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基于复杂区间值费马模糊模型运用决策技术优化高校体育教学质量

Optimization of teaching quality of college physical education by using decision making technique under complex interval valued fermatean fuzzy model.

作者信息

Huang Duo, Liu Yangjun

机构信息

Sports Health and Industrial Development Research Center, School of Physical Education, Shangrao Normal University, Shangrao, 334001, Jiangxi, China.

School of Physical Education and Health, Chengdu University of Traditional Chinese Medicine, Chengdu, 611137, Sichuan, China.

出版信息

Sci Rep. 2025 Jul 1;15(1):22053. doi: 10.1038/s41598-025-06233-0.

DOI:10.1038/s41598-025-06233-0
PMID:40596201
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12218363/
Abstract

Teaching quality in college physical education (PE) promotes students' overall physical and mental development. Improving this quality thus entails assessing mainly intrinsically complex variables that tend to include probabilities and subjective factors. This paper develops a new decision-making framework to enhance the quality of college PE teaching through a Complex Interval-Valued Fermatean Fuzzy Dombi Aggregation (CIVFFDA) Operator. The objective framework incorporates differentiated criteria, such as instructor competence, student activity level, the quality of facilities, and teaching performance during several PE course options. Using complex interval-valued Fermatean fuzzy sets (CIVFFS), this model incorporates the fuzziness and hesitancy inherent in experts' evaluations of teaching activity quality, providing a more comprehensive representation. The Dombi aggregation operator is applied for the evaluation aggregation, so the relative importance of the criteria is appropriately reflected. This paper's findings illustrate the effectiveness of employing fuzzy sets (FS) in supporting the decision to select exemplary teaching practices that foster college PE improvement. Therefore, this study benefits the decision-making process for maximizing educational quality and offers suggestions for enhancing PE to administrators and educators.

摘要

高校体育教学质量促进学生身心全面发展。因此,提高这一质量需要评估主要内在复杂的变量,这些变量往往包括概率和主观因素。本文通过复杂区间值费马模糊Dombi聚合(CIVFFDA)算子,开发了一个新的决策框架,以提高高校体育教学质量。该目标框架纳入了差异化标准,如教师能力、学生活动水平、设施质量以及多个体育课程选项中的教学表现。该模型使用复杂区间值费马模糊集(CIVFFS),纳入了专家对教学活动质量评估中固有的模糊性和犹豫性,提供了更全面的表征。Dombi聚合算子用于评估聚合,因此标准的相对重要性得到了适当反映。本文的研究结果说明了采用模糊集(FS)在支持选择促进高校体育改进的 exemplary 教学实践决策方面的有效性。因此,本研究有利于最大化教育质量的决策过程,并为管理人员和教育工作者提供了提高体育教学的建议。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c17/12218363/b936cb1b1b83/41598_2025_6233_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c17/12218363/c7fcb71cd89a/41598_2025_6233_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c17/12218363/30198e71cd8c/41598_2025_6233_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c17/12218363/ccd9eaab3a1e/41598_2025_6233_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c17/12218363/b936cb1b1b83/41598_2025_6233_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c17/12218363/c7fcb71cd89a/41598_2025_6233_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c17/12218363/30198e71cd8c/41598_2025_6233_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c17/12218363/ccd9eaab3a1e/41598_2025_6233_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c17/12218363/b936cb1b1b83/41598_2025_6233_Fig4_HTML.jpg

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本文引用的文献

1
Fuzzy evaluation model for physical education teaching methods in colleges and universities using artificial intelligence.基于人工智能的高校体育教学方法模糊评价模型
Sci Rep. 2024 Feb 27;14(1):4788. doi: 10.1038/s41598-024-53177-y.