Learning Mode and Exemplar Sequencing in Unsupervised Category Learning

被引:18
|
作者
Zeithamova, Dagmar [1 ,2 ]
Maddox, W. Todd [1 ,2 ]
机构
[1] Univ Texas Austin, Inst Neurosci, Austin, TX 78712 USA
[2] Univ Texas Austin, Dept Psychol, Austin, TX 78712 USA
基金
美国国家卫生研究院;
关键词
unsupervised learning; classification; sequence effects; incidental and intentional learning; HUMAN CATEGORIZATION; CLASSIFICATION; STIMULI; IDENTIFICATION; CONSTRUCTION; SIMILARITY; ATTENTION; DIMENSION;
D O I
10.1037/a0015005
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
Exemplar sequencing effects in incidental and intentional unsupervised category learning were investigated to illuminate how people form categories without an external teacher. Stimuli were perfectly separable into 2 categories based on 1 of 2 dimensions of variation. Sequencing of the first 20 training stimuli was manipulated. In the blocked condition, 10 Category A stimuli were followed by 10 Category B stimuli. In the intermixed condition, these 20 stimuli were ordered randomly. Experiment 1 revealed an interaction between learning mode and sequence, with better intentional learning for intermixed sequences but better incidental learning for blocked sequences. Experiment 2 showed that manipulating trial-to-trial variability along each dimension can impact intentional learning. Training sequences that emphasized variation along the category-relevant dimension resulted in better performance than sequences that emphasized variation along the category-irrelevant dimension. The results suggest that unsupervised category learning is influenced by the mode of learning and the order and nature of encountered exemplars.
引用
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页码:731 / 741
页数:11
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