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Autor/inn/enSchuler, Kathryn D.; Reeder, Patricia A.; Newport, Elissa L.; Aslin, Richard N.
TitelThe Effect of Zipfian Frequency Variations on Category Formation in Adult Artificial Language Learning
QuelleIn: Language Learning and Development, 13 (2017) 4, S.357-374 (18 Seiten)Infoseite zur Zeitschrift
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ZusatzinformationORCID (Aslin, Richard N.)
Spracheenglisch
Dokumenttypgedruckt; online; Zeitschriftenaufsatz
ISSN1547-5441
DOI10.1080/15475441.2016.1263571
SchlagwörterArtificial Languages; Grammar; Classification; Word Frequency; Statistical Distributions; Undergraduate Students; Second Language Learning; Adult Students; Cues; Statistical Analysis; New York (Rochester)
AbstractSuccessful language acquisition hinges on organizing individual words into grammatical categories and learning the relationships between them, but the method by which children accomplish this task has been debated in the literature. One proposal is that learners use the shared distributional contexts in which words appear as a cue to their underlying category structure. Indeed, recent research using artificial languages has demonstrated that learners can acquire grammatical categories from this type of distributional information. However, artificial languages are typically composed of a small number of equally frequent words, while words in natural languages vary widely in frequency, complicating the distributional information needed to determine categorization. In a series of three experiments we demonstrate that distributional learning is preserved in an artificial language composed of words that vary in frequency as they do in natural language, along a Zipfian distribution. Rather than depending on the absolute frequency of words and their contexts, the conditional probabilities that words will occur in certain contexts (given their base frequency) is a better basis for assigning words to categories; and this appears to be the type of statistic that human learners utilize. (As Provided).
AnmerkungenPsychology Press. Available from: Taylor & Francis, Ltd. 325 Chestnut Street Suite 800, Philadelphia, PA 19106. Tel: 800-354-1420; Fax: 215-625-2940; Web site: http://www.tandf.co.uk/journals
Erfasst vonERIC (Education Resources Information Center), Washington, DC
Update2020/1/01
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