Intelligent Prediction Model of CET-4 Passing Rate Based on Multisource Heterogeneous Data Mining

Abstract

With the growing software of English in society, English gaining knowledge is turning into extra and greater important. The software and lookup of fact mining science in English educating and gaining knowledge will turn out to be a new improvement trend. This study is based on the information of non-English majors’ learning situation of Public English course and CET-4 scores. It selects the data related to CET-4 scores as the characteristics, takes CET-4 passing rate as the goal, and makes use of selection tree classification mannequin to predict the passing likelihood of CET-4. After comparison and analysis, it is observed that the multisource heterogeneous statistic mining science can precisely predict students’ grades, which verify the software of multisource heterogeneous information mining technological know-how in university English studying and have an impact on of the mannequin on the end result prediction. The results of College English final examination and gender are the main factors affecting the passing rate of CET4. The higher the score of College English final examination, the higher the passing rate of CET-4. The results of this study show that girls’ passing rate and average score of CET-4 are higher than boys’. Other factors have little influence on CET4 passing rate and can be ignored. There is a significant positive relationship between the scores of CET-4, CET-1, and Putonghua. After analysing the number attributes of the model, blended with the statistical consequences of information analysis, this paper offers some ideas and hints to enhance the instructing administration and the passing charge of CET-4.