Exploring students’ aesthetic imagery cognition in digital illustration styles: implications for art education

Digital illustrations encompass diverse visual styles that subtly shape viewers’ experiences and aesthetic cognition. This study explored students’ perceptions of aesthetic imagery in nine samples of contemporary digital illustrations. Cognition was assessed using the semantic differential method, and responses were analysed through independent samples t-tests. The findings indicated that viewers were influenced by perceived aesthetic imagery associated with emotional qualities, visual forms, and creative styles. Cluster analysis reclassified the illustrations into two categories characterized by distinctive aesthetic traits: cute and therapeutic, and fantastical and novel. While grade level and art background showed no significant effects on cognition, several notable gender-related differences emerged. Male students tended to present cognition of aesthetic imagery described as mature, artistic, retro, dull, and sometimes complicated, whereas female students were more inclined toward imagery described as cute, vulgar, novel, lively, and simple. Specifically, The semantic differential method employed the adjective pair ‘artistic–vulgar’ in the SD scale, where ‘vulgar’ refers to common or popular aesthetics rather than offensive or distasteful ones. The findings of this study offer valuable implications for art and design educators by informing curriculum adjustments and instructional practices in the areas of art appreciation teaching and the selection of visual instructional media.

Authors

Institutions

Publication Details

Journal
Cogent Education
Published
2026-03-05
DOI
https://doi.org/10.1080/2331186x.2026.2639782
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
article

Exploring students’ aesthetic imagery cognition in digital illustration styles: implications for art education

Chia-Rong Lee
Cogent Education
Aesthetic Perception and Analysis
article

Exploring students’ aesthetic imagery cognition in digital illustration styles: implications for art education

Chia-Rong Lee
article en

Abstract

Digital illustrations encompass diverse visual styles that subtly shape viewers’ experiences and aesthetic cognition. This study explored students’ perceptions of aesthetic imagery in nine samples of contemporary digital illustrations. Cognition was assessed using the semantic differential method, and responses were analysed through independent samples t-tests. The findings indicated that viewers were influenced by perceived aesthetic imagery associated with emotional qualities, visual forms, and creative styles. Cluster analysis reclassified the illustrations into two categories characterized by distinctive aesthetic traits: cute and therapeutic, and fantastical and novel. While grade level and art background showed no significant effects on cognition, several notable gender-related differences emerged. Male students tended to present cognition of aesthetic imagery described as mature, artistic, retro, dull, and sometimes complicated, whereas female students were more inclined toward imagery described as cute, vulgar, novel, lively, and simple. Specifically, The semantic differential method employed the adjective pair ‘artistic–vulgar’ in the SD scale, where ‘vulgar’ refers to common or popular aesthetics rather than offensive or distasteful ones. The findings of this study offer valuable implications for art and design educators by informing curriculum adjustments and instructional practices in the areas of art appreciation teaching and the selection of visual instructional media.

Cogent EducationVol. 13(1)
National Yunlin University of Science and Technology (TW)
Quality Education
Openalex Percentile: Top 36%
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.