类别学习理论通常集中在基础类别结构如何影响学习者获得的类别表示。然而,关于其他因素如何影响学习和利用表征以及表征在学习过程中如何变化的研究有限。我们使用了一个新颖的“5/5”分类任务,该任务是从经过充分研究的5/4任务开发的,并增加了一个刺激,以澄清5/4原型中的歧义。我们使用包括计算建模在内的多种方法来识别参与者是否根据样本或原型表示进行分类。我们发现,总的来说,对于我们使用的刺激(类似机器人的示意性刺激),学习的最佳特点是使用原型。最重要的是,我们发现原型和范例策略的相对使用在学习过程中发生了变化,随着样本表示的使用减少,原型表示跨块增加。
Theories of category learning have typically focused on how the underlying category structure affects the category representations acquired by learners. However, there is limited research as to how other factors affect what representations are learned and utilized and how representations might change across the time course of learning. We used a novel \"5/5\" categorization task developed from the well-studied 5/4 task with the addition of one more stimulus to clarify an ambiguity in the 5/4 prototypes. We used multiple methods including computational modeling to identify whether participants categorized on the basis of exemplar or prototype representations. We found that, overall, for the stimuli we used (schematic robot-like stimuli), learning was best characterized by the use of prototypes. Most importantly, we found that relative use of prototype and exemplar strategies changed across learning, with use of exemplar representations decreasing and prototype representations increasing across blocks.