Intelligent Evaluation of College Physical Education Quality Using Advanced Complex Interval-Valued Fermatean Fuzzy Models

The present research proposes a framework for evaluating the teaching quality of physical education in colleges and universities based on the Fermatean fuzzy (FF) evaluation method. First, basic definitions of fuzzy logic and how it contributes to the assessment process are presented since it is a good measure of uncertainty and imprecision in evaluating educational programs. Then, a format for evaluation has been made, animating critical factors like the quality of instruction, physical fitness of students, faculty development, and management of sports facilities. For an objective analysis, evaluation entities and levels are defined, followed by a holistic FF-based evaluation model to develop its specific rankings and analytic insights. Simulations are employed in validating the said model in the actual environment of identifying possible challenges and limitations in physical education implemented at college levels. Thus, based on the obtained outputs, ensuing recommendations for optimal and enhanced physical education programs are recommended. The results are well able to present the impressive ability of FF to translate into reality the complexity of educational quality and give institutions a strong instrument for assessing education quality. This approach can, thus, be broadened to evaluate educational quality in other fields with useful inferences for continuous improvement and policy-making.

Authors

Institutions

Publication Details

Journal
IEEE Access
Published
2025-01-01
DOI
https://doi.org/10.1109/access.2025.3559303
Citations
3
Primary Topic
Evaluation Methods in Various Fields
Type
article
Field-Weighted Citation Impact
5.51
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Intelligent Evaluation of College Physical Education Quality Using Advanced Complex Interval-Valued Fermatean Fuzzy Models

Congmei Liu
3 citations
IEEE Access
Evaluation Methods in Various Fields
5.51
article

Intelligent Evaluation of College Physical Education Quality Using Advanced Complex Interval-Valued Fermatean Fuzzy Models

Congmei Liu
article en
3 citations

Abstract

The present research proposes a framework for evaluating the teaching quality of physical education in colleges and universities based on the Fermatean fuzzy (FF) evaluation method. First, basic definitions of fuzzy logic and how it contributes to the assessment process are presented since it is a good measure of uncertainty and imprecision in evaluating educational programs. Then, a format for evaluation has been made, animating critical factors like the quality of instruction, physical fitness of students, faculty development, and management of sports facilities. For an objective analysis, evaluation entities and levels are defined, followed by a holistic FF-based evaluation model to develop its specific rankings and analytic insights. Simulations are employed in validating the said model in the actual environment of identifying possible challenges and limitations in physical education implemented at college levels. Thus, based on the obtained outputs, ensuing recommendations for optimal and enhanced physical education programs are recommended. The results are well able to present the impressive ability of FF to translate into reality the complexity of educational quality and give institutions a strong instrument for assessing education quality. This approach can, thus, be broadened to evaluate educational quality in other fields with useful inferences for continuous improvement and policy-making.

IEEE Access
Anhui University of Science and Technology (CN), Anhui Science and Technology University (CN)
Quality Education
Openalex Percentile: Top 5%
Evaluation Methods in Various Fields
5.51
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.