![]() After 15 years of research, data mining technology has rapidly evolved and is now widely used in various industries. As early as 1995, a new technology for data analysis was proposed: data mining. In fact, this problem has been studied for quite some time. How to extract and locate useful information from such vast amounts of data to serve as a resource for education and teaching is a new problem that must be resolved immediately. With the expansion of the paperless office, school departments have accumulated a great deal of information, which is increasingly stored on the server. Numerous schools have increased office funding, equipped teachers with office machines, and are gradually realizing the paperless office. Nowadays, digital campus construction has become a synonym for information education, a new development direction in school construction, and a symbol of school running level and conditions. In China, many colleges and universities are creating digital campuses and, in recent years, an increasing number of primary and secondary schools are also actively promoting the establishment of digital campuses. All teachers are faced with the challenge of utilizing information technology in a reasonable, appropriate, and effective manner to address some issues in conventional teaching. In light of the advancement of information technology, teachers are obligated to investigate new ways of learning and teaching methods, as well as the creation of digital campuses. At the same time, the prediction results are combined with the Internet of things technology to produce a student sports prescription management system, which sets different sunshine running parameters for students with different predicted results and provides personalized sports prescriptions for students with different physical conditions, which has extensive and far-reaching application value. Experimental results indicate that the accuracy of the model is above 85%. The nonlinear relationship between students’ performance in sunshine running and endurance performance is determined, and students’ performance in sunshine running is used to predict their endurance performance the following year. Based on BP neural network, an algorithm for predicting students’ endurance performance is proposed, which is applied to the sunshine long-distance intelligent sports testing system at Hangzhou Dianzi University. Using the relevant data of college students’ physical fitness test and sports performance as the object of research, a BP neural network model is developed to predict performance. The mining and analysis of student achievement data is of great importance to teaching management.
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