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将测试增强学习的双重记忆模型扩展到分布和个体差异。

Extension of the dual-memory model of test-enhanced learning to distributions and individual differences.

机构信息

Department of Psychology, University of California, San Diego, 9500 Gilman Drive, San Diego, CA, 91093, USA.

出版信息

Psychon Bull Rev. 2020 Aug;27(4):783-790. doi: 10.3758/s13423-020-01734-7.

Abstract

The dual-memory model of test-enhanced learning (Rickard & Pan, 2018, Psychonomic Bulletin & Review, 25[3], 847-869) provides empirically supported quantitative predictions about multiple core phenomena for the case of cued recall. That model has been evaluated to date only for mean proportion correct. However, it also makes predictions about the distribution over subjects for both test-condition proportion correct and testing-effect magnitude. As a consequence, it makes predictions about aggregate individual difference effects on learning through testing. The current paper evaluates those and other predictions, focusing on a data set of 509 subjects aggregated over multiple experiments that were conducted in my laboratory. Results show that the distribution predictions hold to a close approximation for materials ranging from paired associates to history facts, and for retention intervals ranging from 1 to 7 days. The distribution analyses also allow for a novel assessment of whether accuracy on a training test with feedback is a determinant of testing-effect magnitude, and the results suggest constraints on alternative models. Limitations and prospects are discussed.

摘要

测试增强学习的双重记忆模型(Rickard & Pan,2018,《心理学报与评论》,25[3],847-869)为提示回忆的情况下的多个核心现象提供了经验支持的定量预测。迄今为止,该模型仅针对平均比例正确进行了评估。然而,它还对测试条件比例正确和测试效应幅度的受试者分布做出了预测。因此,它对通过测试进行的学习的总体个体差异效应做出了预测。本文评估了这些和其他预测,重点关注了我实验室进行的多个实验中汇总的 509 名受试者的数据集。结果表明,对于从配对联想到历史事实的材料以及从 1 天到 7 天的保留间隔,分布预测都非常接近。分布分析还可以对具有反馈的训练测试的准确性是否是测试效应幅度的决定因素进行新的评估,结果表明对替代模型的限制。讨论了局限性和前景。

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