Bilingualism and statistical learning: Lessons from studies using artificial languages

Daniel J. Weiss, Natalie Schwob, Amy L. Lebkuecher

Research output: Contribution to journalReview articlepeer-review

15 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)92-97
Number of pages6
Issue number1
StatePublished - Jan 1 2020

All Science Journal Classification (ASJC) codes

  • Education
  • Language and Linguistics
  • Linguistics and Language


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