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Article type: Research Article
Authors: Fu, Liping; *
Affiliations: Shanxi Datong University, Datong, Shanxi, China
Correspondence: [*] Corresponding author. Liping Fu, Shanxi Datong University, Datong, 037009, Shanxi, China. E-mail: dtdxflp@163.com.
Abstract: Today, information technology has penetrated into various fields of universities, and the development of information technology in teaching, scientific research, management, and services has become a catalyst for promoting changes in universities. In terms of teaching informatization, the Internet provides a powerful tool for knowledge dissemination and a huge platform for learning and communication between university teachers and students. Knowledge sharing has become easier, and the era of mutual interaction between teachers and students has arrived. University teachers need to quickly face this challenge, adapt to the new teaching and learning environment, improve their own literacy, enhance their information-based teaching ability, change their teaching behavior, and thereby improve the quality of university education and meet the needs of society for talent cultivation. The informationization teaching ability evaluation of university teachers is a classical MAGDM problems. Recently, the Exponential TODIM(ExpTODIM) and (grey relational analysis) GRA method has been used to cope with MAGDM issues. The interval neutrosophic sets (INSs) are used as a tool for characterizing uncertain information during the informationization teaching ability evaluation of university teachers. In this manuscript, the interval neutrosophic number Exponential TODIM-GRA (INN-ExpTODIM-GRA) method is built to solve the MAGDM under INSs. In the end, a numerical case study for informationization teaching ability evaluation of university teachers is given to validate the proposed method.
Keywords: Multiple attribute group decision making (MAGDM), interval neutrosophic sets (INSs), ExpTODIM, GRA, informationization teaching ability evaluation
DOI: 10.3233/JIFS-233192
Journal: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 1245-1258, 2024
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