A Stochastic Shortest Path Algorithm for Optimizing Spaced Repetition Scheduling

Junyao Ye, Jingyong Su, Yilong Cao

2022Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining16 citationsDOI

Abstract

Spaced repetition is a mnemonic technique where long-term memory can be efficiently formed by following review schedules. For greater memorization efficiency, spaced repetition schedulers need to model students' long-term memory and optimize the review cost. We have collected 220 million students' memory behavior logs with time-series features and built a memory model with Markov property. Based on the model, we design a spaced repetition scheduler guaranteed to minimize the review cost by a stochastic shortest path algorithm. Experimental results have shown a 12.6% performance improvement over the state-of-the-art methods. The scheduler has been successfully deployed in the online language-learning app MaiMemo to help millions of students.

Topics & Concepts

Repetition (rhetorical device)Computer scienceMemorizationMnemonicShortest path problemScheduling (production processes)Markov processAlgorithmParallel computingMathematical optimizationTheoretical computer scienceMathematicsGraphPhilosophyCognitive psychologyLinguisticsMathematics educationPsychologyStatisticsMultimodal Machine Learning ApplicationsTopic ModelingIntelligent Tutoring Systems and Adaptive Learning