Institute of Physical Education, Ludong University, Yantai 264025, China.
J Environ Public Health. 2022 Aug 31;2022:7670725. doi: 10.1155/2022/7670725. eCollection 2022.
Online teaching is carried out nationwide in the context of the new crown epidemic prevention and control, and physical education, as one of the compulsory courses in schools and universities, is included within the content of online line lessons. Online physical education teaching is a new approach and attempt to switch from an auxiliary teaching tool to the main teaching tool. The subject matter, target audience, teaching methods, and content of physical education classes have changed dramatically. The development of online physical education has played an important role in popularizing the concept of "sports for life" and establishing the concept of lifelong exercise. Through the analysis and research on the characteristics of online physical education, we propose the measures to promote the overall online teaching ability and level of physical education teachers in the postepidemic period, gradually promote the reform of online and offline physical education, and promote the integration of school physical education and social sports, as well as to build a physical education teacher training system that integrates online and offline development and improve and strengthen the management of Internet physical education resources. Since the teaching effect of online teaching is limited by the teaching means and content, which leads to the low accuracy of the evaluation of online sports teaching effect, for this reason, this paper designs a model based on big data technology and artificial intelligence algorithm for enhancing closed home sports teaching, obtains the overall situation of online physical education by using convolutional neural network to process physical education video sequences, and improves the system performance by embedding the algorithm into the big data framework, to avoid the interference of teaching environment and complete the evaluation of high precision online sports teaching effect. The experimental results show that the proposed method evaluation can improve the computing rate based on ensuring the high accuracy evaluation of physical education online teaching effect.
在新冠疫情防控背景下，全国范围内开展了在线教学，作为学校和大学必修课程之一的体育课也包含在在线课程内容中。在线体育教学是从辅助教学工具向主要教学工具转变的新途径和尝试。体育课的主题、目标受众、教学方法和内容都发生了巨大变化。在线体育教育的发展对于普及“终身运动”理念和树立终身锻炼观念发挥了重要作用。通过对在线体育教育特点的分析和研究，提出了提高体育教师整体在线教学能力和水平的措施，逐步推进线上线下体育教育改革，促进学校体育与社会体育融合，构建线上线下融合发展的体育教师培训体系，完善和加强互联网体育教育资源管理。由于在线教学的教学效果受到教学手段和内容的限制，导致在线体育教学效果评价的准确性较低，为此，本文设计了一个基于大数据技术和人工智能算法的模型，用于增强封闭式家庭体育教学，通过卷积神经网络处理体育教学视频序列来获取在线体育教学的整体情况，并通过将算法嵌入大数据框架来提高系统性能，以避免教学环境的干扰，完成对高精度在线体育教学效果的评价。实验结果表明，所提出的方法评价可以在保证在线体育教学效果高精度评价的基础上提高计算速度。
