Artificial language learning in adults and children

Folia, Vasiliki; Uddén, Julia; De Vries, Meinou; Forkstam, Christian; Petersson, Karl Magnus

doi:10.1111/j.1467-9922.2010.00606.x

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Artificial language learning in adults and children

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Folia, Vasiliki
Neurobiology of Language Group, MPI for Psycholinguistics, Max Planck Society;
Radboud University;
Stockholm Brain Institute;

/persons/resource/persons186

Uddén, Julia
Neurobiology of Language Group, MPI for Psycholinguistics, Max Planck Society;
Radboud University;
Stockholm Brain Institute;

/persons/resource/persons1204

De Vries, Meinou
Neurobiology of Language Group, MPI for Psycholinguistics, Max Planck Society;
Unification, MPI for Psycholinguistics, Max Planck Society;

/persons/resource/persons59

Forkstam, Christian
Neurobiology of Language Group, MPI for Psycholinguistics, Max Planck Society;
Radboud University;
Stockholm Brain Institute;
Universida do Algarve;

/persons/resource/persons147

Petersson, Karl Magnus
Neurobiology of Language Group, MPI for Psycholinguistics, Max Planck Society;
Unification, MPI for Psycholinguistics, Max Planck Society;
Radboud University;
Stockholm Brain Institute;
Universida do Algarve;

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Folia-LanguageLearning10.pdf
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引用

Folia, V., Uddén, J., De Vries, M., Forkstam, C., & Petersson, K. M. (2010). Artificial language learning in adults and children. Language learning, 60(s2), 188-220. doi:10.1111/j.1467-9922.2010.00606.x.

引用: https://hdl.handle.net/11858/00-001M-0000-0012-CF75-3

要旨

This article briefly reviews some recent work on artificial language learning in children and adults. The final part of the article is devoted to a theoretical formulation of the language learning problem from a mechanistic neurobiological viewpoint and we show that it is logically possible to combine the notion of innate language constraints with, for example, the notion of domain general learning mechanisms. A growing body of empirical evidence suggests that the mechanisms involved in artificial language learning and in structured sequence processing are shared with those of natural language acquisition and natural language processing. Finally, by theoretically analyzing a formal learning model, we highlight Fodor’s insight that it is logically possible to combine innate, domain-specific constraints with domain-general learning mechanisms.