Work

Using a model to compute the optimal schedule of practice.

Year: 2008

Type: article

Abstract: By balancing the spacing effect against the effects of recency and frequency, this paper explains how practice may be scheduled to maximize learning and retention. In an experiment, an optimized condition using an algorithm determined with this method was compared with other conditions. The optimized condition showed significant benefits with large effect sizes for both improved recall and recall latency. The optimization method achieved these benefits by using a modeling approach to develop a quantitative algorithm, which dynamically maximizes learning by determining for each item when the balance between increasing temporal spacing (that causes better long-term recall) and decreasing temporal spacing (that reduces the failure related time cost of each practice) means that the item is at the spacing interval where long-term gain per unit of practice time is maximal. As practice repetitions accumulate for each item, items become stable in memory and this optimal interval increases.

Source: Journal of Experimental Psychology Applied

DOI: 10.1037/1076-898x.14.2.101

Authors: Philip I. Pavlik, John R. Anderson

Institution: Carnegie Mellon University

Language: English

Topic: Memory Processes and Influences

Subfield: Cognitive Neuroscience

Field: Neuroscience

Domain: Life Sciences

Open Access status: green

Funders: National Institutes of Health, U.S. Public Health Service, National Institute of Mental Health

Awards: GRADUATE EDUCATION IN THE NEURAL BASIS OF COGNITION, G6410072904, G7825684250