Abstract
Decades of research has shown that spacing practice trials over time can improve later memory, but there are few concrete recommendations concerning how to optimally space practice. We show that existing recommendations are inherently suboptimal due to their insensitivity to time costs and individual- and item-level differences. We introduce an alternative approach that optimally schedules practice with a computational model of spacing in tandem with microeconomic principles. We simulated conventional spacing schedules and our adaptive model-based approach. Simulations indicated that practicing according to microeconomic principles of efficiency resulted in substantially better memory retention than alternatives. The simulation results provided quantitative estimates of optimal difficulty that differed markedly from prior recommendations but still supported a desirable difficulty framework. Experimental results supported simulation predictions, with up to 40% more items recalled in conditions where practice was scheduled optimally according to the model of practice. Our approach can be readily implemented in online educational systems that adaptively schedule practice and has significant implications for millions of students currently learning with educational technology.
Highlights
There are large potential benefits to applying findings from the cognitive science of learning to educational contexts
If the success or failure of a trial influences efficiency, at what probability of recall should items be practiced to maximize efficiency? In the present study, we aimed to find this optimal efficiency threshold (OET) via simulation, which requires a following simulations combine these ideas by evaluating how scheduling according to a model and difficulty thresholds compared to conventional practices schedules and heuristics
We expected high OETs to lead to better memory retention than both conventional schedules and low OETs
Summary
There are large potential benefits to applying findings from the cognitive science of learning to educational contexts. Spacing practice trials across time has been shown to benefit memory[1,2]. Testing has been shown to benefit memory, relative to restudying[3,4]. Taken together, spaced retrieval practice has been shown to provide substantial benefits to later memory[5]. Integrating these findings into educational technology could benefit millions of students who currently learn in online educational systems. Implementation of these findings has been elusive—research has been unclear regarding exactly how much and when to practice specific information. We provide evidence that adaptive schedules lead to superior performance, better accommodate item and learner variability, and are implementable with a mixture of computational memory models and relatively simple economic decision rules
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