Enhancing High Aptitude TVET Technological Assistance (HATTA) Framework of a Digital Competence Model for TVET Educator's Satisfaction by Using Linear Regression Approaches

Abstract

The integration of digital technologies in education has transformed conventional teaching methodologies, particularly within Technical and Vocational Education and Training (TVET) institutions, which play a crucial role in preparing students for the evolving workforce. As digital transformation accelerates, TVET educators must develop robust digital competencies to integrate technology into vocational training effectively. However, existing literature lacks a structured framework that addresses the challenges and opportunities associated with digital competency among TVET educators. This study aims to bridge this gap by developing the High Aptitude TVET Technology Assistance (HATTA) framework to enhance TVET educators’ digital proficiency and improve educational satisfaction. The research investigates how digital competency is incorporated into practical training, how educators adapt to technological advancements, and how digital tools enhance hands-on skill development for students. A subjective assessment method was employed, focusing on user satisfaction within the Malaysia Technical University Network (MTUN). The study collected Mean Opinion Score (MOS) data through a user acceptability review, followed by linear regression analysis to determine the relationship between user acceptability and factors influencing educator satisfaction. Findings from this study provide critical insights for policymakers, educators, and technology developers in designing effective digital competency frameworks for TVET. The HATTA framework offers a structured approach to integrating digital tools into vocational education, ensuring sustainable digital transformation in TVET institutions.