Department of Psychology, University of Illinois, 603 E. Daniel St., Champaign, IL 61820, USA.
Mem Cognit. 2011 Jul;39(5):764-77. doi: 10.3758/s13421-010-0058-8.
Categories are learned and used in a variety of ways, but the research focus has been on classification learning. Recent work contrasting classification with inference learning of categories found important later differences in category performance. However, theoretical accounts differ on whether this is due to an inherent difference between the tasks or to the implementation decisions. The inherent-difference explanation argues that inference learners focus on the internal structure of the categories--what each category is like--while classification learners focus on diagnostic information to predict category membership. In two experiments, using real-world categories and controlling for earlier methodological differences, inference learners learned more about what each category was like than did classification learners, as evidenced by higher performance on a novel classification test. These results suggest that there is an inherent difference between learning new categories by classifying an item versus inferring a feature.
类别以各种方式被学习和使用，但研究重点一直是分类学习。最近的对比分类和推理学习类别的研究发现，在类别表现上存在重要的后期差异。然而，理论解释在这是由于任务本身的差异还是由于实现决策的差异而导致的存在分歧。内在差异解释认为，推理学习者关注类别内部结构——每个类别是什么样的——而分类学习者关注预测类别成员身份的诊断信息。在两项实验中，使用真实世界的类别并控制早期方法学差异，推理学习者比分类学习者更了解每个类别的特点，表现在新的分类测试中表现更好。这些结果表明，通过分类项目学习新类别与推断特征之间存在内在差异。
