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Interact."],"published-print":{"date-parts":[[2024,10,31]]},"abstract":"<jats:p>Conceptual design is an essential stage in the design process, and its ultimate success largely depends on designers\u2019 creativity. Both physical and digital prototypes are commonly adopted by designers to support ideation and creativity, providing intuitive perception and rapid iteration, respectively. In recent advancements, large-scale generation models are able to offer data-enabled creativity support by generating high-quality solutions comparable to human designers. This opens up an imaginary space for designers and brings new possibilities for design tools. In this study, we proposed a hybrid prototype method that synergistically combines physical models and generative artificial intelligence (AI) in the conceptual design stage. Correspondingly, we developed a hybrid prototype system to implement the proposed method. We conducted a comparative user study with 45 designers who completed a design task using the physical prototype method, standalone generative AI and the hybrid prototype method, respectively. Our results verified the effectiveness of the hybrid prototype method and investigated its mechanism in supporting creativity. Finally, we discussed the application value and optimisation space of the hybrid prototype method.<\/jats:p>","DOI":"10.1145\/3689433","type":"journal-article","created":{"date-parts":[[2024,9,2]],"date-time":"2024-09-02T15:29:20Z","timestamp":1725290960000},"page":"1-34","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":14,"title":["A Hybrid Prototype Method Combining Physical Models and Generative Artificial Intelligence to Support Creativity in Conceptual Design"],"prefix":"10.1145","volume":"31","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5376-9460","authenticated-orcid":false,"given":"Hongbo","family":"Zhang","sequence":"first","affiliation":[{"name":"Zhejiang University, Hangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0962-6459","authenticated-orcid":false,"given":"Pei","family":"Chen","sequence":"additional","affiliation":[{"name":"Zhejiang University, Hangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-1017-3931","authenticated-orcid":false,"given":"Xuelong","family":"Xie","sequence":"additional","affiliation":[{"name":"Zhejiang University, Hangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-7801-4279","authenticated-orcid":false,"given":"Zhaoqu","family":"Jiang","sequence":"additional","affiliation":[{"name":"Zhejiang University, Hangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4729-112X","authenticated-orcid":false,"given":"Zihong","family":"Zhou","sequence":"additional","affiliation":[{"name":"Zhejiang University, Hangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5561-0493","authenticated-orcid":false,"given":"Lingyun","family":"Sun","sequence":"additional","affiliation":[{"name":"Zhejiang University, Hangzhou, China"}]}],"member":"320","published-online":{"date-parts":[[2024,11,10]]},"reference":[{"key":"e_1_3_1_2_2","first-page":"1","volume-title":"Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems","author":"Alhadreti Obead","year":"2018","unstructured":"Obead Alhadreti and Pam Mayhew. 2018. 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