational education;
• Workforce transformation, lifelong learning and future skills;
• International and comparative perspectives on AI in VET.

Submissions should critically examine both the affordances and limitations of these technologies, including ethical, pedagogical, social and policy implications. We particularly encourage manuscripts that identify gaps in current knowledge, synthesise developments across disciplines, and consider the implications of AI for vocational education in diverse cultural, economic and geographical contexts.

This Topical Collection is committed to broadening participation in international scholarship. We warmly encourage contributions from early-career researchers, doctoral researchers and first-time authors, alongside those of established scholars. We particularly welcome perspectives from the Global South and underrepresented regions, recognising that locally grounded innovations and diverse educational traditions are essential for developing a comprehensive understanding of AI in vocational education worldwide.

Potential contributors are encouraged to engage with recent international scholarship, including work published by UNESCO and the OECD on AI and digital education, alongside contemporary research on generative AI, multimodal foundation models, learning analytics, educational datafication, AI governance and the evolving relationship between vocational education, technology and society. By bringing together authoritative Entries and critical Reviews, this collection aims to provide an enduring reference resource that informs research, policy and practice while shaping future directions for AI in vocational education and training.