Adaptation as statistical learning: An individual differences study

dc.contributor.advisorWeinberger, Steven H.
dc.contributor.authorEnochson, Kelly
dc.creatorEnochson, Kelly
dc.date.accessioned2015-09-14T14:18:20Z
dc.date.available2015-09-14T14:18:20Z
dc.date.issued2015
dc.description.abstractA rich body of research has shown that language learners can track and use distributional information in the input to acquire multiple levels of linguistic structure (see krogh et al., 2013 for a review). There is reason to believe, however, that learning about the statistics of the input is not confined to language acquisition, but is part of ongoing language experience. In particular, language processing appears to be influenced by expectations—e.g., about probable sounds, words, structures—which are dynamic and can be rapidly updated based on the current linguistic environment (e.g., fine et al., 2013). If a general mechanism like statistical learning underlies both acquisition and later processing and use, a clear prediction is made: performance on an independent measure of statistical learning should correlate with ability to adapt native language expectations based on novel information.
dc.format.extent110 pages
dc.identifier.urihttps://hdl.handle.net/1920/9840
dc.language.isoen
dc.rightsCopyright 2015 Kelly Enochson
dc.subjectLinguistics
dc.subjectAdaptation
dc.subjectAmazon Mechanical Turk
dc.subjectPsycholinguistics
dc.subjectStatistical Learning
dc.titleAdaptation as statistical learning: An individual differences study
dc.typeDissertation
thesis.degree.disciplineEnglish
thesis.degree.grantorGeorge Mason University
thesis.degree.levelDoctoral

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