LAUSR

Testing is an effective learning method, and it is the basis of mobile quiz apps. Quiz apps have the potential to facilitate remote and self-regulated learning. In this context, automatized feedback plays a crucial role. In two experimental studies, we examined the effects of two feedback types of quiz apps on performance, namely, the standard corrective feedback of quiz apps and a feedback that incorporates additional information related to the correct response option. We realized a controlled lab setting (n = 68, Study 1) and an unsupervised mobile setting (n = 150, Study 2). In the learning phase, participants used the quiz app and received feedback. They also completed a subsequent test as well as a follow-up test 1 week later by using the same quiz app. Irrespective of feedback type and setting, cognitive outcomes (quiz scores) and metacognitive outcomes (response certainty) increased similarly in the short term and long term. Feedback effects were not moderated by participants' overall response certainty during learning, their prior knowledge, and the difficulty of quiz items. Moreover, we found that participants perceived the quiz app to be similarly attractive, interesting, and enjoyable in both feedback conditions and that they spent slightly more time to process quiz items in the lab setting. We discuss these results in detail, including the role of moderating and mediating factors and prospects for further research and practice. Overall, our results underline that quiz apps are useful and effective tools that can support the acquisition and retention of semantic knowledge in different learning settings.