Effects of Input Consistency on Children’s Cross-Situational Statistical Learning of Words and Morphophonological Rules

Children learn linguistic structures from the input they receive. Their learning may depend on several factors such as children’s sensitivity to structure in the input, prior language experience, and the consistency of linguistic structures in the input. In this study, we investigated how inconsistent input (i.e., substitution errors) in an artificial language affects 7 to 11-year-old Dutch-speaking children’s learning of words and rules. Using a cross-situational statistical learning task (CSL task), we assessed children’s learning of label–referent pairs (word learning) and their generalization of two morphophonological rules. Eighty-nine children were randomly allocated to three input conditions: a fully consistent input condition (n = 31), a 12.5% inconsistent input condition (n = 32), and a 25% inconsistent input condition (n = 26). In the inconsistent input conditions, children were exposed to substitution errors, respectively, 12.5% and 25% of the time. We found evidence that substitution errors in children’s language input hindered their cross-situational statistical language learning. While we have evidence that children learned the words in our artificial language, we have no evidence that children—regardless of input condition—detected the morphophonological rules. This study eventually may inform us on how differences in the quality of children’s language environments (arising from, e.g., speaker variability and language proficiency) affect their language learning.

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Publication Details

Journal
Languages
Published
2025-03-14
DOI
https://doi.org/10.3390/languages10030052
Primary Topic
Child and Animal Learning Development
Type
article
Field-Weighted Citation Impact
0.00

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article

Effects of Input Consistency on Children’s Cross-Situational Statistical Learning of Words and Morphophonological Rules

Judith Rispens, Imme Lammertink, Merel van Witteloostuijn, Josje Verhagen et al.
Languages
Child and Animal Learning Development
article

Effects of Input Consistency on Children’s Cross-Situational Statistical Learning of Words and Morphophonological Rules

Judith Rispens, Imme Lammertink, Merel van Witteloostuijn, Josje Verhagen, Marica Savarino
article en

Abstract

Children learn linguistic structures from the input they receive. Their learning may depend on several factors such as children’s sensitivity to structure in the input, prior language experience, and the consistency of linguistic structures in the input. In this study, we investigated how inconsistent input (i.e., substitution errors) in an artificial language affects 7 to 11-year-old Dutch-speaking children’s learning of words and rules. Using a cross-situational statistical learning task (CSL task), we assessed children’s learning of label–referent pairs (word learning) and their generalization of two morphophonological rules. Eighty-nine children were randomly allocated to three input conditions: a fully consistent input condition (n = 31), a 12.5% inconsistent input condition (n = 32), and a 25% inconsistent input condition (n = 26). In the inconsistent input conditions, children were exposed to substitution errors, respectively, 12.5% and 25% of the time. We found evidence that substitution errors in children’s language input hindered their cross-situational statistical language learning. While we have evidence that children learned the words in our artificial language, we have no evidence that children—regardless of input condition—detected the morphophonological rules. This study eventually may inform us on how differences in the quality of children’s language environments (arising from, e.g., speaker variability and language proficiency) affect their language learning.

LanguagesVol. 10(3)
Radboud University Nijmegen (NL), Utrecht University (NL), Netherlands Youth Institute (NL), University of Amsterdam (NL)
Universiteit Utrecht, Amsterdam Brain and Cognition
Openalex Percentile: Top 95%
Child and Animal Learning Development
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