GIFT-AI: Damn!.jpg—visual literacy through image-making with generative AI
Open accessAbstract
This article addresses the growing need for AI literacy by introducing a classroom activity that combines critical theory with hands-on engagement using generative AI image tools. Students were guided through theoretical framing, image selection, AI experimentation, and group analysis. The activity emphasized how prompt design shapes visual outputs and explored the implications of generative systems through selected theoretical frameworks. It created opportunities for students to engage with the aesthetic and epistemological dimensions of AI-generated media. More broadly, he exercise high-lights how image-making can serve as both a critical and creative method for interrogating algorithmic systems across digital art, media education, visual culture, science and technology studies, and critical AI research. The following course framework outlines how the activity was implemented and contextualized within interdisciplinary learning environments.
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A studio intervention reports improved visual literacy and awareness of algorithmic aesthetics, but evidence is interpretive and not linked to expert-rated product outcomes.
“A studio intervention using classroom observation, discussion, and reflective essays reports improved visual literacy and awareness of algorithmic aesthetics, but evidence is interpretive and not linked to expert-rated product outcomes (Källström 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 Källström 2025
Creative improvement depends on cycles of selection, critique, and reworking instead of isolated idea generation.
“This aligns with studio pedagogy in which creative improvement depends on cycles of selection, critique, and reworking instead of isolated idea generation (Källström 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 Källström 2025
A studio-based Midjourney intervention described how iterative prompting aligned with critique and reflection made student processes more systematic and elaborative.
“A studio-based Midjourney intervention described how iterative prompting aligned with critique and reflection made student processes more systematic and elaborative, which matches the present pattern that deeper iteration can translate into stronger refined outputs (Källström 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 Källström 2025
Cites
What is AI Literacy? Competencies and Design Considerations
Long, D., & Magerko, B. (2020) · Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3313831.3376727 · Cited by 3,241 · see citing works
Atlas of AI: power, politics, and the planetary costs of artificial intelligence.
Can, M. (2022) · International Affairs · doi:10.1093/ia/iiac034 · Cited by 614 · see citing works
On the Limits of Artificial Intelligence (AI) in Education
Selwyn, N. (2024) · Nordisk tidsskrift for pedagogikk og kritikk · doi:10.23865/ntpk.v10.6062 · Cited by 185 · see citing works
Do Large Language Models Understand Us?
y Arcas, B. A. (2022) · Daedalus · doi:10.1162/daed_a_01909 · Cited by 157 · see citing works
AI Literacy in K-12 and Higher Education in the Wake of Generative AI: An Integrative Review
Gu, X., & Ericson, B. J. (2025) · ACM Conference on International Computing Education Research (ICER) · doi:10.1145/3702652.3744217 · Cited by 113 · see citing works
A world model: On the political logics of generative AI
Amoore, L., Campolo, A., Jacobsen, B. N., & Rella, L. (2024) · Political Geography · doi:10.1016/j.polgeo.2024.103134 · Cited by 84 · see citing works
AI Literacy in K-12 and Higher Education in the Wake of Generative AI: An Integrative Review
Gu, X., & Ericson, B. J. (2025) · arXiv · doi:10.48550/arxiv.2503.00079 · Cited by 73
Steyerl, H. (2023) · New Left Review · doi:10.64590/uhm · Cited by 39 · see citing works
Introduction. Photographies et algorithmes
Blaschke, E., Bonhomme, M., Joschke, C., & Somaini, A. (2025) · Transbordeur. · doi:10.4000/13dwn · Cited by 3 · see citing works
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He, S. (2026) · Journal of Computer Assisted Learning · doi:10.1002/jcal.70305
Alfabetización visual e inteligencia artificial
Bañuelos, J. (2026) · VISUAL REVIEW International Visual Culture Review / Revista Internacional de Cultura Visual · doi:10.62161/revvisual.v18.6276
The Sixth Novel: Ivan Bezdomny Through the Eyes of Artificial Intelligence
Razumets, V. V. (2026) · Педагогика и просвещение · doi:10.7256/2454-0676.2026.3.81064
Muxamedov, U. (2026) · Science Research and Development · doi:10.65322/j.srd.02162026.57
BADIIY TA’LIMDA SUN’IY INTELLEKTNI QO‘LLASHNING PEDAGOGIK IMKONIYATLARI VA METODOLOGIK ASOSLARI
Karjavovich, B. R. (2026) · Science Research and Development · doi:10.65322/j.srd.02162026.38
Vuelta al curso con IA: ¿cómo evitar que la tecnología sustituya el aprendizaje?
Feridouni, A. (2026) · Fundación Muy Interesante · doi:10.66806/fundacion_muyinteresante.624643
- Authors
- Källström, K.
- Affiliations
- University of Gothenburg (SE)
- Corresponding author
- Källström, Klara
- ORCID
- Källström, Klara
- Venue
- Frontiers in Education
- Publisher
- Frontiers Media SA
- Published
- 2025-09-29
- Volume
- 10
- ISSN
- 2504-284X (ISSN-L)
- OpenAlex
- W4414618143
- Cited by
- 6
- References
- 8
- Citations by year
- 2026: 6
- FWCI
- 59.75
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Frontiers in Education (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Social Sciences › Arts and Humanities › Literature and Literary Theory › Literacy, Media, and Education
- Social Sciences › Arts and Humanities › Visual Arts and Performing Arts › Art Education and Development
- Physical Sciences › Computer Science › Information Systems › Digital Education and Society
- Keywords
- generative AI, AI literacy, visual literacy, image-making, prompt engineering, critical theory, AI-generated content, algorithmic systems, media education, visual culture, science and technology studies, digital art, interdisciplinary learning, classroom activities
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