Our study examines how generative AI (GenAI) influences performance, creative self-efficacy, and cognitive load in architectural conceptual design tasks. Thirty-six student participants from Architectural Engineering and other disciplines completed a two-phase architectural design task, first independently and then with external tools (GenAI-assisted condition and control condition using an online repository of existing architectural projects). Design outcomes were evaluated by expert raters, while self-efficacy and cognitive load were self-reported after each phase. Difference-in-differences analyses revealed no overall performance advantage of GenAI across participants; however, subgroup analyses showed that GenAI significantly improved design performance for novice designers. In contrast, general creative self-efficacy declined for students using GenAI. Cognitive load did not differ significantly between conditions, though prompt usage patterns showed that iterative idea generation and visual feedback prompts were linked to greater reductions in cognitive load. These findings suggest that GenAI effectiveness depends on users' prior expertise and interaction strategies through prompting.

翻译：本研究探讨了生成式人工智能（GenAI）如何影响建筑概念设计任务中的绩效、创意自我效能和认知负荷。来自建筑工程及其他学科的三十六名学生参与者完成了一项两阶段建筑设计任务，首先独立进行，随后借助外部工具（GenAI辅助条件与使用现有建筑项目在线资源库的控制条件）完成。设计成果由专家评审评估，而自我效能和认知负荷则在每阶段结束后由参与者自评。双重差分分析显示，GenAI在所有参与者中并未带来整体绩效优势；然而，亚组分析表明，GenAI显著提升了新手设计师的设计绩效。相比之下，使用GenAI的学生普遍创意自我效能有所下降。不同条件间的认知负荷未呈现显著差异，但提示词使用模式显示，迭代式创意生成和视觉反馈提示与认知负荷的更大程度降低相关。这些发现表明，GenAI的有效性取决于用户先前的专业经验及通过提示词实现的交互策略。