Evaluating Physical Education Quality in Higher Education Using a Picture Fuzzy Decision Framework With Muirhead Mean Operator and MULTIMOORA Method

IF 3.6 3区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS IEEE Access Pub Date : 2025-01-23 DOI:10.1109/ACCESS.2025.3532949
Rui Xue
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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.
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基于Muirhead均值算子和MULTIMOORA方法的图像模糊决策框架评价高校体育教学质量
高等教育体育教学质量评估是促进学生发展和学校卓越发展的必要条件。然而,一些不确定和模糊的因素导致了体育教学质量评价的复杂性。本研究旨在利用图像模糊集(PFS)框架,考虑不确定因素,对体育教学质量进行评估。将比率分析加全乘式多目标优化(MULTIMOORA)方法与Muirhead Mean算子相结合,提出了一种创新的决策模型。PFS实现了专家意见的隶属度(MD)、中立隶属度(DONM)和非隶属度(ND)模型,从而有效地解决了多准则决策问题中的不确定性和模糊性。MM操作符通过捕获评估标准之间的相互依赖性来提高准确性,确保更精确和全面的分析。由于比例系统(RS)、参考点方法(RPA)和全乘法形式(FMF)的组成部分,MULTIMOORA方法确保了在评估体育教学质量的开发决策模型中的稳健分析。这项工作的实际意义是重要的,因为它为利益相关者提供了课程开发、资源优化和体育教育决策的可行见解。一个数值例子证明了该方法在现实世界中的实用性,展示了其在解决高等教育质量评估固有挑战方面的有效性。本研究为评估和改进体育教育项目提供了科学严谨和实际有效的工具,从而推动了决策科学的发展。
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来源期刊
IEEE Access
IEEE Access COMPUTER 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.
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