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

被引:3
|
作者
Yao, Hongyan [1 ]
Wang, Yongsheng [2 ]
Enrique Montenegro-Marin, Carlos [3 ]
Hsu, Ching-Hsien [4 ,5 ]
机构
[1] Hebi Polytech, Sch P & & Sports, Zhengzhou, Henan, Peoples R China
[2] Henan Polytech Univ, Sports Acad, Jiaozuo, Henan, Peoples R China
[3] Univ Dist Francisco Jose de Caldas, Fac Ingn, Bogota, Colombia
[4] Asia Univ, Dept Comp Sci & Informat Engn, Taichung, Taiwan
[5] China Med Univ, China Med Univ Hosp, Dept Med Res, Taichung, Taiwan
关键词
IoT; learning management; physical; education system; physical activities; DATA DELIVERY;
D O I
10.3233/THC-213001
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
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.
引用
收藏
页码:1201 / 1215
页数:15
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