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Combined Probabilistic Linguistic Group Decision-Making for Quality Evaluation of Continuing Education for Primary and Secondary School Teachers

Combined Probabilistic Linguistic Group Decision-Making for Quality Evaluation of Continuing Education for Primary and Secondary School Teachers
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Author(s): Hongzhi Zhao (Physics and Electronic Engineering Department, Xinxiang University, China)and Fengqiang Zhang (Xinxiang No.1 Middle School, China)
Copyright: 2025
Volume: 17
Issue: 1
Pages: 24
Source title: International Journal of Decision Support System Technology (IJDSST)
Editor(s)-in-Chief: Shaofeng Liu (University of Plymouth, United Kingdom)
DOI: 10.4018/IJDSST.368248

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Abstract

With the advancement of material and spiritual aspects of society, alongside improvements in economic, political, technological, and educational systems, continuing education for primary and secondary school teachers has developed rapidly. Evaluating the quality of continuing education programs is a complex task that falls under the category of multiple attribute group decision-making (MAGDM). Recently, methods like Exponential TODIM (ExpTODIM) and grey relational analysis (GRA) have been used to address such challenges, providing effective tools for handling decisions involving multiple criteria. This manuscript proposes a novel method, the probabilistic linguistic ExpTODIM-GRA (PL-ExpTODIM-GRA) approach, to tackle MAGDM problems under PLTSs. By combining the advantages of ExpTODIM and GRA, this method provides a robust framework for evaluating the quality of continuing education for primary and secondary school teachers. To validate the proposed method, a numerical case study is presented, demonstrating its application in real-world evaluations of teacher education programs.

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