论文部分内容阅读
研究以大学生为被试,运用即时反馈训练范式,探讨类别数量对基于规则和信息整合两种结构的类别学习的影响,并探讨被试在类别学习过程中的反应策略。实验结果显示:(1)类别数量不仅影响基于规则结构的类别学习,也影响信息整合结构的类别学习,类别学习成绩随类别数量的增多而下降;(2)在基于规则类别学习中,大多数被试使用理想的分类规则进行类别判断;在信息整合类别学习中,大多数被试使用极端值策略。研究结果支持难度观,不支持多重系统理论。
The research uses college students as subjects, and uses instant feedback training paradigm to explore the influence of the number of categories on category learning based on rules and information integration, and discusses the response strategies of subjects in the course of learning. The results of the experiment show that: (1) The number of categories not only affects the category learning based on the rule structure but also the category learning of the information integration structure, and the category learning scores decrease with the increase of the number of categories; (2) In the rule-based learning, The subjects used the ideal classification rules to judge the categories. In the information integration category learning, most of the subjects used the extreme value strategy. The findings support the notion of difficulty and do not support multiple systems theory.