INFLUENCE OF GENERATIVE AI TOOLS ON THE CREATIVE THINKING PROCESS OF DESIGN STUDENTS IN KERALA

Sreya B; Harikrishnan D.

doi:10.29121/ShodhVichar.v2.i1.2026.94

Authors

Sreya B MA JMC Student, Department of Visual Media and Communication, Amrita Vishwa Vidyapeetham, Kochi Campus, Kerala, India Author
Dr. Harikrishnan D. Assistant Professor (Senior Grade) Department of Visual Media and Communication, Amrita Vishwa Vidyapeetham, Kochi Campus, India Author

DOI:

https://doi.org/10.29121/ShodhVichar.v2.i1.2026.94

Keywords:

Artificial Intelligence (GenAI), Design Education, Creative Thinking, AI-Supported Creativity, Design Students

Abstract

Through a mixed-methods research design, this study evaluates the impact of Generative Artificial Intelligence (GenAI) on the creative thinking processes of design students from Kerala. A structured questionnaire was administered to 184 design students aged 18 to 25 in Kerala, as well as semi-structured interviews and one focus group. The quantitative aspects of the results were evaluated using descriptive statistics while qualitative aspects were addressed using thematic analysis.

Results indicate that 92.9% of design students participating in this study have actively used GenAI tools in their design work, and that 78.4% primarily use GenAI in the ideation/concept development stages of the design process. While 86.6% agreed that GenAI improves the efficiency of the design workflow, there were 65.5% of respondents who expressed concern that GenAI tools will reduce their ability to think creatively and independent of computers.

This research fills an important gap in the area of research on AI-supported creativity, particularly as it relates to design education within South Asia, and offers key implications related to pedagogy, the curriculum in AI literacy, and the appropriate use of generative technologies in the creative learning environment.

References

Amabile, T. M. (1983). The Social Psychology of Creativity. Springer-Verlag.

Atiker, M., et al. (2025). Cognitive Load and Interface Design in AI-Mediated Creativity: A Comparative Study of Text-to-Image and Sketch-to-Image Workflows. Design Studies, 48(2), 112–134.

Bandura, A. (1977). Self-Efficacy: Toward a Unifying Theory of Behavioral Change. Psychological Review, 84(2), 191–215. https://doi.org/10.1037/0033-295X.84.2.191

Braun, V., and Clarke, V. (2006). Using Thematic Analysis in Psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa

Cherry, E., and Latulipe, C. (2014). Quantifying the Creativity Support of Digital Tools Through the Creativity Support Index. ACM Transactions on Computer-Human Interaction, 21(4), Article 21. https://doi.org/10.1145/2617588

Cross, N. (2011). Design Thinking: Understanding How Designers Think and Work. Berg Publishers.

Dwivedi, Y. K., et al. (2023). So What if ChatGPT Wrote It? Multidisciplinary Perspectives on Opportunities, Challenges and Implications of Generative Conversational AI for Research, Practice and Policy. International Journal of Information Management, 71, 102642. https://doi.org/10.1016/j.ijinfomgt.2023.102642

Facione, P. A. (1990). Critical Thinking: A Statement of Expert Consensus for Purposes of Educational Assessment and Instruction. American Philosophical Association.

Finke, R. A., Ward, T. B., and Smith, S. M. (1992). Creative Cognition: Theory, Research, and Applications. MIT Press.

Fleischmann, K. (2024). Student Attitudes Toward Generative AI in Graphic Design Education. Design Education Research, 11(1), 45–62.

Goodfellow, I., Bengio, Y., and Courville, A. (2014). Deep Learning. MIT Press.

Huh, M. B., Miri, M., and Tracy, T. (2025). Students' Perceptions of Generative AI Image Tools in Design Education: Insights From Architectural Education. Education Sciences, 15(9), 1160. https://doi.org/10.3390/educsci15091160

Hwang, Y., and Wu, Y. (2025). The Influence of Generative Artificial Intelligence on Creative Cognition of Design Students: A Chain Mediation Model of Self-Efficacy and Anxiety. Frontiers in Psychology, 15, 1455015. https://doi.org/10.3389/fpsyg.2024.1455015

Kasneci, E., et al. (2023). ChatGPT for Good? On Opportunities and Challenges of Large Language Models for Education. Learning and Individual Differences, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274

Lawson, B. (2006). How Designers Think: The Design Process Demystified (4th ed.). Architectural Press.

McCormack, J., et al. (2019). Is AI Creativity Possible? Arts, 8(1), 26. https://doi.org/10.3390/arts8010026

Medel-Vera, C., Britton, S., and Gates, W. F. (2025). An Exploration of the Role of Generative AI in Fostering Creativity in Architectural Learning Environments. Computers and Education: Artificial Intelligence, 9, 100501. https://doi.org/10.1016/j.caeai.2025.100501

Ouma, B. O., Mwangi, E. K., Okoth, A. A., and Njeri, A. W. (2025). Integrating Generative AI and ChatGPT in Design Education: Impacts on Critical Thinking Development. International Journal of Graphic Design, 3(1), 1–18. https://doi.org/10.11054/yy0jcw48

Papert, S. A. (1980). Mindstorms: Children, Computers, and Powerful Ideas. Basic Books.

Runco, M. A., and Acar, S. (2012). Divergent Thinking as an Indicator of Creative Potential. Creativity Research Journal, 24(1), 66–75. https://doi.org/10.1080/10400419.2012.652929

Runco, M. A., and Jaeger, G. J. (2012). The Standard Definition of Creativity. Creativity Research Journal, 24(1), 92–96. https://doi.org/10.1080/10400419.2012.650092

Shen, Y. (2025). The Impact of Generative AI on the Career Path Choices of Undergraduate Students. Proceedings of the International Academic Conference, 225–230.