Prediction and Word Learning in Young Children with Autism Spectrum Disorder
自闭症谱系障碍幼儿的预测和单词学习
基本信息
- 批准号:10605594
- 负责人:
- 金额:$ 4.68万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-09-01 至 2024-10-27
- 项目状态:已结题
- 来源:
- 关键词:4 year oldAddressAreaCharacteristicsChildCognitionCognitiveDataEnvironmentHyperplasiaImpairmentIndividual DifferencesKnowledgeLabelLanguageLanguage DelaysLanguage DevelopmentLearningLinguisticsMeasuresMethodologyMethodsModelingParentsPatternPerformancePhenotypePopulationResearch PersonnelSeveritiesShapesStimulusTestingToddlerTrainingUnited StatesUpdateVocabularyWeightadult with autism spectrum disorderautism spectrum disorderautisticautistic childrenbaseclinically significantcognitive abilityeducational atmosphereexperienceexperimental studyindividual variationindividuals with autism spectrum disorderinnovationinsightlearning abilitynovelpeersocialstandardize measurestatistical learningstatisticssuccesstheoriestreatment strategyword learning
项目摘要
ABSTRACT
Current estimates suggest that autism spectrum disorder (ASD) impacts 1 in 44 children in the United States.
Many young children with ASD demonstrate language delays, which are often the first area of concern noted by
their parents. Young children with ASD show markedly different word learning profiles than their neurotypical
(NT) peers, characterized primarily by atypical or delayed use of word learning mechanisms. We currently have
an incomplete understanding of these differences. Discerning the mechanisms that underlie language learning
deficits in ASD will afford greater success in alleviating these difficulties and supporting language learning in this
population. One theoretical account, a predictive impairment in autism (PIA) hypothesis, has shown promise for
explaining some phenotypic characteristics of ASD (i.e., difficulty making social predictions). The utility of this
theoretical framework for explaining difficulty with language learning, however, remains largely unclear. Autistic
children show intact statistical word learning abilities on experimental tasks. However, given that children learn
words in their natural, often unpredictable environments, difficulty tracking unpredictable stimuli might have
profound impacts on autistic children’s word learning. The overall objective of the proposed project is to
determine how established, domain-general difficulties with prediction in ASD might impact novel word learning.
This project will employ established eyegaze methodology to test the impact of predictable and unpredictable
presentations on word learning in this population. The central hypothesis is that unpredictable contexts during
training will disproportionately disrupt word learning in children with ASD and result in disproportionate detriments
to the retention and generalization of object-label pairings. Preliminary data suggest that autistic children are
disproportionately disrupted by unpredictable input in a fast-mapping task. Guided by the PIA hypothesis and
this strong preliminary data, the proposed project will address three specific aims. Specific Aim I will characterize
the impact of predictable and unpredictable presentations of novel-word object pairings on initial word learning
(fast-mapping) in autistic toddlers compared to cognitively matched NT peers. Specific Aim II will investigate the
impact of predictability during initial learning on autistic toddlers’ retention and generalization of word-object
pairings over a short (5-minute) delay, compared to NT peers. Specific Aim III will evaluate the extent to which
child characteristics (e.g., language and cognitive abilities) predict individual variability in word learning
performance following predictable and unpredictable input in autistic children. The proposed project will be the
first to apply established eyegaze methodology to test this theoretical framework and its application to initial word
learning, retention, and generalization in this population. The proposed project’s significance is that it will
advance theories of autism and our understanding of language learning in this population. The proposed project’s
impact is that findings will inform best practices and novel treatment strategies that allow for optimal language
learning for autistic children.
摘要
项目成果
期刊论文数量(0)
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JANINE R MATHEE-SCOTT的其他文献
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{{ truncateString('JANINE R MATHEE-SCOTT', 18)}}的其他基金
Prediction and Word Learning in Young Children with Autism Spectrum Disorder
自闭症谱系障碍幼儿的预测和单词学习
- 批准号:
10923344 - 财政年份:2022
- 资助金额:
$ 4.68万 - 项目类别:
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