Bridging the Industry 4.0 Skills Gap: Development of Case-Based Learning Model in AI-Powered Teaching Factory for Automotive Vocational Education

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Hasan Maksum, Wakhinuddin Simatupang, Dedy Irfan, Martias, Muhibbuddin, Hanapi Hasan

2026 International Journal of Interactive Mobile Technologies Vol. 20 Issue 10 Article Cited by 0

Abstract

This study aimed to develop a case-based learning (CBL) in artificial intelligence (AI)-powered teaching factory (CAI-TEFA) model to improve Industry 4.0 competencies of automotive vocational education students. The model was designed to address the skills gap between vocational education graduates and industry needs, integrating AI, Internet of Things (IoT), and automation systems. The development used the Research and Development (R&D) method with a 4D framework (define, design, develop, and disseminate), followed by testing through a quasi-experimental design on 68 students of the Automotive Engineering Education Study Program. Moreover, the CAI-TEFA has four main components, namely Initial Ability (basic skills), AI-Integrated Teaching Factory (TEFA) (technological infrastructure), CBL Framework with AI Integration (pedagogical mediator), and dual outcomes in the form of Industry 4.0 Competencies and Enhanced Learning Outcomes. The CAI-TEFA learning framework generates a systematic four-stage syntax with AI support, comprising Real Industry Case Analysis, Problem Identification and Diagnosis, Solution Development and Testing, as well as Implementation and Reflection. The results showed that the CAI-TEFA was highly effective with excellent validity, explaining 30.6% of the variance in Industry 4.0 competencies and 24.8% of Enhanced Learning Outcomes. Quasi-experimental testing showed significant effectiveness, with the experimental group achieving a post-test score of 84.25 compared to the control group at 67.35 and a gain score of 37.10 vs. 21.53 points (t-count 8.672 > t-table 2.000, p < 0.001). Furthermore, the model was declared “Highly Practical” with an achievement of 94.58%, showing a transformative contribution to automotive vocational education responsive to Industry 4.0, which could prepare graduates with adaptive skills to face the complexities of modern automotive technology. © 2026 by the authors of this article.

Affiliations

Universitas Negeri Padang, Padang, Indonesia; Universitas Syiah Kuala, Banda Aceh, Indonesia; Universitas Negeri Medan, Medan, Indonesia