ExpTODIM-driven framework for 2-tuple linguistic neutrosophic MAGDM with applications to teaching quality evaluation in higher education

Author:

Huang Can,Cheng Zongqian,Guo Huimin

Abstract

Since the new century, the main theme of my country’s higher education is to improve the quality of teaching. To this end, the education administrative department and the vast number of colleges and universities have done a lot of work. Looking back, this teaching quality construction involving thousands of colleges and universities across the country has attracted much attention from all walks of life. The government as the organizer promotes the active participation of colleges and universities in the form of teaching evaluation under the leadership of administrative authority and the “quality engineering” project with resources and reputation, which has played a huge role in improving the teaching quality of colleges and universities. The teaching quality evaluation in higher education is a classical multi-attribute group decision-making (MAGDM) issue. Recently, the Exponential TODIM (ExpTODIM) method has been used to cope with MAGDM issues. The 2-tuple linguistic neutrosophic sets (2TLNSs) are used as a tool for characterizing uncertain information during the teaching quality evaluation in higher education. In this paper, the 2-tuple linguistic neutrosophic number ExpTODIM (2TLNN-ExpTODIM) is built to solve the MAGDM under 2TLNSs. In the end, a numerical case study for teaching quality evaluation in higher education is given to validate the proposed method. The main contribution of this paper is constructed: (1) the Exponential TODIM (ExpTODIM) method is extended to the PLTSs; (2) the 2-tuple linguistic neutrosophic number ExpTODIM (2TLNN-ExpTODIM) is built to solve the MAGDM under 2TLNSs; (3) Finally, a numerical case study for teaching quality evaluation in higher education is given to validate the proposed method.

Publisher

IOS Press

Subject

Artificial Intelligence,Control and Systems Engineering,Software

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