Analysis of students’evaluation of teaching based on rough set theory with unknown decision attribute
Xu Tan · Computer Engineering and Applications Journal · 2012
In order to obtain objective and reasonable results of students’evaluation of teaching, this paper adopts an intelligent approach based on rough set theory. Rough set method can only process decision table containing given decision attribute. However, during the evaluation of teaching, the decision attribute is usually lost because of lacking objective scales in practical measurement. Pointing at this problem, decision attribute values are acquired from experts’evaluation data set based on the method of Kruskal maximum tree fuzzy clustering, and the integrated decision table is designed by combining the students’evaluation data set with the decision attribute data. Objective weight values of all evaluation indexes are obtained under the information entropy method based on rough set theory, and the evaluation is finished for the candidates. Example analysis and contrastive experiments with other existing evaluation methods are given to demonstrate the effectiveness and superiority of the proposed new method.