Data Collection and Analysis in Physical Education Practical Teaching Based on Internet of Things

The Significance Of Big Data In The Application Of Physical Education

Comprehensive analysis of classroom teaching using big data can further improve the evaluation system of physical education teaching, improve teaching efficiency, and improve effectiveness (Al Taai et al., 2023). By collecting students' exercise data, teachers can more accurately understand their exercise status and develop more appropriate teaching plans. In addition, by analyzing these data, teachers can also identify students' exercise habits and potential problems and provide targeted guidance.

In the past few decades, the methods and techniques for collecting data in physical education practical teaching have received widespread attention. Traditional methods mainly rely on manual observation and recording, which is not only time-consuming and laborious, but also prone to errors. In order to collect and fully utilize data from the process of physical education practical teaching, this article studies the effectiveness of the IoT and decision tree algorithms in data collection of physical education practical teaching and evaluates the performance and effectiveness of this method through experimental data analysis. The results indicate that the physical education practical teaching data collection method based on the IoT decision tree algorithm has shown good performance and effectiveness in experiments. This method can effectively extract useful information, provide accurate feedback and guidance to teachers, and is conducive to improving teaching quality and optimizing teaching methods.