Does AI Help? A Review of How AIGC Affects Design Education
DOI:
https://doi.org/10.61173/pdymj625Keywords:
AIGC, Artificial Intelligence Generated Content, Design, Design educationAbstract
With the rising advancement of Artificial Intelligence Generated Content (AIGC) tools such as Midjourney, ChatGPT, Meta and Luma, the design industry is undergoing a new shift. Thus, the great influence of the AIGC application has taken place in the design education area, followed by the question, “How does AIGC integration impact design education”? This study aims to uncover the latest progress and identify the research gap in the design pedagogy area, despite the lack of research on how AIGC integration affects design education in contrast to the explosive growth of ChatGPT research. This study explored impactful and most up-to-date articles for systematic analysis. It reveals that AIGC can enhance students’ design efficiency by empowering ideation, prototyping and personalization. However, further study is called for developing strategies for seamlessly integrating AIGC into design curricula and pedagogical practice and the educational ethics and parity issues during the AIGC integration in design education.
References
[1] Cao, Y., Li, S., Liu, Y., Zhang, Y., Dai, Y., Yu, P. S., … & Sun, L. (2023). A comprehensive survey of ai-generated content (aigc): a history of generative ai from gan to chatgpt.. https://doi. org/10.48550/arxiv.2303.04226
[2] Wang, K. (2024). Pre-service teachers’ genai anxiety, technology self-efficacy, and tpack: their structural relations with behavioral intention to design genai-assisted teaching. Behavioral Sciences, 14(5), 373. https://doi.org/10.3390/ bs14050373
[3] Kurtz, G., Amzalag, M., Shaked, N., Zaguri, Y., Kohen- Vacs, D., Gal, E., … & Barak-Medina, E. (2024). Strategies for integrating generative ai into higher education: navigating challenges and leveraging opportunities. Education Sciences, 14(5), 503. https://doi.org/10.3390/educsci14050503
[4] Sheng, Y. (2024). Exploring the coexisting relationship between artificial intelligence-generated content (aigc) and designer. Applied and Computational Engineering, 34(1), 23-30. https://doi.org/10.54254/2755-2721/34/20230290
[5] Wang, Y., Wang, Z., & Mu, R. (2024). Modern design thinking and aigc intervention. Frontiers in Artificial Intelligence and Applications. https://doi.org/10.3233/faia231500
[6] Chen, L., Wang, P., Dong, H., Shi, F., Han, J., Guo, Y., … & Wu, C. (2019). An artificial intelligence based data-driven approach for design ideation. Journal of Visual Communication and Image Representation, 61, 10-22. https://doi.org/10.1016/ j.jvcir.2019.02.009
[7] Kim, J., Lee, H., & Cho, Y. H. (2022). Learning design to support student-ai collaboration: perspectives of leading teachers for ai in education. Education and Information Technologies, 27(5), 6069-6104. https://doi.org/10.1007/s10639-021-10831-6
[8] Tsai, C.-C., & Chai, C. S. (2012). The “third”-order barrier for technology-integration instruction: Implications for teacher education. Australasian Journal of Educational Technology, 28(6). https://doi.org/10.14742/ajet.810
[9] Gao Chenhui, Liu Liyuan & Wang Jianli. (2024). Research on Design Education Teaching Mode under AI Intelligent Assistance: Roles and Impacts of Artificial Intelligence. Art and Design, No, 226
[10] Zhao, Y. (2023). Exploring the application and influence of artificial intelligence aigc technology on logo design. Atlantis Highlights in Intelligent Systems, 451-459. https://doi. org/10.2991/978-94-6463-266-8_49
[11] Jing, Y., Wang, H., Chen, X., & Wang, C. (2024). What factors will affect the effectiveness of using chatgpt to solve programming problems? a quasi-experimental study. Humanities and Social Sciences Communications, 11(1). https://doi. org/10.1057/s41599-024-02751-w
[12] Williams, R. T. (2024). The ethical implications of using generative chatbots in higher education. Frontiers in Education, 8. https://doi.org/10.3389/feduc.2023.1331607
[13] Gmeiner, F., Yang, H., Yao, L., Holstein, K., & Martelaro, N. (2023). Exploring challenges and opportunities to support designers in learning to co-create with ai-based manufacturing design tools. Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems. https://doi. org/10.1145/3544548.3580999
[14] Ilie, S., Maragkou, K., Brown, A., & Kozman, E. (2022). No budge for any nudge: information provision and higher education application outcomes. Education Sciences, 12(10), 701. https://doi.org/10.3390/educsci12100701
Downloads
Published
Issue
Section
License
Copyright (c) 2024 by the authors.
This work is licensed under a Creative Commons Attribution 4.0 International License.
