Title: 6G-enhanced context-aware systems in adaptive ubiquitous learning environments for music education via edge intelligence

Authors: Hua Wei; Jianhui Lv; Adam Slowik

Addresses: Department of Music, Xinxiang University, Xinxiang 453003, China ' Department of Computer Science, Tsinghua University, Beijing 100084, China ' Department of Electronics and Computer Science, Koszalin University of Technology, Koszalin 75-453, Poland

Abstract: This study proposes an enhanced wireless 6G communications architecture for context-aware systems to enable adaptive u-learning environments for music education. A centralised data processing centre at edge nodes analyses user behaviours and network conditions to enable coordinated control across the core network, transport network, and radio access network, which fully exploits the feature of edge intelligence. The architecture supports self-consistent capabilities within each network function entity and flexible multi-level couplings between entities based on real-time user needs. For radio resource management, an AI-driven intelligent controller is introduced to enable intelligent and automated management of wireless resources. Experiments compared learning effectiveness between groups with and without the proposed enhanced 6G context-aware capabilities in an adaptive u-learning music learning environment. Results demonstrated significantly improved task completion times and learning accuracy with the 6G-enhanced context-aware system in adaptive u-learning environments for music education via edge intelligence.

Keywords: 6G; edge computing; context-aware; ubiquitous learning; music education.

DOI: 10.1504/IJSNET.2025.145636

International Journal of Sensor Networks, 2025 Vol.47 No.4, pp.214 - 230

Received: 19 Oct 2024
Accepted: 17 Dec 2024
Published online: 09 Apr 2025 *

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