Two distinct sequence learning mechanisms for syntax acquisition and word learning

Anne Mc Clure Walk, Christopher M. Conway

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Scopus citations

Abstract

The ability to acquire spoken language depends in part on a sensitivity to the sequential regularities contained within linguistic input. In this chapter, the authors propose that language learning operates via two distinct sequence-learning processes: probabilistic sequence learning, which supports the acquisition of syntax and other structured linguistic patterns, and repetition sequence learning, which supports word learning. First, the authors review work from their lab and others illustrating that performance on tasks that require participants to learn non-linguistic sequential patterns is empirically associated with different measures of language processing. Second, they present recent work from their lab specifically highlighting the role played by probabilistic sequence learning for acquiring syntax in a sample of deaf and hard-of-hearing children. Finally, the authors demonstrate that the learning of repeating sequences is related to vocabulary development in these children. These findings suggest that there may be at least two relatively distinct domain-general sequential processing skills, with each supporting a different aspect of language acquisition.

Original languageEnglish (US)
Title of host publicationTheoretical and Computational Models of Word Learning
Subtitle of host publicationTrends in Psychology and Artificial Intelligence
PublisherIGI Global
Pages350-369
Number of pages20
ISBN (Electronic)9781466629745
ISBN (Print)1466629738, 9781466629738
DOIs
StatePublished - Feb 28 2013

ASJC Scopus subject areas

  • Computer Science(all)
  • Social Sciences(all)

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    Walk, A. M. C., & Conway, C. M. (2013). Two distinct sequence learning mechanisms for syntax acquisition and word learning. In Theoretical and Computational Models of Word Learning: Trends in Psychology and Artificial Intelligence (pp. 350-369). IGI Global. https://doi.org/10.4018/978-1-4666-2973-8.ch015