Over the past decade, there has been an enormous upsurge in the use of educational apps in primary schools. However, few studies have examined how children interact with these apps and how their interaction patterns relate to learning outcomes. An interaction pattern that is potentially detrimental to learning is repeated mistakes, defined as making the same mistake more than once when answering a task. With interaction data from an eight-week digital vocabulary intervention, we examined 1) whether the propensity to make repeated mistakes changes across app sessions, and 2) how repeated mistakes relate to children's prior knowledge and their learning gains from the intervention. Our sample consisted of 363 Norwegian second graders who worked with the vocabulary app in a randomized controlled trial. Using growth curve modeling and confirmatory factor analyses, we found that the propensity to repeat mistakes remained stable over time. Furthermore, a structural equation model showed that repeated mistakes related negatively to both pre-test and post-test scores. A substantial proportion of the total effect of prior knowledge on learning gains was mediated by the propensity to repeat mistakes. Children who made more repeated mistakes had lower expected learning gains across all levels of prior knowledge. We suggest that the propensity to repeat mistakes may pose a double threat to learning by diminishing exposure to relevant content, and amplifying the exposure to incorrect input. Considering the stability of mistake repetition, it is crucial to identify students with a high propensity to repeat mistakes and help them break the pattern to support learning. App developers can help this process by implementing automatic detection and feedback.

在过去的十年中，小学中教育应用程序的使用出现了巨大的热潮。然而，很少有研究探讨儿童如何与这些应用程序互动以及他们的互动模式与学习成果有何关系。一种可能不利于学习的交互模式是重复错误，定义为在回答任务时多次犯同样的错误。利用为期八周的数字词汇干预的交互数据，我们研究了 1) 重复错误的倾向是否会在应用程序会话中发生变化，以及 2) 重复错误与儿童的先验知识以及他们从干预中获得的学习收益之间的关系。我们的样本由 363 名挪威二年级学生组成，他们在一项随机对照试验中使用了词汇应用程序。使用增长曲线模型和验证性因素分析，我们发现重复错误的倾向随着时间的推移保持稳定。此外，结构方程模型显示，重复错误与测试前和测试后的分数均呈负相关。先验知识对学习收益的总影响的很大一部分是由重复错误的倾向调节的。犯更多重复错误的孩子在所有先前知识水平上的预期学习收益较低。我们认为，重复错误的倾向可能会对学习造成双重威胁，因为它会减少对相关内容的接触，并增加对错误输入的接触。考虑到错误重复的稳定性，识别重复错误倾向较高的学生并帮助他们打破模式以支持学习至关重要。应用程序开发人员可以通过实施自动检测和反馈来帮助这一过程。