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    Establishing a Learning Foundation in a Dynamically Changing World: Insights from Artificial Language Work

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    Dissertation not available in ...
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    Author
    Gonzales, Kalim
    Issue Date
    2013
    Keywords
    dynamic change
    exemplar theory
    statistical learning
    Psychology
    artificial language learning
    Advisor
    Gómez, Rebecca L.
    
    Metadata
    Show full item record
    Publisher
    The University of Arizona.
    Rights
    Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
    Embargo
    Dissertation not available (per author's request)
    Abstract
    It is argued that infants build a foundation for learning about the world through their incidental acquisition of the spatial and temporal regularities surrounding them. A challenge is that learning occurs across multiple contexts whose statistics can greatly differ. Two artificial language studies with 12-month-olds demonstrate that infants come prepared to parse statistics across contexts using the temporal and perceptual features that distinguish one context from another. These results suggest that infants can organize their statistical input with a wider range of features that typically considered. Possible attention, decision making, and memory mechanisms are discussed.
    Type
    text
    Electronic Dissertation
    Degree Name
    Ph.D.
    Degree Level
    doctoral
    Degree Program
    Graduate College
    Psychology
    Degree Grantor
    University of Arizona
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