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Enhancing design ldeation: comparing AIGC-engaged and traditional brainstorming in educational contexts.

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Title: Enhancing design ldeation: comparing AIGC-engaged and traditional brainstorming in educational contexts.
Authors: Zou, Jiayi (AUTHOR), Zhao, Xinzhe (AUTHOR), Siu, Kin Wai Michael (AUTHOR), Zhao, Tianjiao (AUTHOR)
Source: Educational Technology Research & Development. Jun2026, Vol. 74 Issue 3, p1305-1345. 41p.
Subjects: Brainstorming, Artificial intelligence, Creative thinking, Design students, Design education
Abstract: Generating creative ideas is essential for designers, as creativity underpins all subsequent stages of the design process. This study investigates the impact of Artificial Intelligence Generated Content (AIGC) and traditional methods on design ideation in the context of design education. A controlled experiment was conducted with 21 undergraduate industrial design students of similar academic backgrounds, divided into an experimental group (AIGC-engaged brainstorming) and a control group (traditional brainstorming). Students' creative outputs were evaluated based on four criteria: novelty, feasibility, correlation, and utility. The study further examined how different design themes and students' questioning strategies influenced outcomes. Results show that, overall, AIGC-engaged brainstorming outperformed traditional methods in enhancing the novelty, feasibility, and correlation of learners' design ideas. However, variations in design themes affected AIGC's creative effectiveness, suggesting the need to balance the strengths of both AIGC and traditional approaches in educational settings. About utility, different interaction patterns between student groups and AIGC led to divergent results. Drawing on the Geneplore model of creative cognition, this study proposes an AIGC-engaged cognitive–prompting model of design ideation, offering practical guidance for effective collaboration to enhance creative performance in design education. [ABSTRACT FROM AUTHOR]
Copyright of Educational Technology Research & Development is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Enhancing design ldeation: comparing AIGC-engaged and traditional brainstorming in educational contexts.
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  Data: <searchLink fieldCode="AR" term="%22Zou%2C+Jiayi%22">Zou, Jiayi</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zhao%2C+Xinzhe%22">Zhao, Xinzhe</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Siu%2C+Kin+Wai+Michael%22">Siu, Kin Wai Michael</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zhao%2C+Tianjiao%22">Zhao, Tianjiao</searchLink> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Educational+Technology+Research+%26+Development%22">Educational Technology Research & Development</searchLink>. Jun2026, Vol. 74 Issue 3, p1305-1345. 41p.
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  Data: <searchLink fieldCode="DE" term="%22Brainstorming%22">Brainstorming</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Creative+thinking%22">Creative thinking</searchLink><br /><searchLink fieldCode="DE" term="%22Design+students%22">Design students</searchLink><br /><searchLink fieldCode="DE" term="%22Design+education%22">Design education</searchLink>
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  Data: Generating creative ideas is essential for designers, as creativity underpins all subsequent stages of the design process. This study investigates the impact of Artificial Intelligence Generated Content (AIGC) and traditional methods on design ideation in the context of design education. A controlled experiment was conducted with 21 undergraduate industrial design students of similar academic backgrounds, divided into an experimental group (AIGC-engaged brainstorming) and a control group (traditional brainstorming). Students' creative outputs were evaluated based on four criteria: novelty, feasibility, correlation, and utility. The study further examined how different design themes and students' questioning strategies influenced outcomes. Results show that, overall, AIGC-engaged brainstorming outperformed traditional methods in enhancing the novelty, feasibility, and correlation of learners' design ideas. However, variations in design themes affected AIGC's creative effectiveness, suggesting the need to balance the strengths of both AIGC and traditional approaches in educational settings. About utility, different interaction patterns between student groups and AIGC led to divergent results. Drawing on the Geneplore model of creative cognition, this study proposes an AIGC-engaged cognitive–prompting model of design ideation, offering practical guidance for effective collaboration to enhance creative performance in design education. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Educational Technology Research & Development is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1007/s11423-026-10600-7
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        Text: English
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      – SubjectFull: Creative thinking
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              Text: Jun2026
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              Y: 2026
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