Article Gold Open Access 2025

The Domains and Components of Industry 4.0 Talent for TVET Students Through Work-Based Learning

Journal of Technical Education and Training
Journal · Vol. 17 · Issue 3 · pp. 106-117
Abstract

The Fourth Industrial Revolution (IR4.0) era of artificial intelligence, characterised by the digitization of technology, has revolutionised organisations worldwide, including corporate organizations. This shift has resulted in the emergence of a workforce with enhanced skills and competencies. This study aims to pinpoint the essential elements of IR4.0 talent domains that students from top technical and Vocational Education and Training (TVET) providers require for their Work-Based Learning (WBL) programmes. Consistent with the IR4.0 National Policy of Malaysia, this study contributes to the current workforce preparedness that could handle the challenges and opportunities of the revolution, consistent with Malaysia's IR4.0 National Policy. Qualitative data was collected through semi-structured interviews with 6 academic and 5 industry experts. The data were analysed through theme analysis and reliability analysis using Fleiss’s Kappa analysis. The study identified 21 key components across four domains: cognitive skills (6 components), operational work skills (5 components), individual skills (7 components), and professionalism (3 components). All of this simply emphasises the importance of acquiring IR4.0 competencies in TVET programmes, particularly through work-based learning, for TVET graduates to have the competencies needed in practice and the mindset towards success within the current context of industry, as well as to contribute to future talent readiness. © 2025, Penerbit UTHM. All rights reserved.

Keywords

Author Keywords

TVET work-based learning Fourth Industrial Revolution talent

Index Keywords

Author Affiliations
Faculty of Technical and Vocational Education, Universiti Tun Hussein Onn Malaysia, Batu Pahat, Johor, Malaysia
Department of Electrical Engineering, Politeknik Sultan Salahuddin Abdul Aziz Shah, Shah Alam, Selangor, Malaysia
Funding & Acknowledgements
Pusat Pengurusan Penyelidikan, Universiti Tun Hussein Onn Malaysia, RMC
This research was supported by the Ministry of Higher Education (MOHE) through the Fundamental Research Grant Scheme (FRGS/1/2022/SS10/UTHM/02/11). We also want to thank to the Research Management Centre, Universiti Tun Hussein Onn Malaysia and the Department of Polytechnic and Community College, MOHE for their contributions and support.
Ministry of Higher Education, MOHE
Grant: FRGS/1/2022/SS10/UTHM/02/11
This research was supported by the Ministry of Higher Education (MOHE) through the Fundamental Research Grant Scheme (FRGS/1/2022/SS10/UTHM/02/11). We also want to thank to the Research Management Centre, Universiti Tun Hussein Onn Malaysia and the Department of Polytechnic and Community College, MOHE for their contributions and support.
Ministry of Higher Education, MOHE
This research was supported by the Ministry of Higher Education (MOHE) through the Fundamental Research Grant Scheme (FRGS/1/2022/SS10/UTHM/02/11). We also want to thank to the Research Management Centre, Universiti Tun Hussein Onn Malaysia and the Department of Polytechnic and Community College, MOHE for their contributions and support.
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