We use learning data of an e-assessment platform for an introductory mathematical statistics course to predict the probability of passing the final exam for each student. Based on these estimated probabilities we sent warning emails to students in the next cohort with a low predicted probability to pass. We analyze the effect of this treatment and propose statistical models to quantify the effect of the email notification. We detect a small but imprecisely estimated effect suggesting effectiveness of such interventions only when administered more intensively.

翻译：我们利用一个电子评估平台的学习数据,用于介绍性数学统计课程,预测每个学生通过期末考试的概率。根据这些估计概率,我们向下一组学生发出了警告性电子邮件,预计通过概率较低。我们分析了这一治疗的效果,并提出了统计模型,以量化电子邮件通知的效果。我们发现了一个微小但不精确的估计效果,表明只有在更加密集地实施时,此类干预措施才会有效。