Literature DB >> 32694882

Individual differences in learning the regularities between orthography, phonology and semantics predict early reading skills.

Noam Siegelman1, Jay G Rueckl1,2, Laura M Steacy3, Stephen J Frost1, Mark van den Bunt1, Jason D Zevin1,4, Mark S Seidenberg5, Kenneth R Pugh1,2,6, Donald L Compton3, Robin D Morris7.   

Abstract

Statistical views of literacy development maintain that proficient reading requires the assimilation of myriad statistical regularities present in the writing system. Indeed, previous studies have tied statistical learning (SL) abilities to reading skills, establishing the existence of a link between the two. However, some issues are currently left unanswered, including questions regarding the underlying bases for these associations as well as the types of statistical regularities actually assimilated by developing readers. Here we present an alternative approach to study the role of SL in literacy development, focusing on individual differences among beginning readers. Instead of using an artificial task to estimate SL abilities, our approach identifies individual differences in children's reliance on statistical regularities as reflected by actual reading behavior. We specifically focus on individuals' reliance on regularities in the mapping between print and speech versus associations between print and meaning in a word naming task. We present data from 399 children, showing that those whose oral naming performance is impacted more by print-speech regularities and less by associations between print and meaning have better reading skills. These findings suggest that a key route by which SL mechanisms impact developing reading abilities is via their role in the assimilation of sub-lexical regularities between printed and spoken language -and more generally, in detecting regularities that are more reliable than others. We discuss the implications of our findings to both SL and reading theories.

Entities:  

Keywords:  Individual differences; Print-speech regularities; Reading acquisition; Statistical learning

Year:  2020        PMID: 32694882      PMCID: PMC7373223          DOI: 10.1016/j.jml.2020.104145

Source DB:  PubMed          Journal:  J Mem Lang        ISSN: 0749-596X            Impact factor:   3.059


  60 in total

1.  Comparing naming, lexical decision, and eye fixation times: word frequency effects and individual differences.

Authors:  H H Schilling; K Rayner; J I Chumbley
Journal:  Mem Cognit       Date:  1998-11

2.  Random effects structure for confirmatory hypothesis testing: Keep it maximal.

Authors:  Dale J Barr; Roger Levy; Christoph Scheepers; Harry J Tily
Journal:  J Mem Lang       Date:  2013-04       Impact factor: 3.059

Review 3.  The multi-component nature of statistical learning.

Authors:  Joanne Arciuli
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2017-01-05       Impact factor: 6.237

4.  The Role of Statistical Learning in Word Reading and Spelling Development: More Questions than Answers.

Authors:  Amy M Elleman; Laura M Steacy; Donald L Compton
Journal:  Sci Stud Read       Date:  2018-12-02

5.  Development and Prediction of Context-Dependent Vowel Pronunciation in Elementary Readers.

Authors:  Laura M Steacy; Donald L Compton; Yaacov Petscher; James D Elliott; Kathryn Smith; Jay G Rueckl; Oliver Sawi; Stephen J Frost; Kenneth R Pugh
Journal:  Sci Stud Read       Date:  2018-05-15

Review 6.  Statistical learning and dyslexia: a systematic review.

Authors:  Xenia Schmalz; Gianmarco Altoè; Claudio Mulatti
Journal:  Ann Dyslexia       Date:  2016-10-20

7.  Regularity effects in word naming: what are they?

Authors:  M J Cortese; G B Simpson
Journal:  Mem Cognit       Date:  2000-12

Review 8.  Statistical Learning, Implicit Learning, and First Language Acquisition: A Critical Evaluation of Two Developmental Predictions.

Authors:  Inbal Arnon
Journal:  Top Cogn Sci       Date:  2019-05-05

9.  Using information-theoretic measures to characterize the structure of the writing system: the case of orthographic-phonological regularities in English.

Authors:  Noam Siegelman; Devin M Kearns; Jay G Rueckl
Journal:  Behav Res Methods       Date:  2020-06

10.  Triangulation of the neurocomputational architecture underpinning reading aloud.

Authors:  Paul Hoffman; Matthew A Lambon Ralph; Anna M Woollams
Journal:  Proc Natl Acad Sci U S A       Date:  2015-06-29       Impact factor: 11.205

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  5 in total

1.  How you read affects what you gain: Individual differences in the functional organization of the reading system predict intervention gains in children with reading disabilities.

Authors:  Noam Siegelman; Jay G Rueckl; Mark van den Bunt; Jan C Frijters; Jason D Zevin; Maureen W Lovett; Mark S Seidenberg; Kenneth R Pugh; Robin D Morris
Journal:  J Educ Psychol       Date:  2021-09-23

2.  Are people consistent when reading nonwords aloud on different occasions?

Authors:  Anastasia Ulicheva; Max Coltheart; Oxana Grosseck; Kathleen Rastle
Journal:  Psychon Bull Rev       Date:  2021-05-13

3.  Neural correlates of sequence learning in children with developmental dyslexia.

Authors:  Martina Hedenius; Jonas Persson
Journal:  Hum Brain Mapp       Date:  2022-04-18       Impact factor: 5.399

4.  Theory-driven classification of reading difficulties from fMRI data using Bayesian latent-mixture models.

Authors:  Noam Siegelman; Mark R van den Bunt; Jason Chor Ming Lo; Jay G Rueckl; Kenneth R Pugh
Journal:  Neuroimage       Date:  2021-08-17       Impact factor: 6.556

5.  Structural brain dynamics across reading development: A longitudinal MRI study from kindergarten to grade 5.

Authors:  Thanh Van Phan; Diana Sima; Dirk Smeets; Pol Ghesquière; Jan Wouters; Maaike Vandermosten
Journal:  Hum Brain Mapp       Date:  2021-07-01       Impact factor: 5.038

  5 in total

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