Evaluating Physical Education Quality in Higher Education Using a Picture Fuzzy Decision Framework With Muirhead Mean Operator and MULTIMOORA Method
The quality assessment of physical education programs in higher education is essential for fostering student development and institutional excellence. However, several uncertain and ambiguous factors cause the complexity of the quality assessment of physical education. This study aims to evaluate th...
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10850913/ |
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| Summary: | The quality assessment of physical education programs in higher education is essential for fostering student development and institutional excellence. However, several uncertain and ambiguous factors cause the complexity of the quality assessment of physical education. This study aims to evaluate the quality of physical education, considering the uncertain factors using a well-known framework known as picture fuzzy set (PFS). This study introduces an innovative decision-making model by integrating the Multi-Objective Optimization by Ratio Analysis plus Full Multiplicative Form (MULTIMOORA) method and the Muirhead Mean (MM) operator. The PFS enables the model of the expert’s opinion using membership degree (MD), degrees of neutral membership (DONM), and non-membership degree (ND) and consequently effectively addresses uncertainty and ambiguity in multi-criteria decision-making problems. The MM operator enhances the accuracy by capturing interdependencies among evaluation criteria, ensuring more precise and comprehensive analyses. The MULTIMOORA method ensures robust analysis in the developed decision model for assessing the physical education quality because of the components of the Ratio System (RS), Reference Point Approach (RPA), and Full Multiplicative Form (FMF). The practical implications of this work are significant, as it equips stakeholders with actionable insights for curriculum development, resource optimization, and policy-making in physical education. A numerical example demonstrates the method’s utility in real-world scenarios, showcasing its effectiveness in addressing challenges inherent in higher education quality assessments. This study advances decision science by providing a scientifically rigorous and practically impactful tool for evaluating and improving physical education programs. |
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| ISSN: | 2169-3536 |