A high-distortion enhancement effect in the prototype-learning paradigm: Dramatic effects of category learning during test

Abstract

Recent research suggests that exemplar models of classification are disconfirmed by the finding of extreme prototype-enhancement effects and steep typicality gradients in a version of the prototype-learning paradigm. We argue that these results are due to learning-during-transfer effects and not to the abstraction of a prototype from the training instances. In the standard version of the paradigm, observers are flooded with multiple presentations of the prototype and its low distortions during transfer. In a modified transfer condition, we instead present multiple instances of an arbitrary high distortion and low distortions of that high distortion. An extreme "high-distortion enhancement effect" is observed. Also, there is a flattening of the typicality gradient associated with the standard patterns (prototype, low distortions, and standard high distortions). The results provide dramatic evidence of the role of learning during transfer in this task and force a reevaluation of the dominant current interpretation of the steep typicality gradient.