Understanding inspiration: Insights into how designers discover inspirational stimuli using an AI-enabled platform

被引:16
作者
Kwon, Elisa [1 ]
Rao, Vivek [1 ]
Goucher-Lambert, Kosa [1 ]
机构
[1] Univ Calif Berkeley, Dept Mech Engn, Berkeley, CA 94720 USA
基金
美国国家科学基金会;
关键词
design tools; design behavior; creativity; protocol analysis; design inspiration; REPRESENTATION; GENERATION; DISTANCE; IDEATION;
D O I
10.1016/j.destud.2023.101202
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Throughout the design process, designers encounter diverse stimuli that influence their work. This influence is particularly notable during idea generation processes that are augmented by novel design support tools that assist in inspiration discovery. However, fundamental questions remain regarding why and how interactions afforded by these tools impact design behaviors. This work explores how designers search for inspirational stimuli using an AI-enabled multi-modal search platform, which supports queries by text and non-text-based inputs. Student and professional designers completed a think-aloud design exploration task using this platform to search for stimuli to inspire idea generation. We identify expertise and search modality as factors influencing design exploration, including the frequency and framing of searches, and the evaluation and utility of search results. & COPY; 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
引用
收藏
页数:36
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