Inference and Classification Learning of Abstract Coherent Categories

Autor/inn/en	Erickson, Jane E.; Chin-Parker, Seth; Ross, Brian H.
Titel	Inference and Classification Learning of Abstract Coherent Categories
Quelle	In: Journal of Experimental Psychology: Learning, Memory, and Cognition, 31 (2005) 1, S.86-99 (14 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0278-7393
Schlagwörter	Inferences; Classification; Learning Processes + Suchen Sie Ihr Suchwort? Inference; Inferenz; Classification system; Klassifikation; Klassifikationssystem; Learning process; Lernprozess
Abstract	Category learning research has primarily focused on how people learn to classify items using simple observable features. However, classification is only 1 way to learn categories. In addition, many concepts have an underlying coherence that explains the featural similarity among exemplars, such as abstract coherent concepts whose instances differ greatly on their observable features. In 3 experiments, the authors investigated how abstract coherent categories are acquired through 2 common means of category learning, classification and inference. Because inference promotes more focus on within-category information than does classification, they hypothesized that inference learning would lead to a better understanding of the underlying coherence of abstract coherent categories. All 3 experiments support this prediction. (Author).
Anmerkungen	American Psychological Association, 750 First Street, NE, Washington, DC 20002-4242. Tel: 800-374-2721 (Toll Free); Tel: 202-336-5510; TDD/TTY: 202-336-6123; Fax: 202-336-5502; e-mail: journals@apa.org.
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10