{"pk":28519,"title":"Modeling individual performance in cross-situational word learning","subtitle":null,"abstract":"What mechanisms underlie people’s ability to use cross-situational statistics to learn the meanings of words? Here wepresent a large-scale evaluation of two major models of cross-situational learning: associative (Kachergis, Yu, & Shiffrin,2012a) and hypothesis testing (Trueswell, Medina, Hafri, &Gleitman, 2013). We fit each model individually to over 1500participants across seven experiments with a wide range ofconditions. We find that the associative model better capturesthe full range of individual differences and conditions whenlearning is cross-situational, although the hypothesis testingapproach outperforms it when there is no referential ambiguityduring training.","language":"eng","license":{"name":"","short_name":"","text":null,"url":""},"keywords":[{"word":"Cross-situational word learning; language acqui-sition; Zipfian distributions"}],"section":"Papers with Oral Presentations","is_remote":true,"remote_url":"https://escholarship.org/uc/item/134389ps","frozenauthors":[{"first_name":"Yung","middle_name":"Han","last_name":"Khoe","name_suffix":"","institution":"Radboud University Nijmegen","department":""},{"first_name":"Amy","middle_name":"","last_name":"Perfors","name_suffix":"","institution":"University of Melbourne","department":""},{"first_name":"Andrew","middle_name":"T.","last_name":"Hendrickson","name_suffix":"","institution":"Tilburg University","department":""}],"date_submitted":null,"date_accepted":null,"date_published":"2019-01-01T18:00:00Z","render_galley":null,"galleys":[{"label":"PDF","type":"pdf","path":"https://journalpub.escholarship.org/cognitivesciencesociety/article/28519/galley/18390/download/"}]}