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Critical dimensions in strengthening education and instructor training using fuzzy based decision algorithm and
1Department of Endocrinology, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, 610072, Sichuan, China.
Scientific Reports
|August 6, 2025
Summary
This study introduces a novel circular Pythagorean fuzzy set (Cr-PyFS) approach for decision-making in educational quality and instructor training. It enhances ranking methods to manage uncertainty and improve educational policy development.
Area of Science:
- Educational Decision-Making
- Fuzzy Set Theory
- Mathematical Optimization
Background:
- Quality education and instructor training are vital for societal development, necessitating effective decision-making in educational policies.
- Existing decision-making frameworks struggle with uncertainty and vagueness inherent in complex educational contexts.
- The need for robust mathematical methodologies to aggregate preferences and rank alternatives in educational settings is evident.
Purpose of the Study:
- To develop a novel decision-making framework using circular Pythagorean fuzzy sets (Cr-PyFS) to address uncertainty in educational quality and instructor training.
- To formulate flexible operations and aggregation operators within the circular Pythagorean fuzzy (Cr-PyF) environment.
- To establish a comprehensive approach for ranking training institutes based on instructor skill development criteria.
Main Methods:
- Modification of fuzzy framework and decision-making techniques.
- Exploration of circular Pythagorean fuzzy sets (Cr-PyFS) and their operations (Frank t-norm and t-conorm).
- Development of Cr-PyF aggregation operators (Cr-PyFFWA, Cr-PyFFWG), CRITIC method for criteria weighting, and WASPAS for alternative ranking.
Main Results:
- A numerical example demonstrated the framework's efficacy in selecting suitable training institutes for enhancing instructor skills.
- The proposed Cr-PyF approach effectively manages uncertainty and vagueness in decision-making processes.
- Comparative analysis validated the superiority of the pioneering methods over existing techniques.
Conclusions:
- The developed Cr-PyF decision-making approach offers a robust and flexible tool for improving educational quality and instructor training.
- This methodology provides a reliable mechanism for ranking alternatives under complex and uncertain conditions.
- The study highlights the potential of advanced fuzzy set theory in optimizing educational policy and practice.
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