Voces y Silencios. Revista Latinoamericana de Educación

Voces silec. rev. latinoam. educ. | eISSN 2215-8421

Reflecting on the Integration of Generative AI in Design Education: Lessons from the Field

No. 2 (2025-05-31)

Abstract

This testimonial article reflects on integrating Generative Artificial Intelligence (GenAI) into design education through three distinct experiences: personal explorations as a designer and educator, collaborative faculty learning in design technology, and integration within an undergraduate digital design course. This paper aims to contribute to discussions on how GenAI tools can support creative and educational practices. It employs a phenomenological approach to document these experiences, assessing the impact of AI on creativity, pedagogical practices, and learning outcomes. The theoretical framework draws on Constructivist Learning Theory, Kolb’s Experiential Learning Theory, Reflective Practice, Technological Pedagogical Content Knowledge (TPACK), and the concept of the democratization of creativity. These theoretical perspectives help to analyze how learners and educators construct knowledge through interaction with AI technologies, iterate through cycles of experimentation, and reflect on their practice. The analysis reveals the transformative role of GenAI in enhancing educational equity and creative engagement while also highlighting ethical considerations such as biases, intellectual property, and the risks of over-reliance. This paper invites educators to critically engage with AI, proposing strategies to integrate these technologies thoughtfully in design education.

Keywords: constructivist theory, design education, experiential learning, generative artificial intelligence, higher education

References

Ahmad, S. F., Han, H., Alam, M. M., Rehmat, M. K., Irshad, M., Arraño-Muñoz, M., & Ariza-Montes, A. (2023). Impact of artificial intelligence on human loss in decision making, laziness, and safety in education. Humanities and Social Sciences Communications, 10, 311. https://doi.org/10.1057/s41599-023-01787-8

Bartlett, K. A., & Camba, J. D. (2024). Generative artificial intelligence in product design education: Navigating concerns of originality and ethics. International Journal of Interactive Multimedia and Artificial Intelligence, 8(5), 55–64. https://doi.org/10.9781/ijimai.2024.02.006

Batista, J., Mesquita, A., & Carnaz, G. (2024). Generative AI and higher education: Trends, challenges, and future directions from a systematic literature review. Information, 15(11), Article 676. https://doi.org/10.3390/info15110676

Bozkurt, A., & Sharma, R. C. (2023). Challenging the status quo and exploring the new boundaries in the age of algorithms: Reimagining the role of generative AI in distance education and online learning. Asian Journal of Distance Education, 18(21), i-viii. https://doi.org/10.5281/zenodo.7755273

Chen, J. (2024). The role of AI: Speculative design in redefining artistic collaboration. Journal of Ecohumanism, 3(8), 2261–2272. https://doi.org/10.62754/joe.v3i8.4899

Chen, B., Zhu, X., & Díaz del Castillo H., F. (2023). Integrating generative AI in knowledge building. Computers and Education: Artificial Intelligence, 5, 100184. https://doi.org/10.1016/j.caeai.2023.100184

Chiu, T. K. F. (2024). Future research recommendations for transforming higher education with generative AI. Computers and Education: Artificial Intelligence, 6, Article 100197. https://doi.org/10.1016/j.caeai.2023.100197

Crawford, J., Allen, K. A., Pani, B., & Cowling, M. (2024). When artificial intelligence substitutes humans in higher education: the cost of loneliness, student success, and retention. Studies in Higher Education, 49(5), 883–897. https://doi.org/10.1080/03075079.2024.2326956

Creswell, J. W. (2014). Research design: Qualitative, quantitative, and mixed methods approaches (4th ed.). SAGE Publications.

Duggal, S. D. (2024, April 9). Democratized creativity: The evolution and impact of AI. Forbes. https://www.forbes.com/councils/forbestechcouncil/2024/04/09/democratized-creativity-theevolution-andimpact-of-ai/

Eapen, T. T., Finkenstadt, D. J., Folk, J., & Venkataswamy, L. (2023). How generative AI can augment human creativity: Use it to promote divergent thinking. Harvard Business Review, 101(4), 56–64. https://hbr.org/2023/07/how-generative-ai-can-augment-human-creativity

Escobar, A. (2017). Designs for the pluriverse: Radical interdependence, autonomy, and the making of worlds. Duke University Press. http://www.jstor.org/stable/j.ctv11smgs6

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, Article 01102. https://doi.org/10.1051/e3sconf/202342601102

Fleischmann, K. (2015). The democratisation of design and design learning: How do we educate the nextgeneration designer. International Journal of Arts & Sciences, 8(6), 101–108.

Fosnot, C. T. (2005). Constructivism: Theory, perspectives, and practice. Teachers College Press.

Ghimire, A., Prather, J., & Edwards, J. (2024). Generative AI in education: A study of educators’ awareness, sentiments, and influencing factors [preprint]. arXiv (arXiv:2403.15586). http://arxiv.org/abs/2403.15586

Gmeiner, F., Yang, H., Yao, L., Holstein, K., & Martelaro, N. (2023, April 19). Exploring challenges and opportunities to support designers in learning to co-create with AI-based manufacturing design tools. In A. Schmidt, K. Väänänen, T. Goyal, P. O. Kristensson, A.a Peters, S. Mueller, J. R. Williamson, M. L. Wilson (Eds.), CHI ‘23: Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (Article 226). https://doi.org/10.1145/3544548.3580999

Günaydin Donduran, C., Kasali, A., & Dogan, F. (2024). Artificial intelligence as a pedagogical tool for architectural design education. Journal of Design Studio, 6(2), 219–229. https://doi.org/10.46474/jds.1533480

Holstein, K., & Aleven, V. (2022). Designing for human–AI complementarity in K-12 education. AI Magazine, 43(2), 239–248. https://doi.org/10.1002/aaai.12058

Hughes, R. T., Zhu, L., & 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

Jin, Y., Yan, L., Echeverria, V., Gašević, D., & Martinez-Maldonado, R. (2024). Generative AI in higher education: A global perspective of institutional adoption policies and guidelines. Computers and Education: Artificial Intelligence, 8, Article 100348. https://doi.org/10.1016/j.caeai.2024.100348

Kolb, D. A. (1984). Experiential learning: Experience as the source of learning and development. Prentice Hall.

Kumar, S., Gunn, A., Rose, R., Pollard, R., Johnson, M., & Ritzhaupt, A. D. (2024). The role of instructional designers in the integration of generative artificial intelligence in online and blended learning in higher education. Online Learning Journal, 28(3), 207–231. https://doi.org/10.24059/olj.v28i3.4501

Li, Z. (2024). Generative AI in higher education academic assignments: Policy implications from a systematic review of student and teacher perceptions [master’s thesis, Massachusetts Institute of Technology]. MIT DSpace. https://hdl.handle.net/1721.1/155977

Lively, J., Hutson, J., & Melick, E. (2023). Integrating AI-generative tools in web design education: Enhancing student aesthetic and creative copy capabilities using image and text-based AI generators. DS Journal of Artificial Intelligence and Robotics (DS-AIR), 1(1), 23–33. https://doi.org/10.59232/AIR-V1I1P103

Lubart, T. (2005). How can computers be partners in the creative process: Classification and commentary on the special issue. International Journal of Human-Computer Studies, 63(4-5), 365–369. https://www.sciencedirect.com/science/article/abs/pii/S1071581905000418

Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education. Pearson.

Meron, Y., & Tekmen Araci, Y. (2023). Artificial intelligence in design education: Evaluating ChatGPT as a virtual colleague for post-graduate course development. Design Science, 9, Article e30. https://doi.org/10.1017/dsj.2023.28

Mishra, P., & Koehler, M. J. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers College Record, 108(6), 1017–1054. https://doi.org/10.1111/j.1467-9620.2006.00684.x

Mollick, E. R., & Mollick, L. (2024). Instructors as innovators: A future-focused approach to new AI learning opportunities, with prompts. The Wharton School Research Paper. http://dx.doi.org/10.2139/ssrn.4802463

Mulyani, H., Istiaq, M. A., Shauki, E. R., Kurniati, F., & Arlinda, H. (2025). Transforming education: Exploring the influence of generative AI on teaching performance. Cogent Education, 12(1), Article 2448066. https://doi.org/10.1080/2331186X.2024.2448066

Piaget, J. (1970). Science of education and the psychology of the child. Orion Press.

Saúde, S., Barros, J. P., & Almeida, I. (2024). Impacts of generative artificial intelligence in higher education: Research trends and students’ perceptions. Social Sciences, 13(8). https://doi.org/10.3390/socsci13080410

Schön, D. A. (1983). The reflective practitioner: How professionals think in action. Basic Books.

Song, B., Zhu, Q., & Luo, J. (2024). Human-AI collaboration by design. Proceedings of the Design Society, 4, 2247–2256. https://doi.org/10.1017/pds.2024.227

Sullivan, M., Kelly, A. & McLaughlan, P. (2023). ChatGPT in higher education: Considerations for academic integrity and student learning. Journal of Applied Learning & Teaching, 6(1), 31–40. https://doi.org/10.37074/jalt.2023.6.1.17

Tang, L., & Su, Y.-S. (2024). Ethical implications and principles of using artificial intelligence models in the classroom: A systematic literature review. International Journal of Interactive Multimedia and Artificial Intelligence, 8(5), 25–36. https://doi.org/10.9781/ijimai.2024.02.010

Tanksley, T. C. (2024). “We’re changing the system with this one”: Black students using critical race algorithmic literacies to subvert and survive AI-mediated racism in school. English Teaching: Practice & Critique, 23(1), 36–56. https://doi.org/10.1108/ETPC-08-2023-0102

Tellez, F. A., & Parrish, L. A. (in press). AI as a tool for beginning design students: Reflections from a case study on generative AI in an introductory design course. In National Conference of Beginning Design Education (NCBDS) 2025. North Carolina State University.

UNESCO. (2024). Generation AI: Navigating the opportunities and risks of artificial intelligence in education. https://www.unesco.org/en/articles/generation-ai-navigating-opportunities-and-risks-artificialintelligence-education

Van Brummelen, J., & Lin, P. (2020). Engaging teachers to co-design integrated AI curriculum for K-12 classrooms [preprint]. arXiv (arXiv:2009.11100). http://arxiv.org/abs/2009.11100

Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes (M. Cole, V. JolmSteiner, S. Scribner, & E. Souberman, Eds.). Harvard University Press. https://doi.org/10.2307/j.ctvjf9vz4

Wood, D., & Moss, S. H. (2024). Evaluating the impact of students’ generative AI use in educational contexts. Journal of Research in Innovative Teaching & Learning, 17(2), 152–167. https://doi.org/10.1108/JRIT06-2024-0151

Zaim, M., Arsyad, S., Waluyo, B., Ardi, H., Al Hafizh, M., Zakiyah, M., Syafitri, W., Nusi, A., & Hardiah, M. (2024). AI-powered EFL pedagogy: Integrating generative AI into university teaching preparation through UTAUT and activity theory. Computers and Education: Artificial Intelligence, 7. https://doi.org/10.1016/j.caeai.2024.100335