A Model for Building Student Physical Health Information Management in a Big Data Environment

Abstract

The emphasis on physical health has grown significantly in recent years. As future contributors to society, students' physical health deserves greater attention. Therefore, it is necessary to strengthen research on managing students’ physical health information, in order to establish a representative, scientific, practical, and operable information management (IM) model. This is highly significant for the scientific assessment and management of students’ physical health in practice. With the rapid growth of information, managing students' physical health now involves handling vast amounts of data, and managing these data relies on applying big data. In view of the problem of low validity of students' physical health information assessment results and difficulty in timely improvement of physical health status, this article constructed a visual, real-time, and comprehensive student physical health IM model using big data. Students' physical health was evaluated using multiple Gaussian distributions, ensuring data reliability, systematic management, comprehensive analysis, and real-time feedback, thereby effectively improving the effectiveness and practical guidance of students’ physical health management results. The experimental results of this article indicated that before the experiment, there were 20 and 19 students in the control group and the experimental group who failed in physical health, and 4 and 5 students in the two groups who had excellent physical health, respectively. After the experiment, there were 15 students in the control group and 8 students in the experimental group who failed in physical health, while 6 and 16 students in excellent physical health. The results showed a significant increase in the number of students with excellent physical health in the experimental group, demonstrating the effectiveness of the proposed big data-based management model. This indicated that by managing student physical health information in the big data environment, students’ physical health can be effectively understood and improved.