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Related Experiment Videos

Children's overregularization of English plurals: a quantitative analysis

G F Marcus1

  • 1Department of Psychology, University of Massachusetts, Amherst 01003, USA.

Journal of Child Language
|June 1, 1995
PubMed
Summary

Children rarely overregularize noun plurals, preferring correct forms. This pattern, similar to past tense development, challenges connectionist models and supports rule-based language acquisition theories.

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Area of Science:

  • Linguistics
  • Developmental Psychology
  • Cognitive Science

Background:

  • Children's language acquisition involves learning grammatical rules and exceptions.
  • Overregularization errors (e.g., "foots" instead of "feet") provide insights into this process.
  • Comparing connectionist and symbolic models is crucial for understanding language development.

Purpose of the Study:

  • To quantitatively analyze children's noun plural overregularizations.
  • To compare noun plural overregularization with past tense overregularization.
  • To evaluate connectionist and symbolic models of language acquisition based on these findings.

Main Methods:

  • Analysis of noun plural overregularization in the speech of 10 English-speaking children (aged 1;3 to 5;2).

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  • Utilized data from the CHILDES database.
  • Calculated the rate of noun overregularization and compared it to past tense overregularization rates.

    • Main Results:

    • Children exhibit a low rate of noun overregularization (mean = 8.5%), preferring correct irregular forms.
    • Noun plural overregularization rates are comparable to past tense overregularization rates.
    • Both noun plurals and past tenses show a U-shaped developmental curve, with correct irregulars appearing before overregularized forms.

    Conclusions:

    • Overregularization patterns in noun plurals and past tenses suggest similar underlying cognitive processes.
    • Findings challenge purely connectionist models of language acquisition.
    • Results align with models positing a default rule for regulars and lexical retrieval for irregulars, such as the blocking-and-retrieval-failure model.