The Analysis Of College Student Achievement Based On Association Rules Mining Technology

The fact, that with the enrollment expansion, the number of students and teachers of college has increased greatly in recent years, gives the management and teaching a severe trial. The traditional management and teaching methods can not adapt to the development of society. There are many information management systems and databases in the college, such as student registration management system, achievement management system and personnel management system. These systems and databases have accumulated large amount of data. In fact, higher education Administrators can obtain the superficial information only by the simple statistical analysis, sorting and backup. However, the information behind the data can not be utilized effectively.Data mining (DM) is focused on the discovery of model hidden from the historical data and use the models to predict the future. DM can make the scientific research, business decision and management based on large amount of data existed, so as to support the decision-making. Association mining is the one of most active research directions. It reflects the direct dependent or associated knowledge between one thing and other things.First of all, this thesis makes a general discussion about DM, including DM history, concepts and related technologies. Then, it makes deep research about the important association rule mining algorithms in DM, analyses the classical Apriori algorithm and AprioriTid algorithm, summs up the problems of the algorithm. Then, one improved algorithm has been proposed based on AprioriTid algorithm. A university 2004-2008 grade student achievement of the course "computer programming base and VF" as the research object, using the standard DM process and improved AprioriTid algorithm. This thesis obtain the factors affecting the student achievement, so as to supply the basis for improving teaching quality.We can not only mine the student achievement but also student age (maturity of cognitive thinking), gender, hobbies, family background, health status, student registration, education, college entrance examination results, course content, exam paper, teacher, and other information, so as to supply the decision-making basis for administrators and teachers, teach students according to their characters, improve the level of college teaching and management effectiveness.