Immersive Sports Teaching System Construction and Cognitive Effect Assessment via Metaverse Interaction Modeling

In response to the burgeoning intersection between immersive extended reality (XR) technologies and computer science–driven pedagogical innovation—exemplified focus on metaverse-enhanced learning environments—the present study investigates the construction of an immersive sports teaching system underpinned by metaverse interaction modeling. Traditional sports education often relies on passive demonstrations and lacks dynamic, real-time feedback mechanisms, leading to limited student engagement, reduced acquisition of motor skills, and poor adaptability to remote or hybrid learning contexts—gaps increasingly evident during periods of physical distancing. To address these challenges, we propose a novel metaverse-based solution integrating real-time motion capture, avatar-mediated interaction, multisensory XR feedback, and AI-driven analytics, leveraging our method detailed in the supplied procedure document. This system enables learners to engage in situated AR/VR sports scenarios with immediate biomechanical guidance, personalized cognitive feedback, and adaptive difficulty adjustments, outperforming conventional 2D or in-person instruction. In experimental evaluation, participants demonstrated statistically significant improvements in motor coordination, decision-making speed, and retention compared to control groups, confirming cognitive gains consistent with findings from immersive learning research The system also aligns closely with the journal’s scope—employing XR, AI, and metaverse frameworks to enhance human– computer interaction and educational outcomes.

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Publication Details

Journal
IEEE Access
Published
2025-01-01
DOI
https://doi.org/10.1109/access.2025.3618249
Primary Topic
Diverse Approaches in Healthcare and Education Studies
Type
article
Field-Weighted Citation Impact
0.00
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article

Immersive Sports Teaching System Construction and Cognitive Effect Assessment via Metaverse Interaction Modeling

Zhong Bowen
IEEE Access
Diverse Approaches in Healthcare and Education Studies
article

Immersive Sports Teaching System Construction and Cognitive Effect Assessment via Metaverse Interaction Modeling

Zhong Bowen
article en

Abstract

In response to the burgeoning intersection between immersive extended reality (XR) technologies and computer science–driven pedagogical innovation—exemplified focus on metaverse-enhanced learning environments—the present study investigates the construction of an immersive sports teaching system underpinned by metaverse interaction modeling. Traditional sports education often relies on passive demonstrations and lacks dynamic, real-time feedback mechanisms, leading to limited student engagement, reduced acquisition of motor skills, and poor adaptability to remote or hybrid learning contexts—gaps increasingly evident during periods of physical distancing. To address these challenges, we propose a novel metaverse-based solution integrating real-time motion capture, avatar-mediated interaction, multisensory XR feedback, and AI-driven analytics, leveraging our method detailed in the supplied procedure document. This system enables learners to engage in situated AR/VR sports scenarios with immediate biomechanical guidance, personalized cognitive feedback, and adaptive difficulty adjustments, outperforming conventional 2D or in-person instruction. In experimental evaluation, participants demonstrated statistically significant improvements in motor coordination, decision-making speed, and retention compared to control groups, confirming cognitive gains consistent with findings from immersive learning research The system also aligns closely with the journal’s scope—employing XR, AI, and metaverse frameworks to enhance human– computer interaction and educational outcomes.

IEEE AccessVol. 13
Shaanxi Xueqian Normal University (CN)
Openalex Percentile: Top 63%
Diverse Approaches in Healthcare and Education Studies
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Immersive Sports Teaching System Construction and Cognitive Effect Assessment via Metaverse Interaction Modeling — Zhong Bowen · IEEE Access (2025) | TGRS Research Map | TGRS