Evidence map›Paper›PMID 42466027›Full record

ArticleFrontiers in psychology2026

The competence paradox: negotiating ease, risk, and creative identity in text-to-image generative AI use among art and design students.

Yihan Liu, Meng Meng, Yue Zhang

Abstract read
In one paragraph

Article in Frontiers in psychology, 2026. 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
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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

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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

3 authors.

Yihan LiuCollege of Architecture and Art, Hefei University of Technology, Hefei, China.
Meng MengCollege of Architecture and Art, Hefei University of Technology, Hefei, China.
Yue ZhangCollege of Architecture and Art, Hefei University of Technology, Hefei, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The rapid diffusion of text-to-image (T2I) generative AI has intensified pressures surrounding assessment and skill reconfiguration in art and design education. However, existing research on T2I adoption in studio-based pedagogy remains limited. This study examines technology acceptance from both educators' and students' perspectives, and illustrates the transformation of intentions and actions in creative learning situations. Methods: A modified exploratory sequential mixed-methods design with an explanatory qualitative follow-up phase (QUAL-QUAN-qual) was employed. Instructor focus groups were first conducted to identify key constructs and inform the development of a contextualized technology acceptance framework. This was followed by a questionnaire survey of 417 college students, and semi-structured interviews to explain unexpected quantitative results. Results: The results indicate that performance expectancy, social influence, novelty value, and creative competence positively influence behavioral intention. In contrast, the negative effects of effort expectancy and facilitating conditions can be interpreted in light of students' shortcut-oriented use of T2I tools in coursework. Furthermore, students with different levels of competence perceive distinct risks across task stages, which helps explain the lack of significant translation from intention and creative competence into use behavior. Discussion: The findings highlight a paradox: although creative competence positively supports behavioral intention, it may also lead to more selective or restrained engagement in actual use. Accordingly, the study extends technology acceptance models in creative education by showing that T2I adoption cannot be understood solely through conventional utilitarian predictors. Instead, it is also shaped by students' interpretations of risk and their developing creative identity, particularly in authorship, originality, and skill preservation. The results reconceptualize T2I adoption as a dynamic process of negotiation between diverse student profiles and technological evolution, ultimately providing an evidence-based foundation and practical recommendations for AI pedagogy in creative education.

Indexed as

art and designgenerative AIhigher educationtext-to-imageUTAUT

Identifiers

PMID42466027
PMCPMC13374163

What OpenQuestion holds

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LicenceCC BY
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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.