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Memory & Cognition

, Volume 36, Issue 7, pp 1335–1350 | Cite as

Prior knowledge and exemplar frequency

  • Harlan D. Harris
  • Gregory L. Murphy
  • Bob Rehder
Article
  • 197 Downloads

Abstract

New concepts can be learned by statistical associations, as well as by relevant existing knowledge. We examined the interaction of these two processes by manipulating exemplar frequency and thematic knowledge and considering their interaction through computational modeling. Exemplar frequency affects category learning, with high-frequency items learned more quickly than low-frequency items, and prior knowledge usually speeds category learning. In two experiments in which both of these factors were manipulated, we found that the effects of frequency are greatly reduced when stimulus features are linked by thematic prior knowledge and that frequency effects on single stimulus features can actually be reversed by knowledge. We account for these results with the knowledge resonance model of category learning (Rehder & Murphy, 2003) and conclude that prior knowledge may change representations so that empirical effects, such as those caused by frequency manipulations, are modulated.

Keywords

Prior Knowledge Input Node Category Learning Knowledge Condition Response Preference 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. Barsalou, L. W. (1985). Ideals, central tendency, and frequency of instantiation as determinants of graded structure in categories. Journal of Experimental Psychology: Learning, Memory, & Cognition, 11, 629–654.CrossRefGoogle Scholar
  2. Barsalou, L. W., Huttenlocher, J., & Lamberts, K. (1998). Basing categorization on individuals and events. Cognitive Psychology, 36, 203–272.CrossRefPubMedGoogle Scholar
  3. Friedman, D., & Massaro, D. W. (1998). Understanding variability in binary and continuous choice. Psychonomic Bulletin & Review, 5, 370–389.Google Scholar
  4. Harris, H. D., & Rehder, B. (2006). Modeling category learning with exemplars and prior knowledge. In R. Sun & N. Miyake (Eds.), Proceedings of the 28th Annual Conference of the Cognitive Science Society (pp. 1440–1445). Mahwah, NJ: Erlbaum.Google Scholar
  5. Heit, E. (1994). Models of the effects of prior knowledge on category learning. Journal of Experimental Psychology: Learning, Memory, & Cognition, 20, 1264–1282.CrossRefGoogle Scholar
  6. Heit, E. (1998). Influences of prior knowledge on selective weighting of category members. Journal of Experimental Psychology: Learning, Memory, & Cognition, 24, 712–731.CrossRefGoogle Scholar
  7. Heit, E., & Bott, L. (2000). Knowledge selection in category learning. In D. L. Medin (Ed.), Psychology of learning and motivation (Vol. 39, pp. 163–199). San Diego: Academic Press.Google Scholar
  8. McClelland, J. L., & Rumelhart, D. E. (1981). An interactive activation model of context effects in letter perception: Part I. An account of basic findings. Psychological Review, 86, 375–407.CrossRefGoogle Scholar
  9. McDowell, B. D., & Oden, G. C. (1995). Categorical decision, rating judgments, and information preservation. Unpublished manuscript, University of Iowa.Google Scholar
  10. Mervis, C. B., Catlin, J., & Rosch, E. (1976). Relationships among goodness-of-exemplar, category norms, and word frequency. Bulletin of the Psychonomic Society, 7, 283–284.Google Scholar
  11. 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.CrossRefGoogle Scholar
  12. Murphy, G. L., & Kaplan, A. S. (2000). Feature distribution and background knowledge in category learning, Quarterly Journal of Experimental Psychology, 53A, 962–982.CrossRefGoogle Scholar
  13. Nosofsky, R. M. (1988), Similarity, frequency, and category representations. Journal of Experimental Psychology: Learning, Memory, & Cognition, 14, 54–65.CrossRefGoogle Scholar
  14. Novick, L. R. (2003). At the forefront of thought: The effect of media exposure on airplane typicality. Psychonomic Bulletin & Review, 10, 971–974.Google Scholar
  15. O’Reilly, R. C. (1986). Biologically plausible error-driven learning using local activation differences: The generalized recirculation algorithm. Neural Computation, 8, 895–938.CrossRefGoogle Scholar
  16. Pazzani, M. J. (1991). Influence of prior knowledge on concept acquisition: Experimental and computational results. Journal of Experimental Psychology: Learning, Memory, & Cognition, 17, 416–432.CrossRefGoogle Scholar
  17. Pitt, M. A., Kim, W., Navarro, D. J., & Myung, J. I. (2006). Global model analysis by parameter space partitioning, Psychological Review, 113, 57–83.CrossRefPubMedGoogle Scholar
  18. Pitt, M. A., & Myung, I. J. (2002). When a good fit can be bad. Trends in Cognitive Sciences, 6, 421–425.CrossRefPubMedGoogle Scholar
  19. Rehder, B., & Murphy, G. L. (2003). A knowledge-resonance (KRES) model of category learning. Psychonomic Bulletin & Review, 10, 759–784.Google Scholar
  20. Rosch, E., & Mervis, C. B. (1975). Family resemblances: Studies in the internal structure of categories. Cognitive Psychology, 7, 573–605.CrossRefGoogle Scholar
  21. Schunn, C. D., & Wallach, D. (2005). Evaluating goodness-of-fit in comparison of models to data. In W. Tack (Ed.), Psychologie der Kognition: Reden and Vorträge anlässlich der Emeritierung von Werner Tack (pp. 115–154). Saarbrücken, Germany: University of Saarland Press.Google Scholar
  22. Spalding, T. L., & Murphy, G. L. (1999). What is learned in knowledge-related categories? Evidence from typicality and feature frequency judgments. Memory & Cognition, 27, 856–867.Google Scholar
  23. Wattenmaker, W. D., Dewey, G. I., Murphy, T. D., & Medin, D. L. (1986). Linear separability and concept learning: Context, relation properties, and concept naturalness. Cognitive Psychology, 18, 158–194.CrossRefPubMedGoogle Scholar

Copyright information

© Psychonomic Society, Inc. 2008

Authors and Affiliations

  • Harlan D. Harris
    • 1
  • Gregory L. Murphy
    • 1
  • Bob Rehder
    • 1
  1. 1.Department of PsychologyNew York UniversityNew York

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