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Assessing the impact of conversational overlap in content on child language growth*

Published online by Cambridge University Press:  20 April 2017

ELIZABETH S. CHE*
Affiliation:
The College of Staten Island and The Graduate Center, CUNY
PATRICIA J. BROOKS*
Affiliation:
The College of Staten Island and The Graduate Center, CUNY
MARIA F. ALARCON
Affiliation:
Long Island University
FRANCIS D. YANNACO
Affiliation:
The Graduate Center, CUNY
SEAMUS DONNELLY
Affiliation:
Australian National University
*
Address for correspondence: Elizabeth Che or Patricia Brooks, Department of Psychology, College of Staten Island, CUNY, 2800 Victory Blvd. 4S-108, Staten Island, NY 10314. e-mail: eche@gradcenter.cuny.edu; patricia.brooks@csi.cuny.edu
Address for correspondence: Elizabeth Che or Patricia Brooks, Department of Psychology, College of Staten Island, CUNY, 2800 Victory Blvd. 4S-108, Staten Island, NY 10314. e-mail: eche@gradcenter.cuny.edu; patricia.brooks@csi.cuny.edu

Abstract

When engaged in conversation, both parents and children tend to re-use words that their partner has just said. This study explored whether proportions of maternal and/or child utterances that overlapped in content with what their partner had just said contributed to growth in mean length of utterance (MLU), developmental sentence score, and vocabulary diversity over time. We analyzed the New England longitudinal corpus from the CHILDES database, comprising transcripts of mother–child conversations at 14, 20, and 32 months, using the CHIP command to compute proportions of utterances with overlapping content. Rates of maternal overlap, but not child overlap, at earlier time-points predicted child language outcomes at later time-points, after controlling for earlier child MLU. We suggest that maternal overlap plays a formative role in child language development by providing content that is immediately relevant to what the child has in mind.

Type
Articles
Copyright
Copyright © Cambridge University Press 2017 

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Footnotes

[*]

Preliminary analyses were presented at the 2015 Boston University Conference on Language Development. We thank Brian MacWhinney for his assistance with the CLAN commands and David Rindskopf for his advice on the statistical analysis. First authorship is shared by Elizabeth S. Che and Patricia J. Brooks.

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