Delayed feedback effects on rule-based and information-integration category learning
Delayed feedback effects on rule-based and information-integration category learning
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DOI：
10.1037/0278-7393.29.4.650
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发表时间：
2003-07-01
影响因子：
2.6
通讯作者：
Bohil, CJ
中科院分区：
文献类型：
--
作者：
Maddox, WT;Ashby, FG;Bohil, CJ
研究了即时反馈和延迟反馈对基于规则和信息整合的类别学习的影响。准确率进行了检查，以隔离全球性能赤字，并进行基于模型的分析，以确定观察员使用的响应策略的类型。在基于规则的类别学习任务中，反馈延迟对反应的准确性或最佳拟合模型的分布没有影响。然而，延迟反馈导致不准确的反应，在信息整合类学习任务。基于模型的分析表明，延迟反馈的准确性下降是由于使用基于规则的策略来解决信息整合任务的增加。这些结果支持多系统的方法来类别学习，并反对单系统的方法的有效性。
The effect of immediate versus delayed feedback on rule-based and information-integration category learning was investigated. Accuracy rates were examined to isolate global performance deficits, and model-based analyses were performed to identify the types of response strategies used by observers. Feedback delay had no effect on the accuracy of responding or on the distribution of best fitting models in the rule-based category-learning task. However, delayed feedback led to less accurate responding in the information-integration category-learning task. Model-based analyses indicated that the decline in accuracy with delayed feedback was due to an increase in the use of rule-based strategies to solve the information-integration task. These results provide support for a multiple-systems approach to category learning and argue against the validity of single-system approaches.