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Bilingualism and statistical learning: Lessons from studies using artificial languages

Published online by Cambridge University Press:  16 October 2019

Daniel J. Weiss ,
Natalie Schwob  and
Amy L. Lebkuecher
Daniel J. Weiss*
Affiliation:
Department of Psychology, The Pennsylvania State University
Natalie Schwob
Affiliation:
Department of Psychology, The Pennsylvania State University
Amy L. Lebkuecher
Affiliation:
Department of Psychology, The Pennsylvania State University
*
Address for correspondence: Daniel J. Weiss, E-mail: djw21@psu.edu
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Abstract

Studies of statistical learning have shaped our understanding of the processes involved in the early stages of language acquisition. Many of these advances were made using experimental paradigms with artificial languages that allow for careful manipulation of the statistical regularities in the input. This article summarizes how these paradigms have begun to inform bilingualism research. We focus on two complementary goals that have emerged from studies of statistical learning in bilinguals. The first is to identify whether bilinguals differ from monolinguals in how they track distributional regularities. The second is determining how learners are capable of tracking multiple inputs, which arguably is an important facet of becoming proficient in more than one language.

Keywords

statistical learningartificial languagesbilingualism
Type
Review Article
Information
Bilingualism: Language and Cognition , Volume 23 , Issue 1 , January 2020 , pp. 92 - 97
Copyright
Copyright © Cambridge University Press 2019 

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