Physical education is an important part of school education. Doing a good job of physical education can not only increase students’ interest in sports but also improve their physical fitness. However, traditional physical education methods lack new ideas and fail to reach the goals of physical education. Therefore, it is extremely urgent to conduct physical education teaching strategies. Based on this, this paper proposes the construction of WeChat mobile teaching platform in the reform of physical education teaching strategy based on deep neural network. This paper adopts literature method and experimental analysis method to conduct in-depth research on the application of deep neural network in physical education and its characteristics, shortcomings, and improvements and build a WeChat mobile based on deep neural network in physical education strategy reform teaching platform. The comparison between the control group and the experimental group is used to compare multiple physical test indicators before and after the test to reflect the teaching effectiveness after the change in the physical education strategy of this paper. This paper mainly analyzes the results of the physical education teaching scale and the results of the students’ physical fitness test, including the students’ learning motivation, learning attitude, and learning process in the physical education process, as well as the male and female students’ results of the experimental group and the control group before and after the test compared. The P values of the boys in the experimental class and the control class are all greater than 0.05, which is limited to the relatively short time of the experiment. The data of the boys in the two classes on these three items show no significant difference. The t-test was performed on the posttest results of the three items of the girls, the P values were all less than 0.05, and there were significant differences, especially in the comparison of the results of the postthrowing solid ball and the corner running. The P values of the two test items were all less than 0.01; there is a very significant difference.

Lin Qi

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