Educational Psychology Review

, Volume 24, Issue 2, pp 313–337 | Cite as

Educational Implications of Expertise Reversal Effects in Learning and Performance of Complex Cognitive and Sensorimotor Skills

  • Slava Kalyuga
  • Remy Rikers
  • Fred Paas


There have been several rather counterintuitive phenomena observed in different fields of research that compared the performance of experts and novices. For example, studies of medical expertise demonstrated that less experienced medical students may in some situations outperform seasoned medical practitioners on recall of specific cases. Studies of cognitive load aspects of complex skill acquisition in technical and academic domains demonstrated that more experienced technical trainees or students may learn less than expected from instructions that are very effective for novices. Finally, research in the execution of movements in sports showed that, while novice players performed well under skill-focused and accuracy conditions, such conditions inhibited performance of experts who benefitted from speed conditions. Apparently, in each of those phenomena, there is a mechanism that disrupted successful expert performance while, at the same time, enhanced performance of less experienced individuals. This paper presents a review of the expertise reversal effects that have been found in the different fields and identifies their specific underlying mechanisms and common origins. Knowledge of theoretical models and empirical findings in one of those fields could enrich research ideas and approaches in others. The implications of these ideas for research aimed at improving learning and instruction are discussed.


Cognitive load theory Encapsulation theory of medical expertise Attention focusing in execution of complex sensorimotor skills Expertise reversal effect Intermediate effect Explicit monitoring effect 


  1. Adams, J. A. (1971). A closed-loop theory of motor learning. Journal of Motor Behavior, 3, 111–150.Google Scholar
  2. Anderson, J. R. (1987). Skill acquisition: Compilation of weak-method problem solutions. Psychological Review, 94, 192–210.CrossRefGoogle Scholar
  3. Baumeister, R. F. (1984). Choking under pressure: Self-consciousness and paradoxical effects of incentives on skillful performance. Journal of Personality and Social Psychology, 46, 610–620.CrossRefGoogle Scholar
  4. Beilock, S. L., & Carr, T. H. (2001). On the fragility of skilled performance: What governs choking under pressure? Journal of Experimental Psychology: General, 130, 701–725.CrossRefGoogle Scholar
  5. Beilock, S. L., & Carr, T. H. (2005). When high-powered people fail: Working memory and “choking under pressure” in math. Psychological Science, 16, 101–105.CrossRefGoogle Scholar
  6. Beilock, S. L., Wierenga, S. A., & Carr, T. H. (2002). Expertise, attention, and memory in sensorimotor skill execution: Impact of novel task constraints on dual-task performance and episodic memory. Quarterly Journal of Experimental Psychology: Human Experimental Psychology, 55A, 1211–1240.Google Scholar
  7. Beilock, S. L., Bertenthal, B. I., McCoy, A. M., & Carr, T. H. (2004). Haste does not always make waste: Expertise, direction of attention, and speed versus accuracy in performing sensorimotor skills. Psychonomic Bulletin & Review, 11, 373–379.CrossRefGoogle Scholar
  8. Beilock, S. L., Jellison, W. A., Rydell, R. J., McConnell, A. R., & Carr, T. H. (2006). On the causal mechanisms of stereotype threat: Can skills that don’t rely heavily on working memory still be threatened? Personality and Social Psychology Bulletin, 32, 1059–1071.CrossRefGoogle Scholar
  9. Bennett, H. L. (1983). Remembering drink orders: The memory skill of cocktail waitresses. Human Learning, 2, 157–169.Google Scholar
  10. Blayney, P., Kalyuga, S., & Sweller, J. (2010). Interactions between the isolated–interactive elements effect and levels of learner expertise: Experimental evidence from an accountancy class. Instructional Science, 38, 277–287.CrossRefGoogle Scholar
  11. Bordage, G. (1994). Elaborated knowledge: A key to successful diagnostic thinking. Academic Medicine, 69, 883–885.CrossRefGoogle Scholar
  12. Boshuizen, H. P. A., & Schmidt, H. G. (1992). On the role of biomedical knowledge in clinical reasoning by experts, intermediates and novices. Cognitive Science, 16, 153–184.CrossRefGoogle Scholar
  13. Butler, J. L., & Baumeister, R. F. (1998). The trouble with friendly faces: Skilled performance with a supportive audience. Journal of Personality and Social Psychology, 75, 1213–1230.CrossRefGoogle Scholar
  14. Camerer, C. F., & Johnson, E. J. (1991). The process–performance paradox in expert judgment: How can experts know so much and predict so badly? In K. A. Ericsson & J. Smith (Eds.), Toward a general theory of expertise (pp. 195–217). Cambridge: Cambridge University Press.Google Scholar
  15. Chamberland, M., St-Onge, C., Setrakian, J., Lanthier, L., Bergeron, L., Bourget, A., Mamede, S., Schmidt, H., & Rikers, R. (2011). The influence of medical students' self-explanations on diagnostic performance. Medical Education, 45, 688–695.CrossRefGoogle Scholar
  16. Chase, W. G., & Simon, H. A. (1973). Perception in chess. Cognitive Psychology, 4, 55–81.CrossRefGoogle Scholar
  17. Chi, M. (1994). Eliciting self-explanations improves understanding. Cognitive Science, 18, 439–477.Google Scholar
  18. Clarke, T., Ayres, P., & Sweller, J. (2005). The impact of sequencing and prior knowledge on learning mathematics through spreadsheet applications. Educational Technology Research and Development, 53, 15–24.CrossRefGoogle Scholar
  19. Cronbach, L. (1967). How can instruction be adapted to individual differences. In R. Gagne (Ed.), Learning and individual differences (pp. 23–39). Columbus: Merrill.Google Scholar
  20. Cronbach, L., & Snow, R. (1977). Aptitudes and instructional methods: A handbook for research on interactions. New York: Irvington.Google Scholar
  21. Custers, E. J. F. M., Boshuizen, H. P. A., & Schmidt, H. G. (1998). The role of illness scripts in the development of medical diagnostic expertise: Results from an interview study. Cognition and Instruction, 16, 367–398.CrossRefGoogle Scholar
  22. De Bruin, A. B. H., Van De Wiel, M. W. J., Rikers, R. M. J. P., & Schmidt, H. G. (2005). Examining the stability of experts’ clinical case processing: An experimental manipulation. Instructional Science, 33, 251–270.CrossRefGoogle Scholar
  23. De Groot, A. (1965). Thought and choice in chess. The Hague: Mouton. (Original work published 1946).Google Scholar
  24. Dunning, D., Johnson, K., Erlinger, J., & Kruger, J. (2003). Why people fail to recognize their own incompetence. Current Directions in Psychological Science, 12, 83–87.CrossRefGoogle Scholar
  25. Dunning, D., Heath, C., & Suls, J. M. (2004). Flawed self-assessment: Implications for health, education, and the workplace. Psychological Science in the Public Interest, 5, 69–106.CrossRefGoogle Scholar
  26. Ericsson, K. A. (1985). Memory skill. Canadian Journal of Psychology, 39, 188–231.CrossRefGoogle Scholar
  27. Ericsson, K. A. (2005). Recent advances in expertise research: A commentary on the contributions to the special issue. Applied Cognitive Psychology, 19, 233–241.CrossRefGoogle Scholar
  28. Ericsson, K. A. (2006). The influence of experience and deliberate practice on the development of superior expert performance. In K. A. Ericsson, N. Charness, R. R. Hoffman, & P. J. Feltovich (Eds.), The Cambridge handbook of expertise and expert performance (pp. 39–68). New York: Cambridge University Press.Google Scholar
  29. Ericsson, K. A., & Lehmann, A. C. (1996). Expert and exceptional performance: Maximal adaptation to task constraints. Annual Review of Psychology, 47, 273–305.CrossRefGoogle Scholar
  30. Ericsson, K. A., & Polson, P. G. (1988). A cognitive analysis of exceptional memory for restaurant orders. In M. T. H. Chi, R. Glaser, & M. J. Farr (Eds.), The nature of expertise. Hillsdale: Erlbaum.Google Scholar
  31. Ericsson, K. A., & Simon, H. A. (1984). Protocol analysis: Verbal reports as data. Cambridge: Bradford Books/MIT Press.Google Scholar
  32. Ericsson, K. A., & Simon, H. A. (1993). Protocol analysis: Verbal reports as data (Rev. Ed.). Cambridge: Bradford Books/MIT Press.Google Scholar
  33. Eva, K. W., Norman, G. R., Neville, A. J., Wood, T. J., & Brooks, L. R. (2002). Expert–novice differences in memory: A reformulation. Teaching and Learning in Medicine, 14, 257–263.CrossRefGoogle Scholar
  34. Feltovich, P. J., & Barrows, H. S. (1984). Issues of generality in medical problem solving. In H. G. Schmidt & M. L. De Volder (Eds.), Tutorials in problem-based learning (pp. 128–142). Assen: Van Gorcum.Google Scholar
  35. Fitts, P. M., & Posner, M. I. (1967). Human performance. Belmont: Brooks/Cole.Google Scholar
  36. Gilhooly, K. J. (1996). Thinking: Directed, undirected and creative (3rd ed.). London: Academic.Google Scholar
  37. Gilhooly, K. J., & Simpson, S. (1992). Deep knowledge in human medical expertise. In E. Keravnou (Ed.), Deep models for medical knowledge in engineering (pp. 273–285). Amsterdam: Elsevier.Google Scholar
  38. Gobet, F., & Simon, H. A. (1996). Recall of rapidly presented random chess positions is a function of skill. Psychonomic Bulletin & Review, 3, 159–163.CrossRefGoogle Scholar
  39. Gray, R. (2004). Attending to the execution of a complex sensorimotor skill: Expertise differences, choking, and slumps. Journal of Experimental Psychology: Applied, 10, 42–54.CrossRefGoogle Scholar
  40. Gucciardi, D. F., & Dimmock, J. A. (2008). Choking under pressure in sensorimotor skills: Conscious processing or depleted attentional resources? Psychology of Sport and Exercise, 9, 45–59.CrossRefGoogle Scholar
  41. Haerem, T., & Rau, D. (2007). The influence of degree of expertise and objective task complexity on perceived task complexity and performance. Journal of Applied Psychology, 92, 1320–1331.CrossRefGoogle Scholar
  42. Jensen, A. R. (1990). Speed of information processing in a calculating prodigy. Intelligence, 14, 259–274.CrossRefGoogle Scholar
  43. Jordet, G., & Hartman, E. (2008). Avoidance motivation and choking under pressure in soccer penalty shootouts. Journal of Sport & Exercise Psychology, 30, 450–457.Google Scholar
  44. Kalyuga, S. (2006a). Assessment of learners’ organized knowledge structures in adaptive learning environments. Applied Cognitive Psychology, 20, 333–342.CrossRefGoogle Scholar
  45. Kalyuga, S. (2006b). Rapid cognitive assessment of learners’ knowledge structures. Learning and Instruction, 16, 1–11.CrossRefGoogle Scholar
  46. Kalyuga, S. (2007). Expertise reversal effect and its implications for learner-tailored instruction. Educational Psychology Review, 19, 509–539.CrossRefGoogle Scholar
  47. Kalyuga, S. (2008). When less is more in cognitive diagnosis: A rapid assessment method for adaptive learning environments. Journal of Educational Psychology, 100, 603–612.CrossRefGoogle Scholar
  48. Kalyuga, S. (2011). Cognitive load theory: How many types of load does it really need? Educational Psychology Review, 23, 1–19.CrossRefGoogle Scholar
  49. Kalyuga, S., & Renkl, A. (2010). Expertise reversal effect and its instructional implications. Instructional Science, 38, 209–215.CrossRefGoogle Scholar
  50. Kalyuga, S., & Sweller, J. (2004). Measuring knowledge to optimize cognitive load factors during instruction. Journal of Educational Psychology, 96, 558–568.CrossRefGoogle Scholar
  51. Kalyuga, S., & Sweller, J. (2005). Rapid dynamic assessment of expertise to improve the efficiency of adaptive e-learning. Educational Technology Research and Development, 53, 83–93.CrossRefGoogle Scholar
  52. Kalyuga, S., Chandler, P., & Sweller, J. (1998). Levels of expertise and instructional design. Human Factors, 40, 1–17.CrossRefGoogle Scholar
  53. Kalyuga, S., Chandler, P., & Sweller, J. (2000). Incorporating learner experience into the design of multimedia instruction. Journal of Educational Psychology, 92, 126–136.CrossRefGoogle Scholar
  54. Kalyuga, S., Chandler, P., & Sweller, J. (2001a). Learner experience and efficiency of instructional guidance. Educational Psychology, 21, 5–23.CrossRefGoogle Scholar
  55. Kalyuga, S., Chandler, P., Tuovinen, J., & Sweller, J. (2001b). When problem solving is superior to studying worked examples. Journal of Educational Psychology, 93, 579–588.Google Scholar
  56. Kalyuga, S., Ayres, P., Chandler, P., & Sweller, J. (2003). The expertise reversal effect. Educational Psychologist, 38, 23–31.CrossRefGoogle Scholar
  57. Kalyuga, S., Renkl, A., & Paas, F. (2010). Facilitating flexible problem solving: A cognitive load perspective. Educational Psychology Review, 22, 175–186.CrossRefGoogle Scholar
  58. Lewis, B. P., & Linder, D. E. (1997). Thinking about choking? Attentional processes and paradoxical performance. Personality and Social Psychology Bulletin, 23, 937–944.CrossRefGoogle Scholar
  59. Lombrozo, T. (2006). The structure and function of explanations. Trends in Cognitive Sciences, 10, 464–470.CrossRefGoogle Scholar
  60. Luchins, A. S., & Luchins, E. H. (1987). Einstellung effects. Science, New Series, 238(4827), 598. (Oct. 30, 1987).Google Scholar
  61. Masters, R. S. W. (1992). Knowledge, knerves and know-how: The role of explicit versus implicit knowledge in the breakdown of a complex motor skill under pressure. British Journal of Psychology, 83, 343–358.CrossRefGoogle Scholar
  62. Newell, A. (1991). Motor skill acquisition. Annual Review of Psychology, 42, 213–237.CrossRefGoogle Scholar
  63. Nisbett, R. E., & Wilson, T. D. (1977). Telling more than we can know: Verbal reports on mental processes. Psychological Review, 84, 231–259.CrossRefGoogle Scholar
  64. Norman, G. R., Brooks, L. R., & Allen, S. W. (1989). Recall by expert medical practitioners and novices as a record of processing attention. Journal of Experimental Psychology: Learning, Memory and Cognition, 15, 1166–1174.Google Scholar
  65. Oksa, A., Kalyuga, S., & Chandler, P. (2010). Expertise reversal effect in using explanatory notes for readers of Shakespearean text. Instructional Science, 38, 217–236.CrossRefGoogle Scholar
  66. Paas, F. (1992). Training strategies for attaining transfer of problem-solving skill in statistics: A cognitive-load approach. Journal of Educational Psychology, 84, 429–434.CrossRefGoogle Scholar
  67. Paas, F., & Van Merriënboer, J. J. G. (1994). Variability of worked examples and transfer of geometrical problem-solving skills: A cognitive-load approach. Journal of Educational Psychology, 86, 122–133.CrossRefGoogle Scholar
  68. Paas, F., Renkl, A., & Sweller, J. (2003). Cognitive load theory and instructional design: Recent developments. Educational Psychologist, 38, 1–4.CrossRefGoogle Scholar
  69. Paas, F., Renkl, A., & Sweller, J. (2004). Cognitive load theory: Instructional implications of the interaction between information structures and cognitive architecture. Instructional Science, 32, 1–8.CrossRefGoogle Scholar
  70. Paas, F., Tuovinen, J. E., Van Merrienboer, J. J. G., & Darabi, A. A. (2005). A motivational perspective on the relation between mental effort and performance. Educational Technology Research and Development, 53, 25–34.CrossRefGoogle Scholar
  71. Patel, V. L., & Groen, G. J. (1986). Knowledge based solution strategies in medical reasoning. Cognitive Science, 10, 91–116.CrossRefGoogle Scholar
  72. Patel, V. L., & Groen, G. J. (1991). Developmental accounts of the transition from medical student to doctor: Some problems and suggestions. Medical Education, 25, 527–535.CrossRefGoogle Scholar
  73. Patel, V. L., Evans, D. A., & Groen, G. J. (1989). Biomedical knowledge and clinical reasoning. In D. A. Evans & V. L. Patel (Eds.), Cognitive science in medicine: Biomedical modeling (pp. 53–112). Cambridge: MIT Press.Google Scholar
  74. Patel, V. L., Groen, G. J., & Arocha, J. F. (1990). Medical expertise as a function of task difficulty. Memory and Cognition, 18, 394–406.CrossRefGoogle Scholar
  75. Pollock, E., Chandler, P., & Sweller, J. (2002). Assimilating complex information. Learning and Instruction, 12, 61–86.CrossRefGoogle Scholar
  76. Reisslein, J., Atkinson, R. K., Seeling, P., & Reisslein, M. (2006). Encountering the expertise reversal effect with a computer-based environment on electrical circuit analysis. Learning and Instruction, 16, 92–103.CrossRefGoogle Scholar
  77. Renkl, A. (1997). Learning from worked-out examples: A study on individual differences. Cognitive Science, 21, 1–29.CrossRefGoogle Scholar
  78. Renkl, A., & Atkinson, R. K. (2003). Structuring the transition from example study to problem solving in cognitive skills acquisition: A cognitive load perspective. Educational Psychologist, 38, 15–22.CrossRefGoogle Scholar
  79. Rikers, R. M. J. P., Schmidt, H. G., & Boshuizen, H. P. A. (2000). Knowledge encapsulation and the intermediate effect. Contemporary Educational Psychology, 25, 150–166.CrossRefGoogle Scholar
  80. Rikers, R. M. J. P., Schmidt, H. G., & Boshuizen, H. P. A. (2002). On the constraints of encapsulated knowledge: Clinical case representations by medical experts and subexperts. Cognition and Instruction, 20, 27–45.CrossRefGoogle Scholar
  81. Rikers, R. M., Loyens, S., te Winkel, W., Schmidt, H. G., & Sins, P. H. (2005). The role of biomedical knowledge in clinical reasoning: A lexical decision study. Academic Medicine, 80, 945–949.CrossRefGoogle Scholar
  82. Schmidt, R. A. (1975). A schema theory of discrete motor skill learning. Psychological Review, 82, 225–260.CrossRefGoogle Scholar
  83. Schmidt, H. G., & Boshuizen, H. P. A. (1992). Encapsulation of biomedical knowledge. In D. A. Evans & V. L. Patel (Eds.), Advanced models of cognition for medical training and practice (pp. 265–282). New York: Springer.Google Scholar
  84. Schmidt, H. G., & Boshuizen, H. P. A. (1993). On the origin of intermediate effects in clinical case recall. Memory and Cognition, 21, 338–351.CrossRefGoogle Scholar
  85. Schmidt, H. G., & Rikers, R. M. J. P. (2007). How expertise develops in medicine: Knowledge encapsulation and illness script formation. Medical Education, 41, 1133–1139.Google Scholar
  86. Schmidt, H. G., Boshuizen, H. P. A., & Hobus, P. P. M. (1988). Transitory stages in the development of medical expertise: The “intermediate effect” in clinical case representation studies. In Proceedings of the Cognitive Science Society Meeting (pp. 139–145). Hillsdale: Lawrence Erlbaum Associates, Inc.Google Scholar
  87. Schnotz, W. (2010). Reanalyzing the expertise reversal effect. Instructional Science, 38, 315–323.CrossRefGoogle Scholar
  88. Schnotz, W., & Kürschner, C. (2007). A reconsideration of cognitive load theory. Educational Psychology Review, 19, 469–508.CrossRefGoogle Scholar
  89. Simpson, S. A., & Gilhooly, K. J. (1997). Diagnostic thinking processes: Evidence from a constructive interaction study of electrocardiogram (ECG) interpretation. Applied Cognitive Psychology, 11, 543–554.CrossRefGoogle Scholar
  90. Snow, R., & Lohman, D. (1984). Toward a theory of cognitive aptitude for learning from instruction. Journal of Educational Psychology, 76, 347–376.CrossRefGoogle Scholar
  91. Sweller, J. (2010). Element interactivity and intrinsic, extraneous, and germane cognitive load. Educational Psychology Review, 22, 123–138.CrossRefGoogle Scholar
  92. Sweller, J., Ayres, P., & Kalyuga, S. (2011). Cognitive load theory. New York: Springer.CrossRefGoogle Scholar
  93. Tobias, S. (1976). Achievement treatment interactions. Review of Educational Research, 46, 61–74.Google Scholar
  94. Tobias, S. (1989). Another look at research on the adaptation of instruction to student characteristics. Educational Psychologist, 24, 213–227.CrossRefGoogle Scholar
  95. Tobias, S. (2010). The expertise reversal effect and aptitude treatment interaction research. Instructional Science, 38, 309–314.CrossRefGoogle Scholar
  96. Tuovinen, J., & Sweller, J. (1999). A comparison of cognitive load associated with discovery learning and worked examples. Journal of Educational Psychology, 91, 334–341.CrossRefGoogle Scholar
  97. Van de Wiel, M. W. J., Boshuizen, H. P. A., & Schmidt, H. G. (2000). Knowledge restructuring in expertise development: Evidence from pathophysiological representations of clinical cases by students and physicians. European Journal of Cognitive Psychology, 12, 323–355.CrossRefGoogle Scholar
  98. Van Gog, T., Ericsson, K. A., Rikers, R. M. J. P., & Paas, F. (2005). Instructional design for advanced learners: Establishing connections between the theoretical frameworks of cognitive load and deliberate practice. Educational Technology, Research and Development, 53, 73–81.CrossRefGoogle Scholar
  99. Van Merriënboer, J. J. G. (1990). Strategies for programming instruction in high school: Program completion vs. program generation. Journal of Educational Computing Research, 6, 265–287.CrossRefGoogle Scholar
  100. Van Merrienboer, J. J. G., & Paas, F. (1990). Automation and schema acquisition in learning elementary computer programming: Implications for the design of practice. Computers in Human Behavior, 6, 273–289.CrossRefGoogle Scholar
  101. Verkoeijen, P. P. J. L., Rikers, R. M. J. P., Schmidt, H. G., Van de Wiel, M. W. J., & Kooman, J. P. (2004). Case representation by medical experts, intermediates and novices for laboratory data presented with and without a clinical context. Medical Education, 38, 617–627.CrossRefGoogle Scholar
  102. Vincente, K. J., & Wang, J. H. (1998). An ecological theory of expertise effects in memory recall. Psychological Review, 105, 33–57.CrossRefGoogle Scholar
  103. Wiley, J. (1998). Expertise as a mental set: The effects of domain knowledge in creative problem solving. Memory & Cognition, 26, 716–730.CrossRefGoogle Scholar
  104. Wimmers, P. F., Schmidt, H. G., Verkoeijen, P. P. J. L., & Van de Wiel, M. W. J. (2005). Inducing expertise effects in clinical case recall. Medical Education, 39, 949–957.CrossRefGoogle Scholar
  105. Wright, E. F., Jackson, W., Christie, S. D., McGuire, G. R., et al. (1991). The home-course disadvantage in golf championships: Further evidence for the undermining effect of supportive audiences on performance under pressure. Journal of Sport Behavior, 14, 51–60.Google Scholar
  106. Wright, E. F., Voyer, D., Wright, R. D., & Roney, C. (1995). Supporting audiences and performance under pressure: The home-ice disadvantage in hockey championships. Journal of Sport Behavior, 18, 21–28.Google Scholar
  107. Wulf, G., Shea, C., & Lewthwaite, R. (2010). Motor skill learning and performance: A review of influential factors. Medical Education, 44, 75–84.CrossRefGoogle Scholar
  108. Yeung, A. S., Jin, P., & Sweller, J. (1998). Cognitive load and learner expertise: Split attention and redundancy effects in reading with explanatory notes. Contemporary Educational Psychology, 23, 1–21.CrossRefGoogle Scholar
  109. Zimmerman, B. J., & Kitsantas, A. (1997). Developmental phases in self-regulation: Shifting from process goals to outcome goals. Journal of Educational Psychology, 89, 29–36.CrossRefGoogle Scholar

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© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  1. 1.School of EducationUniversity of New South WalesSydneyAustralia
  2. 2.Institute of PsychologyErasmus University RotterdamRotterdamThe Netherlands
  3. 3.Faculty of EducationUniversity of WollongongWollongongAustralia

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