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Abstract Numerous studies have found that selective attention affects category learning. However, previous research did not distinguish between the contribution of focusing and filtering components of selective attention. This study addresses this issue by examining how components of selective attention affect category representation. Participants first learned a rule‐plus‐similarity category structure, and then were presented with category priming followed by categorization and recognition tests. Additionally, to evaluate the involvement of focusing and filtering, we fit models with different attentional mechanisms to the data. In Experiment 1, participants received rule‐based category training, with specific emphasis on a single deterministic feature (D feature). Experiment 2 added a recognition test to examine participants’ memory for features. Both experiments indicated that participants categorized items based solely on the D feature, showed greater memory for the D feature, were primed exclusively by the D feature without interference from probabilistic features (P features), and were better fit by models with focusing and at least one type of filtering mechanism. The results indicated that selective attention distorted category representation by highlighting the D feature and attenuating P features. To examine whether the distorted representation was specific to rule‐based training, Experiment 3 introduced training, emphasizing all features. Under such training, participants were no longer primed by the D feature, they remembered all features well, and they were better fit by the model assuming only focusing but no filtering process. The results coupled with modeling provide novel evidence that while both focusing and filtering contribute to category representation, filtering can also result in representational distortion.
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Using language to discover categories: More nameable features improve category learning
Does the lexicon of a language have consequences for cognition? Here, we provide evidence that the ease with which category features can be named can influence category learning. Across two experiments, participants learned to distinguish images composed of colors (Experiment 1) and shapes (Experiment 2) that were either easy or more difficult to name in English. Holding the category structure constant, when the underlying features of the category were easy to name, participants were faster and more accurate in learning the novel category. We argue that these findings suggest that labels allow learners to form more compact hypotheses, which in turn can be confirmed or disconfirmed in the course of learning. These results have consequences for considering how cross-linguistic differences in lexical inventory affect how readily novel categories are learned.
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- Award ID(s):
- 1734260
- PAR ID:
- 10074363
- Date Published:
- Journal Name:
- Proceedings of the 12th International Conference on the Evolution of Language (Evolang12)
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.12775/3991-1.136
