Using a model to compute the optimal schedule of practice
Using a model to compute the optimal schedule of practice
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DOI：
10.1037/1076-898x.14.2.101
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发表时间：
2008-06-01
影响因子：
2.6
通讯作者：
Anderson, John R.
中科院分区：
文献类型：
--
作者：
Pavlik, Philip I., Jr.;Anderson, John R.
通过平衡间隔效应对近因和频率的影响，本文解释了如何安排练习，以最大限度地提高学习和保持。在实验中，将使用由该方法确定的算法的优化条件与其他条件进行比较。优化的条件下表现出显着的好处与大的效果大小改善回忆和回忆潜伏期。优化方法通过使用建模方法来开发定量算法来实现这些益处，其通过为每个项目确定何时增加时间间隔之间的平衡来动态最大化学习（这会导致更好的长期回忆）和减少时间间隔（这减少了每次实践的故障相关时间成本）意味着项目处于间隔时间，其中长-每单位练习时间的术语增益是最大的。随着每个项目重复练习的积累，项目在记忆中变得稳定，最佳间隔也会增加。
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.