A holistic framework to create intelligent systems for psychomotor learning: a systematic review and insights from the virtual reality Kenpo learning simulator

Abstract Developing Intelligent Systems for Psychomotor Learning (ISPLs) is a complex challenge, particularly when integrating psychomotor, cognitive, and affective learning domains with advanced technologies like Artificial Intelligence (AI) and Extended Reality (XR) for personalization and immersivity. Despite growing interest, there is no comprehensive framework to create such systems. This paper introduces PsyLearn , a comprehensive framework that addresses this gap, developed through combining and analyzing tools, methods, and frameworks identified through a systematic review, and insights from the creation of the Kenpo Learning Simulator (KLS), a VR-based ISPL that teaches martial arts defensive movements using AI-based pose estimation, rules, real-time feedback, and a virtual agent. The framework integrates emerging technologies while addressing ethics, feasibility, and system evaluation, offering a modular and scalable approach to ISPL development. Key contributions include: (1) PsyLearn , a comprehensive framework for ISPL development; (2) KLS, a proof-of-concept VR-based ISPL for martial arts training; and (3) a systematic review identifying gaps and providing tools for ISPL development. By bridging theory and practice, PsyLearn advances ISPL development and lays the groundwork for integrating AI, XR, and emerging technologies into educational systems. Preliminary evaluations of KLS demonstrate its potential to improve motor skills, while also highlighting areas for refinement. This work emphasizes the importance of interdisciplinary collaboration and iterative design in creating effective, ethical, and scalable learning solutions that address the complexities of psychomotor, cognitive, and affective learning domains.