ISSN 0439-755X
CN 11-1911/B

心理学报 ›› 2009, Vol. 41 ›› Issue (02): 103-113.

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  1. 华南师范大学心理应用研究中心,广州 510631
  • 收稿日期:2007-12-18 修回日期:1900-01-01 出版日期:2009-02-28 发布日期:2009-02-28
  • 通讯作者: 莫雷

Which One Is Better? Based on Categories or Based on Feature Association When Categorization Is Uncertain

MO Lei;CHEN Lin   

  1. Center for Studies of Psychological Application, South China Normal University, Guangzhou 510631, China
  • Received:2007-12-18 Revised:1900-01-01 Online:2009-02-28 Published:2009-02-28
  • Contact: MO Lei

摘要: 共有3个实验探讨归类不确定情况下的特征推理是基于类别进行还是基于特征联结进行。实验1在中文条件下重复了Verde等人2005的实验,得出了与之相符的结果,这个结果用基于类别的理性模型的设想或者是用基于特征联结的设想都可以解释。实验2考察被试在靶类别的类别特征频次并且特征结合出现频次高低不同的条件下特征推理的情况,实验2的结果表明,高集中与低集中两种条件下特征推理没有显著差异,不符合特征推理是基于类别进行的设想,而与特征推理是基于特征联结进行的设想吻合。实验3进一步考察被试在特征结合出现的总频次并且靶类别中特征结合出现的总频次高低不同的条件下特征推理的情况,结果表明,在高结合条件下进行特征推理要优于在低结合条件,支持了在归类不确定情况下的特征推理是基于特征联结进行的设想。据此可以认为,人们的特征推理是基于特征之间联结的频次进行,而不是基于类别进行

关键词: 单类说, 理性模型, 基于类别, 基于特征联结, 特征推理

Abstract: When categorization is uncertain, the inner mechanism of people’s feature induction induced some arguments. In terms of predicting features, Rational Model indicated that people would take all categories into consideration while single-category theory advanced that people only paid attention to the target category. The essential difference between Rational Model and single-category theory is whether people would take the alternative categories into consideration when predicting features. But neither Rational Model nor single-category theory could explain the results of the research by Verde et al in 2005. So Verde et al concluded that the feature prediction in their research might be based on feature association. Therefore, three experiments were designed in this research to investigate how people predicted features when categorization was uncertain.
Experiment 1 replicated the experiment of Verde et al (2005) in Chinese circumstance so that the effect of language would be excluded. In Experiment 2, the frequency of the feature association in order to find out whether categories were considered. Experiment 3 the variable of category was controlled in order to find out whether people’s induction was based on feature association.
Seventy subjects were evenly grouped into experiment 1 and experiment 2, and thirty-four subjects in experiment 3. All of the subjects were individually tested on computers, which controlled list generation, stimulus presentation, and response recording. The procedure comprised five phases: (1) study, (2) a training test, (3) study, (4) a training test, and (5) a final test. During the study phase, all exemplars were shown once. Each exemplar was shown for 4000msec. During the training test phase, subjects should categorize all exemplars into their correct categories. During the final test phase, subjects should decide whether or not the to-be-predicted feature was the one that most likely to appear with the given feature and then to make a yes-no judgment.
Experiment 1 gained the same results as the experiment conducted by Verde et al (2005). By controlling the variable of feature association, Experiment 2 found that there was no significant difference in feature prediction between two conditions, which indicated that people’s induction was not category-based. Via controlling the variable of category, Experiment 3 found that there was significant difference in feature prediction between two feature association conditions, which indicated that people’s induction was based on feature association.
The three experiments illustrate that people are inclined to predict features on the basis of feature association when categorization is uncertain. In contrast to the category-based prediction, prediction based on feature association is an economical strategy, which can be adopted to explain many results of the previous studies

Key words: ingle-category theory, Rational Model, based on categories, based on feature association, feature prediction


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