ISSN 0439-755X
CN 11-1911/B

心理学报 ›› 2014, Vol. 46 ›› Issue (8): 1052-1061.doi: 10.3724/SP.J.1041.2014.01052

• 论文 • 上一篇    下一篇



  1. (1华南师范大学心理应用研究中心/心理学院, 广州 510631) (2北京师范大学心理学院, 北京 100875)
  • 收稿日期:2013-05-03 发布日期:2014-08-25 出版日期:2014-08-25
  • 通讯作者: 刘志雅
  • 基金资助:


The Representation of Partial Exemplars in Classification Learning

WANG Ruiming;LIN Zheting;LIU Zhiya   

  1. (1 Center for Studies of Psychological Application/School of Psychology, South China Normal University, Guangzhou 510631, China) (2 School of Psychology, Beijing Normal University, Beijing 100875, China)
  • Received:2013-05-03 Online:2014-08-25 Published:2014-08-25
  • Contact: LIU Zhiya


先前研究者普遍认为, 类别推理学习条件下可以同时表征诊断性信息和非诊断性信息, 而类别分类学习条件下中只能表征诊断性信息, 不能表征非诊断性信息。而最近又有研究者发现部分呈现条件下的类别分类学习可以表征非诊断性信息。本研究通过两个实验系统比较了全部呈现和部分呈现条件下类别分类学习的结果, 进一步探讨了分类学习条件下信息的表征情况, 并进一步探讨了部分呈现条件下的分类学习能够表征非诊断性信息的原因。实验1发现全部呈现6个特征、缺失1个特征(即部分呈现5个特征)、缺失2个特征(即部分呈现4个特征)3种条件下都能表征诊断性信息, 但只有部分呈现条件下能表征非诊断性信息。实验2发现全部呈现7个特征、缺失2个特征(即部分呈现5个特征)、全部呈现5个特征3种条件下都能表征诊断性信息, 但只有部分呈现条件下能表征非诊断性信息。总的实验结果表明:全部呈现条件下的分类学习只能表征诊断性信息, 而部分呈现条件下的分类学习能够同时表征诊断性信息和非诊断性信息, 并且部分呈现条件下表征非诊断性信息的原因是被试进行了推理学习, 而非注意广度的变化。

关键词: 类别学习, 分类学习, 推理学习, 诊断性信息, 典型性信息


Previous researches have showed that category learning by inference way can represent diagnostic information and nondiagnostic information, but learning by classifying way only can represent diagnostic information such as exemplar features information. However, recently studies show that learning partial exemplars by classifying also can represent nondiagnostic information (Taylor & Ross, 2009). Taylor & Ross (2009) offered an explanation of selective attention that there are comparably loose of attention resources in partial condition than entire condition. They left out the possibility that the subject might inference the missing features in the partial condition. In the real world, exemplars often appear with occluded features, but in laboratory research, they are almost always presented in their entirety. Two experiments were conducted to explore how partial classification leads to nondiagnostic features learning. Experiment 1 replicated the Taylor & Ross (2009) finding that learners who classified exemplars with missing features (the partial condition) processed nondiagnostic features. Experiment 2 explored how partial exemplars of classification learning could represent nondiagnostic (prototypical) information. Linearly separable category structures were used in this study. Experiment 1 used the “6 dimensions category” and experiment 2 used the “7 and 5 dimensions category”. During learning phase, an individual exemplar was presented, the participant was asked to infer and indicate which category (Deeger or Koozle) the exemplar belonged to, and feedback as to whether the subject was right or wrong was provided. After a number of such trials of inference and feedback, participants reached the learning criterion and were considered to have formed new category knowledge. During the transfer phase, different prototypical and diagnostic exemplars were presented, the participant was asked to estimate their categorical typicality. Experiment 1 replicate the finding of Taylor & Ross (2009) that the entire and the partial conditions both can represent diagnostic information, but only the partial condition can represent prototypical information. In other word, the entire condition only can represent diagnostic information, but partial condition not only can represent diagnostic information but also nondiagnostic information. The results of experiment 2 support the previous prediction that subject inference the missing features automatically but not adjust their attention in the partial learning condition.

Key words: category learning, classification learning, inference learning, diagnostic information, prototypical information