CAREER: Statistical Learning in Language Acquisition

University Of Wisconsin-Madison, Madison WI

Investigators

Abstract

Statistical learning is a promising addition to the language learning arsenal, given the massive amount of statistical information in linguistic input. However, the fact that such mechanisms exist raises several pressing problems. In particular, different types of statistical learning mechanisms are required for the acquisition of different aspects of language. What remains unknown is how these mechanisms interact to derive linguistic structure, given multiple possible levels of analysis. A related issue concerns the domain-specificity of statistical language learning processes. The following objectives will be addressed, using previously developed laboratory learning paradigms which permit careful manipulation of the input and detailed assessment of what participants are able to learn: (1) to determine whether learners can track the multiple levels of statistical regularity present in linguistic input, (2) to reveal constraints on the particular types of computations performed by infant, child, and adult language learners, (3) to determine whether the same types of regularities are detected in linguistic and non-linguistic learning tasks. The answers to these questions will inform an emerging theoretical framework, constrained statistical learning, intended to elucidate the study of language acquisition and other pressing issues in human learning and development. The proposed teaching objectives will serve to extend the excitement of the psychology laboratory to the classroom by training undergraduate Research and Teaching Fellows to bridge the gap between research and teaching by leading discussion sections, by facilitating the participation of students in a large lecture class in running small-scale research projects, and by encouraging scientific writing in the psychology classroom.