Student Education Management Strategy Based on Artificial Intelligence Information Model under the Support of 5G Wireless Network

Abstract

With the popularity of the Internet and the advancement of information technology, more and more people are accepting the teaching and sharing of knowledge through the digitalization of information. The widespread adoption of 5G technology has pushed online learning even further into the mainstream. However, because online teaching does not have the drawback of being intuitive like classroom teaching, teachers’ assessments of students’ learning situations are less accurate. As a result, how to effectively evaluate students’ academic performance in the context of 5G wireless network technology is a pressing issue that must be investigated. By processing these heterogeneous large-scale learning records and integrating multiple perspectives to analyze this learning record information to identify students’ learning behaviors, this study proposes an integrated analysis algorithm based on artificial intelligence information technology. The possible learning outcomes of students are predicted based on their current learning situation, so teachers can provide auxiliary teaching strategies to students who may have learning difficulties based on the predicted information. The method proposed in this article uses information technology to predict students’ grades, and the analysis shows that the method is very effective. In this article, different grades of classification methods are used to analyze and predict the whole students. All grade classification methods are effective in describing decision rules. No matter what grades classification method is used, the error rate of students’ grades distribution is predicted to be below 40%.