Literature DB >> 21264587

How prior knowledge affects selective attention during category learning: an eyetracking study.

Shinwoo Kim1, Bob Rehder.   

Abstract

Research has shown that category learning is affected by (a) attention, which selects which aspects of stimuli are available for further processing, and (b) the existing semantic knowledge that learners bring to the task. However, little is known about how knowledge affects what is attended. Using eyetracking, we found that (a) knowledge indeed changes what features are attended, with knowledge-relevant features being fixated more often than irrelevant ones, (b) this effect was not due to an initial attentional bias toward relevant dimensions but rather emerged gradually as a result of observing category members, and (c) this effect grew even after a learning criterion was reached, that is, despite the absence of negative feedback. We argue that models of knowledge-based learning will remain incomplete until they specify mechanisms that dynamically select prior knowledge in response to observed category members and which then directs attention to knowledge-relevant dimensions and away from irrelevant ones.

Mesh:

Year:  2011        PMID: 21264587     DOI: 10.3758/s13421-010-0050-3

Source DB:  PubMed          Journal:  Mem Cognit        ISSN: 0090-502X


  28 in total

1.  Category learning with minimal prior knowledge.

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6.  Prior knowledge and functionally relevant features in concept learning.

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