Abstract:

This study explored how nameable features affect category learning. It compared the differences when nameable features served as diagnostic features or probabilistic features in category learning. Stimuli with features of color (Experiment 1A), complex shape (Experiment 1B) and simple shape (Experiment 2) were used separately. The result showed that, compared to when nameable features were probabilistic features, the performance of category learning was better when nameable features were diagnostic features. In the early stage of category learning, participants often focused on nameable features first. Participants took these features as references throughout the learning process even though such features were not the best basis for classification. The result indicates that nameable features facilitate category learning only when they are diagnostic, providing evidence for the significance of linguistic label in promoting category learning at the feature level.

Key words: category learning, linguistic label, nameability, diagnostic feature

摘要：

为探究易命名特征如何影响类别学习，研究以颜色(实验1A)、复杂形状(实验1B)和简单形状(实验2)特征刺激为材料，比较当易命名特征作为诊断性特征或概率性特征时的类别学习的差异。结果显示，相较于易命名特征作为概率性特征，当易命名特征为诊断性特征时，类别学习成绩更好。在类别学习的初期，学习者往往首先关注那些容易命名的特征，即使这些特征并非最佳的分类依据，他们在整个学习过程中仍然将其作为分类的参考之一。研究表明，只有当易命名特征具有诊断性时才有助于类别学习，为言语标签在特征层面促进类别学习提供了证据。

关键词: 类别学习, 言语标签, 命名性, 诊断性特征