Research on Campus Digital Teaching System of Smart u Based on Data Mining Algorithm

With the continuous development of data mining technology, the informatization level of colleges and universities is gradually improving. However, the traditional digital teaching system has many problems such as low utilization rate of data resources, non-sharing of information and data between systems, and it is difficult to meet the emerging new needs of colleges and universities. Therefore, it is of great significance to study the smart u campus digital teaching system based on data mining. Aiming at the problems of many links, serious information islands and low data utilization rate in traditional university teaching, this paper studies the smart u campus digital teaching system based on data mining. The core module of the system is the decision analysis module, which is based on the C4.5 algorithm framework, reduces the decision number of threshold points according to the Fayyad boundary point decision principle, and uses the equivalent infinitesimal principle to simplify the calculation of information entropy, overcoming the disadvantages of C4.5 algorithm. The module generates decision tree, generates classification rules through IF-THEN form, and realizes achievement prediction. The experimental data in this paper is the teaching data of a university. The experimental results show that the designed system can effectively realize data preprocessing, complete the learning effect prediction, provide personalized guidance for students, and realize the digital teaching work of smart u campus.