Research Of Application Of Data-mining Technology In Action Oriented Teaching Quality Evaluation

With the reformation higher vocational education, action-oriented teaching method hasbeen more and more adopted. Therefore, the focus of talents cultivation has shifted fromknowledge acquisition to formation of applied abilities. More attention has been drawn to thestudents’ initiative and their hand-on ability. In the procedure of action-oriented teaching, thestudents performances has been evaluated from the former theory foremost, practice leastsummative to hand-on foremost formative assessment. In this way students’ everydayperformance and experiments have been recorded so as to urge the students to pay attention topractice and form a good foundation for the career life.With action-oriented teaching deepening into application, higher vocational colleges haveobtained a large amount of scores and data in the evaluation of teaching and learning circulation.At present the precession for the data mainly focuses on the storage and retrieval. The author hasintroduced the fuzzy association rule data-mining technology into the analysis of the data in orderto seek out the correlations between various experiments and the effects on the comprehensivepractice and training so as to provide reference for the teachers and instructors to progress thehands-on ability of the students.The paper first illustrates the principles and process of the fuzzy C clustering algorithm inthe fuzzy association rule mining process and optimizes the trap of part minima in the randomlyselected cluster centers in the evaluation. Through case-study of optimization of current data, it isproved that algorithm shall mine significant association rules and bears a quite good experimentresult. The optimized algorithm has been applied in the scores analysis in the action-orientedteaching to direct and guide the teaching and learning to increase the competence of students’career preparation.