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Self-avatar-supported observational learning: Designing and evaluating VR-based physical exercise tutorial systems for older adults
Date Issued
2026
Publisher
Elsevier BV
ISSN
1071-5819
1095-9300
Citation
International Journal of Human-Computer Studies, 2026, vol. 212, article no. 103826.
Description
Open access
Type
Peer Reviewed Journal Article
Abstract
The global trend toward longer life spans presents an opportunity to promote active and healthy aging. Physical exercises like Qigong support holistic well-being by integrating physical, cognitive, and emotional health. However, traditional programs lack adaptability to accommodate age-related changes in physical and cognitive abilities, which can limit accessibility and engagement for older adults. Virtual Reality (VR) offers a novel solution by creating immersive, customizable environments. In our study, we designed a VR-based physical exercise tutorial (VRPET) system and assessed the efficacy of using an adaptive self-avatar (i.e., a virtual representation of the user) to enhance user exercise performance and attitudes, while examining its impact on perceived workload. We conducted a two-phase mixed-methods investigation: (1) A formative phase involving focus group interviews (n=14), a consultation with a Qigong master on movement standardization, and a heuristic evaluation (n=5) to establish design requirements; (2) A user study (n = 30) that compared the self-avatar versus non-self-avatar conditions to assess their effects on perceived workload, exercise performance, and attitude metrics. Despite a significant dip in exercise performance (p=0.03) and a non-significant increase in perceived workload (p=0.58), participants expressed a preference for the self-avatar’s real-time feedback when scaffolded appropriately. Multi-modal analysis revealed auditory cues as most effective, followed by tactile and visual feedback. Based on these findings, we propose the ACT Framework (Adaptive, Cultural, Targeted) for developing age-appropriate VR exercise systems. Furthermore, we distill our iterative process into a tripartite validation workflow, advocating for a methodology that harmonizes user desirability, expert safety, and HCI usability. These evidence-based insights advance the design of therapeutic VR interventions that can support healthy aging populations.
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