Metacognition and Learning

, Volume 11, Issue 2, pp 171–185 | Cite as

The instinct fallacy: the metacognition of answering and revising during college exams

  • Justin J. Couchman
  • Noelle E. Miller
  • Shaun J. Zmuda
  • Kathryn Feather
  • Tina Schwartzmeyer
Article

Abstract

Students often gauge their performance before and after an exam, usually in the form of rough grade estimates or general feelings. Are these estimates accurate? Should they form the basis for decisions about study time, test-taking strategies, revisions, subject mastery, or even general competence? In two studies, undergraduates took a real multiple-choice exam, described their general beliefs and feelings, tracked their performance for each question, and noted any revisions or possible revisions. Beliefs formed after the exams were poor predictors of performance. In contrast, real-time metacognitive monitoring – measured by confidence ratings for each individual question – accurately predicted performance and were a much better decisional guide. Measuring metacognitive monitoring also allowed us to examine the process of revising an answer. Should a test-taker rely on their first choice or revise in the face of uncertainty? Experience seems to show that first instincts are correct. The decision-making literature calls this the first-instinct fallacy, based on extensive analysis of revisions, and recommends revising more. However, whereas revisions have been analyzed in great detail, previous studies did not analyze the efficacy of sticking with an original choice. We found that both revising and sticking resulted in significantly more correct than incorrect outcomes, with real-time metacognition predicting when each was most appropriate.

Keywords

Metacognition Metamemory Decision making Exam revising First-instinct fallacy 

References

  1. Balance, C. T. (1977). Students’ expectations and their answer-changing behavior. Psychological Reports, 41, 163–166.CrossRefGoogle Scholar
  2. Balcomb, F. K., & Gerkin, L. (2008). Three-year-old children can access their own memory to guide responses on a visual matching task. Developmental Science, 11, 750–750.CrossRefGoogle Scholar
  3. Benjamin, L. T., Cavell, A., & Shallenberger, W. R. (1984). Staying with initial answers on objective tests: Is it a myth? Teaching of Psychology, 11(3), 133–141.CrossRefGoogle Scholar
  4. Bisanz, G. L., Vesonder, G. T., & Voss, J. F. (1978). Knowledge of one’s own responding and the relation of such knowledge to learning: a developmental study. Journal of Experimental Child Psychology, 25, 116–128.CrossRefGoogle Scholar
  5. Bol, L., & Hacker, D. (2001). A comparison of the effects of practice tests and traditional review on performance and calibration. Journal of Experimental Education, 69, 133–151.CrossRefGoogle Scholar
  6. Bol, L., & Hacker, D. J. (2012). Calibration research: where do we go from here? Frontiers in Psychology, 3, 229.CrossRefGoogle Scholar
  7. Connor, L. T., Dunlosky, J., & Hertzog, C. (1997). Age-related differences in absolute but not relative metamemory accuracy. Psychology and Aging, 12, 50–71.CrossRefGoogle Scholar
  8. Couchman, J. J., Coutinho, M. V. C., Beran, M. J., & Smith, J. D. (2010). Beyond stimulus cues and reinforcement history: a new approach to animal metacognition. Journal of Comparative Psychology, 124(4), 356–368.CrossRefGoogle Scholar
  9. Crawford, C. (1928). The technique of study. Boston: Houghton Mifflin.Google Scholar
  10. Crocker, L., & Benson, J. (1980). Does answer changing affect test quality? Measurement and Evaluation in Guidance, 12, 223–239.Google Scholar
  11. de Gardelle, V., & Mamassian, P. (2014). Does confidence use a common currency across two visual tasks? Psychological Science, 25(6), 1286–1288.CrossRefGoogle Scholar
  12. Dinsmore, D. L., & Parkinson, M. M. (2013). What are confidence judgments made of? Students’ explanations for their confidence ratings and what that means for calibration. Learning and Instruction, 24, 4–14.CrossRefGoogle Scholar
  13. Dunlosky, J., & Metcalfe, J. (2009). Metacognition. Thousand Oaks: SAGE Publications.Google Scholar
  14. Dunlosky, J., & Connor, L. T. (1997). Age differences in the allocation of study time account for age differences in memory performance. Memory & Cognition, 25, 691–700.CrossRefGoogle Scholar
  15. Dunlosky, J., & Rawson, K. A. (2011). Overconfidence produces underachievement: inaccurate self-evaluations undermine students’ learning and retention. Learning and Instruction, 22, 271–280.CrossRefGoogle Scholar
  16. Fleming, S. M., & Dolan, R. J. (2012). The neural basis of accurate metacognition. Philosophical Transactions of the Royal Society B, 367, 1338–49.CrossRefGoogle Scholar
  17. Foote, R., & Belinky, C. (1972). It pays to switch? Consequences of changing answers on multiple-choice examinations. Psychological Reports, 31, 667–673.CrossRefGoogle Scholar
  18. Geiger, M. A. (1996). On the benefits of changing multiple- choice answers: student perception and performance. Education, 117, 108–119.Google Scholar
  19. Hacker, D. J., Bol, L., Horgan, D., & Rakow, E. A. (2000). Test prediction and performance in a classroom context. Journal of Educational Psychology, 92, 160–170.CrossRefGoogle Scholar
  20. Harvil, L. M., & Davis, G. (1997). Medical students’ reasons for changing answers on multiple-choice tests. Academic Medicine, 72, S97–S99.CrossRefGoogle Scholar
  21. Higham, P. A., & Gerrard, C. (2005). Not all errors are created equal: metacognition and changing answers on multiple-choice tests. Canadian Journal of Experimental Psychology, 59(1), 28–34.CrossRefGoogle Scholar
  22. Hines, J. C., Touron, D. R., & Hertzog, C. (2009). Metacognitive influences on study time allocation in an associative recognition task: an analysis of adult age differences. Psychology and Aging, 24, 462–475.CrossRefGoogle Scholar
  23. Kahneman, D., Knetsch, J. L., & Thaler, R. H. (1991). Anomalies: the endowment effect, loss aversion, and status quo bias. The Journal of Economic Perspectives, 5, 193–206.CrossRefGoogle Scholar
  24. Kearney, E. M., & Zechmeister, E. B. (1989). Judgments of item difficulty by good and poor associative learners. American Journal of Psychology, 102, 365–383.CrossRefGoogle Scholar
  25. Kelemen, W. L., Frost, P. J., & Weaver, C. A., III. (2000). Individual differences in metacognition: evidence against a general metacognitive ability. Memory & Cognition, 28, 92–107.CrossRefGoogle Scholar
  26. Kelley, C. M., & Jacoby, L. L. (1996). Memory attributions: remembering, knowing, and feeling of knowing. In L. M. Reder (Ed.), Implicit memory and metacognition (pp. 287–308). Mahwah: Erlbaum.Google Scholar
  27. Koriat, A. (2007). Metacognition and consciousness. In P. D. Zelazo, M. Moscovitch, & E. Thompson (Eds.), The Cambridge handbook of consciousness (pp. 289–325). New York: Cambridge University Press.CrossRefGoogle Scholar
  28. Koriat, A., & Goldsmith, M. (1996). Memory as something that can be counted vs. memory as something that can be counted on. In D. J. Herrmann, C. McEvoy, C. Hertzog, P. Hertel, & M. K. Johnson (Eds.), Basic and applied memory research: Practical applications (Vol. 2, pp. 3–18). NJ: Erlbaum.Google Scholar
  29. Koriat, A., Bjork, R. A., Sheffer, L., & Bar, S. K. (2004). Predicting one’s own forgetting: the role of experience-based and theory-based processes. Journal of Experimental Psychology: General, 133, 643–656.CrossRefGoogle Scholar
  30. Kornell, N., Son, L., & Terrace, H. (2007). Transfer of metacognitive skills and hint seeking in monkeys. Psychological Science, 18, 64–71.CrossRefGoogle Scholar
  31. Kruger, J., Wirtz, D., & Miller, D. T. (2005). Counterfactual thinking and the first instinct fallacy. Journal of Personality and Social Psychology, 88(5), 725–35.CrossRefGoogle Scholar
  32. Lilienfeld, S. O., Lynn, S. J., Ruscio, J., Beyerstein, B. L. (2011). 50 Geat myths of popular psychology: Shattering widespread misconceptions about human behavior. Wiley.Google Scholar
  33. Lovelace, E. A. (1984). Metamemory: monitoring future recallability during study. Journal of Experimental Psychology: Learning, Memory, and Cognition, 10, 756–766.Google Scholar
  34. Lynch, D. O., & Smith, B. C. (1975). Item response changes: effects on test scores. Measurement and Evaluation in Guidance, 7, 220–224.Google Scholar
  35. Maki, R. H., & Berry, S. L. (1984). Metacomprehension of text material. Journal of Experimental Psychology: Learning, Memory, and Cognition, 10, 663–679.Google Scholar
  36. Maki, R. H., & Swett, S. (1987). Metamemory for narrative text. Memory & Cognition, 15, 72–83.CrossRefGoogle Scholar
  37. Mathews, C. O. (1929). Erroneous first impressions on objective tests. Journal of Educational Psychology, 20, 280–286.CrossRefGoogle Scholar
  38. McMorris, R. F., DeMers, L. P., & Schwartz, S. P. (1987). Attitudes, behaviours, and reasons for changing respons- es following answer-changing instruction. Journal of Educational Measurement, 24, 131–143.CrossRefGoogle Scholar
  39. Metcalfe, J. (2002). Is study time allocated selectively to a region of proximal learning? Journal of Experimental Psychology: General, 131, 349–363.CrossRefGoogle Scholar
  40. Metcalfe, J., & Finn, B. (2008). Evidence that judgments of learning are causally related to study choice. Psychonomic Bulletin and Review, 15, 174–179.CrossRefGoogle Scholar
  41. Metcalfe, J., & Kornell, N. (2005). A region of proximal learning model of study time allocation. Journal of Memory and Language, 52, 463–477.CrossRefGoogle Scholar
  42. Miller, T. M., & Geraci, L. (2011). Training metacognition in the classroom: the influence of incentives and feedback on exam predictions. Metacognition and Learning, 6, 303–314.CrossRefGoogle Scholar
  43. Mueller, D. J., & Shwedel, A. (1975). Some correlates of net gain resultant from answer changing on objective achievement test items. Journal of Educational Measurement, 12, 251–254.CrossRefGoogle Scholar
  44. Mueller, D. J., & Wasser, V. (1977). Implications of changing answers on objective test items. Journal of Educational Measurement, 14, 9–13.CrossRefGoogle Scholar
  45. Nelson, T. O., & Narens, L. (1990). Metamemory: A theoretical framework and new findings. In G. Bower (Ed.), The psychology of learning and motivation: Advances in research and theory (pp. 125–173). New York: Academic.Google Scholar
  46. Nietfeld, J. L., Cao, L., & Osborne, J. W. (2005). Metacognitive monitoring accuracy and student performance in the postsecondary classroom. The Journal of Experimental Education, 74(1), 7–28.Google Scholar
  47. Nietfeld, J. L., Cao, L., & Osborne, J. W. (2006a). The effect of distributed monitoring exercises and feedback on performance, monitoring accuracy, and self-efficacy. Metacognition and Learning, 1, 159–179.CrossRefGoogle Scholar
  48. Nietfeld, J. L., Enders, C. K., & Schraw, G. (2006b). A Monte Carlo comparison of measures of relative and absolute monitoring accuracy. Educational and Psychological Measurement, 66, 258–271.CrossRefGoogle Scholar
  49. Perfect, T. J. (2002). When does eyewitness confidence predict performance? In T. J. Perfect & B. I. Schwartz (Eds.), Applied metacognition (pp. 95–120). Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  50. Revuelta, J., Ximénez, C., & Olea, J. (2003). Psychometric and psychological effects of item selection and review on computerized testing. Educational and Psychological Measurement, 63, 791–808.CrossRefGoogle Scholar
  51. Samuelson, W., & Zeckhauser, R. (1988). Status quo bias in decision making. Journal of Risk and Uncertainty, 1, 7–59.CrossRefGoogle Scholar
  52. Schneider, W. (2008). The development of metacognitive knowledge in children and adolescents: major trends and implications for education. Mind Brain and Education, 2, 114–121.CrossRefGoogle Scholar
  53. Schwartz, B. L. (2011). The effect of being in a tip-of-the-tongue state on subsequent items. Memory & Cognition, 39(2), 245–250.CrossRefGoogle Scholar
  54. Schwartz, B. L., & Bacon, E. (2008). Metacognitive neuroscience. In J. Dunlosky & R. A. Bjork (Eds.), Handbook of memory and metamemory: Essays in honor of Thomas O. Nelson (pp. 355–371). New York: Psychology Press.Google Scholar
  55. Schwarz, N., Sanna, L. J., Skurnik, I., & Yoon, C. (2007). Metacognitive experiences and the intricacies of setting people straight: implications for debiasing and public information campaigns. Advances in Experimental Social Psychology, 39, 127–161.CrossRefGoogle Scholar
  56. Shatz, M. A., & Best, J. B. (1987). Students’ reasons for changing answers on objective tests. Teaching of Psychology, 14(4), 241–242.CrossRefGoogle Scholar
  57. Smith, A., White, K. P., & Coop, R. H. (1979). The effect of item type on the consequences of changing answers on multiple-choice tests. Journal of Educational Measurement, 16, 203–208.CrossRefGoogle Scholar
  58. Smith, J. D., Couchman, J. J., & Beran, M. J. (2014). The highs and lows of theoretical interpretation in animal-metacognition research. In S. M. Fleming & C. D. Frith (Eds.), The cognitive neuroscience of metacognition. Berlin: Springer.Google Scholar
  59. Swanson, H. L. (1990). Influence of metacognitive knowledge and aptitude on problem solving. Journal of Educational Psychology, 82, 306–314.CrossRefGoogle Scholar
  60. Tversky, A., & Kahneman, D. (1973). Availability: a heuristic for judging frequency and probability. Cognitive Psychology, 5, 207–232.CrossRefGoogle Scholar
  61. Underwood, B. J. (1996). Individual and group predictions of item difficulty for free learning. Journal of Experimental Psychology, 71, 673–679.CrossRefGoogle Scholar
  62. Vispoel, W. (1998). Reviewing and changing answers on computer-adaptive and self-adaptive vocabulary tests. Journal of Educational Measurement, 35, 329–346.Google Scholar
  63. Vispoel, W. (2000). Reviewing and changing answers on computerized fixed-item vocabulary tests. Educational and Psychological Measurement, 60, 371–384.CrossRefGoogle Scholar
  64. Vuk, J., & Morse, D. T. (2012). College students’ behavior on self-tailored, multiple-choice examinations. Innovative Teaching, 1, 2165–2236.Google Scholar
  65. Yan, W. (1994). Learning ability and memory monitoring. Intelligence, 18, 215–229.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Justin J. Couchman
    • 1
  • Noelle E. Miller
    • 1
  • Shaun J. Zmuda
    • 2
  • Kathryn Feather
    • 2
  • Tina Schwartzmeyer
    • 2
  1. 1.Albright CollegeReadingUSA
  2. 2.Fredonia State UniversityFredoniaUSA

Personalised recommendations