Topic Search Algorithm for Network Multimedia Tennis Teaching Resources Using 5G-Enabled Internet of Things Technology. (9th May 2022)

• Record Type: Journal Article
• Authors: Chen, Hui; Yang, Yu; Xie, Shaokang
• Other Names: Hashmi Mohammad Farukh Academic Editor.
• Is Part Of: Wireless communications and mobile computing. Volume 2022(2022)
• Publication Date: 2022-05-09
• Subjects: Wireless communication systems -- Periodicals; Mobile communication systems -- Periodicals; 621.38205
• DOI: 10.1155/2022/1155522
• Languages: English
• ISSNs: 1530-8669

Abstract

Abstract : With the emergence of the knowledge economy, computing, media, and networking technologies have developed rapidly. With the development of reforms in China's education system, the use of computer-assisted instruction has become an essential part of modern teaching methods. Under such circumstances, computer-assisted teaching methodologies have been gradually introduced in physical education teaching. Compared with other disciplines, physical education has many limitations, such as the size of the venue, the type of equipment, environmental conditions, and climate factors, which will affect the teaching. This brings about the difference between theoretical teaching and practical impact. Due to the differences in physical education teaching, it is indispensable to improve the quality of physical education teaching through the use of rich media teaching system, and the rich network teaching system can perfectly replace the shortcomings of traditional physical education teaching. This paper investigates the design and development of a tennis network rich media teaching system based on 5G Internet of Things and resource-based algorithm by using literature method, survey method, interview method, statistical method, learning laboratory method, and other methods. Based on the tennis cyber media learning system, this study provided recommendations and guidelines for the expansion of the cyber media learning system to other sports programs and explored the future prospects of the cyber media learning system in teaching. The results show that 93.3% of all students are very interested in this learning method, 96.7% of students deepen their memory of tennis technical movements, and the satisfaction rate is 86.7%.