Redundant morphological marking facilitates children's learning of a novel construction

Shira Tal, Inbal Arnon

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

The presence of redundant marking in languages raises interesting questions about the balance of different pressures in language learning and use. Speakers tend to avoid redundant elements in production: omitting (or reducing) more predictable elements. At the same time, languages maintain different types of redundant marking, such as encoding thematic assignment by both word order and case marking. Why is redundancy found in languages even though speakers seem to avoid it? Here, we propose that redundant cues can facilitate learning. We test this hypothesis in an artificial language learning study with children, where either word order alone or both word order and case marking serve as cues for thematic assignment in a novel construction. Results show that children learned the redundant language better despite having to learn an additional morpheme. We discuss implications for the effect of different cognitive pressures on language change.

Original languageEnglish
Title of host publicationProceedings of the 41st Annual Meeting of the Cognitive Science Society
Subtitle of host publicationCreativity + Cognition + Computation, CogSci 2019
PublisherThe Cognitive Science Society
Pages2912-2918
Number of pages7
ISBN (Electronic)0991196775, 9780991196777
StatePublished - 2019
Event41st Annual Meeting of the Cognitive Science Society: Creativity + Cognition + Computation, CogSci 2019 - Montreal, Canada
Duration: 24 Jul 201927 Jul 2019

Publication series

NameProceedings of the 41st Annual Meeting of the Cognitive Science Society: Creativity + Cognition + Computation, CogSci 2019

Conference

Conference41st Annual Meeting of the Cognitive Science Society: Creativity + Cognition + Computation, CogSci 2019
Country/TerritoryCanada
CityMontreal
Period24/07/1927/07/19

Bibliographical note

Publisher Copyright:
© Cognitive Science Society: Creativity + Cognition + Computation, CogSci 2019.All rights reserved.

Keywords

  • artificial language learning
  • language acquisition
  • language evolution
  • redundancy

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