协作大型语言模型工具进行头脑风暴以激发创造性思维的框架
A Framework for Collaborating a Large Language Model Tool in Brainstorming for Triggering Creative Thoughts
AI总结：
本研究提出GPS框架，通过目标、提示和策略指导设计师与LLM工具协作，提升头脑风暴中生成想法的创造力，并改编TTCT测验验证其有效性。
摘要：
创造力不仅涉及从零开始产生新想法，还包括重新定义现有概念和综合先前的见解。在为培养创造性思维而开发的各种技术中，头脑风暴被广泛使用。随着大型语言模型（LLMs）的最新进展，像ChatGPT这样的工具通过使用提示来促进复杂任务，已经显著影响了各个领域。虽然当前的研究主要集中在生成准确的响应上，但有必要探索提示工程如何增强创造力，特别是在头脑风暴中。因此，本研究通过提出一个名为GPS的框架来解决这一空白，该框架采用目标、提示和策略来指导设计师系统地与LLM工具合作，以提高头脑风暴期间产生想法的创造力。此外，我们改编了Torrance创造性思维测验（TTCT）来测量AI产生想法的创造力。我们的框架通过一个设计示例和一个案例研究进行了测试，证明了其在激发创造力方面的有效性及其将LLM工具无缝集成到设计实践中的能力。结果表明，我们的框架可以使带有LLM工具的头脑风暴会议受益，提高生成想法的创造力和实用性。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
