计划以神秘的方式起作用：评估电子表格代理的计划模式
Plans Work in Mysterious Ways: Evaluating a Plan Mode for Spreadsheet Agents
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中文总结 AI 辅助
研究电子表格代理计划模式，构建原型并通过用户研究与非计划基线评估，发现虽任务结果相似，但计划模式可减少优化，提升用户对工具在创造力支持和人机协作方面的感知，探讨了对计划模式设计及人机规划的影响。
中文摘要 AI 辅助
计划模式已成为智能编程工具的标准功能，能让用户在任务执行前与代理合作制定计划，从而获得透明度和控制权。但尚不清楚此功能的优势能否转化到电子表格等终端用户编程环境中。因为电子表格程序员倾向于迭代工作，不太在意技术正确性，前期规划可能不易融入其工作流程。本文构建了电子表格编程计划模式的原型，并通过一项有24名参与者的主体内用户研究，将其与非计划基线进行评估。结果发现，尽管两种工具的任务结果相似，但使用计划模式能减少优化，并在创造力支持和人机协作方面让用户对工具的感知更好。我们讨论了这些结果对计划模式未来设计以及人机规划在终端用户编程中更广泛作用的影响。
英文摘要
Plan Modes have become standard features in agentic programming tools, allowing users to gain transparency and control by working with the agent to develop a plan before task execution. However, it remains unclear whether the benefits of this feature translate to end-user programming environments such as spreadsheets. Since spreadsheet programmers tend to work iteratively and care less about technical correctness, upfront planning may not fit into their workflows as easily. In this paper, we build a prototype of a Plan Mode for spreadsheet programming and evaluate it against a non-planning baseline through a within-subjects user study (N=24). We found that despite similar task outcomes with both tools, using Plan Mode led to a reduction in refinement and a better perception of the tool across dimensions of creativity support and human-machine collaboration. We discuss the implications of these results for the future design of Plan Modes, and for the broader role of human-AI planning in end-user programming.
发表机构
- Microsoft（微软）
机构由 AI 辅助整理，请以论文原文为准。
