Data Mining And Analysis Of Students’ Score Based On Decision Tree Algorithm

As a new research field, data mining has come into being from the end of the last century. At present, it is wildly used in the finance, retailing, telecommunication and production sectors. It has also produced many commercial data mining systems. Therefore, where there is data accumulation, there is data mining technology that can bring its skills into full play. However, the application of data mining in education is relatively less than that in some other fields, especially in the management of students’ achievements. With the growing number of university students, the government and society pay more and more attention to the high education. The reform of high education has made significant progress. Improving the quality of high education and cultivating talents with special characteristics have been set as the schools’ mission. On one hand, it requires that the teaching management should comply with the needs of the schools’ development. On the other hand, it requires that the improving and innovating of the traditional management mode. Thereby, the high schools can use scientific management mode to enhance the teaching and management. It is generally known that the students’achievement is an important standard of the teaching quality judgments. Meanwhile, it is also the important standard of the judgments of knowledge mastering. Therefore, students’ achievements management plays an important role in the management of institutions.This article discusses the concept and algorithms of data mining, the actual mining process, the usage of two decision tree algorithms C4.5data mining to classify2010students’test for computer---band two results in Anhui Xinhua University. At first, the paper determined the objects, the goals and the sampling of the data mining. Then, considering the factors that effect the results of students’ test for computer---band two, after a series of procedure of data integration, cleaning and transformation, the paper used the C4.5algorithm to mine the results to generate a decision tree, to find out the relevant classification of the results. As a result, the above analysis could provide guidance for future teaching of computer to improve the test passing rates, the quality of teaching and to promote the educational reform.