学习前的委托：生成式AI在学生专业沟通中的定位

中文摘要 AI 辅助

我们对12名学生使用生成式AI进行学术沟通的情况开展了访谈研究。学生在需要体现专业性压力最大的场景中，会将专业信息委托给AI处理，比如给教师和管理人员的邮件。AI参与的程度从修改作者自身文本到完全构思并撰写信息不等，学生对AI生成文本的核查依据是两个标准：它看起来是否像AI生成的，以及它是否符合自身的表达风格。基于这些发现，我们以观察到的最高AI参与程度，构建了学生给教师写邮件的AI中介写作过程模型，并将其与基于参与者描述和经典写作过程模型构建的无辅助写作模型进行比较。二者出现了三个差异：构建写作技能的学习循环被移除，信息不再为特定接收者撰写，成功交流带来的成就感转向使用系统而非作者自身能力。从这些差异中我们得出两个风险：个人能力无法形成，以及沟通中的真实性和信任成为额外负担。设计可应对这两种风险，但仅靠设计可能不够，因此这些风险也需要研究和政策层面的关注。

英文摘要

We conducted an interview study with twelve students on their use of generative AI in academic communication. Students delegated professional messages to AI most where the pressure to sound professional is highest: email to instructors and administrators. AI involvement ranged from correcting the writer's own text to working out and writing the message outright, and students checked AI-written text against two criteria: whether it looks like AI and whether it sounds like them. Building on these findings, we model the AI-mediated process of writing a student--instructor email at the highest level of involvement we observed, and compare it with an unaided model of writing the same messages, built from participants' accounts and a classic model of the writing process. Three differences emerge: the learning loop that builds writing skill is removed, the message is no longer written for its specific recipient, and the confidence a successful exchange returns goes to using the system rather than to the writer's own ability. From these differences we derive two risks, that individual capacities never form and that authenticity and trust in communication become work. Design can respond to both but is unlikely to be enough, so the risks also need research and policy attention.

发表机构

• University of Washington（华盛顿大学）

机构由 AI 辅助整理，请以论文原文为准。