Application of the Data Mining Model in Smart Mobile Education

Abstract

In order to solve the problem that education departments urgently need intelligent and efficient information technology to deal with massive data, so as to mine valuable information for management decision-making, an overall scheme framework of education informatization is proposed. The framework takes data mining as a tool, combined with the theoretical knowledge of cloud computing, and takes the student data of a school as an example to verify the practicability of the framework system. The results are as follows: the framework clusters the students of a school. The overall level of students in cluster 1 is high, accounting for 45.07% of the total number. These kinds of students have solid basic theory, strong logical thinking ability, and excellent professional knowledge learning. The overall level of students in cluster 2 is average, accounting for 38.03% of the total number. This kind of students should pay attention to the study of professional courses and the cultivation of professional skills. The rest are students in cluster 3. These kinds of students have weak basic professional knowledge and poor thinking and logic ability. Through the accuracy before and after pruning output from the model, the accuracy before pruning is 87.32% and the accuracy after pruning is 97.37%. The noise data are eliminated in the process of pruning. The framework established in this study provides a certain decision-making basis for education and teaching and explains the feasibility and effectiveness of the application of data mining technology in educational informatization.