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Learning to Read and Dyslexia: From Theory to Intervention Through Personalized Computational Models
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In: ISSN: 0963-7214 ; EISSN: 1467-8721 ; Current Directions in Psychological Science ; https://hal-amu.archives-ouvertes.fr/hal-02566111 ; Current Directions in Psychological Science, Association for Psychological Science, 2020, pp.096372142091587. ⟨10.1177/0963721420915873⟩ (2020)
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Learning to Read and Dyslexia: From Theory to Intervention Through Personalized Computational Models
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In: Current Directions in Psychological Science, Vol. 29, no. 3 (Jun 2020), pp. 293-300 (2020)
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Learning to Read and Dyslexia: From Theory to Intervention Through Personalized Computational Models
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In: Curr Dir Psychol Sci (2020)
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Modeling the Variability of Developmental Dyslexia
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In: Developmental Dyslexia across Languages and Writing Systems ; https://hal-amu.archives-ouvertes.fr/hal-02308934 ; Developmental Dyslexia across Languages and Writing Systems, Cambridge University Press, pp.350-371, 2019, ⟨10.1017/9781108553377.016⟩ (2019)
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Understanding Dyslexia Through Personalized Large-Scale Computational Models ...
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Understanding Dyslexia Through Personalized Large-Scale Computational Models ...
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Understanding dyslexia through personalized large-scale computational models
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In: Psychological Science, Vol. 30, no. 3 (Feb 2019), pp. 386-395 (2019)
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Abstract:
Learning to read is foundational for literacy development, yet many children in primary school fail to become efficient readers despite normal intelligence and schooling. This condition, referred to as developmental dyslexia, has been hypothesized to occur because of deficits in vision, attention, auditory and temporal processes, and phonology and language. Here, we used a developmentally plausible computational model of reading acquisition to investigate how the core deficits of dyslexia determined individual learning outcomes for 622 children (388 with dyslexia). We found that individual learning trajectories could be simulated on the basis of three component skills related to orthography, phonology, and vocabulary. In contrast, single-deficit models captured the means but not the distribution of reading scores, and a model with noise added to all representations could not even capture the means. These results show that heterogeneity and individual differences in dyslexia profiles can be simulated only with a personalized computational model that allows for multiple deficits.
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URL: https://doi.org/10.1177/0956797618823540
http://hdl.handle.net/1959.3/447863
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Modeling the variability of developmental dyslexia
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In: Developmental dyslexia across languages and writing systems / Ludo Verhoeven, Charles Perfetti and Kenneth Pugh (eds.), pp. 350-371 (2019)
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Understanding Dyslexia Through Personalized Large-Scale Computational Models
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When silent letters say more than a thousand words: An implementation and evaluation of CDP plus plus in French
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In: ISSN: 0749-596X ; EISSN: 1096-0821 ; Journal of Memory and Language ; https://hal.archives-ouvertes.fr/hal-01432444 ; Journal of Memory and Language, Elsevier, 2014, 72, pp.98-115. ⟨10.1016/j.jml.2014.01.003⟩ (2014)
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CDP plus plus .Italian: Modelling Sublexical and Supralexical Inconsistency in a Shallow Orthography
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In: ISSN: 1932-6203 ; EISSN: 1932-6203 ; PLoS ONE ; https://hal.archives-ouvertes.fr/hal-01432442 ; PLoS ONE, Public Library of Science, 2014, 9 (4), ⟨10.1371/journal.pone.0094291⟩ (2014)
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When silent letters say more than a thousand words: an implementation and evaluation of CDP plus plus in French
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In: Journal of Memory and Language, Vol. 72 (Apr 2014), pp. 98-115 (2014)
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CDP plus plus. Italian: modelling sublexical and supralexical inconsistency in a shallow orthography
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In: PL o S One, Vol. 9, no. 4 (Apr 2014), article no. e94291 (2014)
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Modelling reading development through phonological decoding and self-teaching: Implications for dyslexia
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In: Philosophical Transactions of the Royal Society B: Biological Sciences, Vol. 369, no. 1634 (Dec 2014) (2014)
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CDP++.Italian: Modelling Sublexical and Supralexical Inconsistency in a Shallow Orthography
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Modelling reading development through phonological decoding and self-teaching: implications for dyslexia
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A computational and empirical investigation of graphemes in reading
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In: Cognitive Science, Vol. 37, no. 5 (Jul 2013), pp. 800-828 (2013)
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