Evidence map›Paper›PMID 30120444›Full record

ReviewLanguage, speech, and hearing services in schools2018

Distributional Cues to Language Learning in Children With Intellectual Disabilities.

Sara T Kover

Abstract readReview
In one paragraph

Review in Language, speech, and hearing services in schools, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Sara T KoverDepartment of Speech and Hearing Sciences, University of Washington, Seattle.

Funding

Intellectual and Developmental Disabilities Research CenterU54HD083091 · NICHD · UNIVERSITY OF WASHINGTON · PI GARDEN, GWENN A · 2014 to 2019
$7.9M
Language and Learning in Boys with Fragile X SyndromeF31DC010959 · NIDCD · UNIVERSITY OF WISCONSIN-MADISON · PI KOVER, SARA TERESA · 2010 to 2011
$57k
NICHD NIH HHS U54 HD083091NIDCD NIH HHS F31 DC010959
6 · The paper itself

Abstract

Purpose: In typical development, distributional cues-patterns in input-are related to language acquisition processes. Statistical and implicit learning refer to the utilization of such cues. In children with intellectual disability, much less is known about the extent to which distributional cues are harnessed in mechanisms of language learning. Method: This tutorial presents what is known about the process of language learning in children with language impairments associated with different sources of intellectual disability: Williams syndrome, autism spectrum disorder, Down syndrome, and fragile X syndrome. Results: A broad view is taken on distributional cues relevant to language learning, including statistical learning (e.g., transitional probabilities) and other patterns that support lexical acquisition (e.g., sensitivities to sound patterns, cross-situational word learning) or relate to syntactic development (e.g., nonadjacent dependencies). Conclusions: Critical gaps in the literature are highlighted. Research in this area is especially limited for Down syndrome and fragile X syndrome. Future directions for taking learning theories into account in interventions for children with intellectual disability are discussed, with a focus on the importance of language input.

Indexed as

CuesLanguageLanguage DevelopmentLearningAdolescentAutism Spectrum DisorderChildChild, PreschoolHumansInfantIntellectual DisabilityLanguage DisordersVerbal Learning

Identifiers

PMID30120444
PMCPMC6198915

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.