用目标、提示和策略引导LLM，提升头脑风暴创意质量
A Framework for Collaborating a Large Language Model Tool in Brainstorming for Triggering Creative Thoughts
- 设计GPS框架，用目标、提示和策略系统引导LLM参与创意生成
- 在案例中提升创意想法的创造性与实用性，经TTCT测试验证
- 适合设计师或创新团队在实际项目中使用LLM激发新思路
创造力不仅包括从零生成新想法，还涉及重新定义现有概念和整合先前洞察。在众多促进创造性思维的技术中，头脑风暴被广泛应用。随着大语言模型（LLMs）的发展，如ChatGPT等工具通过提示词显著影响多个领域，完成复杂任务。当前研究多聚焦于生成准确响应，却较少探索提示工程如何增强创造力，尤其在头脑风暴场景中的应用。为此，本研究提出名为GPS的框架，通过目标（Goals）、提示（Prompts）和策略（Strategies）指导设计师系统性地与LLM协作，以提升头脑风暴中生成想法的创造力。此外，我们适配了托兰斯创造性思维测验（Torrance Tests of Creative Thinking, TTCT）来评估AI生成想法的创造性。通过一个设计实例和案例研究验证，该框架能有效激发创意，并实现与LLM工具的无缝集成。结果表明，该框架有助于提升头脑风暴中生成想法的创造性和实用性。
原文摘要 · Abstract (English)
Creativity involves not only generating new ideas from scratch but also redefining existing concepts and synthesizing previous insights. Among various techniques developed to foster creative thinking, brainstorming is widely used. With recent advancements in Large Language Models (LLMs), tools like ChatGPT have significantly impacted various fields by using prompts to facilitate complex tasks. While current research primarily focuses on generating accurate responses, there is a need to explore how prompt engineering can enhance creativity, particularly in brainstorming. Therefore, this study addresses this gap by proposing a framework called GPS, which employs goals, prompts, and strategies to guide designers to systematically work with an LLM tool for improving the creativity of ideas generated during brainstorming. Additionally, we adapted the Torrance Tests of Creative Thinking (TTCT) for measuring the creativity of the ideas generated by AI. Our framework, tested through a design example and a case study, demonstrates its effectiveness in stimulating creativity and its seamless LLM tool integration into design practices. The results indicate that our framework can benefit brainstorming sessions with LLM tools, enhancing both the creativity and usefulness of generated ideas.
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