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

被引:0
|
作者
F. Gregory Ashby
Jeff Rey B. O’Brien
机构
[1] University of California,Department of Psychology
来源
Perception & Psychophysics | 2007年 / 69卷 / 6期
关键词
Category Learning; Feedback Trial; Full Feedback; General Linear Classifier; Partial Feedback Condition;
D O I
10.3758/BF03193923
中图分类号
学科分类号
摘要
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, rulebased 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.
引用
收藏
页码:865 / 878
页数:13
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