Exploring the relations between oral language and reading instruction in a computational model of reading

Ya Ning Chang, J. S.H. Taylor, Kathleen Rastle, Padraic Monaghan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

To become a proficient reader, children have to learn mappings between print, sound and meaning. There is debate over whether reading instruction should focus on the relations between print and sound, as in phonics, or on the relationship between print and meaning, as in sight word reading. In a study where participants learned a novel artificial orthography, Taylor, Davis and Rastle (2017) compared print to sound focused or print to meaning focused reading training, demonstrating that sound training was superior for learning to read. However, a benefit from sound focused training is likely dependent on prior acquisition of effective sound to meaning relations of words. To explore this issue, we developed a connectionist model of reading. We exposed the model to a sound or a meaning focused training, but varied the model's pre-acquired oral language skills. The simulation results showed that proficiency in oral language is a determinant of the advantage of print to sound focused reading training, suggesting that reading training should address both oral language skills and print to sound mappings.

Original languageEnglish
Title of host publicationCogSci 2017 - Proceedings of the 39th Annual Meeting of the Cognitive Science Society
Subtitle of host publicationComputational Foundations of Cognition
PublisherThe Cognitive Science Society
Pages1740-1745
Number of pages6
ISBN (Electronic)9780991196760
Publication statusPublished - 2017
Event39th Annual Meeting of the Cognitive Science Society: Computational Foundations of Cognition, CogSci 2017 - London, United Kingdom
Duration: 2017 Jul 262017 Jul 29

Publication series

NameCogSci 2017 - Proceedings of the 39th Annual Meeting of the Cognitive Science Society: Computational Foundations of Cognition

Conference

Conference39th Annual Meeting of the Cognitive Science Society: Computational Foundations of Cognition, CogSci 2017
Country/TerritoryUnited Kingdom
CityLondon
Period17-07-2617-07-29

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Science Applications
  • Human-Computer Interaction
  • Cognitive Neuroscience

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