Human memory is imperfect; thus, periodic review is required for the long-term preservation of knowledge and skills. However, students at every educational level are challenged by an ever-growing amount of material to review and an ongoing imperative to master new material. We developed a method for efficient, systematic, personalized review that combines statistical techniques for inferring individual differences with a psychological theory of memory. The method was integrated into a semester-long middle-school foreign-language course via retrieval-practice software. Using a cumulative exam administered after the semester's end, we compared time-matched review strategies and found that personalized review yielded a 16.5% boost in course retention over current educational practice (massed study) and a 10.0% improvement over a one-size-fits-all strategy for spaced study.
Keywords: Bayesian modeling; adaptive scheduling; classroom education; declarative memory; educational psychology; individual differences; long-term memory; spacing effect.