Research On The Application Of Data Mining Technology In The Analysis Of Student Achievement

Teaching is the central task of university. The focus is to improve the quality of education. And student achievement is the important basis for measuring the quality of teaching. Therefore the data mining in student achievement has great significance. The relations among courses can be found out through the data mining in student achievement, which can provide suggestions for the decision of teaching and student management to improve teaching quality.Firstly, this dissertation introduces its basic theory based on study in data warehouse and data mining, and emphatically expounds creating data warehouse and online analytical processing.Secondly, the dissertation introduces the basic algorithm of association rule in data mining, and emphasizing on Apriori algorithm. Through deep research on Apriori algorithm, it presents an improved algorithm by reducing scan times of transaction database for the drawbacks of Apriori algorithm. And it illustrates the advantage of this algorithm with some cases.Lastly, the dissertation creates the data warehouse for the student achievement with SQL Server2005, in which the process can be broke down into three steps, conceptual modeling, logic modeling and physical modeling. The data warehouse is constructed by extracting data, cleaning data, transforming data and loading data. The data mining system of the student achievement is designed and implemented with Visual C++. And it applies the improved association rule algorithm in data mining of the student achievement. Through mining the student achievement stored in data warehouse, some valid association rules hiding in the current database is discovered and analyzed. According to these rules, the dissertation provides some proposal for the decision of teaching arrangement and student management in the future.