Evidence map›Paper›PMID 40830384›Full record

ArticleScientific reports2025

Evaluation of sports teaching quality in universities based on fuzzy decision support system.

Kunjian Han, Jian Wan

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Kunjian HanXinyang Agriculture and Forestry University, Xinyang, Henan, 464000, China.
Jian WanGongqing College of Nanchang University, Jiujiang, 332020, Jiangxi, China. wanjian126@hotmail.com.

Funding

Research on the Governance Path of Rural Sports Revitalization in Henan Province with Digital Empowerment QN2023062
6 · The paper itself

Abstract

Sports teaching in universities relies on staff experience, training modes., evaluated by the student's performance and competitive outcomes. The teaching quality assessment requires a large volume of data related to teaching patterns, training. A Teaching Convoluted Quality Assessment Model (TCQAM) is proposed in this article to provide a robust teaching quality assessment. The proposed model intakes different factors, such as training patterns, sessions, time, associated with the teaching sessions. Based on the sports training requisites, the above, like associated factors, are validated using a fuzzy decision system. In this decision system, the possible factors for maximum teaching quality are convoluted with each of the above-mentioned factors. The fuzzy membership derivatives identify the least performance factor to perform an improvement assessment. This improvement assessment replaces the low teaching quality factors with the recommended or novel inputs. The fuzzy performs high-quality membership derivatives on this improved assessment to ensure better teaching is provided. Therefore, a balanced teaching input improves the quality of sports teaching for different training sessions.

Indexed as

Decision Support TechniquesFuzzy LogicSportsTeachingHumansUniversitiesFuzzy decision systemMembership functionsQuality assessmentSports teaching

Identifiers

PMID40830384
PMCPMC12365259

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.