{"pk":26140,"title":"The impact of biased hypothesis generation on self-directed learning","subtitle":null,"abstract":"Self-directed learning confers a number of advantages relativeto passive observation, including the ability to test hypothe-ses rather than learn from data generated by the environment.However, it remains unclear to what extent self-directed learn-ing is constrained by basic cognitive processes and how thoselimits are related to the structure of the to-be-learned material.The present study examined how hypothesis generation af-fects the success of self-directed learning of categorical rules.Two experiments manipulated the hypothesis generation pro-cess and assessed its impact on the ability to learn 1D and 2Drules. Performance was strongly influenced by whether thestimulus representation facilitated the generation of hypothe-ses consistent with the target rule. Broadly speaking, the find-ings suggest that the opportunity to actively gather informa-tion is not enough to guarantee successful learning, and thatthe efficacy of self-directed learning closely depends on howhypothesis generation is shaped by the structure of the learn-ing environment.","language":"eng","license":{"name":"","short_name":"","text":null,"url":""},"keywords":[{"word":"self-directed learning"},{"word":"category learning"},{"word":"activelearning"},{"word":"information search"},{"word":"hypothesis generation"}],"section":"Papers","is_remote":true,"remote_url":"https://escholarship.org/uc/item/0bw050s2","frozenauthors":[{"first_name":"Doug","middle_name":"","last_name":"Markant","name_suffix":"","institution":"Max Planck Institute for Human Development","department":""}],"date_submitted":null,"date_accepted":null,"date_published":"2016-01-01T18:00:00Z","render_galley":null,"galleys":[{"label":"PDF","type":"pdf","path":"https://journalpub.escholarship.org/cognitivesciencesociety/article/26140/galley/15776/download/"}]}