Effects of AI-generated images in visual art education on students' classroom engagement, self-efficacy and cognitive load
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In recent years, Generative Artificial Intelligence (GAI) has demonstrated remarkable potential for producing creative content, including artwork, which has sparked discussions regarding its role in education. Although AI-generated art is gaining recognition in the art world, its application in visual art education remains underexplored. To address this gap, we focused on AI-generated images-a specific category within AI-generated art that emphasizes visual representation. We integrated these images into visual art education and conducted an experiment to evaluate their effects. Seventy-eight fifth-grade students were randomly assigned to a treatment group (n = 39) and a control group (n = 39). Initially, both groups received conventional visual art instruction using classical images. Subsequently, the treatment group was introduced to a GAI-assisted teaching method utilizing AI-generated images, while the control group continued with conventional instruction. The results revealed that students in the treatment group exhibited significantly higher levels of classroom engagement compared to their peers in the control group. Moreover, the treatment group reported a strong sense of self-efficacy with the GAI-assisted method. Importantly, there were no significant differences in cognitive load between the two groups. A comparative analysis of the students’ paintings was conducted, focusing on technical skill, adherence to theme, composition and design, creativity and originality, effort, and improvement, which aligns with the increased classroom engagement and self-efficacy, thereby supporting the effectiveness of AI-generated images. This study is one of the pioneering works to propose and validate the use of AI-generated images to address challenges in developing learning materials within the context of visual art education.
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AI-generated images can strengthen classroom engagement and self-efficacy without increasing cognitive load, but this evidence is only partially transferable to undergraduate illustration settings.
“Evidence from visual art education further suggests that Artificial Intelligence (AI)-generated images can strengthen classroom engagement and self-efficacy without increasing cognitive load, yet this evidence remains only partially transferable to undergraduate illustration settings where originality, authorship, and final artefact quality carry greater assessment weight (Bian et al. 2025).”
From A Study on the Role of Midjourney, A Generative Artificial Intelligence Tool, in Enhancing Student Creativity in Illustration Design Classes (2026) · cites this paper as Bian et al. 2025
The Introduction reports higher engagement and self-efficacy, with no increased cognitive load, in a study of 78 fifth-grade art students. The limitations section calls for research across other grades and settings, supporting caution about transferability. It does not establish how transferable the findings are to undergraduate illustration or whether originality, authorship, and final artefact quality carry greater assessment weight there. (LLM, conf=0.85)
Experimental — accuracy not yet measuredThe study extends classroom evidence from AI-generated visual materials by shifting the endpoint from engagement or self-efficacy to expert-rated illustration artefacts.
“It also extends classroom evidence from AI-generated visual materials by shifting the endpoint from engagement or self-efficacy to expert-rated illustration artefacts (Bian et al. 2025).”
From A Study on the Role of Midjourney, A Generative Artificial Intelligence Tool, in Enhancing Student Creativity in Illustration Design Classes (2026) · cites this paper as Bian et al. 2025
The Introduction and Discussion report classroom evidence that AI-generated images improved engagement and self-efficacy. But the Stage 4 assessment and artwork results show that Bian et al. also used expert ratings of students’ paintings, so the implied contrast between those endpoints and expert-rated artefacts is incomplete. The citing study’s own choice of endpoint is not something this source can establish. (LLM, conf=0.86)
Experimental — accuracy not yet measuredIn visual art education, AI-generated images have improved classroom engagement and self-efficacy without increasing cognitive load, although outcomes remain centred on engagement, self-belief, cognitive load, and painting-related performance.
“In visual art education, AI-generated images have improved classroom engagement and self-efficacy without increasing cognitive load, although the measured outcomes remain centred on engagement, self-belief, cognitive load, and painting-related performance (Bian et al. 2025).”
From A Study on the Role of Midjourney, A Generative Artificial Intelligence Tool, in Enhancing Student Creativity in Illustration Design Classes (2026) · cites this paper as Bian et al. 2025
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Deep Learning-Based Intangible Cultural Heritage Art Transfer for Aesthetic Education
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Seeing against the machine: reframing generative AI error as pedagogical insight in art education
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Why Does AI Dance “Featuring” Audrey Hepburn Not Feel “Authentic”?
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Reimagining Art Education: Teaching Drawing and Painting in the Age of Artificial Intelligence
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- Authors
- Bian, C., Wang, X., Huang, Y., Zhou, S., & Lu, W.
- Affiliations
- Ocean University of China (CN)
- Venue
- Humanities and Social Sciences Communications
- Published
- 2025-09-30
- Volume
- 12
- Issue
- 1
- ISSN
- 2055-1045 (ISSN-L)
- 2662-9992
- OpenAlex
- W4414662178
- Cited by
- 30
- References
- 73
- Citations by year
- 2026: 29 · 2025: 1
- FWCI
- 31.19
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Humanities and Social Sciences Communications (publishedVersion, cc-by-nc-nd)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Natural Science Foundation of Shandong Province (ZR2024QF075)
- National Natural Science Foundation of China (62407042, 62277045)
- Humanities and Social Science Fund of Ministry of Education of China (24YJC880004)
- Topics
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Social Sciences › Arts and Humanities › Visual Arts and Performing Arts › Art Education and Development
- Physical Sciences › Computer Science › Computer Graphics and Computer-Aided Design › Digital Media and Visual Art
- Keywords
- AI-generated images, generative AI, visual arts education, classroom engagement, self-efficacy, cognitive load, fifth grade students, art education, artistic creativity, learning materials
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