Motion Capture as an Immersive Learning Technology: A Systematic Review of Its Applications in Computer Animation Training
Year: 2025
Type: review
Study design: Systematic Review
Abstract: Motion capture (MoCap) is increasingly recognized as a powerful multimodal immersive learning technology, providing embodied interaction and real-time motion visualization that enrich educational experiences. Although MoCap is gaining prominence within educational research, its pedagogical value and integration into computer animation training environments have received relatively limited systematic investigation. This review synthesizes findings from 17 studies to analyze how MoCap supports instructional design, creative development, and workflow efficiency in animation education. Results show that MoCap enables a multimodal learning process by combining visual, kinesthetic, and performative modalities, strengthening learners’ sense of presence, agency, and perceptual–motor understanding. Furthermore, we identified five key technical affordances of MoCap, including precision and fidelity, multi-actor and creative control, interactivity and immersion, perceptual–motor learning, and emotional expressiveness, which together shape both cognitive and creative learning outcomes. Emerging trends highlight MoCap’s growing convergence with VR/AR, XR, real-time rendering engines, and AI-augmented motion analysis, expanding its role in the design of immersive and interactive educational systems. This review offers insights into the use of MoCap in animation education research and provides a springboard for future work on more immersive and industry-relevant training.
DOI: 10.3390/mti10010001
Institutions: Anhui Xinhua University, Universiti Teknologi MARA
Language: English
Topic: Human Motion and Animation
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
SDG: Quality education
Open Access status: gold
Estimated APC paid: $1,930
Funder: Anhui Xinhua University
OpenAlex ID: W7116861382