Statistical Learning and Language Impairments: Toward More Precise Theoretical Accounts

Louisa Bogaerts*, Noam Siegelman, Ram Frost

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

30 Scopus citations


Statistical-learning (SL) theory offers an experience-based account of typical and atypical spoken and written language acquisition. Recent work has provided initial support for this view, tying individual differences in SL abilities to linguistic skills, including language impairments. In the current article, we provide a critical review of studies testing SL abilities in participants with and without developmental dyslexia and specific language impairment and discuss the directions that this field of research has taken so far. We identify substantial vagueness in the demarcation lines between different theoretical constructs (e.g., “statistical learning,” “implicit learning,” and “procedural learning”) as well as in the mappings between experimental tasks and these theoretical constructs. Moreover, we argue that current studies are not designed to contrast different theoretical approaches but rather test singular confirmatory predictions without including control tasks showing normal performance. We end by providing concrete suggestions for how to advance research on SL deficits in language impairments.

Original languageAmerican English
Pages (from-to)319-337
Number of pages19
JournalPerspectives on Psychological Science
Issue number2
StatePublished - Mar 2021
Externally publishedYes

Bibliographical note

Publisher Copyright:
© The Author(s) 2020.


  • developmental disorders
  • dyslexia
  • implicit learning
  • language acquisition
  • literacy
  • procedural learning
  • reading
  • specific language impairment
  • statistical learning


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