A comparison of adaptive and fixed schedules of practice.

Abstract

Understanding and optimizing spacing of learning events is a central topic in basic research in learning and memory and has widespread and substantial implications for learning and instruction in real-world settings. Spacing memory retrievals across time improves memory relative to massed practice – the well-known spacing effect. Most spacing research has utilized fixed (predetermined) spacing schedules. Some findings indicate advantages of expanding spacing intervals over equal spacing (e.g., Landauer & Bjork, 1978); however, evidence is mixed (e.g., Karpicke & Roediger, 2007). One potential account of differing findings is that spacing per se is not the primary determinant; rather learning may depend on interactions of spacing with an underlying variable of learning strength that varies for learners and items. If so, learning may be better optimized by adaptive schedules that change spacing in relation to a learner’s ongoing performance. In two studies, we investigated an adaptive spacing algorithm, Adaptive Response-Time-based Sequencing (ARTS; Mettler, Massey & Kellman, 2011) that uses response time along with accuracy in interactive learning to generate spacing. In Experiment 1, we compared adaptive scheduling with fixed schedules having either expanding or equal spacing. In Experiment 2, we compared adaptive scheduling to two fixed “yoked” schedules that were copied from adaptive participants; these equated average spacing and trial characteristics across conditions. In both experiments, adaptive scheduling outperformed fixed conditions at immediate and delayed tests of retention. No evidence was found for differences between expanding and equal spacing. The advantage of adaptive spacing in yoked conditions was primarily due to adaptation to individual items and learners. Adaptive spacing based on ongoing assessments of learning strength for individual items and learners yields greater learning gains than fixed schedules, a finding that helps to understand the spacing effect theoretically and has direct applications for enhancing learning in many domains.

Evaluating the Theoretic Adequacy and Applied Potential of Computational Models of the Spacing Effect

“…Such predictions, if valid, could be used to prescribe personalized review (Mettler et al, 2016;Pavlik & Anderson, 2008). Such predictions, if valid, could be used to prescribe personalized review (Mettler et al, 2016;Pavlik & Anderson, 2008).…”

“…To be maximally useful, a computational model of the spacing effect should make individual-level out-of-sample temporal predictions. Such predictions, if valid, could be used to prescribe personalized review (Mettler et al, 2016;Pavlik & Anderson, 2008). We have begun to explore this issue in PPE and have found that the model can, in fact, make accurate individualized predictions for a range of skill-based and declarative tasks (Jastrzembski et al, 2017).…”

“…In terms of application, computational models provide the kind of rigor that Anderson and Schunn (2000) call for and can lead to technologies that improve education (Anderson, Corbett, Koedinger, & Pelletier, 1995;Mettler, Massey, & Kellman, 2016;Pavlik & Anderson, 2008; for a review, see Walsh & Lovett, 2016). In terms of theory, computational models offer a way to unify the ever-expanding collection of empirical results related to the spacing effect.…”

From no to yes : the impact of an intervention on the persistence of algebraic misconceptions among secondary school algebra students

“…The spacing effect has been studied extensively over time, with large effect sizes giving evidence of its robust effectiveness in increasing long term retention (Dunlosky, Rawson, Marsh, Nathan, & Willingham, 2013;Kapler, Weston, & Wiseheart, 2015;Mettler, Massey, & Kellman, 2016;Rohrer, Dedrick, & Stershic, 2015). In these studies, it was more effective to space out practice on a topic than to mass practice all at once.…”

“…The literature consistently shows that spacing learning is a simple, robustly effective technique that can increase long term retention (Dunlosky et al, 2013;Kapler et al, 2015;Mettler et al, 2016). intervention group students were required to complete three different practice slips correctly on three different days, which built spaced learning into the intervention.…”