Internet of things-based technological acceptance learning management framework for the physical education system

Author:

Yao Hongyan1,Wang Yongsheng2,Montenegro-Marin Carlos Enrique3,Hsu Ching-Hsien45

Affiliation:

1. Hebi Polytechnic, School of P.E and Sports, Henan, China

2. Henan Polytechnic University, Sports Academy, Henan, China

3. Facultad de ingeniería, Universidad Distrital Francisco José de Caldas, Colombia

4. Department of Computer Science and Information Engineering, Asia University, Taichung, Taiwan

5. Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, Taiwan

Abstract

BACKGROUND: Internet of Things (IoT) is a hopeful advancement that is an accurate international link for smart devices for total initiatives. Physical Education (PE) builds students’ abilities and trust to engage in various physical activities, both within and outside their classrooms. The challenging characteristics in the learning management system include lack of setting a clear goal, lack of system integration, and failure to find an implementation team is considered as an essential factor. OBJECTIVE: In this paper, an IoT-based technological acceptance learning management framework (IoT-TALMF) has been proposed to identify the objectives, resource allocation, and effective team for group work in the physical education system. METHOD: Physical Educators primarily use the learning management framework as databases of increased management components, choosing to interact with students, teammates, organizations. Statistical course content analysis is introduced to identify and set clear goals that motivate students for the physical education system. The course instructor learning technique is incorporated with IoT-TALMF to improve system integration based on accuracy and implement an effective team to handle unexpected cost delays in the physical education system. RESULTS: The numerical results show that the IoT-TALMF framework enhances the identity accuracy ratio of 97.33%, the performance ratio of students 96.2%, and the reliability ratio of 97.12%, proving the proposed framework’s reliability.

Publisher

IOS Press

Subject

Health Informatics,Biomedical Engineering,Information Systems,Biomaterials,Bioengineering,Biophysics

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Integrating IoT, AI, and Robotics for Enhanced Learning Experiences at Neulbom School in Korea;2024 IEEE 4th International Conference on Electronic Communications, Internet of Things and Big Data (ICEIB);2024-04-19

2. Data Collection and Analysis in Physical Education Practical Teaching Based on Internet of Things;International Journal of Information Technology and Web Engineering;2023-10-26

3. Application of 5G Internet of Things Technology in the Design of Physical Education Platform;Computational Intelligence and Neuroscience;2022-04-21

4. Online shopping behavior analysis for smart business using big data analytics and blockchain security;International Journal of Modeling, Simulation, and Scientific Computing;2022-03-28

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