We propose and carry-out a novel method of formative assessment called Assessment via Teaching (AVT), in which learners demonstrate their understanding of CS1 topics by tutoring more novice students. AVT has powerful benefits over traditional forms of assessment: it is centered around service to others and is highly rewarding for the learners who teach. Moreover, teaching greatly improves the learners' own understanding of the material and has a huge positive impact on novices, who receive free 1:1 tutoring. Lastly, this form of assessment is naturally difficult to cheat -- a critical property for assessments in the era of large-language models. We use AVT in a randomised control trial with learners in a CS1 course at an R1 university. The learners provide tutoring sessions to more novice students taking a lagged online version of the same course. We show that learners who do an AVT session before the course exam performed 20 to 30 percentage points better than the class average on several questions. Moreover, compared to students who did a practice exam, the AVT learners enjoyed their experience more and were twice as likely to study for their teaching session. We believe AVT is a scalable and uplifting method for formative assessment that could one day replace traditional exams.

翻译：我们提出并实施了一种名为“通过教学评估”（AVT）的形成性评估新方法，即学习者通过辅导更初学的学生来展示他们对CS1主题的理解。与传统评估形式相比，AVT具有显著优势：它以服务他人为核心，且对进行教学的学习者而言具有高度回报性。此外，教学极大提升了学习者自身对材料的理解，并对新手产生巨大积极影响——后者可获得免费的1:1辅导。最后，这种评估形式天然难以作弊——这是大语言模型时代评估的关键属性。我们在某R1大学CS1课程的学习者中开展了随机对照试验，由学习者对同一课程延后在线版本中更初学的学生进行辅导。结果表明，在课程考试前参与AVT的学习者在若干问题上的表现比班级平均分高出20至30个百分点。此外，与参加模拟考试的学生相比，AVT学习者的体验满意度更高，且为辅导环节进行复习的可能性是前者的两倍。我们认为AVT是一种可扩展且具有激励性的形成性评估方法，未来有望取代传统考试。