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<p>The rapid evolution of Industry 4.0 requires innovative approaches in engineering education, particularly in Computer Numerical Control (CNC) training, where machine-based instruction can be costly, safety-sensitive, and constrained by limited access to equipment. This study examined the effectiveness of Augmented Reality (AR) for CNC instruction among third-year mechanical engineering students at Universitas Negeri Padang using a quasi-experimental, non-equivalent groups design (<i>n</i> = 32). Students were assigned to an AR-based condition (<i>n</i> = 16) or a comparison condition consisting of non-AR digital simulation-based instruction (<i>n</i> = 16). Data collection combined pre- and post-tests, an engagement survey, and focus group discussions to triangulate quantitative and qualitative evidence. The AR group showed significantly higher learning gains, with mean scores increasing from 52.08 to 88.12, a high normalized gain (mean N-Gain = 0.75), and a large effect size (Cohen’s d = 1.185). Post-test score dispersion was lower in the AR group within this cohort, indicating more uniform learning outcomes without implying system-level equity effects. Qualitative feedback suggested that AR supported spatial understanding and learner engagement, while tracking stability and the continued need for real-machine practice were noted as implementation challenges. Overall, these findings provide preliminary evidence that AR can enhance CNC learning outcomes over an already technology-enhanced baseline, warranting multi-site and longitudinal validation.</p>

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Enhancing CNC instruction with augmented reality: empirical evidence from mechanical engineering education

  • 期刊论文

  • 发表日期：

    2026年2月25日

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  • Febri Prasetya,
  • Aprilla Fortuna,
  • Agariadne Dwinggo Samala,
  • Syahril Syahril,
  • Waskito Waskito,
  • Suci Andri,
  • Soha Rawas,
  • Firas Tayseer Ayasrah

摘要

The rapid evolution of Industry 4.0 requires innovative approaches in engineering education, particularly in Computer Numerical Control (CNC) training, where machine-based instruction can be costly, safety-sensitive, and constrained by limited access to equipment. This study examined the effectiveness of Augmented Reality (AR) for CNC instruction among third-year mechanical engineering students at Universitas Negeri Padang using a quasi-experimental, non-equivalent groups design (n = 32). Students were assigned to an AR-based condition (n = 16) or a comparison condition consisting of non-AR digital simulation-based instruction (n = 16). Data collection combined pre- and post-tests, an engagement survey, and focus group discussions to triangulate quantitative and qualitative evidence. The AR group showed significantly higher learning gains, with mean scores increasing from 52.08 to 88.12, a high normalized gain (mean N-Gain = 0.75), and a large effect size (Cohen’s d = 1.185). Post-test score dispersion was lower in the AR group within this cohort, indicating more uniform learning outcomes without implying system-level equity effects. Qualitative feedback suggested that AR supported spatial understanding and learner engagement, while tracking stability and the continued need for real-machine practice were noted as implementation challenges. Overall, these findings provide preliminary evidence that AR can enhance CNC learning outcomes over an already technology-enhanced baseline, warranting multi-site and longitudinal validation.