2026 ASEE Annual Conference & Exposition

Effective development of psychomotor skills where perception, cognition, and motor coordination converge is central to workforce preparation in STEM and technical fields. However, traditional training environments often lack scalability, consistent feedback, and adaptive support. This study presents the design and evaluation of an XR-enhanced Intelligent Tutoring Environment (XR-ITE) that integrates extended reality (XR) technologies with adaptive feedback and performance analytics to foster psychomotor skill learning. The environment was designed using a human-centered framework emphasizing realistic affordances, embodied interaction, and adaptive task scaffolding. Within the XR-ITE, learners manipulate virtual tools, receive multimodal cues, and engage in progressively complex tasks while the system dynamically adjusts feedback and guidance based on performance metrics. Empirical results demonstrate significant improvements in motion accuracy, task completion time, and retention, compared to traditional instruction. The findings highlight key design considerations for XR-based psychomotor environments including alignment between virtual and physical affordances, fidelity of motion tracking, and cognitive load management and discuss implications for scalable, immersive, and equitable STEM workforce training.