Abstract
Participants learned to classify seemingly arbitrary words into categories that also corresponded to ad hoc categories (see, e.g., Barsalou, 1983). By adapting experimental mechanisms previously used to study knowledge restructuring in perceptual categorization, we provide a novel account of how experimental and preexperimental knowledge interact. Participants were told of the existence of the ad hoc categories either at the beginning or the end of training. When the ad hoc labels were revealed at the end of training, participants switched from categorization based on experimental learning to categorization based on preexperimental knowledge in some, but not all, circumstances. Important mediators of the extent of that switch were the amount of performance error experienced during prior learning and whether or not prior knowledge was in conflict with experimental learning. We present a computational model of the trade-off between preexperimental knowledge and experimental learning that accounts for the main results.
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Barsalou, L. W. (1983). Ad hoc categories.Memory & Cognition,11, 211–227.
Erickson, M. A., &Kruschke, J. K. (1998). Rules and exemplars in category learning.Journal of Experimental Psychology: General,127, 107–140.
Feldman, J. (2003). The simplicity principle in human concept learning.Current Directions in Psychological Science,12, 227–232.
Geman, S., Bienenstock, E., &Doursat, R. (1992). Neural networks and the bias/variance dilemma.Neural Computation,4, 1–58.
Gluck, M. A., &Bower, G. H. (1988). From conditioning to category learning: An adaptive network model.Journal of Experimental Psychology: General,117, 227–247.
Hall, G. (1991).Perceptual and associative learning. Oxford: Oxford University Press, Clarendon Press.
Heit, E. (1994). Models of the effects of prior knowledge on category learning.Journal of Experimental Psychology: Learning, Memory, & Cognition,20, 1264–1282.
Heit, E. (1997). Knowledge and concept learning. In K. Lamberts & D. Shanks (Eds.),Knowledge, concepts, and categories (pp. 7–41). London: Psychology Press.
Heit, E., &Bott, L. (2000). Knowledge selection in category learning. In D. L. Medin (Ed.),The psychology of learning and motivation: Advances in research and theory (Vol. 39, pp. 163–199). San Diego: Academic Press.
Heit, E., Briggs, J., &Bott, L. (2004). Modeling the effects of prior knowledge on learning incongruent features of category members.Journal of Experimental Psychology: Learning, Memory, & Cognition,30, 1065–1081.
Jacobs, R. A. (1997). Nature, nurture, and the development of functional specializations: A computational approach.Psychonomic Bulletin & Review,4, 299–309.
Kalish, M. L., Lewandowsky, S., &Davies, M. (2005). Error-driven knowledge restructuring in categorization.Journal of Experimental Psychology: Learning, Memory, & Cognition,31, 846–861.
Kalish, M. L., Lewandowsky, S., &Kruschke, J. K. (2004). Population of linear experts: Knowledge partitioning and function learning.Psychological Review,111, 1072–1099.
Kaplan, A. S., &Murphy, G. L. (2000). Category learning with minimal prior knowledge.Journal of Experimental Psychology: Learning, Memory, & Cognition,26, 829–846.
Kruschke, J. K. (1992). ALCOVE: An exemplar-based connectionist model of category learning.Psychological Review,99, 22–44.
Lewandowsky, S., Kalish, M., &Griffiths, T. L. (2000). Competing strategies in categorization: Expediency and resistance to knowledge restructuring.Journal of Experimental Psychology: Learning, Memory, & Cognition,26, 1666–1684.
Murphy, G. L., &Allopenna, P. D. (1994). The locus of knowledge effects in concept learning.Journal of Experimental Psychology: Learning, Memory, & Cognition,20, 904–919.
Murphy, G. L., &Medin, D. L. (1985). The role theories in conceptual coherence.Psychological Review,92, 289–316.
Nosofsky, R. M., Palmeri, T. J., &McKinley, S. C. (1994). Ruleplus-exception model of classification learning.Psychological Review,101, 53–79.
Palmeri, T. J., &Nosofsky, R. M. (1995). Recognition memory for exceptions to the category rule.Journal of Experimental Psychology: Learning, Memory, & Cognition,21, 548–568.
Pothos, E. M., &Chater, N. (2002). A simplicity principle in unsupervised human categorization.Cognitive Science,26, 303–343.
Rehder, B., &Murphy, G. L. (2003). A knowledge-resonance (KRES) model of category learning.Psychonomic Bulletin & Review,10, 759–784.
Ross, B. H. (1999). Postclassification category use: The effects of learning to use categories after learning to classify.Journal of Experimental Psychology: Learning, Memory, & Cognition,25, 743–757.
Spalding, T. L., &Murphy, G. L. (1999). What is learned in knowledgerelated categories?Evidence from typicality and feature frequency judgments. Memory & Cognition,27, 856–867.
Wilson, M. [D.] (1988). MRC Psycholinguistic Database: Machineusable dictionary, version 2.00.Behavior Research Methods, Instruments, & Computers,20, 6–10.
Wisniewski, E. J. (1995). Prior knowledge and functionally relevant features in concept learning.Journal of Experimental Psychology: Learning, Memory, & Cognition,21, 449–468.
Yamauchi, T., &Markman, A. B. (1998). Category learning by inference and classification.Journal of Memory & Language,39, 124–148.
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Preparation of this article was facilitated by a Discovery Grant from the Australian Research Council to the second author and Mike Kalish.
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Little, D.R., Lewandowsky, S. & Heit, E. Ad hoc category restructuring. Memory & Cognition 34, 1398–1413 (2006). https://doi.org/10.3758/BF03195905
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DOI: https://doi.org/10.3758/BF03195905