Literature DB >> 27858279

The effect of encoding conditions on learning in the prototype distortion task.

Jessica C Lee1, Evan J Livesey2.   

Abstract

The prototype distortion task demonstrates that it is possible to learn about a category of physically similar stimuli through mere observation. However, there have been few attempts to test whether different encoding conditions affect learning in this task. This study compared prototypicality gradients produced under incidental learning conditions in which participants performed a visual search task, with those produced under intentional learning conditions in which participants were required to memorize the stimuli. Experiment 1 showed that similar prototypicality gradients could be obtained for category endorsement and familiarity ratings, but also found (weaker) prototypicality gradients in the absence of exposure. In Experiments 2 and 3, memorization was found to strengthen prototypicality gradients in familiarity ratings in comparison to visual search, but there were no group differences in participants' ability to discriminate between novel and presented exemplars. Although the Search groups in Experiments 2 and 3 produced prototypicality gradients, they were no different in magnitude to those produced in the absence of stimulus exposure in Experiment 1, suggesting that incidental learning during visual search was not conducive to producing prototypicality gradients. This study suggests that learning in the prototype distortion task is not implicit in the sense of resulting automatically from exposure, is affected by the nature of encoding, and should be considered in light of potential learning-at-test effects.

Entities:  

Keywords:  Category learning; Implicit; Prototype distortion; Recognition; Visual search

Mesh:

Year:  2017        PMID: 27858279     DOI: 10.3758/s13420-016-0252-z

Source DB:  PubMed          Journal:  Learn Behav        ISSN: 1543-4494            Impact factor:   1.986


  33 in total

1.  False prototype enhancement effects in dot pattern categorization.

Authors:  Safa R Zaki; Robert M Nosofsky
Journal:  Mem Cognit       Date:  2004-04

2.  Perceived distance and the classification of distorted patterns.

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Authors:  Robert M Nosofsky; Stephen E Denton; Safa R Zaki; Anne F Murphy-Knudsen; Frederick W Unverzagt
Journal:  J Exp Psychol Learn Mem Cogn       Date:  2012-07       Impact factor: 3.051

5.  Re-evaluating dissociations between implicit and explicit category learning: an event-related fMRI study.

Authors:  Todd M Gureckis; Thomas W James; Robert M Nosofsky
Journal:  J Cogn Neurosci       Date:  2010-08-04       Impact factor: 3.225

6.  Intact learning of artificial grammars and intact category learning by patients with Parkinson's disease.

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Journal:  Behav Neurosci       Date:  1999-04       Impact factor: 1.912

7.  Categorization and recognition performance of a memory-impaired group: evidence for single-system models.

Authors:  Safa R Zaki; Robert M Nosofsky; Nenette M Jessup; Frederick W Unverzagt
Journal:  J Int Neuropsychol Soc       Date:  2003-03       Impact factor: 2.892

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Authors:  F G Ashby; L A Alfonso-Reese; A U Turken; E M Waldron
Journal:  Psychol Rev       Date:  1998-07       Impact factor: 8.934

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Review 10.  Underpowered samples, false negatives, and unconscious learning.

Authors:  Miguel A Vadillo; Emmanouil Konstantinidis; David R Shanks
Journal:  Psychon Bull Rev       Date:  2016-02
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  2 in total

1.  The Lords of the Rings: People and pigeons take different paths mastering the concentric-rings categorization task.

Authors:  Ellen M O'Donoghue; Matthew B Broschard; John H Freeman; Edward A Wasserman
Journal:  Cognition       Date:  2021-10-04

2.  A Meta-Analysis Suggests Different Neural Correlates for Implicit and Explicit Learning.

Authors:  Roman F Loonis; Scott L Brincat; Evan G Antzoulatos; Earl K Miller
Journal:  Neuron       Date:  2017-10-11       Impact factor: 17.173

  2 in total

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