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Article type: Research Article
Authors: Xiao, Fan
Affiliations: Henan Polytechnic Institute, Nanyang, Henan 473000, China | E-mail: 2007046@hnpi.edu.cn
Correspondence: [*] Corresponding author: Henan Polytechnic Institute, Nanyang, Henan 473000, China. E-mail: 2007046@hnpi.edu.cn.
Abstract: College English is an important basic course in higher education. Promoting the reform of college English teaching and constructing a scientific and standardized quality assurance system for college English teaching are important guarantees and powerful means to improve the quality of talent cultivation in higher education. In terms of ideology, it is necessary to attach great importance to strengthening the awareness of monitoring and ensuring the quality of college English teaching system construction; In terms of management, ensure the operation of a diversified governance and evaluation system for college English teaching; Practice in improving the quality monitoring and guarantee system of college English teaching in action; In terms of overall coordination, build a high-quality and efficient college English teaching resource sharing system. The classroom teaching quality evaluation in college English is classical multiple-attribute group decision-making (MAGDM) issues. Recently, the Exponential TODIM (ExpTODIM) method has been used to solve MAGDM issues. The probabilistic uncertain linguistic term sets (PULTSs) are used as a tool for characterizing uncertain information during the classroom teaching quality evaluation in college English. In this paper, the probabilistic uncertain linguistic ExpTODIM (PUL-ExpTODIM) method is defined to solve the MAGDM under PULTSs. In the end, a numerical case study for classroom teaching quality evaluation in college English is given to validate the proposed method.
Keywords: Multiple-attribute group decision-making (MAGDM), probabilistic uncertain linguistic term sets (PULTSs), ExpTODIM, classroom teaching quality evaluation
DOI: 10.3233/KES-230082
Journal: International Journal of Knowledge-based and Intelligent Engineering Systems, vol. 27, no. 2, pp. 245-257, 2023
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