title: Costs and benefits of automatization in category learning of ill-defined rules.
abstract: Learning ill-defined categories (such as the structure of Medin & Schaffer, 1978) involves multiple learning systems and different corresponding category representations, which are difficult to detect. Application of latent Markov analysis allows detection and investigation of such multiple latent category representations in a statistically robust way, isolating low performers and quantifying shifts between latent strategies. We reanalyzed data from three experiments presented in Johansen and Palmeri (2002), which comprised prolonged training of ill-defined categories, with the aim of studying the changing interactions between underlying learning systems. Our results broadly confirm the original conclusion that, in most participants, learning involved a shift from a rule-based to an exemplar-based strategy. Separate analyses of latent strategies revealed that (a) shifts from a rule-based to an exemplar-based strategy resulted in an initial decrease of speed and an increase of accuracy; (b) exemplar-based strategies followed a power law of learning, indicating automatization once an exemplar-based strategy was used; (c) rule-based strategies changed from using pure rules to rules-plus-exceptions, which appeared as a dual processes as indicated by the accuracy and response-time profiles. Results suggest an additional pathway of learning ill-defined categories, namely involving a shift from a simple rule to a complex rule after which this complex rule is automatized as an exemplar-based strategy.
authors.affiliation: Department of Psychology, University of Amsterdam, The Netherlands; Amsterdam Brain and Cognition (ABC), University of Amsterdam, The Netherlands. Electronic address: m.e.j.raijmakers@uva.nl.
authors.forename: Maartje E J
authors.initials: ME
authors.lastname: Raijmakers
authors.affiliation: Department of Methodology and Statistics, Tilburg School of Social and Behavioral Sciences, The Netherlands.
authors.forename: Verena D
authors.initials: VD
authors.lastname: Schmittmann
authors.affiliation: Department of Psychology, University of Amsterdam, The Netherlands; Amsterdam Brain and Cognition (ABC), University of Amsterdam, The Netherlands.
authors.forename: Ingmar
authors.initials: I
authors.lastname: Visser
mesh_terms: D003210:Concept Formation; D003362:Cost-Benefit Analysis; D005260:Female; D005793:Generalization, Psychological; D006801:Humans; D007858:Learning; D008297:Male; D008390:Markov Chains; D008960:Models, Psychological; D010364:Pattern Recognition, Visual
keywords: Automaticity; Category learning; Exemplar-based learning; Ill-defined categories; Individual differences; Latent Markov analysis; Representational shifts; Rule-based learning; Strategies