Research
My research focuses on how children learn words, how children learn to combine words into sentences and how these processes can be supported by caregivers and early years practitioners. It uses a range of methods, including corpus analysis, behavioural experiments and computational modelling and has a strong cross-linguistic focus. It also includes work on children with language difficulties.
Example Project: Modelling the cross-linguistic pattern of verb-marking deficits in children with Developmental Language Disorder
Developmental Language Disorder (DLD) refers to ‘a significant deficit in language ability that cannot be attributed to hearing loss, low non-verbal intelligence or neurological damage’ (Leonard, 2014: 3). Research suggests that approximately 7% of the preschool-age population exhibit this kind of developmental profile, with boys more likely to be affected than girls - 8% versus 6%, respectively (Tomblin et al, 1997).
Children with DLD are not a homogeneous population, and may show deficits in a number of different ways, including phonology, word learning, morpho-syntax and pragmatics. However, they tend to show a particular deficit in the acquisition and use of verb morphology. Interestingly, however, the size and nature of this deficit varies across languages. For example, children with DLD learning English show large deficits in verb-marking relative to both age-matched and language-matched controls (Rice, Wexler & Hershberger, 1998); children with DLD learning German show large deficits in verb marking relative to age-matched controls, but only marginal deficits relative to language-matched controls (Rice, Noll & Grimm, 1997); and, children with DLD learning Spanish show only marginal deficits in verb marking relative to age-matched controls and no deficits relative to language-matched controls (Bedore & Leonard, 2005).
In this project, we are using corpus analysis and computational modelling techniques to investigate the nature of the deficit that underlies the cross-linguistic pattern of verb marking error in children with DLD. This will be done by modifying an existing computational model of language learning (MOSAIC), which has already been shown to simulate the pattern of verb marking error in typically developing children learning English, German and Spanish (Freudenthal, Pine, Aguado-Orea & Gobet, 2007; Freudenthal, Pine, Jones & Gobet, 2015). Additional mechanisms will be implemented in MOSAIC based on processes that have been argued to underlie the pattern of verb marking error in typically developing children and children with DLD learning English. These will include: 1) Defaulting on the basis of the relative frequency of different forms of the verb (Räsänen, Ambridge & Pine, 2014; Kueser, Leonard & Deevy, 2018); 2) Learning from inappropriate sentential contexts (Theakston, Lieven & Tomasello, 2003; Leonard, Fey, Deevy & Bredin-Oja, 2015) and 3) Producing telegraphic speech (Conti-Ramsden, Botting & Farragher, 2001) as a result of limited sequence learning ability (Hsu, Tomblin & Christiansen, 2014)
Models incorporating each of these mechanisms will be used to investigate a) the extent to which incorporating each mechanism improves MOSAIC’s fit to the cross-linguistic data on TD children, and b) the extent to which reducing the rate at which the effect of each mechanism decreases over development allows us to capture cross-linguistic variation in the pattern of verb marking deficit in children with DLD. Of particular interest will be whether it is possible to use exactly the same version of the model to simulate the large deficit in verb-marking in children with DLD learning English relative to language-matched controls, the much smaller deficit in verb marking in children with DLD learning German relative to language-matched controls, and the lack of any deficit in verb-marking in children with DLD learning Spanish relative to language-matched controls.
Research grants
The Centre for Language and Communicative Development.
ECONOMIC AND SOCIAL RESEARCH COUNCIL
September 2014 - October 2025
Child Language Development
MAX PLANCK GESELLSCHAFT ZUR FOERDERUNG DER WISSENSCHAFTEN E.V.(GERMANY)
December 2018 - August 2027
Story Starters
POSTCODE DREAM TRUST (UK)
April 2017 - March 2019
Developing a psychologically realistic generalisation mechanism within MOSAIC
ECONOMIC AND SOCIAL RESEARCH COUNCIL
July 2012 - June 2015
The formation and restriction of linguistic generalizations: Integrating experimental and computer-modelling approaches.
LEVERHULME TRUST (UK)
October 2011 - September 2014
The role of the agent in sentence comprehension by preschool children
ECONOMIC AND SOCIAL RESEARCH COUNCIL
November 2010 - October 2012
Modelling the cross-linguistic pattern of verb-marking and utterance-internal omission errors in MOSAIC using syllabified input
ECONOMIC AND SOCIAL RESEARCH COUNCIL
August 2008 - July 2011
Comparing two new single-process accounts of the restriction of argument-structure generalizations
ECONOMIC AND SOCIAL RESEARCH COUNCIL
July 2008 - June 2010
Modelling the cross-linguistic pattern of finiteness marking in declaratives and questions
ECONOMIC AND SOCIAL RESEARCH COUNCIL
June 2006 - May 2008
How do children restrict their linguistic generalizations? An empirical approach.
ECONOMIC AND SOCIAL RESEARCH COUNCIL
October 2005 - September 2006
Modelling the development of finiteness marking in English, German, and Spanish.
ECONOMIC AND SOCIAL RESEARCH COUNCIL
September 2004 - May 2006
Research collaborations
Professor Anna Theakston and Professor Gert Westermann
The ESRC International Centre for Language and Communicative Development
Universities of Manchester and Lancaster
Working with partners from across the world to transfrom our understanding of how childen learn to communicate with language
Dr Colin Bannard
Univeresity of Manchester
Using computational modelling to understand verb-marking errors in typically developing children and children with Developmental Language Disorder.
Dr Kirsten Abbot-Smith
The University of Kent at Canterbury
An ESRC-funded project focused on using eye-tracking measures to investigate children's comprehension of active and passive sentence structure.
Professor Caroline Rowland
The 0-5 project
Max Planck Institute for Psycholinguistics
Understanding individual differences in children's language development
Professor Danielle Matthews
The University of Sheffield
Developing low-intensity digital interventions to promote language-boosting behaviour in caregivers and support language development from 0 to 5.
Professor Fernand Gobet
London School of Economics and Political Science
An ESRC-funded project that uses computational modelling techniques to investigate segmentation and early word learning