Design and Evaluation of Augmented Reality for Automotive Technical Skills Training

Thesis Abstract

The rapid advancement of automotive technology necessitates innovative approaches to technical skills training that are both effective and engaging for learners. Traditional training methodologies often face limitations in providing realistic, safe, and scalable operational experiences, which can hinder skill acquisition and retention among automotive trainees. This study aims to design and evaluate an augmented reality (AR)-based training system tailored for automotive technical education, with the objective of enhancing practical skills, conceptual understanding, and learner engagement. The specific objectives include developing an AR training prototype for key automotive procedures, assessing its usability and effectiveness relative to conventional training methods, and exploring learners' perceptions of AR integration into automotive education. Employing a mixed-methods research design, the study integrates quantitative experimental procedures with qualitative feedback analysis. The population comprises 120 automotive technical students and trainees from three vocational colleges, with a purposive sample of 60 participants divided equally into control (traditional training) and experimental (AR-based training) groups. Data collection instruments include structured skill assessments, pre-and post-intervention questionnaires grounded in Kirkpatrick’s Evaluation Model, and semi-structured interview protocols for focus groups. The reliability of quantitative instruments is established through Cronbach's alpha exceeding 0.85, while content validity is assured via expert review. Quantitative data are analyzed using statistical techniques such as t-tests for mean differences, ANOVA to assess interaction effects, and regression analysis to identify predictors of skill acquisition. Qualitative data undergo thematic analysis to extract overarching themes related to usability, engagement, and perceived learning benefits. It is anticipated that the AR training system will significantly improve learners’ practical skills performance, with higher post-test scores compared to the control group, supported by increased motivation and confidence levels as captured in questionnaire responses. The qualitative insights are expected to reveal positive perceptions of AR's immersive and interactive features, as well as its potential to simulate complex automotive procedures safely and cost-effectively. The study’s findings are projected to demonstrate that AR technology facilitates enhanced learning outcomes aligning with constructivist learning theories and the Cognitive Load Theory, which emphasize active engagement and visual-spatial processing. This research contributes novel insights into the application of augmented reality within automotive technical education, filling existing gaps related to empirical evidence of AR’s effectiveness in vocational skills training and learner-centered pedagogies. It advances the theoretical understanding of technology-enhanced learning (TEL) by contextualizing AR’s role in experiential and simulation-based learning environments. Practically, the study offers a validated framework for developing scalable AR-based training modules that can be integrated into automotive technical curricula, ultimately improving skill competency, reducing training costs, and increasing occupational safety. The main conclusion underscores that AR-based training is a superior and sustainable alternative to conventional methods in automotive education, fostering higher engagement, improved skill retention, and enhanced learner confidence. The study recommends broader implementation of AR technologies in technical training institutions, alongside continuous evaluation and customization aligned with evolving automotive technologies. Future research should explore longitudinal impacts of AR integration, expand sample sizes across diverse educational settings, and incorporate emerging technologies like artificial intelligence to further personalize learning experiences and optimize training effectiveness.