Bilingualism and statistical learning: Lessons from studies using artificial languages

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.

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Bilingualism and statistical learning: Lessons from studies using artificial languages

Semantic Scholar · Linguistics · 2019

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.

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