BibTex format
@article{Wang:2025:10.1017/S0890060425100127,
author = {Wang, P and Khinvasara, Y and Creijghton, GJ and Scholing, T and Wang, Y and Zhou, Z and Childs, PRN and Yin, Y},
doi = {10.1017/S0890060425100127},
journal = {Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM},
title = {Enhancing designer creativity through human-AI co-ideation: a co-creation framework for design ideation with custom GPT},
url = {http://dx.doi.org/10.1017/S0890060425100127},
volume = {39},
year = {2025}
}
RIS format (EndNote, RefMan)
TY - JOUR
AB - The emergence of large language models (LLMs) provides an opportunity for AI to operate as a co-ideation partner during the creative processes. However, designers currently lack a comprehensive methodology for engaging in co-ideation with LLMs, and there is a limited framework that describes the process of co-ideation between a designer and ChatGPT. This research thus aimed to explore how LLMs can act as codesigners and influence creative ideation processes of industrial designers and whether the ideation performance of a designer could be improved by employing the proposed framework for co-ideation with custom GPT. A survey was first conducted to detect how LLMs influenced the creative ideation processes of industrial designers and to understand the problems that designers face when using ChatGPT to ideate. Then, a framework which based on mapping content to guide the co-ideation between humans and custom GPT (named as Co-Ideator) was promoted. Finally, a design case study followed by a survey and an interview was conducted to evaluate the ideation performance of the custom GPT and framework compared with traditional ideation methods. Also, the effect of custom GPT on co-ideation was compared with a non-artificial intelligence (AI)-used condition. The findings indicated that if users employed co-ideation with custom GPT, the novelty and quality of ideation outperformed by using traditional ideation.
AU - Wang,P
AU - Khinvasara,Y
AU - Creijghton,GJ
AU - Scholing,T
AU - Wang,Y
AU - Zhou,Z
AU - Childs,PRN
AU - Yin,Y
DO - 10.1017/S0890060425100127
PY - 2025///
SN - 0890-0604
TI - Enhancing designer creativity through human-AI co-ideation: a co-creation framework for design ideation with custom GPT
T2 - Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM
UR - http://dx.doi.org/10.1017/S0890060425100127
UR - https://www.cambridge.org/core/journals/ai-edam/article/enhancing-designer-creativity-through-humanai-coideation-a-cocreation-framework-for-design-ideation-with-custom-gpt/BCC2CBE43EECE6F0D937BBC0D2F44868
VL - 39
ER -