Enhancing Creative Agency in Human-AI Collaboration: Story Models and Critical Prompting in Design Fiction
DOI:
https://doi.org/10.23726/cij.2026.1851Keywords:
Generative AI, Creative agency, Design fiction, Human-AI collaboration, Prompting frameworks, Educational innovationAbstract
Integrating Generative AI into educational settings raises critical questions about creative agency. While AI tools can enhance ideation efficiency, concerns persist about whether they diminish students’ sense of authorship and critical judgment. This study examines how the combination of story models with prompting frameworks enhances creative agency in human-AI collaboration through a controlled comparison of basic versus critical prompting approaches. Twenty-five students completed two design fiction activities: one using basic narrative scaffolding, another adding strategic critical prompting organized around Task, Format, Voice, and Context dimensions. Analysis revealed differences across four dimensions—engagement depth, creative insight generation, empathy development, and output quality. Findings illuminate a three-stage agency progression: from basic initiation capabilities through strategic direction to metacognitive awareness of how choices shape AI behavior. A critical “credibility gap” emerged where participants distinguished AI-generated professional polish from authentic believability, suggesting technical sophistication does not guarantee conceptual validity. Results demonstrate that structured prompting combined with story-based knowledge scaffolding can preserve human agency while leveraging AI capabilities, challenging both technophobic and uncritical approaches to AI integration in creative education.
References
Amabile, T. M. (1982). Social psychology of creativity: A consensual assessment technique. Journal of Personality and Social Psychology, 43(5), 997–1013.
Antony, V., & Huang, C. (2023). ID.8: Co-Creating Visual Stories with Generative AI. ArXiv, abs/2309.14228.
Bell, R., & Bell, H. (2023). Entrepreneurship education in the era of generative artificial intelligence. Entrepreneurship Education, 6(3), 229–244.
Bleecker, J. (2009). Design Fiction: A short essay on design, science, fact and fiction. Near Future Laboratory.
Bowen, J. A., & Watson, C. E. (2024). Teaching with AI: A practical guide to a new era of human learning. Johns Hopkins University Press.
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101.
Bruner, J. (1985). Narrative and paradigmatic modes of thought. In E. Eisner (Ed.), Learning and teaching the ways of knowing (84th Yearbook of the National Society for the Study of Education, Part II, pp. 97–115). University of Chicago Press.
Carroll, J. M. (2000). Making use: Scenario-based design of human-computer interactions. MIT Press.
Cotroneo, P., & Hutson, J. (2023). Generative AI tools in art education: Exploring prompt engineering and iterative processes for enhanced creativity. Metaverse, 4(1),14. https://doi.org/10.54517/m.v4i1.2164
Dell'Acqua, F., McFowland, E., Mollick, E., Lifshitz-Assaf, H., Kellogg, K. C., Rajendran, S., Krayer, L., Candelon, F., & Lakhani, K. R. (2023). Navigating the jagged technological frontier: Field experimental evidence of the effects of AI on knowledge worker productivity and quality (Harvard Business School Working Paper No. 24-013).
Doshi, A. R., & Hauser, O. P. (2024). Generative AI enhances individual creativity but reduces the collective diversity of novel content. Science Advances, 10(28), eadn5290.
Dunne, A., & Raby, F. (2013). Speculative everything: Design, fiction, and social dreaming. MIT Press.
Epstein, Z., Hertzmann, A., Herman, L., Mahari, R., Frank, M., Groh, M., Schroeder, H., Smith, A., Akten, M., Fjeld, J., Farid, H., Leach, N., Pentland, A., & Russakovsky, O. (2023). Art and the science of generative AI. Science, 380, 1110–1111.
Eshraghian, J. (2020). Human ownership of artificial creativity. Nature Machine Intelligence, 2, 157–160.
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.
Fisher, W. R. (1984). Narration as a human communication paradigm: The case of public moral argument. Communication Monographs, 51(1), 1–22.
Floridi, L. (2025). AI as Agency without Intelligence: On Artificial Intelligence as a New Form of Artificial Agency and the Multiple Realisability of Agency Thesis: L. Floridi. Philosophy & Technology, 38(1), 30.
Introne, J., Gokce Yildirim, I., Iandoli, L., DeCook, J., & Elzeini, S. (2018). How people weave online information into pseudoknowledge. Social media+ society, 4(3), 2056305118785639.
Kim, J., & Maher, M. (2023). The effect of AI-based inspiration on human design ideation. International Journal of Design Creativity and Innovation, 11, 81–98. https://doi.org/10.1080/21650349.2023.2167124
Kouprie, M., & Sleeswijk Visser, F. (2009). A framework for empathy in design: stepping into and out of the user's life. Journal of Engineering Design, 20(5), 437–448.
Lipman, D. (1995). Storytelling games: Creative activities for language, communication, and composition across the curriculum. Oryx Press.
Lupton, E. (2017). Design is storytelling. Museum of Cooper-Hewitt.
Malpass, M. (2017). Critical design in context: History, theory, and practices. Bloomsbury Academic.
Patel, N.S. and Iandoli, L. (2026). Who is prompting whom? Designing a Voice-Only Anthropomorphic Sparring Partner for Sustainable Dialogic Reasoning. In: Dunstan, B.J., Koh, J.T.K.V., Samani, H. (eds) Cultural Robotics: Diversified Sustainable Practices. CR 2025. Lecture Notes in Computer Science, vol 16404. Springer, Cham. https://doi.org/10.1007/978-3-032-15501-6_13
Pellas, N. (2023). The effects of generative AI platforms on undergraduates’ narrative intelligence and writing self-efficacy. Education Sciences.
Pennington, N., & Hastie, R. (1992). Explaining the evidence: Tests of the Story Model for juror decision making. Journal of Personality and Social Psychology, 62(2), 189.
Reed, J., & Dodson, T. (2023). Generative AI Backstories for Simulation Preparation.. Nurse educator, 49(4), 184-188. https://doi.org/10.1097/NNE.0000000000001
Schank, R. C., & Berman, T. R. (2002). The pervasive role of stories in knowledge and action. In M. C. Green, J. J. Strange, & T. C. Brock (Eds.), Narrative impact: Social and Cognitive Foundations (pp. 287–313). Lawrence Erlbaum Associates.
The Wall Street Journal. (2026, January 22). CEOs and workers see AI very differently.
Tholander, J., & Jonsson, M. (2023). Design ideation with AI - sketching, thinking and talking with generative machine learning models. In Proceedings of the 2023 ACM Designing Interactive Systems Conference. https://doi.org/10.1145/3563657.3596014
Yilmaz, R., & Goktas, Y. (2017). Using augmented reality technology in storytelling activities: Examining elementary students’ narrative skill and creativity. Virtual Reality, 21, 75–89.
Vygotsky, L. S., & Cole, M. (1978). Mind in society: Development of higher psychological processes. Harvard University Press.
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