Effect of chunk strength on the performance of children with developmental dyslexia on artificial grammar learning task may be related to complexity

Rachel Schiff, Pesia Katan, Ayelet Sasson, Shani Kahta

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

There’s a long held view that chunks play a crucial role in artificial grammar learning performance. We compared chunk strength influences on performance, in high and low topological entropy (a measure of complexity) grammar systems, with dyslexic children, age-matched and reading-level-matched control participants. Findings show that age-matched control participants’ performance reflected equivalent influence of chunk strength in the two topological entropy conditions, as typically found in artificial grammar learning experiments. By contrast, dyslexic children and reading-level-matched controls’ performance reflected knowledge of chunk strength only under the low topological entropy condition. In the low topological entropy grammar system, they appeared completely unable to utilize chunk strength to make appropriate test item selections. In line with previous research, this study suggests that for typically developing children, it is the chunks that are attended during artificial grammar learning and create a foundation on which implicit associative learning mechanisms operate, and these chunks are unitized to different strengths. However, for children with dyslexia, it is complexity that may influence the subsequent memorability of chunks, independently of their strength.

Original languageEnglish
Pages (from-to)180-199
Number of pages20
JournalAnnals of Dyslexia
Volume67
Issue number2
Early online date13 Apr 2017
DOIs
StatePublished - 1 Jul 2017

Bibliographical note

Publisher Copyright:
© 2017, The International Dyslexia Association.

Keywords

  • Artificial grammar learning
  • Chunk strength
  • Complexity
  • Developmental dyslexia
  • Implicit statistical learning

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