Probabilistic Double Hierarchy Linguistic TOPSIS Method for MAGDM and Its Application to Teaching Quality Evaluation of College English

Abstract

College English is a compulsory course for college students. The teaching level of teachers in this course has naturally been evaluated by various schools. The teaching quality evaluation of college English is frequently viewed as a multiple attribute group decision-making (MAGDM) issue. The probabilistic double hierarchy linguistic not only conforms to people’s language expression habit of “adverb + adjective,” but can also accurately express its importance. Therefore, this paper comes up with the PDHL-TOPSIS mean for MAGDM based on the PDHLTS environment and applies it to the teaching quality evaluation of college English. On the one hand, we bring information entropy into the determination of target weight. The PDHL-TOPSIS technique is constructed and utilized for teaching level evaluation. Eventually, the PDHL-TOPSIS technique is compared with other decision-making means, and the novel mean turns out to be significant and valid.