Reducing Traditional Lecture Time Through Asynchronous Spaced Retrieval

Traditional teaching methods require learners to spend significant time studying material outside of the classroom in addition to lecture. Spaced retrieval, a learning technique involving repeated memory testing over time, offers a promising way to maximize studying outside of the classroom and better prioritize classroom time. In the present study, we examined whether an AI-driven mobile app that delivers traditional lecture content via spaced retrieval practice could sufficiently teach learners a new topic in the absence of a lecture. Participants watched a recorded lecture and then used the app for a few minutes a day for four weeks to answer a set of questions about the lecture and a set of questions about a new topic that had not been lectured. They were then tested on their ability to apply their knowledge of each topic on a memory test featuring never seen multiple-choice and short-essay questions. During the app usage phase, participants took longer to review questions about non-lectured vs. lectured content (9.05 vs. 7.92 min per week, respectively) and participants started off with significantly lower app accuracy on non-lectured vs. lectured questions. However, after one week of app use, the difference in accuracy disappeared, and participants performed equally well on lectured vs. non-lectured questions on the final multiple-choice and essay tests. These results suggest that, in the conventional classroom, some lecture time may be replaced by efficient, asynchronous learning tools.