Construction and Analysis of School Moral Education System Based on Big Data Technology

Abstract

Using educational big data to enhance the performance of the moral education system in colleges and universities is important to smart moral education. However, educational big data has an obvious diversity. For this reason, combined with multiple resources, the “adaptive” data processing method with strong dynamic and active adaptability is cited to analyze the big data in colleges and universities to understand and grasp the dynamic of users’ thoughts and behaviors. At the same time, according to the interest bias, the concept of “interest group” is used to classify the interests of a large number of users form different groups for modeling and use it as the core framework to build an intelligent research model of moral and ideological education. Then, on this basis, the experiment was carried out using the WeChat public account data of 20 universities, and the WeChat Communication Index (WCI), WeChat Service Index (WSI), and WeChat Management Index (WMI) were used to evaluate the function of the WeChat public accounts of universities in ideological and moral education. The roles and characteristics in the system are classified into three categories: communication-oriented, service-oriented, and general type. Among them, the communication-oriented type is mainly used to provide and disseminate educational information, while the service type can be the bridge to build direct connection between teachers and students. Therefore, the performance of ideological and moral education system in universities can be enhanced. While the general type is multifunctional, its performance in information dissemination and interaction is modest. Therefore, it is suggested that the WeChat public account should take the dissemination of information and the interaction between teachers and students into account.