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The Application of Artificial Intelligence (AI) In Vehicle Motion Mechanics Learning to Optimize Students' Critical Thinking and Problem-Solving Skills Zuhdi Almunawar, Amin; Maksum, Hasan; Adri, Muhammad; Yulia Basri, Irma
Journal of World Science Vol. 4 No. 12 (2025): Journal of World Science
Publisher : Riviera Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58344/jws.v4i12.1611

Abstract

The integration of Artificial Intelligence (AI) in vocational education opens up transformative opportunities to develop 21st-century skills, especially critical thinking and problem-solving, which are key competencies for prospective professionals in the automotive sector. This study examines the effectiveness of using AI (Claude and Pollo AI) through the Project-Based Learning (PjBL) model in improving the critical thinking and problem-solving skills of automotive engineering students in the Vehicle Motion Mechanics course. The study, using a pre-experimental intact group comparison design, involved 37 third-semester students, consisting of an experimental group () and a control group (). The experimental group learned using AI-based PjBL, while the control group received conventional Discovery Learning. Data were collected through validated analytical rubrics and analyzed using an independent samples t-test and effect size. The results showed that the experimental group obtained a much higher critical thinking score (M = 82.45; SD = 6.23) compared to the control group (M = 71.33; SD = 7.89), . Similar improvements were also found in problem-solving skills (M = 84.12; SD = 5.87 vs. M = 69.78; SD = 8.45), , which indicates a strong practical impact. These findings confirm that the integration of AI through PjBL effectively strengthens critical thinking and problem-solving skills in automotive vocational education, while providing empirical evidence to drive technology-based engineering learning transformation.