Design And Implementation Of Management Information System In College Based On Association Rules Mining

With the rapid development of information technology, the trend of campus informatization is forming. In year2002, the criterion of educational management informatization is published which, to some extent, shows that the normalized and standard construction period is coming in our country. In the process of informatization, a complete system of information management is necessary in colleges and universities. Then, the process is further propelled by the measure of developing education career. Under the circumstance, some colleges and universities try to achieve their goals of becoming classic colleges or universities by increasing investment, increasing educational resources and enrolling more students.A classic college or university should have the classic level of management, so campus informatization is the primary problem should be solved. After years of construction and development, colleges and universities have accumulated lots of primary data, by analyzing these students data, teachers data, educational administration data with data mining technologies, we can find the useful rules which are instructive to the management of colleges or universities and can further improve education quality, optimize the allocation of educational resources, arrange classes more reasonably. As a result, the comprehensive strength of the colleges or universities will be improved, so the colleges or universities will advantage over others and then propel their overall developments.We involve data mining technologies in the system of college or university information management, and the informatization construction experiences in college or university abroad are considered. After analyzing the advantages and disadvantages of data mining technologies, we find the conjunction point. The system in this paper will help different departments in colleges or universities cooperate together and conduct potential information to instruct their work which will lead to the increase of efficiency. The main research contents are as following:First, we can get the potential and instructive rules by mining the educational historical data with the technologies of associate rules mining, and these rules will benefit future work. After applying these extracted rules in educational management, we can inspect the effect on educational resources configuration, educational management and decision support.Second, by mining the historical data and analyzing the students’scores of different courses, semesters, etc. We can find potential relative modes or rules which will be helpful to decision making.Last, by mining and analyzing the historical data of teaching evaluation with the technologies of associate rules mining, we can find out the main factors which influence teaching quality from the scales of professional qualification, school age and age. Then, we can further improve the configuration of teachers, arouse students’ enthusiasm and improve teaching quality.