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What counts as effective input for word learning?*

Published online by Cambridge University Press:  10 May 2012

LAURA A. SHNEIDMAN*
Affiliation:
University of Chicago
MICHELLE E. ARROYO
Affiliation:
University of Chicago
SUSAN C. LEVINE
Affiliation:
University of Chicago
SUSAN GOLDIN-MEADOW
Affiliation:
University of Chicago
*
Address for correspondence: Laura Shneidman, Center for Early Childhood Research, University of Chicago, 5848 S. University Ave., Chicago, IL, 60637. e-mail: lauras@uchicago.edu
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Abstract

The talk children hear from their primary caregivers predicts the size of their vocabularies. But children who spend time with multiple individuals also hear talk that others direct to them, as well as talk not directed to them at all. We investigated the effect of linguistic input on vocabulary acquisition in children who routinely spent time with one vs. multiple individuals. For all children, the number of words primary caregivers directed to them at age 2 ; 6 predicted vocabulary size at age 3 ; 6. For children who spent time with multiple individuals, child-directed words from all household members also predicted later vocabulary and accounted for more variance in vocabulary than words from primary caregivers alone. Interestingly, overheard words added no predictive value to the model. These findings suggest that speech directed to children is important for early word learning, even in households where a sizable proportion of input comes from overheard speech.

Information

Type
Brief Research Reports
Copyright
Copyright © Cambridge University Press 2012
Figure 0

Table 1. The distribution of single-speaker and multi-speaker families by ethnicity and income

Figure 1

Fig. 1. The total number of words (tokens, top graph) and total number of different words (types, bottom graph) that children in single-speaker and multi-speaker families heard in speech directed to them by their primary caregiver, in speech directed to them by others in the household, and in speech that they overheard at age 2 ; 6.

Figure 2

Table 2. Regression models using input measures at 2 ; 6 (word tokens) to predict children's receptive vocabulary skills at 3 ; 6 (PPVT) in the multi-speaker group (n=15)

Figure 3

Table 3. Regression models using input measures at 2 ; 6 (word types) to predict children's receptive vocabulary skills at 3 ; 6 (PPVT) in the multi-speaker group (n=15)