Integrating AI-Driven Wearable Metaverse Technologies into Ubiquitous Blended Learning: A Framework Based on Embodied Interaction and Multi-Agent Collaboration
Ubiquitous blended learning, leveraging mobile devices, has democratized education by enabling autonomous and readily accessible knowledge acquisition. However, its reliance on traditional interfaces often limits learner immersion and meaningful interaction. The emergence of the wearable metaverse o...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-07-01
|
| Series: | Education Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2227-7102/15/7/900 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849406844329525248 |
|---|---|
| author | Jiaqi Xu Xuesong Zhai Nian-Shing Chen Usman Ghani Andreja Istenic Junyi Xin |
| author_facet | Jiaqi Xu Xuesong Zhai Nian-Shing Chen Usman Ghani Andreja Istenic Junyi Xin |
| author_sort | Jiaqi Xu |
| collection | DOAJ |
| description | Ubiquitous blended learning, leveraging mobile devices, has democratized education by enabling autonomous and readily accessible knowledge acquisition. However, its reliance on traditional interfaces often limits learner immersion and meaningful interaction. The emergence of the wearable metaverse offers a compelling solution, promising enhanced multisensory experiences and adaptable learning environments that transcend the constraints of conventional ubiquitous learning. This research proposes a novel framework for ubiquitous blended learning in the wearable metaverse, aiming to address critical challenges, such as multi-source data fusion, effective human–computer collaboration, and efficient rendering on resource-constrained wearable devices, through the integration of embodied interaction and multi-agent collaboration. This framework leverages a real-time multi-modal data analysis architecture, powered by the MobileNetV4 and xLSTM neural networks, to facilitate the dynamic understanding of the learner’s context and environment. Furthermore, we introduced a multi-agent interaction model, utilizing CrewAI and spatio-temporal graph neural networks, to orchestrate collaborative learning experiences and provide personalized guidance. Finally, we incorporated lightweight SLAM algorithms, augmented using visual perception techniques, to enable accurate spatial awareness and seamless navigation within the metaverse environment. This innovative framework aims to create immersive, scalable, and cost-effective learning spaces within the wearable metaverse. |
| format | Article |
| id | doaj-art-7ed3e131e2c44a4fbab2e12016051d5e |
| institution | Kabale University |
| issn | 2227-7102 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Education Sciences |
| spelling | doaj-art-7ed3e131e2c44a4fbab2e12016051d5e2025-08-20T03:36:14ZengMDPI AGEducation Sciences2227-71022025-07-0115790010.3390/educsci15070900Integrating AI-Driven Wearable Metaverse Technologies into Ubiquitous Blended Learning: A Framework Based on Embodied Interaction and Multi-Agent CollaborationJiaqi Xu0Xuesong Zhai1Nian-Shing Chen2Usman Ghani3Andreja Istenic4Junyi Xin5Graduate School of Education, Peking University, Beijing 100871, ChinaCollege of Education, Zhejiang University, Hangzhou 310058, ChinaProgram of Learning Sciences, National Taiwan Normal University, Taipei 100610, TaiwanDepartment of Business Administration, Iqra University, Karachi 75500, PakistanFaculty of Education, University of Primorska, Cankarjeva 5, 6000 Koper, SloveniaSchool of Information Engineering, Hangzhou Medical College, Hangzhou 311399, ChinaUbiquitous blended learning, leveraging mobile devices, has democratized education by enabling autonomous and readily accessible knowledge acquisition. However, its reliance on traditional interfaces often limits learner immersion and meaningful interaction. The emergence of the wearable metaverse offers a compelling solution, promising enhanced multisensory experiences and adaptable learning environments that transcend the constraints of conventional ubiquitous learning. This research proposes a novel framework for ubiquitous blended learning in the wearable metaverse, aiming to address critical challenges, such as multi-source data fusion, effective human–computer collaboration, and efficient rendering on resource-constrained wearable devices, through the integration of embodied interaction and multi-agent collaboration. This framework leverages a real-time multi-modal data analysis architecture, powered by the MobileNetV4 and xLSTM neural networks, to facilitate the dynamic understanding of the learner’s context and environment. Furthermore, we introduced a multi-agent interaction model, utilizing CrewAI and spatio-temporal graph neural networks, to orchestrate collaborative learning experiences and provide personalized guidance. Finally, we incorporated lightweight SLAM algorithms, augmented using visual perception techniques, to enable accurate spatial awareness and seamless navigation within the metaverse environment. This innovative framework aims to create immersive, scalable, and cost-effective learning spaces within the wearable metaverse.https://www.mdpi.com/2227-7102/15/7/900metaverseembodied interactionwearablemulti-agentartificial intelligenceubiquitous blended learning |
| spellingShingle | Jiaqi Xu Xuesong Zhai Nian-Shing Chen Usman Ghani Andreja Istenic Junyi Xin Integrating AI-Driven Wearable Metaverse Technologies into Ubiquitous Blended Learning: A Framework Based on Embodied Interaction and Multi-Agent Collaboration Education Sciences metaverse embodied interaction wearable multi-agent artificial intelligence ubiquitous blended learning |
| title | Integrating AI-Driven Wearable Metaverse Technologies into Ubiquitous Blended Learning: A Framework Based on Embodied Interaction and Multi-Agent Collaboration |
| title_full | Integrating AI-Driven Wearable Metaverse Technologies into Ubiquitous Blended Learning: A Framework Based on Embodied Interaction and Multi-Agent Collaboration |
| title_fullStr | Integrating AI-Driven Wearable Metaverse Technologies into Ubiquitous Blended Learning: A Framework Based on Embodied Interaction and Multi-Agent Collaboration |
| title_full_unstemmed | Integrating AI-Driven Wearable Metaverse Technologies into Ubiquitous Blended Learning: A Framework Based on Embodied Interaction and Multi-Agent Collaboration |
| title_short | Integrating AI-Driven Wearable Metaverse Technologies into Ubiquitous Blended Learning: A Framework Based on Embodied Interaction and Multi-Agent Collaboration |
| title_sort | integrating ai driven wearable metaverse technologies into ubiquitous blended learning a framework based on embodied interaction and multi agent collaboration |
| topic | metaverse embodied interaction wearable multi-agent artificial intelligence ubiquitous blended learning |
| url | https://www.mdpi.com/2227-7102/15/7/900 |
| work_keys_str_mv | AT jiaqixu integratingaidrivenwearablemetaversetechnologiesintoubiquitousblendedlearningaframeworkbasedonembodiedinteractionandmultiagentcollaboration AT xuesongzhai integratingaidrivenwearablemetaversetechnologiesintoubiquitousblendedlearningaframeworkbasedonembodiedinteractionandmultiagentcollaboration AT nianshingchen integratingaidrivenwearablemetaversetechnologiesintoubiquitousblendedlearningaframeworkbasedonembodiedinteractionandmultiagentcollaboration AT usmanghani integratingaidrivenwearablemetaversetechnologiesintoubiquitousblendedlearningaframeworkbasedonembodiedinteractionandmultiagentcollaboration AT andrejaistenic integratingaidrivenwearablemetaversetechnologiesintoubiquitousblendedlearningaframeworkbasedonembodiedinteractionandmultiagentcollaboration AT junyixin integratingaidrivenwearablemetaversetechnologiesintoubiquitousblendedlearningaframeworkbasedonembodiedinteractionandmultiagentcollaboration |