Department of Psychology, University of California, 9500 Gilman Drive #0109, La Jolla, San Diego, CA 92093-0109, USA.
Mem Cognit. 2012 Apr;40(3):434-49. doi: 10.3758/s13421-011-0154-4.
Analogical transfer is the ability to transfer knowledge despite significant changes in the surface features of a problem. In categorization, analogical transfer occurs if a classification strategy learned with one set of stimuli can be transferred to a set of novel, perceptually distinct stimuli. Three experiments investigated analogical transfer in rule-based and information-integration categorization tasks. In rule-based tasks, the optimal strategy is easy to describe verbally, whereas in information-integration tasks, accuracy is maximized only if information from two or more stimulus dimensions is integrated in a way that is difficult or impossible to describe verbally. In all three experiments, analogical transfer was nearly perfect in the rule-based conditions, but no evidence for analogical transfer was found in the information-integration conditions. These results were predicted a priori by the COVIS theory of categorization.
类比迁移是一种能够在问题表面特征发生重大变化的情况下转移知识的能力。在分类中，如果一种用一组刺激物习得的分类策略可以转移到一组新的、知觉上不同的刺激物上，那么就会发生类比迁移。三项实验研究了基于规则和信息整合的分类任务中的类比迁移。在基于规则的任务中，最佳策略很容易用语言描述，而在信息整合任务中，只有当来自两个或更多刺激维度的信息以一种难以或不可能用语言描述的方式整合时，准确性才能最大化。在所有三项实验中，基于规则的条件下类比迁移几乎是完美的，但在信息整合条件下没有发现类比迁移的证据。这些结果是根据 COVIS 分类理论预先预测的。
