[en] In four experiments, adherence to grammatical rules and associative chunk strength (including different measures, each calculated on the basis of the frequency with which bigrams and trigrams present in the test strings appeared in the learning strings) were manipulated independently in the test phase of an artificial grammar learning task. When participants learned few items of the grammar (Experiments 1a and 2a), the associated items were more often classified as grammatical than the nonassociated ones. On the other hand, when the learning phase included most of the grammatical items (Experiments 1b and 2b), the only effect observed was an effect of grammaticality. These results suggest that, depending on the specific constraints of the tasks, knowledge based on bigrams and trigrams and knowledge based on the abstraction of the grammatical structure can be used for the classification task.
Research center :
Centre de Neurosciences Cognitives et Comportementales - ULiège
Disciplines :
Theoretical & cognitive psychology
Author, co-author :
Meulemans, Thierry ; Université de Liège - ULiège > Département des sciences cognitives > Neuropsychologie
Van der Linden, Martial ; Université de Liège - ULiège > Département des sciences cognitives > Psychopathologie cognitive
Language :
English
Title :
Associative chunk strength in artificial grammar learning
Publication date :
1997
Journal title :
Journal of Experimental Psychology. Learning, Memory and Cognition
ISSN :
0278-7393
eISSN :
1939-1285
Publisher :
American Psychological Association, Washington, United States - District of Columbia
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