Recently, in order to adapt to the ever expanding enrollment scale, high school is beginning to change its education management method to increase its management level. Each management information system, such as education management information system, finance management information system, enrollment and employment management information system and etc. had accumulated massive data. But today, administrative staff can only do some simplistic operations, such as counting, selecting and sorting, because of the lack of information consciousnesses and abilities. Data mining technology is to extracting effective knowledge by analyzing massive imperfect data. We can make more deep analysis by using data mining technology into student score processing.With this method, on the one side, we can improve the effectiveness of administrative staff by helping them adapting education decision;and on the other side, we can also let teachers arrange the teaching process by knowing students’study status in time. Meanwhile it can help the students improve their score in a scientific and effective way. We found the patterns and multidimensional relations hidden in the score data by using data mining technology on CE-4score data.This paper introduced association rules and classification technologies first. Then apriori algorithm of association rules and decision trees are applied to the performance analysis of college students CET-4, mining the association between College English four semesters’ final grade and CET-4results, and the influence of CET-4exam’s four parts (listening, reading, writing and Consolidation) on CET-4’s total score.This method provides decision-makers with decision-making data, and may further enhance the level of college English teaching. |