Research on the Optimization Path of College Physical Education Teaching Based on Artificial Intelligence
- DOI
- 10.2991/978-2-38476-384-9_7How to use a DOI?
- Keywords
- Artificial intelligence; college physical education; teaching model; optimization path
- Abstract
Artificial intelligence (AI) is an emerging interdisciplinary field with a wide range of applications. It has achieved remarkable results in serving China’s physical education sector. In the process of reforming physical education in colleges and advancing higher education, AI provides diversified intelligent services and data support. By utilizing AI technology in physical education, colleges can implement personalized, efficient, and scientific teaching and training, continuously enhancing students’ competitive levels and physical capabilities. Therefore, the application of AI in college physical education is of significant practical importance. This article analyzes the optimization paths of college physical education teaching based on AI with the aim of promoting a more efficient and intelligent approach to physical education, thereby improving the quality of student development.
- Copyright
- © 2025 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Li Lin PY - 2025 DA - 2025/04/03 TI - Research on the Optimization Path of College Physical Education Teaching Based on Artificial Intelligence BT - Proceedings of the 2024 3rd International Conference on Educational Science and Social Culture (ESSC 2024) PB - Atlantis Press SP - 53 EP - 63 SN - 2352-5398 UR - https://doi.org/10.2991/978-2-38476-384-9_7 DO - 10.2991/978-2-38476-384-9_7 ID - Lin2025 ER -