Assessment of the Impact of Artificial Intelligence on Creative Storytelling for Enhancing the Ideation Process at the Individual Level
DOI:
https://doi.org/10.4108/eetct.10417Keywords:
Artificial Intelligence, Ideation, Creativity, Creative storytellingAbstract
The emergence of Artificial Intelligence dramatically changes the creative process of generating new ideas, which is called "ideation." The objective of this research is to study its impact on the "ideation" phase at the individual level. Ten students from Polytechnic schools participated in two activities that measured the characteristics of divergent-creative thinking: "fluency," "flexibility," and "originality." The first activity was Guilford's Alternative Uses Test, and the second was a creative storytelling technique. The students were divided into two groups, and one of the groups collaborated with ChatGPT. From the data analysis, it was found that in Guilford's test, Artificial Intelligence significantly enhances "fluency" and "flexibility" and considerably improves "originality." However, in the production of a creative text, the research showed no enhancement of the above characteristics. A possible cause is identified in the different degree of experience in creative writing among the students who collaborated with ChatGPT, and consequently in the different way they provided prompts. In conclusion, Artificial Intelligence can prove to be a valuable collaborator in the "ideation" phase, but its effectiveness depends on users' experience in prompting techniques.
References
[1] Hasso Plattner Institute. An Introduction to Design Thinking Process Guide [Internet]. 2019 [cited 2025 Nov 5]. Available from: https://s3-eu-west-1.amazonaws.com/ih-materials/uploads/Introduction-to-design-thinking.pdf
[2] Knight J, Fitton D, Phillips C, Price D, Fitton D, Phillips C. Design Thinking for Innovation. Stress Testing Human Factors in Ideation Sessions. The Design Journal. 2019;22:10–12. https://doi.org/10.1080/14606925.2019.1594950
[3] Manias D, Mavrommati I. Creative Narration as a Design Technique. Information. 2022;13(6). https://doi.org/10.3390/info13060266
[4] Feuerriegel S, Hartmann J, Janiesch C, Zschech P. Generative AI. Business and Information Systems Engineering. 2024;66(1):111–126. https://doi.org/10.1007/s12599-023-00834-7
[5] Jovanovic M, Campbell M. Generative Artificial Intelligence: Trends and Prospects. Computer. 2022;55(10):107–112. https://doi.org/10.1109/MC.2022.3192720
[6] Eapen T, Finkenstadt DJ, Folk J, Venkataswamy L. How Generative AI Can Augment Human Creativity. SSRN Electronic Journal [Internet]. 2023 [cited 2025 Nov 5]. Available from: https://doi.org/10.2139/ssrn.4759930
[7] Haase J, Hanel PHP. Artificial muses: Generative artificial intelligence chatbots have risen to human-level creativity. Journal of Creativity. 2023;33(3):100066. https://doi.org/10.1016/j.yjoc.2023.100066
[8] Runco MA, Acar S. Divergent Thinking as an Indicator of Creative Potential. Creativity Research Journal. 2012;24(1):66–75. https://doi.org/10.1080/10400419.2012.652929
[9] Seddon GM. The measurement and properties of divergent thinking ability as a single compound entity. Journal of Educational Measurement. 1983;20(4):393–402. https://doi.org/10.1111/j.1745-3984.1983.tb00216.x
[10] Fletcher A, Benveniste M. A new method for training creativity: narrative as an alternative to divergent thinking. Ann N Y Acad Sci. 2022. https://doi.org/10.1111/nyas.14763
[11] Grosdos S. Δημιουργικότητα και Δημιουργική Γραφή στην Εκπαίδευση: από το παιδί γραμματέα στο παιδί δημιουργό κειμένων [Creativity and Creative Writing in Education: from the child as scribe to the child as creator of texts]. Στρατηγικές δημιουργικής γραφής. Θεσσαλονίκη: Εκδόσεις Πανεπιστημίου Μακεδονίας; 2014.
[12] Boden MA. The creative mind: myths and mechanisms. 2nd ed. London: Routledge; 2003.
[13] Heale R, Twycross A. Validity and reliability in quantitative studies. Evidence-Based Nursing [Internet]. [cited 2025 Nov 5]. Available from: https://doi.org/10.1136/eb-2015-102129
[14] Moskal BM, Leydens JA. Scoring Rubric Development: Validity and Reliability. Practical Assessment, Research, and Evaluation. 2000;7(1). https://doi.org/10.7275/q7rm-gg74
[15] McKnight PE, Najab J. Mann–Whitney U Test. In: The SAGE Encyclopedia of Research Design. Thousand Oaks (CA): Sage; 2022. https://doi.org/10.4135/9781412961288.n228
[16] Milenović Ž. Application of Mann-Whitney U test in research of professional training of primary school teachers. Metodički Obzori (Methodological Horizons). 2011;6(1):73–79. https://doi.org/10.32728/mo.06.1.2011.06
[17] Guo K. Exploring an AI-supported approach to creative writing: Effects on secondary school students’ creativity. ResearchGate [Internet]. [cited 2025 Nov 5]. Available from: https://doi.org/10.13140/RG.2.2.24489.06247
[18] Vicente-Yagüe-Jara MI, López-Martínez O, Navarro- Navarro V, Cuéllar-Santiago F. Writing, creativity, and artificial intelligence. ChatGPT in the university context. Comunicar. 2023;31(77). https://doi.org/10.3916/c77-2023-04
[19] Chen B, Zhang Z, Langrené N, Zhu S. Unleashing the potential of prompt engineering in Large Language Models: a comprehensive review. arXiv preprint [Internet]. 2023 [cited 2025 Nov 5]. Available from: https://arxiv.org/abs/2310.14735v4
[20] Lo LS. The Art and Science of Prompt Engineering: A New Literacy in the Information Age. Internet Reference Services Quarterly. 2023;27(4):203–210. https://doi.org/10.1080/10875301.2023.2227621
[21] Lo LS. The CLEAR path: A framework for enhancing information literacy through prompt engineering. The Journal of Academic Librarianship. 2023;49(4):102720. https://doi.org/10.1016/j.acalib.2023.102720
[22] Velásquez-Henao JD, Franco-Cardona CJ, Cadavid-Higuita L. Prompt Engineering: a methodology for optimizing interactions with AI-Language Models in the field of engineering. DYNA. 2023;90(230). https://doi.org/10.15446/dyna.v90n230.111700
[23] Han Y, Qiu Z, Cheng J, LC R. When Teams Embrace AI: Human Collaboration Strategies in Generative Prompting in a Creative Design Task. Proceedings of the ACM CHI Conference on Human Factors in Computing Systems. 2024:1–14. https://doi.org/10.1145/3613904.3642133
[24] Robertson J, Ferreira C, Botha E, Oosthuizen K. Game changers: A generative AI prompt protocol to enhance human-AI knowledge co-construction. Business Horizons. 2024. https://doi.org/10.1016/j.bushor.2024.04.008
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