Research Of Analysis Of Teaching Quality Based On Association Rule Mining

Education quality is still most concerned in higher education, student achievement management and teaching quality analysis are the most intractable problems for teaching management workers. College has been committed to teaching innovation, improve teaching quality, most universities still using the traditional management model. This approach can not fundamentally solve the new problems we faced in today's modernization. We cannot find the existence of the "knowledge" in thousands of student result sheet, so they need to improve the previous management style, new technology method to discover the relationship between performances, find out the real factors affecting student achievement, In order to truly solve the effect of improving teaching quality and teaching issues.In this paper, a careful analysis of the situation in colleges and universities based on performance management, data mining techniques proposed in association mining results used in the analysis of the experimental program. Through the association relationship mining for the experimental results, analysis on the student achievement of a number of related factors on the teaching quality and prediction. In association rules mining process, the original algorithm is analysed in-depth, proposed an improved algorithm called Apriori is applied in association rule mining. Meanwhile, at this stage is not based on Apriori algorithm for mining because of the special circumstances, using gray correlation analysis on the situation of small amounts of data analysis and mining of association. Association rule mining results from an experimental program to other experimental results of degree programs, valuable rules and information are obtained to make the right decision and provide a great convenience for teaching management education. The linear regression techniques were introduced to the teaching evaluation teaching, Matlab software to analyze the data obtained in all evaluation and the relationships between teaching effectiveness, so that recommendations can be used for teaching and instruction.