The Application Research Of Data Mining Technology In Teaehing Quality Evaluation

With the deepening of the reform of higher education, teaching quality assessment tools and methods are constantly improved. Main function of teaching quality evaluation system is comprehensively evaluate the teaching quality of teachers and college, and gives analysis of evaluation results. The main aim is that presenting the main factors affecting the quality of teaching and improves teaching quality. Currently, the traditional method of teaching quality evaluation of data processing is simple, the main factor of evaluation is much less, no correlation analysis between the evaluation factors, can not fully meet the current teaching quality assessment the actual demand. Teaching quality assessment is a multi-subject, multiple factors, and multivariable, nonlinear objective process of fuzzy uncertainty.Teaching quality evaluation system in reference to the data mining method, statistics and analysis of data from the flood of data to identify potential law, to find hidden patterns, accurate knowledge of future developments. Through data mining techniques, can be able to solve these problems, and get maximum use of the information systems function used to meet the needs of school management.In this paper, AHP, Fuzzy comprehensive evaluation and other methods are used to calculate the weight of each index, and prepare for the following data mining.After the data pre-processing, Theory of decision tree was used for data mining. The decision tree, which was constructed by using the ID3 and C4.5 algorithm, analysis the factors that affect teaching quality assessment and derive classification rules for evaluating the quality of teachers. Which can provide teaching department informations support to decision-making, and improve the quality of teaching finally.