Literature DB >> 19966255

Stimulus set size and statistical coverage of the grammar in artificial grammar learning.

Fenna H Poletiek1, Tessa J P van Schijndel.   

Abstract

Adults and children acquire knowledge of the structure of their environment on the basis of repeated exposure to samples of structured stimuli. In the study of inductive learning, a straightforward issue is how much sample information is needed to learn the structure. The present study distinguishes between two measures for the amount of information in the sample: set size and the extent to which the set of exemplars statistically covers the underlying structure. In an artificial grammar learning experiment, learning was affected by the sample's statistical coverage of the grammar, but not by its mere size. Our result suggests an alternative explanation of the set size effects on learning found in previous studies (McAndrews & Moscovitch, 1985; Meulemans & Van der Linden, 1997), because, as we argue, set size was confounded with statistical coverage in these studies.

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Year:  2009        PMID: 19966255     DOI: 10.3758/PBR.16.6.1058

Source DB:  PubMed          Journal:  Psychon Bull Rev        ISSN: 1069-9384


  12 in total

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6.  What is learned about fragments in artificial grammar learning? A transitional probabilities approach.

Authors:  Fenna H Poletiek; Gezinus Wolters
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7.  Perceptual manifestations of an analytic structure: the priority of holistic individuation.

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Authors:  M P McAndrews; M Moscovitch
Journal:  Mem Cognit       Date:  1985-09

9.  The influence of grammatical, local, and organizational redundancy on implicit learning: an analysis using information theory.

Authors:  Randall K Jamieson; D J K Mewhort
Journal:  J Exp Psychol Learn Mem Cogn       Date:  2005-01       Impact factor: 3.051

Review 10.  Negative evidence in language acquisition.

Authors:  G F Marcus
Journal:  Cognition       Date:  1993-01
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  9 in total

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3.  Information theory and artificial grammar learning: inferring grammaticality from redundancy.

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4.  Implicit learning of two artificial grammars.

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5.  Input Variability Facilitates Unguided Subcategory Learning in Adults.

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Journal:  Psychol Res       Date:  2011-03-25

7.  Exemplar variability facilitates rapid learning of an otherwise unlearnable grammar by individuals with language-based learning disability.

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Journal:  J Speech Lang Hear Res       Date:  2012-09-17       Impact factor: 2.297

8.  An entropy model for artificial grammar learning.

Authors:  Emmanuel M Pothos
Journal:  Front Psychol       Date:  2010-06-17

9.  Learning simple and complex artificial grammars in the presence of a semantic reference field: effects on performance and awareness.

Authors:  Esther Van den Bos; Fenna H Poletiek
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  9 in total

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