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Orthographic influences on division of labor in learning to read Chinese and English: Insights from computational modeling*

Published online by Cambridge University Press:  14 September 2012

JIANFENG YANG ,
HUA SHU ,
BRUCE D. McCANDLISS  and
JASON D. ZEVIN
JIANFENG YANG
Affiliation:
Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China
HUA SHU
Affiliation:
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
BRUCE D. McCANDLISS
Affiliation:
Department of Psychology, Vanderbilt University Peabody College of Education and Human Development, Nashville, TN 37240, USA
JASON D. ZEVIN*
Affiliation:
Sackler Institute for Developmental Psychobiology, Weill Cornell Medical College, NY 10021, USA
*
Address for correspondence: Jason D. Zevin, Box 140, Sackler Institute for Developmental Psychobiology, Weill Cornell Medical College, New York, NY 10021, USA[email protected]
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Abstract

Learning to read in any language requires learning to map among print, sound and meaning. Writing systems differ in a number of factors that influence both the ease and the rate with which reading skill can be acquired, as well as the eventual division of labor between phonological and semantic processes. Further, developmental reading disability manifests differently across writing systems, and may be related to different deficits in constitutive processes. Here we simulate some aspects of reading acquisition in Chinese and English using the same model for both writing systems. The contribution of semantic and phonological processing to literacy acquisition in the two languages is simulated, including specific effects of phonological and semantic deficits. Further, we demonstrate that similar patterns of performance are observed when the same model is trained on both Chinese and English as an “early bilingual”. The results are consistent with the view that reading skill is acquired by the application of statistical learning rules to mappings among print, sound and meaning, and that differences in the typical and disordered acquisition of reading skill between writing systems are driven by differences in the statistical patterns of the writing systems themselves, rather than differences in cognitive architecture of the learner.

Keywords

computational modelingreadingdyslexia
Type
Research Article
Information
Bilingualism: Language and Cognition , Volume 16 , Issue 2: Computational Modeling of Bilingualism , April 2013 , pp. 354 - 366
Copyright
Copyright © Cambridge University Press 2012

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Footnotes

*

This research was supported by Open Research Fund of the State Key Laboratory of Cognitive Neuroscience and Learning (CNKOPZD1005, J.Y.), NSF of China 31171077 (J.Y.), 30870758 (H.S.) and the Fundamental Research Funds for the Central Universities (H.S.), NIH R01 HD06579, R01-HD067364 (J.D.Z.) and R01 DC007694 (B.D.M.), NSF REC 0337765 (B.D.M.). The authors wish to thank Ping Li and two anonymous reviewers for their helpful comments on this manuscript.

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