{"title":"Evaluating Physical Education Quality in Higher Education Using a Picture Fuzzy Decision Framework With Muirhead Mean Operator and MULTIMOORA Method","authors":"Rui Xue","doi":"10.1109/ACCESS.2025.3532949","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"18277-18293"},"PeriodicalIF":3.4000,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10850913","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Access","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10850913/","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
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.
IEEE AccessCOMPUTER SCIENCE, INFORMATION SYSTEMSENGIN-ENGINEERING, ELECTRICAL & ELECTRONIC
CiteScore
9.80
自引率
7.70%
发文量
6673
审稿时长
6 weeks
期刊介绍:
IEEE Access® is a multidisciplinary, open access (OA), applications-oriented, all-electronic archival journal that continuously presents the results of original research or development across all of IEEE''s fields of interest.
IEEE Access will publish articles that are of high interest to readers, original, technically correct, and clearly presented. Supported by author publication charges (APC), its hallmarks are a rapid peer review and publication process with open access to all readers. Unlike IEEE''s traditional Transactions or Journals, reviews are "binary", in that reviewers will either Accept or Reject an article in the form it is submitted in order to achieve rapid turnaround. Especially encouraged are submissions on:
Multidisciplinary topics, or applications-oriented articles and negative results that do not fit within the scope of IEEE''s traditional journals.
Practical articles discussing new experiments or measurement techniques, interesting solutions to engineering.
Development of new or improved fabrication or manufacturing techniques.
Reviews or survey articles of new or evolving fields oriented to assist others in understanding the new area.