| Since the appearance of educational evaluation as a kind of professional activity in 50's of 20 centuries, the function of educational evaluation is continuous to expand outwardly from the teaching and the course realms, becoming gradually important means for education and administration. Currently, International community all look it as necessary means for assessing and deciding the effect of the educate organization to conduct, evaluating personal work results, improving educational policy, improving effect of manage system and making the educational quantity raise continuously. In recent years, with various emergence of network terrace, each high school built up the educational administration system of their own, these systems operate and handle a great deal of business like data information everyday, but lack making use of the data information to carry on the comprehensive analysis or to educational evaluate which present decision support for the process of the educational administration in the end. Therefore, building up a set of decision support system used for the educational evaluation, has the very important and realistic meaning for promoting the educational quantity and making education develop. At the same time, the naissance of data DW and OLAP bring the revolution of the system structure for information system realm, also bring the intelligence ages of the decision management, this provides the technical guarantee for the comprehensive decision support system to be built.This paper at first introduces DW and Data Mining and its relevant conception and it also studies data mining technology and its mining algorithms, mainly dealing with the approaches of decision tree and its improved algorithmic methods, its relevant rules and its improved algorithmic methods and its practical application in teaching quality evaluation system. Through data mining on the students' evaluation data on faculties' teaching in AnHui University of Science and Technology and database of some teachers, we can take advantage of its association rules to mine some key factor affecting teaching quality, and after that we can analyze the mining results and approve its validity. This paper studies and analyzes the realizing progress of ID3 algorithm in decision tree methods by applying the practical data in teaching quality appreciation. A detailed description is given to mine the association rules, by scooping out the classic algorithm—Apriori algorithm and improved Apriori, and give all pseudocodes. By combining the reference to the method of the born association rules and from frequent (k-l)-itemset that generates candidate k-itemsets, the author put forward the view that the antecedent of the rule goes before the consequent, thus produces the corresponding calculation of the association rules, and succeeds in carrying out that calculation in the teaching quality evaluation data mining system.This paper gives two kinds of solution based on the SQL Server, and gives teaching quality evaluation data mining system in AnHui University of Science and Technology. Finally it also proposed to realize teaching quality evaluation system in our country through the Education Network. From this time the common people may judge various universities' quality clearly through universities' teaching quality data from the Education Government. In the end, the article carried on the summary to the whole system, and pointed out the shortage and the future work.Figure [10] table [4] reference [39]... |
PDF Full Text Request