Hostname: page-component-8448b6f56d-42gr6 Total loading time: 0 Render date: 2024-04-19T01:25:38.893Z Has data issue: false hasContentIssue false
  • English
  • Français

Differentiating word learning processes may yield new insights – a commentary on Stoel-Gammon's ‘Relationships between lexical and phonological development in young children’*

Published online by Cambridge University Press:  18 October 2010

HOLLY L. STORKEL
HOLLY L. STORKEL*
Affiliation:
University of Kansas
*
Address for correspondence: Holly Storkel, PhD, Associate Professor, Department of Speech-Language-Hearing: Sciences and Disorders, University of Kansas, 3001 Dole Human Development Center, 1000 Sunnyside Avenue, Lawrence, KS 66045-7555. e-mail: hstorkel@ku.edu
Get access Rights & Permissions [Opens in a new window]

Extract

Stoel-Gammon (this issue) states that ‘from birth to age 2 ; 6, the developing phonological system affects lexical acquisition to a greater degree than lexical factors affect phonological development’ (this issue). This conclusion is based on a wealth of data; however, the available data are somewhat limited in scope, focusing on rather holistic measures of the phonological and lexical systems (e.g. production accuracy, number of words known). Stoel-Gammon suggests a number of important avenues to pursue, but does not discuss a critical one that is emerging in the broader literature on word learning. Specifically, recent connectionist models and adult word learning research provide evidence that greater differentiation of the cognitive processes that underlie word learning yields new insights (Leach & Samuel, 2007). This approach may be fruitful for future investigations of the relationship between phonological and lexical development in young children.

Type
Review Article and Commentaries
Information
Journal of Child Language , Volume 38 , Issue 1 , January 2011 , pp. 51 - 55
Copyright
Copyright © Cambridge University Press 2010

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

[*]

The research described in this commentary was supported by NIH Grant DC 08095.

References

REFERENCES

Carpenter, G. A. & Grossberg, S. (1987). A massively parallel architecture for a self-organizing neural pattern recognition machine. Computer, Vision, Graphics, and Image Processing 37, 54–115.Google Scholar
Davis, M. H. & Gaskell, M. G. (2009). A complementary systems account of word learning: neural and behavioural evidence. Philosophical Transactions of the Royal Society of London, Series B, Biological Science 364, 3773–800.CrossRefGoogle ScholarPubMed
Dumay, N. & Gaskell, M. G. (2007). Sleep-associated changes in the mental representation of spoken words. Psychological Science 18, 35–39.Google Scholar
Edwards, J., Beckman, M. & Munson, B. (2004). The interaction between vocabulary size and phonotactic probability effects on children's production accuracy and fluency in nonword repetition. Journal of Speech, Language and Hearing Research 47, 421–36.CrossRefGoogle ScholarPubMed
Gaskell, M. G. & Dumay, N. (2003). Lexical competition and the acquisition of novel words. Cognition 89, 105–132.Google Scholar
Gathercole, S. E., Frankish, C. R., Pickering, S. J. & Peaker, S. (1999). Phonotactic influences on short-term memory. Journal of Experimental Psychology: Learning, Memory, and Cognition 25, 84–95.Google ScholarPubMed
Hoover, J. R., Storkel, H. L. & Hogan, T. P. (2010). A cross-sectional comparison of the effects of phonotactic probability and neighborhood density on word learning by preschool children. Journal of Memory and Language 63, 100–116.CrossRefGoogle ScholarPubMed
Leach, L. & Samuel, A. G. (2007). Lexical configuration and lexical engagement: when adults learn new words. Cognitive Psychology 55, 306–353.CrossRefGoogle ScholarPubMed
Li, P., Farkas, I. & MacWhinney, B. (2004). Early lexical development in a self-organizing neural network. Neural Networks 17, 1345–62.Google Scholar
Roodenrys, S. & Hinton, M. (2002). Sublexical or lexical effects on serial recall of nonwords? Journal of Experimental Psychology: Learning, Memory, and Cognition 28, 29–33.Google ScholarPubMed
Storkel, H. L. & Hoover, J. R. (2010). An on-line calculator to compute phonotactic probability and neighborhood density based on child corpora of spoken American English. Behavior Research Methods 42, 497–506.Google Scholar
Storkel, H. L. & Lee, S. Y. (in press). The independent effects of phonotactic probability and neighborhood density on lexical acquisition by preschool children. Language and Cognitive Processes.Google Scholar
Storkel, H. L., Maekawa, J. & Hoover, J. R. (2010). Differentiating the effects of phonotactic probability and neighborhood density on vocabulary comprehension and production: A comparison of preschool children with versus without phonological delays. Journal of Speech, Language, and Hearing Research 53, 933–49.CrossRefGoogle ScholarPubMed
Tamminen, J. & Gaskell, M. G. (2008). Newly learned spoken words show long-term lexical competition effects. Quarterly Journal of Experimental Psychology 61, 361–71.CrossRefGoogle ScholarPubMed
Thomson, J. M., Richardson, U. & Goswami, U. (2005). Phonological similarity neighborhoods and children's short-term memory: typical development and dyslexia. Memory & Cognition 33, 1210–19.CrossRefGoogle ScholarPubMed
Thorn, A. S. & Frankish, C. R. (2005). Long-term knowledge effects on serial recall of nonwords are not exclusively lexical. Journal of Experimental Psychology: Learning, Memory, and Cognition 31, 729–35.Google Scholar