Application Research Of Data Mining Technology In Secondary Vocational Teaching Evaluation

Entering the21st century, with the rapid development of computer technologyand information technology, great changes have taken place in human society,appeared excess "data" and "knowledge poverty" phenomenon. Data mining：fromlarge amounts of data, through data analysis, to extract the implicit one ofthe useful information, the process of knowledge. With the development of datamining technology, data mining plays an increasingly important role in many areas,has been more and more decision makers.The article embarks from the practical application of engineering project,in order to trade in Guangzhou business vocational school of the applicationresearch of data mining as an example, the understanding, on the basis of datamining theory and technology, to dig out the useful information from the dataand knowledge as the goal, to explore in the secondary vocational teachingevaluation data mining application in project design, implementation andapplication.Data mining can help school to micro, meso and macro data statistics,analysis, synthesis and reasoning, through the establishment and applicationof data mining model, find out secondary vocational education has seen thespecial pattern and tendency, found some implicit rules, characteristics in theprocess of education, education reform for policy makers, sector adjustment,courses, etc. Provide the correct basis, assist managers to make scientificdecision, for the development of the school to win competitive advantage, improvethe level of school education.Secondary vocational school’s development cannot leave the cultivation ofexcellent teachers and cultivate excellent students, this article researchmainly revolves around three questions:1、 Secondary vocational teachers’ goodwhat factors related.2、Schools dropped out of trend, the dropout rate isrelated to what factors.3、 What is the connection between secondary vocationalcourses. Around the secondary vocational schools of these three problems in the development, this paper adopts the data mining process CRISP_DM (businessunderstanding, data understanding, data preparation, modeling, evaluation modeland deployment) for data mining. Using the data mining of association rules andclustering analysis, technical analysis out for good teachers model mining;Using time series analysis of the data mining technology come to schoolenrollment trends, and through the decision tree of data mining technology tofurther analysis reasons students drop out of school; Using the correlationanalysis of data mining association rules between basic course and specializedcourse.Model of data mining results according to the good teacher, the schoolaccording to the outstanding teachers create conditions, makes more teachersto become a good teacher, the application of the results in hiring teachers canpredict when apply for whether good, for school recruit more teachers talents;Students come from different level analysis of the data mining results studentaffairs office provided to the school, the school leadership, they adjustaccording to the results of the analysis of the moral education teaching work,focus on a relatively low credit grade students learning situation, through aseries of change, student drop-out rates have been reduced; Mining course, therelationship between the use of mining results to guide the teaching work, adjustthe teaching plan, change the proportion of the basic courses and professionalcourses, improving the students’ professional level and ability. Data miningresearch project of this paper can provide reference with other secondaryvocational school, according to data mining project your school the educationlaw of the mining analysis for optimizing secondary vocational school teachersteam construction, teaching reform of moral education and curriculum reformprovides a decision-making basis.Three data mining study results indicate that the article is feasible, usingthe results of the analysis to guide the reform of education is effective.