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Literacy and early language development: Insights from computational modelling

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Literacy and early language development: Insights from computational modelling. / Monaghan, Padraic.
In: Journal of Child Language, 22.03.2023.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

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Monaghan P. Literacy and early language development: Insights from computational modelling. Journal of Child Language. 2023 Mar 22. Epub 2023 Mar 22. doi: 10.1017/S0305000923000193

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Bibtex

@article{db205cf30476442cbb53e753bea8b88c,
title = "Literacy and early language development: Insights from computational modelling",
abstract = "Computational models of reading have tended to focus on the cognitive requirements of mapping among written, spoken, and meaning representations of individual words in adult readers. Consequently, the alignment of these computational models with behavioural studies of reading development has been limited. Computational models of reading have provided us with insights into the architecture of the reading system, and these have recently been extended to investigate literacy development, and the early language skills that influence children{\textquoteright}s reading. These models show us: how learning to read builds on early language skills, why various reading interventions might be more or less effective for different children, and how reading develops across different languages and writing systems. Though there is growing alignment between descriptive models of reading behaviour and computational models, there remains a gap, and I lay out the groundwork for how translation may become increasingly effective through future modelling work.",
author = "Padraic Monaghan",
year = "2023",
month = mar,
day = "22",
doi = "10.1017/S0305000923000193",
language = "English",
journal = "Journal of Child Language",
issn = "0305-0009",
publisher = "Cambridge University Press",

}

RIS

TY - JOUR

T1 - Literacy and early language development: Insights from computational modelling

AU - Monaghan, Padraic

PY - 2023/3/22

Y1 - 2023/3/22

N2 - Computational models of reading have tended to focus on the cognitive requirements of mapping among written, spoken, and meaning representations of individual words in adult readers. Consequently, the alignment of these computational models with behavioural studies of reading development has been limited. Computational models of reading have provided us with insights into the architecture of the reading system, and these have recently been extended to investigate literacy development, and the early language skills that influence children’s reading. These models show us: how learning to read builds on early language skills, why various reading interventions might be more or less effective for different children, and how reading develops across different languages and writing systems. Though there is growing alignment between descriptive models of reading behaviour and computational models, there remains a gap, and I lay out the groundwork for how translation may become increasingly effective through future modelling work.

AB - Computational models of reading have tended to focus on the cognitive requirements of mapping among written, spoken, and meaning representations of individual words in adult readers. Consequently, the alignment of these computational models with behavioural studies of reading development has been limited. Computational models of reading have provided us with insights into the architecture of the reading system, and these have recently been extended to investigate literacy development, and the early language skills that influence children’s reading. These models show us: how learning to read builds on early language skills, why various reading interventions might be more or less effective for different children, and how reading develops across different languages and writing systems. Though there is growing alignment between descriptive models of reading behaviour and computational models, there remains a gap, and I lay out the groundwork for how translation may become increasingly effective through future modelling work.

U2 - 10.1017/S0305000923000193

DO - 10.1017/S0305000923000193

M3 - Journal article

JO - Journal of Child Language

JF - Journal of Child Language

SN - 0305-0009

ER -