Memory & Cognition

, Volume 17, Issue 5, pp 627–638 | Cite as

The relation between problem categorization and problem solving among experts and novices

  • Pamela Thibodeau Hardiman
  • Robert Dufresne
  • Jose P. Mestre


These investigations were conducted to examine the relationship between problem-solving ability and the criteria used to decide that two classical mechanics problems would be solved similarly. We began by comparing experts and novices on a similarity judgment task and found that the experts predominantly relied on the problems’ deep structures in deciding on similarity of solution, although the presence of surface-feature similarity had a clear adverse effect on performance. The novices relied predominantly on surface features, but were capable of using the problems’ deep structures under certain conditions. In a second experiment, we compared groups of novices, at the same level of experience, who tended to employ different types of reasoning in making similarity judgments. Compared to novices who relied predominantly on surface features, novices who made greater use of principles tended to categorize problems similarly to how experts categorized them, as well as score higher in problem solving. These results suggest that principles play a fundamental role in the organization of conceptual and procedural knowledge for good problem solvers at all levels.


  1. Chi, M. T. H., Bassock, M., Lewis, M.W., Relmann, P., &Glaser, R. (1987).Self-explanations: How students study and use examples in learning to solve problems (Tech. Rep. No. 9). Pillslxtrgh PA: University of Pittsburgh, Learning Reasearch and Development Center.Google Scholar
  2. Chi, M. T. H., Feltovich, P. J., &Glaser, R. (1981). Categorization and representation of physics problems by experts and novicesCognitive Science,5, 121–152.CrossRefGoogle Scholar
  3. Collins, A., Baown, J. S., Newman, S. E. (in press). Cogniuve prenticeship: Teaching the crafts of reading, writing, and mathematics. In L. B. Resnick (Ed.), Knowing,learning and instruction: Essays in honor of Robert Gtaser. Hillsdale, NJ: Erlbaum.Google Scholar
  4. Eylon, B. S., &Reif, F. (1984). Effects of knowledge organization on task performance.Cognition & Instruction,1, 5–44.CrossRefGoogle Scholar
  5. Hayes, J. R., Simon, H. A. (1976). The understanding process: Problem isomorphs.Cognitive Psychology,8, 165–190.CrossRefGoogle Scholar
  6. Heller, J. I., &Reif, F. (1984). Prescribing effective human problem solving processes: Problem description in physics.Cognitive & Instruction,1, 177–216.CrossRefGoogle Scholar
  7. Hinsley, D. A., Hayes, J. R., Simon, H. A. (1977). From words to equations: Meaning and representation in algebra word problems. In M. A. Just & P. A. Carpenter (Eds.),Cognitive processes in comprehension (pp. 89–106). Hillsdale, NJ: Erlbaum.Google Scholar
  8. Larkin, J. H. (1981). Enriching formal knowledge: A model for learning to solve problems in physics. In J. R. Anderson (Ed.),Cognitive skills and their acquisition (pp. 311–334). Hillsdale, NJ: Erlbaum.Google Scholar
  9. Larkin, J. H. (1983). The role of problem representation in physics. In D. Gentner & A. L. Stevens (Eds.),Mental models (pp. 75–98). Hillsdale, NJ: Erlbaum.Google Scholar
  10. Larkin, J. H., McDemott, J., Simon, D. P., &Simon, H. A. (1980). Models of competence in solving physics problems.Cognitive Science,4, 317–345.CrossRefGoogle Scholar
  11. Mervis, C. B. (1980). Category sa-uc~e and the developn~nt of categorization. In R. J. Shapiro, B. C. Brace, & W. F. Brewer (Eds.),Theoretical issues in reading comprehension: Perspectives from cognitive psychology, linguistics, artificial intelligence and education (pp. 279–307). Hillsdale, NJ: Erlbaum.Google Scholar
  12. Mestre, J. P., Dufresne, R., Gerace, W., Hardiman, P. T., TooGea, J. (1988). Promoting expert-like behavior among beginning physics students (Tech. Rep. No. 178). Amherst: Scientific Reasoning Research Institute, University of Massachusetts.Google Scholar
  13. Newell, A., &Simon, H. A. (1972).Human problem solving. Englewood Cliffs, NJ: Prentice-Hall.Google Scholar
  14. Niegemann, H., Paar, I. (1986).Classification of algebra and physics word problems by subjects of different levels of expertise (Tech. Rep. No. 33). Saarbrucken, Germany: Universität des Saadandes, Fachrichtung Allgemeine Erziehangswissenschaft.Google Scholar
  15. Resnick, R., &Halliday, D. (1977).Physics. New York: WileyGoogle Scholar
  16. Rosch, E., Mervis, C. B. (1975). Family resemblances: Studies in the internal structure of categories.Cognitive Psychology,8, 382–439.CrossRefGoogle Scholar
  17. Schoenfeld, A. H., &Herrmann, D. J. (1982). Problem perception and knowledge structure in expert and novice mathematical problem solvers.Journal of Experimental Psychology: Learning, Memory, & Cognition,8, 484.-494.CrossRefGoogle Scholar
  18. Silver, E. A. (1979). Student perceptions of relatedness among mathematical verbal problems.Journal for Research in Mathematics Education,10, 195–210.CrossRefGoogle Scholar
  19. Simon, D. P., Simon, H. A. (1978). Individual differences in solving physics problems. In R. S. Sigler (Ed.),Children’s thinki’ng: What develops? (pp. 325–348). Hillsdale, NJ: Erlbaum.Google Scholar
  20. Smith, E. E., Shoben, E. J., &Rips, L. J. (1974). Structure and process in semantic memory: A featural model for semantic decisions.Psychological Review,81, 214–241.CrossRefGoogle Scholar

Copyright information

© Psychonomic Society, Inc. 1989

Authors and Affiliations

  • Pamela Thibodeau Hardiman
    • 1
  • Robert Dufresne
    • 1
  • Jose P. Mestre
    • 1
  1. 1.Department of Physics and AstronomyUniversity of MassachusettsAmherst

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