Programming instructors have diverse philosophies about integrating generative AI into their classes. Some encourage students to use AI, while others restrict or forbid it. Regardless of their approach, all instructors benefit from understanding how their students actually use AI while writing code. Such insight helps instructors assess whether AI use aligns with their pedagogical goals, enables timely intervention when they find unproductive usage patterns, and establishes effective policies for AI use. However, our survey with programming instructors found that many instructors lack visibility into how students use AI in their code-writing processes. To address this challenge, we introduce Editrail, an interactive system that enables instructors to track students' AI usage, create personalized assessments, and provide timely interventions, all within the workflow of monitoring coding histories. We found that Editrail enables instructors to detect AI use that conflicts with pedagogical goals accurately and to determine when and which students require intervention.

翻译：编程教师对于将生成式AI融入课堂持有不同的理念。有些教师鼓励学生使用AI，而另一些则限制或禁止其使用。无论采取何种方式，了解学生在编写代码过程中实际如何使用AI对所有教师都大有裨益。这种洞察有助于教师评估AI使用是否符合其教学目标，在发现低效使用模式时能够及时干预，并制定有效的AI使用政策。然而，我们对编程教师的调查发现，许多教师缺乏对学生在其代码编写过程中如何使用AI的可见性。为应对这一挑战，我们提出了Editrail——一个交互式系统，使教师能够在监控编码历史的工作流程中追踪学生的AI使用情况、创建个性化评估并提供及时干预。我们发现，Editrail能够帮助教师准确检测与教学目标相冲突的AI使用行为，并确定何时对哪些学生进行干预。