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Toward a model of multiple paths to language learning: Response to commentaries

Published online by Cambridge University Press:  28 September 2017

LARA J. PIERCE ,
FRED GENESEE ,
AUDREY DELCENSERIE  and
GARY MORGAN
LARA J. PIERCE*
Affiliation:
Boston Children's Hospital/Harvard Medical School
FRED GENESEE
Affiliation:
McGill University
AUDREY DELCENSERIE
Affiliation:
Université de Montréal
GARY MORGAN
Affiliation:
City University of London
*
ADDRESS FOR CORRESPONDENCE Lara J. Pierce, Division of Developmental Medicine, Boston Children's Hospital, 1 Autumn Street, Boston, MA 02115. E-mail: [email protected] or [email protected]
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Language learning, while seemingly effortless for young learners, is a complex process involving many interacting pieces, both within the child and in their language-learning environments, which can result in unique language learning trajectories and outcomes. How does the brain adjust to or accommodate the myriad variations that occur during this developmental process. How does it adapt and change over time? In our review, we proposed that the timing, quantity, and quality of children's early language experiences, particularly during an early sensitive period for the acquisition of phonology, shape the establishment of neural phonological representations that are used to establish and support phonological working memory (PWM). The efficiency of the PWM system in turn, we argued, influences the acquisition and processing of more complex aspects of language. In brief, we proposed that experience modulates later language outcomes through its early effects on PWM. We supported this claim by reviewing research from several unique groups of language learners who experience delayed exposure to language (children with cochlear implants [CI] or internationally adopted [IA] children, and children with either impoverished [signing deaf children with hearing parents)] or enriched [bilingual] early language experiences). By comparing PWM and language outcomes in these groups, we sought to highlight general patterns in language development that emerge based on variation in early language exposure. Moving forward, we also proposed that the language acquisition patterns in these groups, and others, can be used to understand how variability in early language input might affect the neural systems supporting language development and how this might affect language learning itself.

Type
Authors' Response
Information
Applied Psycholinguistics , Volume 38 , Issue 6 , November 2017 , pp. 1351 - 1362
Copyright
Copyright © Cambridge University Press 2017 

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References

REFERENCES

Abutalebi, J., & Green, D. (2007). Bilingual language production: The neurocognition of language representation and control. Journal of Neurolinguistics, 20, 242–275.Google Scholar
Aslin, R. N., & Newport, E. L. (2012). Statistical learning from acquiring specific items to forming general rules. Current Directions in Psychological Science, 21, 170–176.Google Scholar
Aslin, R. N., & Newport, E. L. (2014). Distributional language learning: Mechanisms and models of category formation. Language Learning, 64, 86–105.Google Scholar
Baddeley, A. (2012). Working memory: Theories, models, and controversies. Annual Review of Psychology, 63, 1–29.Google Scholar
Bialystok, E. (2017). The bilingual adaptation: How minds accommodate experience. Psychological Bulletin, 143, 233.Google Scholar
Coady, J. A., & Aslin, R. N. (2004). Young children's sensitivity to probabilistic phonotactics in the developing lexicon. Journal of Experimental Child Psychology, 89, 183–213.Google Scholar
Delcenserie, A., & Genesee, F. (2016). The effects of age of acquisition and bilingualism on verbal working memory. International Journal of Bilingualism. Advance online publication. doi:1177/1367006916639158 Google Scholar
Eichenbaum, H., & Cohen, N. J. (2004). From conditioning to conscious recollection: Memory systems of the brain (No. 35). Oxford: Oxford University Press.Google Scholar
Fernald, A., Marchman, V. A., & Weisleder, A. (2013). SES differences in language processing skill and vocabulary are evident at 18 months. Developmental Science, 16, 234–248.Google Scholar
Fisher, S. E., & DeFries, J. C. (2002). Developmental dyslexia: Genetic dissection of a complex cognitive trait. Nature Reviews Neuroscience, 3, 767–780.Google Scholar
Fox, K., & Wong, R. O. (2005). A comparison of experience-dependent plasticity in the visual and somatosensory systems. Neuron, 48, 465–477.Google Scholar
French, L. M., & O'Brien, I. (2008). Phonological memory and children's second language grammar learning. Applied Psycholinguistics, 29, 463–487. doi:10.1017/S0142716408080211 Google Scholar
Gathercole, S. E. (2006). Nonword repetition and word learning: The nature of the relationship. Applied Psycholinguistics, 27, 513–543.Google Scholar
Hart, B., & Risley, T. (1995). Meaningful differences in the everyday experience of young American children. Baltimore, MD: Paul H. Brookes.Google Scholar
Hoff, E. (2003). Causes and consequences of SES-related differences in parent-to-child speech. In Bornstein, M. & Bradley, R. H. (Eds.), Socioeconomic status, parenting, and child development. Mahwah, NJ: Erlbaum.Google Scholar
Keren-Portnoy, T., Vihman, M. M., DePaolis, R. A., Whitaker, C. J., & Williams, N. M. (2010). The role of vocal practice in constructing phonological working memory. Journal of Speech, Language, and Hearing Research, 53, 1280–1293.Google Scholar
MacDermot, K. D., Bonora, E., Sykes, N., Coupe, A. M., Lai, C. S., Vernes, S. C., . . . Fisher, S. E. (2005). Identification of FOXP2 truncation as a novel cause of developmental speech and language deficits. American Journal of Human Genetics, 76, 1074–1080.Google Scholar
MacKenzie, H., Curtin, S., & Graham, S. A. (2012). 12 month-olds’ phonotactic knowledge guides their word-object mappings. Child Development, 83, 1129–1136. doi:10.1111/j.1467-8624.2012.01764.x Google ScholarPubMed
Maye, J., Weiss, D. J., & Aslin, R. N. (2008). Statistical phonetic learning in infants: Facilitation and feature generalization. Developmental Science, 11, 122–134.Google Scholar
Maye, J., Werker, J. F., & Gerken, L. (2002). Infant sensitivity to distributional information can affect phonetic discrimination. Cognition, 82, B101–B111.Google Scholar
Messer, M. H., Leseman, P. P. M., Boom, J., & Mayo, A. Y. (2010). Phonotactic probability effect in nonword recall and its relationship with vocabulary in monolingual and bilingual preschoolers. Journal of Experimental Child Psychology, 105, 306–323.Google Scholar
Morton, J. B., & Harper, S. N. (2007). What did Simon say? Revisiting the bilingual advantage. Developmental Science, 10, 719–726.Google Scholar
Parra, M., Hoff, E., & Core, C. (2010). Relations among language exposure, phonological memory, and language development in Spanish-English bilingually developing 2-year olds. Journal of Experimental Child Psychology, 108, 113–125.Google Scholar
Pierce, L. J., Genesee, F., & Klein, D. (2016). Language loss or retention in internationally-adopted children: Neurocognitive implications for language learning. In Genesee, F. & Delcenserie, A. (Eds.), Starting over—The language development of internationally-adopted children (pp. 179–202). Amsterdam: John Benjamins.Google Scholar
Rowe, M. L. (2008). Child-directed speech: Relation to socioeconomic status, knowledge of child development and child vocabulary skill. Journal of Child Language, 35, 185–205.Google Scholar
Shibata, K., Sasaki, Y., Bang, J. W., Walsh, E. G., Machizawa, M. G., Tamaki, M., . . . Watanabe, T. (2017). Overlearning hyperstabilizes a skill by rapidly making neurochemical processing inhibitory-dominant. Nature Neuroscience, 20, 470–475.Google Scholar
Smith, N. V., & Tsimpli, I. M. (1995). The mind of a savant: Language learning and modularity. Oxford: Blackwell.Google Scholar
Smith, N., Tsimpli, I. M., Morgan, G., & Woll, B. (2010). Signs of the savant. Cambridge: Cambridge University Press.Google Scholar
Thorn, A. S. C., & Gathercole, S. E. (1999). Language-specific knowledge and short-term memory in bilingual and non-bilingual children. Quarterly Journal of Experimental Psychology Section A: Human Experimental Psychology, 52, 303–324.Google Scholar
Werker, J. F., & Hensch, T. K. (2015). Critical periods in speech perception: New directions. Psychology, 66, 173.Google Scholar
Werker, J. F., Yeung, H. H., & Yoshida, K. A. (2012). How do infants become experts at native-speech perception? Current Directions in Psychological Science, 21, 221–226.Google Scholar
Yoshida, K. A., Pons, F., Maye, J., & Werker, J. F. (2010). Distributional phonetic learning at 10 months of age. Infancy, 15, 420–433.Google Scholar