PointAloud：一种面向AI支持的指针中心思考- aloud计算的交互套件
PointAloud: An Interaction Suite for AI-Supported Pointer-Centric Think-Aloud Computing
AI总结：
PointAloud 通过指针中心的 AI 驱动交互，提升用户在实时任务中的口头化表达、低干扰反馈和上下文丰富的工作流程记录，促进人机协同创造。
摘要：
思考- aloud计算是一种在软件任务中捕捉用户口头化想法的方法，允许实时获取用户 evolving intentions、struggles 和 decision-making processes 的丰富上下文洞察。然而，现有方法面临实际挑战：用户往往缺乏对系统捕获内容的意识，未能有效被鼓励说话，且系统反馈可能被错过或中断。此外，思考 aloud 应该因获得的上下文 AI 协助而对用户有意义。为了更好地支持和利用思考- aloud 计算，我们引入 PointAloud，一种新的 AI 驱动的指针中心交互套件，用于即时口头化鼓励、低干扰系统反馈以及上下文丰富的流程文档记录，以及主动 AI 协助。我们的 12 名参与者用户研究提供了关于指针中心思考- aloud 计算对流程文档记录和人机协同创造价值的见解。我们最后讨论了我们发现的更广泛影响以及指针中心和 AI 支持的思考- aloud 计算工作流的设计考虑。
英文摘要：
Think-Aloud Computing, a method for capturing users' verbalized thoughts during software tasks, allows eliciting rich contextual insights into evolving intentions, struggles, and decision-making processes of users in real-time. However, existing approaches face practical challenges: users often lack awareness of what is captured by the system, are not effectively encouraged to speak, and miss or are interrupted by system feedback. Additionally, thinking aloud should feel worthwhile for users due to the gained contextual AI assistance. To better support and harness Think-Aloud Computing, we introduce PointAloud, a suite of novel AI-driven pointer-centric interactions for in-the-moment verbalization encouragement, low-distraction system feedback, and contextually rich work process documentation alongside proactive AI assistance. Our user study with 12 participants provides insights into the value of pointer-centric think-aloud computing for work process documentation and human-AI co-creation. We conclude by discussing the broader implications of our findings and design considerations for pointer-centric and AI-supported Think-Aloud Computing workflows.
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。
