Psychological Research

, Volume 54, Issue 1, pp 44–50 | Cite as

Children and chess expertise: The role of calibration

  • Dianne D. Horgan

Summary

Three studies of calibration are reported. Calibration refers to the accuracy with which one can predict one's own performance. In the first study child chess players, non-chess playing parents, and statistics students were asked to predict chances of winning chess games against hypothetical opponents. These subjective probabilities were compared to the actual probabilities, based on the Elo rating system. Better players' predictions were better calibrated. Confidence and ratings are negatively correlated, indicating that with lower ratings, players are overconfident. Skilled child players' predictions were better calibrated than any of the adults'. In the second study subjects were asked to estimate chances of winning in conjunctive situations, e. g., winning all the rounds in a tournament. Again, better child players were more accurate in their predictions and more accurate than adults. In the third study, child players were asked to predict their chances of winning in a non-chess domain after hearing a hypothetical win/loss history. Higher-rated players' predictions were again better calibrated, even though the domain was outside their expertise. The motivational and cognitive implications of calibration are discussed.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Anderson, J. R. (1985).Cognitive psychology and its implications. New York: W. H. Freeman and Company.Google Scholar
  2. Chi, M. T. (1978). Knowledge structures and memory development. In R. S. Siegler (Ed.),Children's thinking: What develops? Hillsdale, NJ: Erlbaum.Google Scholar
  3. Christiaen, J., & Verholfstadt, D. C. (1981). Chess and cognitive development.Nederlandse Tydschrift voor de Psychologie en haar Grensgebieden, 36, 561–582.Google Scholar
  4. Christensen-Szalanski, J., & Bushyhead, J. (1981). Physicians' use of probabilistic information in real clinical settings.Journal of Experimental Psychology: Human Perception and Performance, 7, 928–935.Google Scholar
  5. Dreyfus, H. L., & Dreyfus, S. E. (1986).Mind over machine: The power of human intuition and expertise in the era of the computer. New York: The Free Press.Google Scholar
  6. Einhorn, H., & Hogarth, R. (1978). Confidence in judgment: Persistence of the illusion of validity.Psychological Review, 85, 395–416.Google Scholar
  7. Elo, A. (1978).The rating of chessplayers, past and present. New York: Aroc.Google Scholar
  8. Hogarth, R. (1987).Judgement and choice. New York: Wiley.Google Scholar
  9. Holding, D. H. (1985).The psychology of chess skill. Hillsdale, NJ: Erlbaum.Google Scholar
  10. Horgan, D. (1987). Chess as a way to teach thinking.Teaching Thinking and Problem Solving, 9, 4–9.Google Scholar
  11. Horgan, D. (1990, April).Students' predictions of test grades: Calibration and metacognition. Paper presented at the meetings of the American Educational Research Association, Boston, MA.Google Scholar
  12. Horgan, D., & Morgan, D. (1989). Chess expertise in children.Applied Cognitive Psychology, 3, 109–128.Google Scholar
  13. Juvonen, J. (1988). Outcome and attributional disagreements between students and their teachers.Journal of Educational Psychology, 80, 330–336.Google Scholar
  14. Keren, G. (1987). Facing uncertainty in the game of bridge: A calibration study.Organizational Behavior and Human Decision Processes, 39, 98–114.Google Scholar
  15. Lichtenstein, S., & Fischhoff, B. (1977). Do those who know more also know more about how much they know?Organizational Behavior and Human Performance, 20, 159–183.Google Scholar
  16. Lichtenstein, S., & Fischhoff, B. (1980). Training for calibration.Organizational Behavior and Human Performance, 26, 149–171.Google Scholar
  17. Lichtenstein, S., Fischhoff, B., & Phillips, L. (1982). Calibration of probabilities: The state of the art to 1980. In D. Kahneman, P. Slovic, & A. Tversky (Eds.),Judgment under uncertainty: Heuristics and biases (pp. 306–334). New York: Cambridge University Press.Google Scholar
  18. Mabe, P., & Wells, S. (1982). Validity of self-evaluation of ability: A review and meta-analysis.Journal of Applied Psychology, 67, 230–296.Google Scholar
  19. The nation's top players, as of August 31, 1989. (November 1989).Chess Life, p. 32.Google Scholar
  20. Raven, J., Court, J., & Raven, J. (1985).Manual for Raven's Progressive Matrices and Vocabulary Scales. London: H. K. Lewis.Google Scholar
  21. Siegler, R. S. (1983). Information-processing approaches to development. In H. Mussen (Ed.),Carmichael's manual of child psychology. New York: Wiley.Google Scholar
  22. Tversky, A., & Kahneman, D. (1982). Judgment under uncertainty: Heuristics and biases. In D. Kahneman, P. Slovic, & A. Tversky (Eds.),Judgment under uncertainty: Heuristics and biases (pp 3–20). New York: Cambridge University Press.Google Scholar
  23. Vertinsky, P., Kanetkar, V., Vertinsky, I., & Wilson, G. (1986). Prediction of wins and losses in a series of field hockey games: A study of probability assessment quality and cognitive information processing models of players.Organizational Behavior and Human Decision Processes, 38, 392–404.Google Scholar
  24. Wagenaar, W., & Keren, G. (1985). Calibration of probability assessments by professional blackjack dealers, statistical experts, and lay people.Organizational Behavior and Human Decision Processes, 36, 406–416.Google Scholar
  25. Weiner, B. (1986).An attributional theory of motivation and emotion. New York: Springer.Google Scholar

Copyright information

© Springer-Verlag 1992

Authors and Affiliations

  • Dianne D. Horgan
    • 1
  1. 1.Foundations of Education DepartmentMemphis State UniversityMemphisUSA

Personalised recommendations