Expert-Derived Evaluative Criteria and Aesthetic Judgments of Clothing: A Comparison of Guided and Unguided Non-Expert Evaluations

Aesthetic judgments are shaped by both visual properties and evaluative knowledge. However, it remains unclear how explicit expert-derived criteria relate to non-experts’ aesthetic judgments of clothing. This study compared non-experts’ judgments under guided and unguided evaluation procedures and examined their correspondence with expert evaluations. Seventeen criteria were developed through a three-round modified Delphi study. Twenty-six experts rated 48 clothing images. Of 60 non-experts randomly assigned to the guided or unguided condition, 59 were included in the analysis (29 guided, 30 unguided). Guided participants rated 17 criteria before giving an overall judgment; unguided participants provided overall ratings only. The guided condition was associated with lower overall aesthetic ratings and smaller absolute deviations from expert evaluations than the unguided condition. At the image level, guided judgments showed a stronger correlation with expert evaluations than unguided judgments (r = 0.771 vs. 0.222). Fifteen criteria showed positive within-person associations with overall judgments after multiple-testing correction, but only visual emphasis remained significant when all criteria were modeled together. These findings suggest that structured evaluation warrants further investigation. Differences in task demands and visual anchors prevent us from isolating the contribution of expert-derived criteria.

Authors

Institutions

Publication Details

Journal
Behavioral Sciences
Published
2026-11-06
DOI
https://doi.org/10.3390/bs16112119
Primary Topic
Aesthetic Perception and Analysis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
NOV
article

Expert-Derived Evaluative Criteria and Aesthetic Judgments of Clothing: A Comparison of Guided and Unguided Non-Expert Evaluations

Rong Zheng, Dingwei Liu, Qing Chen, Jintu Fan et al.
Behavioral Sciences
Aesthetic Perception and Analysis
article

Expert-Derived Evaluative Criteria and Aesthetic Judgments of Clothing: A Comparison of Guided and Unguided Non-Expert Evaluations

Rong Zheng, Dingwei Liu, Qing Chen, Jintu Fan, Peng Jin
article en

Abstract

Aesthetic judgments are shaped by both visual properties and evaluative knowledge. However, it remains unclear how explicit expert-derived criteria relate to non-experts’ aesthetic judgments of clothing. This study compared non-experts’ judgments under guided and unguided evaluation procedures and examined their correspondence with expert evaluations. Seventeen criteria were developed through a three-round modified Delphi study. Twenty-six experts rated 48 clothing images. Of 60 non-experts randomly assigned to the guided or unguided condition, 59 were included in the analysis (29 guided, 30 unguided). Guided participants rated 17 criteria before giving an overall judgment; unguided participants provided overall ratings only. The guided condition was associated with lower overall aesthetic ratings and smaller absolute deviations from expert evaluations than the unguided condition. At the image level, guided judgments showed a stronger correlation with expert evaluations than unguided judgments (r = 0.771 vs. 0.222). Fifteen criteria showed positive within-person associations with overall judgments after multiple-testing correction, but only visual emphasis remained significant when all criteria were modeled together. These findings suggest that structured evaluation warrants further investigation. Differences in task demands and visual anchors prevent us from isolating the contribution of expert-derived criteria.

Behavioral SciencesVol. 16(11)
Ningbo University (CN), Hong Kong Polytechnic University (HK), Donghua University (CN)
Openalex Percentile: Top 19%
Aesthetic Perception and Analysis
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.

Laika access coming soon