Developing a Demand-Driven TVET Institution Framework in Malaysia via Fuzzy Delphi Analysis

Abstract

As Industry 4.0 transforms the workplace, technical and vocational education and training (TVET) institutions are specialised in providing skills and knowledge competencies for a variety of fields. The industrial recruiters reported that they prefer to hire foreigners due to skill mismatches amongst local graduates. Therefore, this study aimed to develop a demand-driven framework for TVET institutions in Malaysia. The Fuzzy Delphi Method (FDM) had been employed to analyse experts’ judgements and determine the relevant items. The study questionnaire consisted of three constructs and eight items on a seven-point Likert scale. A total of thirteen experts were selected through the purposive sampling technique. The findings of the FDM analysis indicated a high level of expert agreement, supported by empirical evidence from quantitative data, with percentage values (≥ 75%), threshold (d ≤ 0.2), and alpha-cut level (α-cut ≥ 0.5). Resultantly, it was found that all items can be used, as expert consensus has been achieved. The framework has implications for students’ employability and supports the growth of both industry stakeholders and TVET institutions. The study recommends TVET trainers take a sabbatical to stay abreast of current industry practices and retain the TVET ecosystem with affiliated companies.