用生成式AI做3D建模时，用户直接动手试提示词，不再看教程。
"I Just Need GPT to Refine My Prompts": Rethinking Onboarding and Help-Seeking with Generative 3D Modeling Tools
- 用户以提示词为入口，跳过教程直接上手，把学习变成即时操作。
- 专业人士靠经验优化迭代，常舍弃不达标模型；普通人接受‘够用就行’。
- 部分用户用外部大模型生成提示词，形成AI辅助AI的新协作模式。
学习功能丰富的软件始终是难题，而生成式AI通过自然语言提示取代复杂操作，有望降低门槛。我们通过对26名参与者（14名普通用户，12名专业人士）的观察研究发现，用户普遍跳过教程和手册，依赖试错。在生成式AI背景下，提示框成为学习入口，将入门过程压缩为即时行动；部分普通用户转向外部大模型获取提示词。专业人士利用3D建模经验优化迭代结果，并对输出进行严格评估，常舍弃未达标准的模型；而普通用户则接受“够用即可”。本研究揭示了生成式AI如何重塑求助行为，提出新的入门方式、递归的AI辅助支持机制，以及输出解读中专家角色的变化。
原文摘要 · Abstract (English)
Learning to use feature-rich software is a persistent challenge, but generative AI tools promise to lower this barrier by replacing complex navigation with natural language prompts. We investigated how people approach prompt-based tools for 3D modeling in an observational study with 26 participants (14 casuals, 12 professionals). Consistent with earlier work, participants skipped tutorials and manuals, relying on trial and error. What differed in the generative AI context was how and why they sought support: the prompt box became the entry point for learning, collapsing onboarding into immediate action, while some casual users turned to external LLMs for prompts. Professionals used 3D expertise to refine iterations and critically evaluated outputs, often discarding models that did not meet their standards, whereas casual users settled for "good enough." We contribute empirical insights into how generative AI reshapes help-seeking, highlighting new practices of onboarding, recursive AI-for-AI support, and shifting expertise in interpreting outputs.
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