Identifying Strategy Use in Category Learning Tasks: A Case for More Diagnostic Data and Models

Autor/inn/en	Donkin, Chris; Newell, Ben R.; Kalish, Mike; Dunn, John C.; Nosofsky, Robert M.
Titel	Identifying Strategy Use in Category Learning Tasks: A Case for More Diagnostic Data and Models
Quelle	In: Journal of Experimental Psychology: Learning, Memory, and Cognition, 41 (2015) 4, S.933-948 (16 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0278-7393
DOI	10.1037/xlm0000083
Schlagwörter	Classification; Learning; Learning Strategies; Identification; Models; Perception; College Students; Stimuli; Foreign Countries; Australia + Suchen Sie Ihr Suchwort? Classification system; Klassifikation; Klassifikationssystem; Lernen; Learning methode; Learning techniques; Lernmethode; Lernstrategie; Identifikation; Identifizierung; Analogiemodell; Wahrnehmung; Collegestudent; Anreizsystem; Ausland; Australien
Abstract	The strength of conclusions about the adoption of different categorization strategies--and their implications for theories about the cognitive and neural bases of category learning--depend heavily on the techniques for identifying strategy use. We examine performance in an often-used "information-integration" category structure and demonstrate that strategy identification is affected markedly by the range of models under consideration, the type of data collected, and model-selection techniques. We use a set of 27 potential models that represent alternative rule-based and information-integration categorization strategies. Our experimental paradigm includes the presentation of nonreinforced transfer stimuli that improve one's ability to discriminate among the predictions of alternative models. Our model-selection techniques incorporate uncertainty in the identification of individuals as either rule-based or information-integration strategy users. Based on this analysis we identify 48% of participants as unequivocally using an information-integration strategy. However, adopting the standard practice of using a restricted set of models, restricted data, and ignoring the degree of support for a particular strategy, we would typically conclude that 89% of participants used an information-integration strategy. We discuss the implications of potentially erroneous strategy identification for the security of conclusions about the categorization capabilities of various participant and patient groups. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01