The Cognitive Affective Model of Motion Capture Training: A Theoretical Framework for Enhancing Embodied Learning and Creative Skill Development in Computer Animation Design

Abstract

There has been a surge in interest in and implementation of motion capture (MoCap)-based lessons in animation, creative education, and performance training, leading to an increasing number of studies on this topic. While recent studies have summarized these developments, few have been conducted that synthesize existing findings into a theoretical framework. Building upon the Cognitive Affective Model of Immersive Learning (CAMIL), this study proposes the Cognitive Affective Model of Motion Capture Training (CAMMT) as a theoretical and research-based framework for explaining how MoCap fosters creative cognition in computer animation practice. The model identifies six affective and cognitive constructs: Control and Active Learning, Reflective Thinking, Perceptual Motor Skills, Emotional Expressive, Artistic Innovation, and Collaborative Construction that describe how MoCap’s technological affordances of immersion and interactivity support creativity in animation practice. The findings indicate that instructional and design methods from less immersive media can be effectively adapted to MoCap environments. Although originally developed for animation education, CAMMT contributes to broader theories of creative design processes by linking cognitive, affective, and performative dimensions of embodied interaction. This study offers guidance for researchers and designers exploring creative and embodied interaction across digital performance and design contexts.