Year: 2026
Type: article
Abstract: Industry 4.0 (IR4.0) has rapidly transformed the global labour market through artificial intelligence, robotics, and big data, creating new competency demands and redefining traditional occupations.However, there remains a lack of validated empirical frameworks that integrate educational and industrial perspectives on IR4.0 talent within the TVET context.This study addresses this gap by developing and validating a data-driven IR4.0 Talent Framework for Technical and Vocational Education and Training (TVET) students in Work-Based Learning (WBL) programmes at Malaysian polytechnics.An exploratory sequential mixed methods design was employed, involving document analysis, semi-structured expert interviews, and a structured questionnaire administered to 159 final-year undergraduate WBL students.The findings indicated a high level of proficiency in cognitive skills, particularly innovative thinking (mean = 4.30), creativity (mean = 4.22), and adaptability (mean = 4.18).Operational skills, including leadership (mean = 4.12) and communication (mean = 4.10), were also identified as strengths.The study developed and validated a competency classification model comprising intellectual, technical, individual, and professional competencies.These findings highlight the role of WBL in strengthening students' IR4.0 readiness and offer practical insights for educators, policymakers, and industry stakeholders in enhancing TVET implementation and future workforce development.
Language: English
Subfield: Education
Field: Social Sciences
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W7224687578