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    Infant statistical learning

    Saffran, J. and Kirkham, Natasha Z. (2018) Infant statistical learning. Annual Review of Psychology 69 , pp. 181-203. ISSN 0066-4308.

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    Abstract

    Perception involves making sense of a dynamic, multimodal environment. In the absence of mechanisms capable of exploiting the statistical patterns in the natural world, infants would face an insurmountable computational problem. Infant statistical learning mechanisms facilitate the detection of structure. These abilities allow the infant to compute across elements in their environmental input, extracting patterns for further processing and subsequent learning. In this selective review, we summarize findings that show that statistical learning is both a broad and flexible mechanism (supporting learning from different modalities across many different content areas) and input specific (shifting computations depending on the type of input and goal of learning). We suggest that statistical learning not only provides a framework for studying language development and object knowledge in constrained laboratory settings, but also allows researchers to tackle realworld problems, such as multilingualism, the role of ever-changing learning environments, and differential developmental trajectories.

    Metadata

    Item Type: Article
    School: Birkbeck Schools and Departments > School of Science > Psychological Sciences
    Research Centre: Brain and Cognitive Development, Centre for (CBCD)
    Depositing User: Dr Natasha Kirkham
    Date Deposited: 23 Feb 2018 08:44
    Last Modified: 23 Feb 2018 08:45
    URI: http://eprints.bbk.ac.uk/id/eprint/21335

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