Data Mining Technology Applied Research, University Teaching Model

With the rapid development of the recruiting students scale of Colleges and Universities and information technology, every university has set up the MIS of educational administration. It has heightened the level of educational management to a great extent, and has accumulated a large amount of data. However, most of the previous teaching management systems are the On-Line Transaction Processing systems that have no ability of synthetic analysis, decision support, and can not analyze deeply and Classify to the data which we collected. So, the manager can not find out the correlative information when they face the complex cases and the leader has no useful data when they decide.Analysis of teaching model is an important way to improve the teaching quality. After reading and analyzing lots of papers about data mining, this paper analyze and mine the data of teaching model multilayered from different angle, which can guarantee the quality of teaching and improve the intrinsic of students.In this thesis, I introduce the fundamental theory and the main algorithms of data mining, research association rule and the methods of decision tree classification in data mining. Through using the improved Apriori algorithm we can analyse the influences of teachers'age, professional posts, educational backgrounds and students'results to teaching quality. Through using the C4.5 decision tree algorithm we can analyse the influences of the results of C language, teaching methods, students' fear of difficulty to Data Structure and ALGOL.Though the concrete practice in the teaching model, we can obtain many valuable information, which can undoubtedly help school to train students better and grasp students' situation and the courses' teaching.