On Learning Natural-Science Categories That Violate the Family-Resemblance Principle

被引:24
作者
Nosofsky, Robert M. [1 ]
Sanders, Craig A. [1 ]
Gerdom, Alex [1 ]
Douglas, Bruce J. [2 ]
McDaniel, Mark A. [3 ]
机构
[1] Indiana Univ Bloomington, Dept Psychol & Brain Sci, 1101 E Tenth St, Bloomington, IN 47405 USA
[2] Indiana Univ Bloomington, Dept Geol Sci, Bloomington, IN USA
[3] Washington Univ, Dept Psychol & Brain Sci, St Louis, MO 63130 USA
基金
美国国家科学基金会;
关键词
category learning; similarity; computational modeling; open data; DECISION BOUND MODELS; EXEMPLAR; MEMORY; SIMILARITY; IDENTIFICATION; RETRIEVAL; ATTENTION; PROTOTYPE;
D O I
10.1177/0956797616675636
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
The general view in psychological science is that natural categories obey a coherent, family-resemblance principle. In this investigation, we documented an example of an important exception to this principle: Results of a multidimensional-scaling study of igneous, metamorphic, and sedimentary rocks (Experiment 1) suggested that the structure of these categories is disorganized and dispersed. This finding motivated us to explore what might be the optimal procedures for teaching dispersed categories, a goal that is likely critical to science education in general. Subjects in Experiment 2 learned to classify pictures of rocks into compact or dispersed high-level categories. One group learned the categories through focused high-level training, whereas a second group was required to simultaneously learn classifications at a subtype level. Although high-level training led to enhanced performance when the categories were compact, subtype training was better when the categories were dispersed. We provide an interpretation of the results in terms of an exemplar-memory model of category learning.
引用
收藏
页码:104 / 114
页数:11
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