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

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Bibliographic Details
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]
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Database: Psychology and Behavioral Sciences Collection
Description
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]
ISSN:10421629
DOI:10.1007/s11423-026-10600-7