Artificial Intelligence (AI) is not merely another technological trend for Technical and Vocational Education and Training (TVET); it challenges some of its foundational assumptions. As AI reshapes occupational profiles and production processes, TVET systems are compelled to reconsider what constitutes vocational competence, how skills are assessed, and who benefits from technological change. It is influencing changing skill demands, driving curriculum transformation, and redefining approaches to teaching, learning, and assessment. As a result, AI is becoming an increasingly influential force in the way vocational education is designed, implemented, and experienced. This issue aims to examine the dynamic relationship between AI and TVET and to highlight emerging developments at this critical intersection.
The contributions in this issue demonstrate that AI integration in TVET is neither linear nor uniform. Instead, it unfolds across unequal infrastructures, diverse institutional cultures, and contrasting pedagogical traditions. The tension between technological innovation and structural constraint emerges as a recurring theme throughout the issue.
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About TVET@Asia
TVET@Asia is an open content online journal for scientists and practitioners in the field of Technical and Vocational Education and Training (TVET) and Vocational Teacher Education (VTE) in the East and Southeast- Asian region.
Its main purpose is to provide access to peer reviewed papers and thus to enhance the dissemination of relevant content and the initiation of open discussions within the TVET community.
Impact of equity, inclusiveness, and digital divide on Artificial Intelligence adoption in Technical and Vocational Education and Training Institutions in Africa. A case of Zimbabwe
This study examines the challenges and opportunities presented by equity, inclusiveness, and the digital divide in the adoption of Artificial Intelligence (AI) within Technical and Vocational Education and Training (TVET) institutions in Zimbabwe. The study adopted mixed methods design, employing quantitative surveys to map infrastructural and device equity disparities (the digital divide) and qualitative critical ethnography. It used a sample size totalling 5 TVET institutions and 50 key informants. Quantitative data was analysed using frequency distributions to map the prevalence of infrastructural disparities and regression analysis to determine the statistical significance of access gaps related to socio-economic factors. Qualitative data was analysed using thematic analysis to identify, analyse, and report patterns (themes) within the interview and focus group data. Findings revealed significant disparities in AI readiness, with urban institutions generally better equipped. Challenges such as limited funding and high internet costs disproportionately affect marginalized groups. The study concludes that while AI has transformative potential for TVET, equitable adoption is obstructed by systemic inequities and the digital divide. Key recommendations include investing in digital infrastructure, creating national AI strategies for TVET, integrating digital literacy into curricula, and fostering public-private partnerships for AI training.
When Crisis Drives Innovation: How VET Leaders Interpret AI as Response to Workforce Challenges and Status Decline
Across vocational education institutions in England and Australia, educators are adopting artificial intelligence (AI) out of necessity rather than through policy directive. Staff managing 47-hour marking loads within 36.25 paid hours have discovered that AI tools can reduce administrative time by up to 80%, even when their use operates beyond formal policy frameworks. This study utilises uncertainty reduction theory to explore how vocational education and training (VET) leaders engage with proactive (anticipating future possibilities) and retroactive (interpreting observed behaviours) processes to navigate technological disruption. Through qualitative semi-structured interviews, the research investigates how technological uncertainty intersects with broader sector challenges, including recruitment, workload, and professional recognition. Analysis reveals leaders managing complex information flows about technology adoption occurring outside formal channels. With teaching staff age averaging 55–57 years, leaders describe facilitating information exchange between generations, with some educators lacking fundamental computer skills whilst others bring industry-derived technological confidence. VET administrators recognise educator resilience emerging through crisis-driven technological adaptations, despite persistent structural constraints. The research demonstrates organisational uncertainty management through recursive cycles linking observation with planning. Successfully integrating AI requires balancing informal experimentation with formal compliance, protecting staff whilst maintaining regulatory adherence within risk-averse cultures. Addressing technological uncertainty and structural workforce challenges must occur simultaneously.
Readiness of TVET Educators for AI-Supported Instruction: A Multi-Dimensional Assessment of Competencies and Pedagogical Adaption
Artificial intelligence (AI) is transforming teaching and learning in technical and vocational education and training (TVET), yet educators’ readiness for AI-supported instruction remains underexplored in developing contexts. This study assessed the levels and interrelationships of AI readiness, digital literacy, pedagogical adaptability, perception of AI, and attitudinal competencies among TVET educators, as well as differences across selected demographic variables. A cross-sectional survey design was adopted, involving 416 university-based TVET educators. Data were analysed using descriptive statistics, ANOVA, and correlation techniques. Findings revealed moderate levels of AI readiness and digital literacy, alongside high levels of pedagogical adaptability, perception of AI, and attitudinal competencies. Educators demonstrated strong foundational competencies but limited engagement with advanced AI-enabled instructional practices. Significant differences were observed in pedagogical adaptability across age groups, while attitudinal competencies were highest among educators with six to ten years of teaching experience. The competency dimensions were positively and significantly interrelated, indicating a coherent readiness ecosystem. Overall, while TVET educators exhibit favourable dispositions towards AI, their readiness for AI-supported instruction is still emerging, highlighting the need for structured professional development, improved digital infrastructure, and institution-wide AI integration frameworks.
Empowering Adult Educators’ Artificial Intelligence Competence: Current Understanding and Strategies for Future Directions in Brunei
The rapid emergence of artificial intelligence (AI) is transforming global industries and labour markets at an unprecedented rate, making it essential to fundamentally shift technical and vocational education and training (TVET) to equip the future-proof workforce with the essential AI competencies it needs. This shift has significant implications for TVET educators, who must be competent in integrating AI into their teaching and learning processes. This chapter draws on data from an international study examining the current landscape and future trends of adult educators’ practice and perceptions on AI. Whilst the study was conducted across multiple countries, this chapter focuses on findings from Brunei, situating it within broader discourses on AI in adult education. An online survey was conducted between June and August 2024. A total of 118 respondents working across the higher education and TVET institutions completed the survey in Brunei. This survey was used to examine the current landscape and future trends in adult educators’ practice and perceptions of AI in higher education and adult education contexts. Based on the findings, the chapter proposes a multi-layered strategy to empower adult educators, including TVET educators, that embeds AI literacy into their professional learning within a broader digital competence framework. This strategy repositions TVET educators as critical practitioners capable of mediating between AI and pedagogy to ensure AI adoption strengthens, rather than undermines, equity and learner agency. The chapter concludes by advocating for systemic professional learning, communities of practice, and policies that recognise AI competence as central to TVET educator professionalism.
Integration of AI into Art & Design TVET Curricula: Expert Perspectives on Strategies and Implications for Pakistan
The current study is a qualitative research examining the urgent need to consider utilizing Artificial Intelligence (AI) technologies in Technical and Vocational Education and Training (TVET) curricula and training programs in different Art and Design courses. Given that AI is rapidly changing the creative and technical sectors, TVET systems should keep up with it to provide graduates with the appropriate skills. A group of 12 informants participated in a focus group discussion (FGD), including specialists in five significant areas of the TVET: fashion design, graphic design, textile, interior design, and digital technology. During the FGD session, the discussions on the strategies to be used, opportunities, and challenges involved in integrating AI in the selected vocational training areas were thoroughly discussed. The results indicate that the most effective integration has been regarded as important in keeping TVET relevant. The respondents also found opportunity areas that should be developed in their curriculum, such as developing the skills to be more productive, to develop innovation, and to teach hybrid skill sets that could combine the technical AI skills with creative and critical thinking. Nevertheless, it was observed that there were immense obstacles that included educator training, ethical issues, and revision of old curricula. The paper concludes that a proactive and strategic approach toward AI integration, with outlined learning outcomes, ongoing instructional growth, and adaptable instructions, is needed to match the results of TVET and the needs of the digital economy in the South Asian market, in particular, Pakistan.
Toward an AI-Ready VR Machine Workshop: Transforming CNC Machining Training in TVET for Industry 4.0
The Fourth Industrial Revolution (IR 4.0) requires innovative teaching approaches in Technical and Vocational Education and Training (TVET). This paper presents the VR Machine Workshop, a digital learning environment designed to introduce measurement concepts and machining fundamentals through an immersive 3D platform. By allowing learners to explore visual representations of precision measurement tools such as vernier callipers, micrometers, and height gauges, the system provides a safe and cost-effective environment for repeated practice while reducing dependency on physical equipment.
The project was piloted with Sijil Kemahiran Malaysia (SKM) Level 3 CNC Machining students using a blended learning approach that combined VR-based training through the Artsteps platform with conventional workshop practice. Results indicate improvements in conceptual understanding, measurement accuracy, and learner confidence, accompanied by higher engagement and sustained learning focus.
At its current stage, the VR Machine Workshop functions as a VR-based instructional environment rather than a fully autonomous artificial intelligence (AI) system. It should therefore be understood as an AI-ready learning approach that demonstrates potential for future integration of intelligent features such as adaptive learning guidance, performance analytics, and personalised learning pathways. The study illustrates how immersive VR environments can support the digital transformation of TVET pedagogy in the Industry 4.0 context.
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Call for Papers:
Issue 28: Bridging the Skills Gap: Industry–TVET Partnerships for Workforce Readiness
TVET@Asia invites researchers, scholars, practitioners, and policymakers to contribute to a special issue focused on the theme of Bridging the Skills Gap: Industry–TVET Partnerships for Workforce Readiness.
Scope and Objective:
The rapid acceleration of digitalization, the transformative influence of artificial intelligence (AI) and robotics, the transition toward a green economy, and the volatility of global markets have created an urgent need for a workforce capable of adapting through continuous skill expansion and professional development. As industry requirements evolve more rapidly than traditional curricula, the synergy between Technical and Vocational Education and Training (TVET) and the industrial sector has become a strategic imperative. To ensure genuine workforce readiness, we must move beyond superficial cooperation toward deep, systemic partnerships.
Sustainable industry-TVET partnerships require alignment across multiple dimensions. At the institutional and legal level, public-private partnerships must be grounded in clear obligations and mutual requirements. Curricula must integrate the evolving competences demanded by industry, while teaching and learning methodologies should mirror actual workplace conditions. Furthermore, TVET institutions require the necessary infrastructure to support high-quality work-based learning, and educators must maintain an up-to-date understanding of industrial production processes to deliver industry-driven skills. Achieving these goals requires structured communication frameworks to facilitate continuous exchange between all stakeholders.
This issue aims to examine the various dimensions of industry-TVET partnerships in promoting workforce readiness. We invite original research papers, conceptual and theoretical works, policy-focused studies, and practical case analyses that investigate how established private-public partnerships can close the skills gap and enhance employability. Contributions may also provide critical reflections on policies, models, innovations, and the broader impact of these partnerships on learners, industries, and communities.
Potential areas of interest include, but are not limited to:
- Co-Curriculum Development: Strategies for agile curriculum design involving industry stakeholders to ensure alignment with real-world labor market needs.
- Work-Integrated Learning: Evaluation of dual-education systems, apprenticeships, and internship models that effectively transition students from classroom to workplace.
- Teacher & Trainer Professionalization: Models for "industry-to-classroom" knowledge transfer and the continuous upskilling of TVET instructors.
- Policy & Governance: Analysis of public-private partnership frameworks that incentivize industry investment in vocational education.
- Inclusive Readiness: Ensuring that TVET partnerships address equity, diversity, and the inclusion of marginalized groups in the modern workforce.
This issue is intended to serve as an important reference and knowledge platform for educators, industry stakeholders, researchers, and policymakers who are dedicated to strengthening TVET’s role in bridging skills gap and promoting work readiness.
Submission Guidelines:
Authors are invited to submit their original manuscripts following the guidelines provided by TVET@Asia Online Journal. All submissions will undergo a rigorous peer-review process to ensure the quality, relevance, and originality of the research. Manuscripts should be written in English and adhere to the journal's formatting and citation style.
Please note that the journal does not provide language editing or copyediting services. Authors are therefore responsible for ensuring that their manuscripts are written in clear and correct English prior to submission. Authors are encouraged to carefully check grammar, spelling, and language quality before submission and may consider using professional language editing services or AI-supported writing tools where appropriate.
We welcome submissions from any interested authors!
We look forward to receiving your contributions!
Please find below:
- the template for the article template_TVETAsia.docx
- the form for the abstract form-abstract_tvet-online.docx
Editors of Issue 28
These are the editors of our upcoming TVET@Asia issue:
Adeline Goh Yuen Sze (University of Brunei Darussalam)
Philipp Grollmann (TU Dortmund University)
Siriphorn Schlattmann (Rajamangala University of Technology Lanna)
Lee Ming Foong (Tun Hussein Onn University of Malaysia)
Become an Author
This Call for Papers is open to any interested author.
We invite scholars, scientists, curriculum developers, practitioners and teachers from the TVET community to contribute to the upcoming Issue 28 of TVET@Asia.
We look forward to receiving your contributions!
TIMELINE
Submit Your Abstract
by August 30th, 2026
To participate we ask you to send us the following documents:
- an abstract of no more than one page (please download this form),
- a short CV/profile (half page),
- a photograph of yourself, and
- a list of publications
Please submit your work via E-Mail:
Abstract Notification
by September 11th, 2026 you will be informed whether your abstract has been accepted.
Paper Submission
Please use this article template to submit your paper.
The full draft paper should be submitted until: October 20th, 2026.
Peer Review
Notification of acceptance and peer review feedback by November 27th, 2026.
Final Submission
Submission of the final, correctly-formatted paper by January 8th, 2027.
Publication
Tentative publication date: February 12th, 2027.
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Here you can subscribe to our newsletter! Through the newsletter we will inform you about new Calls for Papers, the publication of new issues of TVET@Asia as well as the latest publications and events in the field of Technical and Vocational Education and Training.
