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积极反馈与消极反馈对信息整合类别学习的影响。

The effects of positive versus negative feedback on information-integration category learning.

作者信息

Ashby F Gregory, O'Brien Jeffrey B

机构信息

Department of Psychology, University of California, Santa Barbara, California 93106, USA.

出版信息

Percept Psychophys. 2007 Aug;69(6):865-78. doi: 10.3758/bf03193923.

Abstract

A number of studies have shown that in category learning, providing feedback about errors allows faster learning than providing feedback about correct responses. However, these previous studies used explicit, rule-based tasks in which the category structures could be separated by a simple rule that was easily verbalized. Here, the results of the first experiment known to compare the efficacy of positive versus negative feedback during information-integration category learning are reported. Information-integration tasks require participants to integrate perceptual information from incommensurable dimensions, and evidence suggests that optimal responding recruits procedural learning. The results show that although nearly all of the full-feedback control participants demonstrated information-integration learning, participants receiving either positive-only or negative-only feedback generally used explicit, rule-based strategies. It thus appears that, unlike rule-based learning, consistent information-integration learning requires full feedback. The theoretical implications of these findings for current models of information-integration learning are discussed.

摘要

多项研究表明,在类别学习中,提供关于错误的反馈比提供关于正确反应的反馈能使学习速度更快。然而,这些先前的研究使用的是明确的、基于规则的任务,其中类别结构可以通过一个易于用语言表述的简单规则来区分。在此,报告了已知的第一项比较信息整合类别学习中积极反馈与消极反馈效果的实验结果。信息整合任务要求参与者整合来自不可通约维度的感知信息,并且有证据表明最佳反应需要程序性学习。结果表明,尽管几乎所有的全反馈控制组参与者都表现出信息整合学习,但仅接受积极反馈或仅接受消极反馈的参与者通常使用明确的、基于规则的策略。因此,与基于规则的学习不同,一致的信息整合学习似乎需要全反馈。讨论了这些发现对当前信息整合学习模型的理论意义。

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