DEALING WITH AI IMAGE GENERATORS IN THE DESIGN STUDY PROCESS
DOI:
https://doi.org/10.55877/cc.vol33.553Keywords:
attitude toward AI, collaboration with AI, design education, image generationAbstract
The authors of this article pay particular attention to attitudes toward AI image generation capabilities and their relevance to the outcome of the design study process. This study seeks to investigate how AI can be used in a goal-oriented collaborative way to enhance the study process for future graphic and interior designers. The research question is: What are the key prerequisites for the involvement of AI in the study process for future designers? Data were collected using structured electronic e-mail expert interviews (N1 = 4) and two student surveys (N2a = 87, N2b = 64; one sample, two different times). The researchers use a mixed-method research design with case study features and conclude that design education should provide an opportunity to familiarize oneself with the possibilities of using AI tools sufficiently comprehensively, so that designers can compete in the labour market in their professional lives. Design value criteria are important for evaluation of variously created images and the use of AI tools to their advantage. AI involvement should follow when students have mastered the basics of professional activity and visual art. Considering that several students completely reject the use of AI, special attention should be paid to solving motivation problems. Future research should develop and explore the best methods and forms for integrating AI into the design study process.
Downloads
References
Anantrasirichai, N. and Bull, D. (2022). Artificial intelligence in the creative industries: A review. Artificial Intelligence Review, 55(1), 589–656.
Castañer, X. and Oliveira, N. (2020). Collaboration, coordination, and cooperation among organizations: Establishing the distinctive meanings of these terms through a systematic literature review. Journal of Management, 46(6), 965–1001.
Creswell, J. W. and Guetterman, T. C. (2019). Educational Research: Planning, Conducting, and Evaluating Quantitative and Qualitative Research. 6th ed. Upper Saddle River, NJ: Pearson.
Dehouche, N. and Dehouche, K. (2023). What’s in a text-to-image prompt? The potential of stable diffusion in visual arts education. Heliyon, 9(6). https://doi.org/10.1016/j.heliyon.2023.e16757
Du, Y., Li, T. and Gao, C. (2023). Why do designers in various fields have different attitude and behavioral intention towards AI painting tools? An extended UTAUT model. Procedia Computer Science, 221, 1519–1526.
Ehsan, U., Liao, Q. V., Muller, M., Riedl, M. O. and Weisz, J. D. (2021). Expanding explainability: Towards social transparency in AI systems. In: CHI ‘21: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. New York: Association for Computing Machinery, a. 82.
Fathoni, A. F. C. A. (2023). Leveraging generative AI solutions in art and design education: Bridging sustainable creativity and fostering academic integrity for innovative society. E3S Web of Conferences, 426, a. 01102.
Fui-Hoon Nah, F., Zheng, R., Cai, J., Siau, K. and Chen, L. (2023). Generative AI and ChatGPT: Applications, challenges, and AI-human collaboration. Journal of Information Technology Case and Application Research, 25(3), 277–304.
Hughes, R. T., Zhu, L. and Bednarz, T. (2021). Generative adversarial networks-enabled human-artificial intelligence collaborative applications for creative and design industries: A systematic review of current approaches and trends. Frontiers in Artificial Intelligence, 4. https://doi.org/10.3389/frai.2021.604234
Hutson, J. and Lang, M. (2023). Content creation or interpolation: AI generative digital art in the classroom. Metaverse, 4(1). https://doi.org/10.54517/m.v4i1.2158
Jauhiainen, J. S. and Guerra, A. G. (2023). Generative AI and ChatGPT in school children’s education: Evidence from a school lesson. Sustainability, 15(18). https://doi.org/10.3390/su151814025
Lim, J., Leinonen, T., Lipponen, L., Lee, H., DeVita, J. and Murray, D. (2023). Artificial intelligence as relational artifacts in creative learning. Digital Creativity, 34 (3), 192–210.
Liu, V. and Chilton, L. B. (2022). Design guidelines for prompt engineering text-to-image generative models. In: CHI ‘22: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems. New York: Association for Computing Machinery, a. 384.
Lyu, Y., Wang, X., Lin, R. and Wu, J. (2022). Communication in human-AI co-creation: Perceptual analysis of paintings generated by text-to-image system. Applied Sciences, 12(22). https://doi.org/10.3390/app122211312
McCormack, J., Cruz Gambardella, C., Rajcic, N., Krol, S. J., Llano, M. T. and Yang, M. (2023). Is writing prompts really making art? In: International Conference on Computational Intelligence in Music, Sound, Art and Design. Cham: Springer, 196–211.
Oppenlaender, J. (2022). The creativity of text-to-image generation. In: Academic Mindtrek 2022: Proceedings of the 25th International Academic Mindtrek Conference. New York: Association for Computing Machinery, 192–202.
Ouyang, F. and Jiao, P. (2021). Artificial intelligence in education: The three paradigms. Computers and Education: Artificial Intelligence, 2. https://doi.org/10.1016/j.caeai.2021.100020
Pipere, A. (2021). Kvalitatīvā kontentanalīze [Qualitative content analysis]. In: K. Mārtinsone, A. Pipere (eds.), Zinātniskās darbības metodoloģija: starpdisciplināra perspektīva [Research Methodology: An Interdisciplinary Perspective]. Rīga: Rīgas Stradiņa universitāte, 401–408.
Sarkar, A. (2023). Exploring perspectives on the impact of artificial intelligence on the creativity of knowledge work: Beyond mechanised plagiarism and stochastic parrots. In: CHIWORK ‘23: Proceedings of the 2nd Annual Meeting of the Symposium on Human-Computer Interaction for Work. New York: Association for Computing Machinery, a. 13.
Tang, T., Li, P. and Tang, Q. (2022). New strategies and practices of design education under the background of artificial intelligence technology: Online animation design studio. Frontiers in Psychology, 13. https://doi.org/10.3389/fpsyg.2022.767295
Vartiainen, H. and Tedre, M. (2023). Using artificial intelligence in craft education: Crafting with text-to-image generative models. Digital Creativity, 34(1), 1–21.
Vartiainen, H., Tedre, M. and Jormanainen, I. (2023). Co-creating digital art with generative AI in K-9 education: Socio-material insights. International Journal of Education Through Art, 19(3), 405–423.
Xu, J., Zhang, X., Li, H., Yoo, C. and Pan, Y. (2023). Is everyone an artist? A study on user experience of AI-based painting system. Applied Sciences, 13(11). https://doi.org/10.3390/app13116496
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Culture Crossroads

This work is licensed under a Creative Commons Attribution 4.0 International License.