<![CDATA[Purpose of the study: Micro-learning has gained increasing attention as an effective instructional approach for delivering concise and focused learning content, particularly in teacher education. However, its application in Physical Education Teacher Training (PETT) remains limited, especially in addressing the integration of cognitive knowledge and psychomotor skill development. The integration of motion capture (MoCap) technology offers new opportunities to enhance embodied learning through real-time biomechanical feedback and interactive visualization. This study aimed to develop MoCap-integrated micro-learning content for PETT and to examine its effects on cognitive outcomes, psychomotor performance, learner satisfaction, and engagement. Materials and methods: A quasi-experimental design was conducted with 80 PETT students (mean age = 23.5 years) from an Indonesian public university. Participants were randomly assigned to an experimental group (MoCap-based micro-learning) or a control group (traditional micro-learning). The intervention lasted eight weeks, with weekly sessions of 15–20 minutes. Cognitive knowledge, psychomotor performance, learner satisfaction, and engagement were assessed using validated instruments. Data were analyzed using independent and paired-samples t-tests and Pearson correlation analysis. Results: The experimental group demonstrated significantly higher post-test scores in cognitive knowledge, psychomotor performance, learner satisfaction, and engagement compared to the control group (p < 0.001). Strong positive correlations were found between MoCap-based engagement and learning outcomes (r = 0.68–0.74). Learning gains were substantially greater in the experimental group across all measured domains. Conclusions: MoCap-enhanced micro-learning significantly improves cognitive and psychomotor outcomes while increasing learner engagement and satisfaction in PETT. This approach effectively bridges the gap between theoretical understanding and practical skill execution, highlighting its potential as an innovative and scalable model for IT-based physical education teacher training.]]>
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