Applications Of Data Mining Techniques In Educational Administration Management System

One of the most important facts in higher education system is quality. It concerns with all the circumstances that enhance the higher educational organizations. For many years, Teachers have accumulated a great deal of data while teaching and managing education work. But nowadays, their dealing with data still rest on primary data backup, data query and simple statistics phase instead of providing effective means to help educators and teachers make decisions about teaching process. Data warehouse and data mining techniques are key factors of decision supporting system. Their combination can help Higher school decision makers take decisions.Data mining is a technique that aims to analyze and understand large source data and reveal knowledge hidden in the data. Association rule mining is an important branch of data mining that it has obtained many valuable results but there still are a deal of more challenging problems to discuss. According to nowadays-educational administration data, data mining techniques, research on association rule mining and its developing trend, we choose this topic and carry out relevant work.In this paper, we built a warehouse about Educational administration management system. Its architecture can be divided into front and back main parts. The architecture includes: data source, data preprocessing, metadata, departmental data marts, data warehouse, front application etc. This kind of architecture can make full use of all kinds of resources, promote school decision maker's level, accelerate development of school, strengthen competitive power and build one modern digitized learning environment.Through analysis and research on classical Apriori algorithm, we proposed one opinion that applied Apriori algorithm based HASH technology and timesharing mining method to educational administration management system. Therefore we can find relation between front curriculums and rear curriculums. We did beneficial search about data mining techniques in Higher vocational teaching plan making.