Book contents
- The Cambridge Handbook of Dyslexia and Dyscalculia
- The Cambridge Handbook of Dyslexia and Dyscalculia
- Copyright page
- Contents
- Figures and Tables
- Contributors
- Acknowledgements
- General Introduction
- Part I Theoretical Frameworks and Computational Models
- 1 Theories of Dyslexia
- 2 Theories of Dyscalculia
- 3 Computational Models of Reading and Mathematical Difficulties
- Summary: Theoretical Frameworks and Computational Models
- Part II Cognitive Profiles and Behavioural Manifestations
- Part III Genetic and Environmental Influences
- Part IV Neurodevelopmental Foundations
- Part V Gender, Ethnicity, and Socioeconomic Background
- Part VI Cultural Unity and Diversity
- Part VII Early Prediction
- Part VIII Intervention and Compensation
- Part IX Best Practice – Diagnostics and Prevention
- Part X Best Practice – Schooling and Educational Policy
- General Summary
- References
- Index
- References
3 - Computational Models of Reading and Mathematical Difficulties
from Part I - Theoretical Frameworks and Computational Models
Published online by Cambridge University Press: 28 July 2022
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Book contents
- The Cambridge Handbook of Dyslexia and Dyscalculia
- The Cambridge Handbook of Dyslexia and Dyscalculia
- Copyright page
- Contents
- Figures and Tables
- Contributors
- Acknowledgements
- General Introduction
- Part I Theoretical Frameworks and Computational Models
- 1 Theories of Dyslexia
- 2 Theories of Dyscalculia
- 3 Computational Models of Reading and Mathematical Difficulties
- Summary: Theoretical Frameworks and Computational Models
- Part II Cognitive Profiles and Behavioural Manifestations
- Part III Genetic and Environmental Influences
- Part IV Neurodevelopmental Foundations
- Part V Gender, Ethnicity, and Socioeconomic Background
- Part VI Cultural Unity and Diversity
- Part VII Early Prediction
- Part VIII Intervention and Compensation
- Part IX Best Practice – Diagnostics and Prevention
- Part X Best Practice – Schooling and Educational Policy
- General Summary
- References
- Index
- References
Summary
Computational modelling is a powerful tool in cognitive science to evaluate or compare existing theories and to make novel experimental predictions. In contrast to the vague formulation of traditional verbal theories (e.g., box-and-arrow models), computational models need to be formally explicit in any implementational detail and can produce accurate simulations of human performance. Computational modelling has many different flavours that reflect distinct theoretical approaches to understanding human cognition (see McClelland 2009, for a review).
- Type
- Chapter
- Information
- The Cambridge Handbook of Dyslexia and Dyscalculia , pp. 45 - 60Publisher: Cambridge University PressPrint publication year: 2022
References
Suggestions for Further Reading
Harm, M. W., and Seidenberg, M. S.. 1999. ‘Phonology, Reading Acquisition, and Dyslexia: Insights from Connectionist Models’. Psychological Review, 106 (3): 491–528.CrossRefGoogle ScholarPubMed
Perry, C., Zorzi, M., and Ziegler, J. C.. 2019. ‘Understanding Dyslexia Through Personalized Large-Scale Computational Models’. Psychological Science, 30: 386–95.CrossRefGoogle ScholarPubMed
Testolin, A., Zou, W. Y., and McClelland, J. L.. 2020. ‘Numerosity Discrimination in Deep Neural Networks: Initial Competence, Developmental Refinement and Experience Statistics’. Developmental Science, 23 (5): e12940.Google Scholar
Ziegler, J. C., Perry, C., and Zorzi, M.. 2020. ‘Learning to Read and Dyslexia: From Theory to Intervention Through Personalized Computational Models’. Current Directions in Psychological Science, 29 (3): 293–300.CrossRefGoogle ScholarPubMed
Zorzi, M., and Testolin, A.. 2018. ‘An Emergentist Perspective on the Origin of Number Sense’. Philosophical Transactions of the Royal Society B: Biological Sciences, 373 (1740): 20170043.CrossRefGoogle Scholar
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