Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 287

The DOI matches its Crossref record; 103 of the 103 references it cites were found in a registry or an index.

Language learning, socioeconomic status, and child‐directed speech

Open access
Schwab, Jessica F., Lew‐Williams, Casey·2016·WIREs Cognitive Science
DOI 10.1002/wcs.1393
Open this paper in CoChat — free account

Abstract

Young children's language experiences and language outcomes are highly variable. Research in recent decades has focused on understanding the extent to which family socioeconomic status (SES) relates to parents’ language input to their children and, subsequently, children's language learning. Here, we first review research demonstrating differences in the quantity and quality of language that children hear across low‐, mid‐, and high‐SES groups, but also—and perhaps more importantly—research showing that differences in input and learning also exist within SES groups. Second, in order to better understand the defining features of ‘high‐quality’ input, we highlight findings from laboratory studies examining specific characteristics of the sounds, words, sentences, and social contexts of child‐directed speech (CDS) that influence children's learning. Finally, after narrowing in on these particular features of CDS, we broaden our discussion by considering family and community factors that may constrain parents’ ability to participate in high‐quality interactions with their young children. A unification of research on SES and CDS will facilitate a more complete understanding of the specific means by which input shapes learning, as well as generate ideas for crafting policies and programs designed to promote children's language outcomes.WIREs Cogn Sci 2016, 7:264–275. doi: 10.1002/wcs.1393 This article is categorized under:Linguistics > Language Acquisition Psychology > Language

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1002/wcs.1393

Cites

103 of 103 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Cited by

See all 287

Metadata

Authors
Schwab, J. F., & Lew‐Williams, C.
Venue
WIREs Cognitive Science
Publisher
Wiley
Published
2016-05-19
Volume
7
Issue
4
Pages
264-275
ISSN
  • 1939-5078 (ISSN-L)
  • 1939-5086
DOI
10.1002/wcs.1393
OpenAlex
W2395225233
Cited by
287
References
103
FWCI
19.75
Type
journal article
Language
en
Open access
green

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.