A data mining analysis of College English Test (CET) results of Haojing College, China

Abstract

The data mining technology is one of the hot issues of information technology research. Data mining has already used in many fields, such as bank, finance, insurance, and retail. But unfortunately, data mining technology is seldom used in the field of education. With the continuous enrollment of Chinese universities, more and more students go into university to study. Meanwhile, a mass of data were produced which about the students? basic information and their subject mark. There are still some deeply relationship among subject mark under cover. Using data mining technology into analysis of students? mark can find the real factors which affect their subject and then improve the teaching quality. In this paper, the theoretical knowledge of data mining was studied. Research and Application of data mining technology in student CET mark analysis is based on data mining technology research. Before the excavation, the paper established students? achievement analysis of data, and data cleaning, data conversion, data reduction, data preprocessing, processing vacancy data, the continuous-valued attribute discretization, to lay the foundation for further excavation. After comparison of various algorithms in data mining, association rules algorithm was chosen, which is suitable for student achievement analysis model Apriori algorithm to conduct students? CET mark analysis. In the final realization of the process, the relationship between CET mark and employment salary were found and also found the main factors which affect the CET mark. These finding are very useful which can improve the teaching quality.