工作记忆容量与内容相关性对类别学习的影响
The Influences of Working Memory Capacity and Content Relevance on Category Learning

类别学习是通过不断地分类练习,学会如何将类别刺激进行归类的过程。采用2(工作记忆容量:高、低)×4(内容相关性:方向、宽度、亮度、控制组)被试间实验设计,通过两个实验探讨工作记忆容量与内容相关性对基于规则类别学习和信息整合类别学习的影响。结果显示:(1)对基于规则类别学习来说,在高工作记忆容量条件下,当关注相关维度时,类别学习的成绩更好;(2)对基于信息整合类别学习来说,不管工作记忆容量如何,只要关注相关维度类别学习的成绩更好。
Category learning is a process in which human beings classify perceptual simulations and acquire category knowledge by classification learning. 2(working memory capacity:high, low)×4(content relevance:direction, width, brightness, control) between-subject experiment were designed to explore the effects of working memory capacity and content relevance on category learning by two experiments.The results showed that:(1) Only under the condition of high capacity, focusing on the related dimensions can improve the classification performance in the rule-based category learning; (2) no matter what the working capacity is high or low, it can receive better classification performance if participants focus on the related dimensions of the information-integration category learning.