Version 1
: Received: 25 April 2024 / Approved: 26 April 2024 / Online: 26 April 2024 (08:45:59 CEST)
How to cite:
Brandl, R.; Wang, J. Collaborative Learning Networks for Enhanced Education: A Framework for Device-to-Device Collaboration. Preprints2024, 2024041715. https://doi.org/10.20944/preprints202404.1715.v1
Brandl, R.; Wang, J. Collaborative Learning Networks for Enhanced Education: A Framework for Device-to-Device Collaboration. Preprints 2024, 2024041715. https://doi.org/10.20944/preprints202404.1715.v1
Brandl, R.; Wang, J. Collaborative Learning Networks for Enhanced Education: A Framework for Device-to-Device Collaboration. Preprints2024, 2024041715. https://doi.org/10.20944/preprints202404.1715.v1
APA Style
Brandl, R., & Wang, J. (2024). Collaborative Learning Networks for Enhanced Education: A Framework for Device-to-Device Collaboration. Preprints. https://doi.org/10.20944/preprints202404.1715.v1
Chicago/Turabian Style
Brandl, R. and Jen-Han Wang. 2024 "Collaborative Learning Networks for Enhanced Education: A Framework for Device-to-Device Collaboration" Preprints. https://doi.org/10.20944/preprints202404.1715.v1
Abstract
This paper presents a novel framework for Collaborative Learning Networks (CLNs) in classrooms, aiming to optimize resource utilization and enhance educational services. The study addresses the inefficiencies of traditional education models, particularly the underutilization of computational resources and limited access to specialized software. The proposed framework employs a mix of task-based and random allocation strategies to distribute computational tasks within the CLN, considering each device’s capabilities and task requirements. The findings show significant improvement in resource utilization, facilitated by device-to-device collaboration and task sharing, thus enriching students’ learning experiences. This work contributes to optimizing resource utilization in education, advancing the field of CLNs.
Computer Science and Mathematics, Data Structures, Algorithms and Complexity
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
