Cognitive Interruption as an Object of Metacognitive Monitoring: Feeling of Difficulty and Surprise



An important question regarding metacognition in problem solving is what triggers the metacognitive experience of feeling of difficulty? In this chapter, we present three experiments suggesting that feeling of difficulty arises from lack of fluency in processing due to either working memory load or cognitive interruption. Experiments 1 and 2 showed that working memory load reduces performance (as measured by accuracy of response and reaction times) and increases feeling of difficulty. Experiment 3 further demonstrated that reaction times and feeling of difficulty ratings increase with cognitive interruption caused by discrepancies in processing. Interestingly, in Experiment 3, feeling of difficulty correlated highly and positively with surprise, which is another response to discrepant events. The implications of these findings are discussed as are suggestions for future research.


Arithmetic Operation Presentation Order Work Memory Load Response Production Metacognitive Knowledge 
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  1. Adams, J. W., & Hitch, G. J. (1997). Working memory and children’s mental addition. Journal of Experimental Child Psychology, 67(1), 21–38.CrossRefGoogle Scholar
  2. Alberdi, E., Sleeman, D. H., & Korpi, M. (2000). Accommodating surprise in taxonomic tasks: The role of expertise. Cognitive Science, 24(1), 53–91.CrossRefGoogle Scholar
  3. Alter, A. L., Oppenheimer, D. M., Epley, N., & Eyre, R. N. (2007). Overcoming intuition: Metacognitive difficulty activates analytic reasoning. Journal of Experimental Psychology: General, 136(4), 569–576.CrossRefGoogle Scholar
  4. Ashcraft, M. H. (1992). Cognitive arithmetic: A review of data and theory. Cognition, 44(1–2), 75–106.CrossRefGoogle Scholar
  5. Ayres, P. L. (2001). Systematic mathematical errors and cognitive load. Contemporary Educational Psychology, 26, 227–248.CrossRefGoogle Scholar
  6. Ayres, P. (2006). Using subjective measures to detect variations of intrinsic cognitive load within problems. Learning and Instruction, 16(5), 389–400.CrossRefGoogle Scholar
  7. Barch, D. M., Braver, T. S., Nystrom, L. E., Forman, S. D., Noll, D. C., & Cohen, J. D. (1997). Dissociating working memory from task difficulty in human prefrontal cortex. Neuropsychologia, 35(10), 1373–1380.CrossRefGoogle Scholar
  8. Borg, G. (1978). Subjective aspects of physical and mental load. Ergonomics, 21(3), 215–220.CrossRefGoogle Scholar
  9. Borg, G., Bratfisch, O., & Dornič, S. (1971). On the problems of perceived difficulty. Scandinavian Journal of Psychology,12, 249–260. CrossRefGoogle Scholar
  10. Botvinick, M. M., Braver, T. S., Barch, D. M., Carter, C. S., & Cohen, J. D. (2001). Conflict monitoring and cognitive control. Psychological Review, 108(3), 624–652.CrossRefGoogle Scholar
  11. Botvinick, M. M., Cohen, J. D., & Carter, C. S. (2004). Conflict monitoring and anterior cingulate cortex: An update. Trends in Cognitive Sciences, 8(12), 539–546.CrossRefGoogle Scholar
  12. Brinkmann, K., & Gendolla, G. H. E. (2007). Dysphoria and mobilization of mental effort: Effects on cardiovascular reactivity. Motivation and Emotion, 31, 71–82.CrossRefGoogle Scholar
  13. Bruner, J., & Postman, L. (1949). On the perception of incongruity: A paradigm. Journal of Personality, 18, 206–223.CrossRefGoogle Scholar
  14. Bush, G., Luu, P., & Posner, M. I. (2000). Cognitive and emotional influences in anterior cingulate cortex. Trends in Cognitive Sciences, 4(6), 215–222.CrossRefGoogle Scholar
  15. Campbell, J. I. D., & Xue, Q. (2001). Cognitive arithmetic across cultures. Journal of Experimental Psychology: General, 130(2), 299–315.CrossRefGoogle Scholar
  16. Carter, C. S., Braver, T. S., Barch, D. M., Botvinick, M. M., Noll, D., & Cohen, J. D. (1998). Anterior cingulate cortex, error detection, and the online monitoring of performance. Science, New Series, 280(5354), 748–749.Google Scholar
  17. Carver, C. S. (2003). Pleasure as a sign you can attend to something else: Placing positive feelings within a general model of affect. Cognition and Emotion, 17(2), 241–261.CrossRefGoogle Scholar
  18. Critchley, H. D., Mathias, C. J., Josephs, O., O’Doherty, J., Zanini, S., Dewar, B.-K., et al. (2003). Human cingulate cortex and autonomic control: Converging neuroimaging and clinical evidence. Brain, 126, 2139–2152.CrossRefGoogle Scholar
  19. Davidson, J. E., Deuser, R., & Sternberg, R. J. (1994). The role of metacognition in problem ­solving. In J. Metcalfe & A. P. Shimamura (Eds.), Metacognition: Knowing about knowing (pp. 207–226). Cambridge, MA: Bradford.Google Scholar
  20. de Hoyos, M., Gray, E., & Simpson, A. (2004). Uncertainty during the early stages of problem solving. Proceedings of the 28th Conference of the International Group for the Psychology of Mathematics Education, 2, 255–262.Google Scholar
  21. Dehaene, S., Posner, M. I., & Tucker, D. M. (1994). Localization of a neural system for error detection and compensation. Psychological Science, 5(5), 303–305.CrossRefGoogle Scholar
  22. Delignières, D. (1998). Perceived difficulty and resources investment in motor tasks. European Yearbook of Sport Psychology, 2, 33–54.Google Scholar
  23. D’Esposito, M., Detre, J. A., Alsop, D. C., Shin, R. K., Atlas, S., & Grossman, M. (1995). The neural basis of the central executive system of working memory. Nature, 378, 279–281.CrossRefGoogle Scholar
  24. DeStefano, D., & LeFevre, J.-A. (2004). The role of working memory in mental arithmetic. European Journal of Cognitive Psychology, 16(3), 353–386.CrossRefGoogle Scholar
  25. Dewey, J. (1910). How we think. London: Health.CrossRefGoogle Scholar
  26. Duncan, J., & Owen, A. M. (2000). Common regions of the human frontal lobe recruited by diverse cognitive demands. Review, 23(10), 475–483.Google Scholar
  27. Efklides, A. (2001). Metacognitive experiences in problem solving: Metacognition, motivation, and self-regulation. In A. Efklides, J. Kuhl, & R. M. Sorrentino (Eds.), Trends and prospects in motivation research (pp. 297–323). Dordrecht, The Netherlands: Kluwer.Google Scholar
  28. Efklides, A. (2002). The systemic nature of metacognitive experiences: Feelings, judgments, and their interrelations. In M. Izaute, P. Chambres, & P.-J. Marescaux (Eds.), Metacognition: Process, function, and use (pp. 19–34). Dordrecht, The Netherlands: Kluwer.CrossRefGoogle Scholar
  29. Efklides, A. (2005). Emotional experiences during learning: Multiple, situated and dynamic. Learning and Instruction, 15, 377–380.CrossRefGoogle Scholar
  30. Efklides, A. (2006). Metacognition and affect: What can metacognitive experiences tell us about the learning process? Educational Research Review, 1, 3–14.CrossRefGoogle Scholar
  31. Efklides, A., & Tsiora, A. (2002). Metacognitive experiences, self-concept, and self-regulation. Psychologia: An International Journal of Psychology in the Orient, 45, 222–236.CrossRefGoogle Scholar
  32. Efklides, A., Kourkoulou, A., Mitsiou, F., & Ziliaskopoulou, D. (2006). Metacognitive knowledge of effort, personality factors, and mood state: Their relationships with effort-related metacognitive experiences. Metacognition and Learning, 1(1), 33–49.CrossRefGoogle Scholar
  33. Efklides, A., Papadaki, M., Papantoniou, G., & Kiosseoglou, G. (1997). Effects of cognitive ability and affect on school mathematics performance and feelings of difficulty. American Journal of Psychology, 110(2), 225–258.CrossRefGoogle Scholar
  34. Efklides, A., Papadaki, M., Papantoniou, G., & Kiosseoglou, G. (1998). Individual differences in feelings of difficulty: The case of school mathematics. European Journal of Psychology of Education, 13(2), 207–226.CrossRefGoogle Scholar
  35. Efklides, A., & Petkaki, C. (2005). Effects of mood on students’ metacognitive experiences. Learning and Instruction, 15(5), 415–431.CrossRefGoogle Scholar
  36. Efklides, A., Samara, A., & Petropoulou, M. (1999). Feeling of difficulty: An aspect of monitoring that influences control. European Journal of Psychology of Education, 14(4), 461–476.CrossRefGoogle Scholar
  37. Eysenck, M. W., & Keane, M. (2005). Cognitive psychology: A student’s handbook (5th ed.). New York: Taylor & Francis.Google Scholar
  38. Fernandez-Duque, D., Baird, J. A., & Posner, M. I. (2000). Awareness and metacognition. Consciousness and Cognition, 9(2), 324–326.CrossRefGoogle Scholar
  39. Flavell, J. H. (1979). Metacognition and cognitive monitoring: A new era of cognitive-developmental inquiry. American Psychologist, 34, 906–911.CrossRefGoogle Scholar
  40. Frijda, N. H. (1986). The emotions. Cambridge, UK: Cambridge University Press.Google Scholar
  41. Gendolla, G. H. E. (1999). Self-relevance of performance, task difficulty, and task engagement assessed as cardiovascular response. Motivation and Emotion, 23(1), 45–66.CrossRefGoogle Scholar
  42. Gendolla, G. H. E., & Krüsken, J. (2001). The joint impact of mood state and task difficulty on cardiovascular and electrodermal reactivity in active coping. Psychophysiology, 38, 548–556.CrossRefGoogle Scholar
  43. Han, S., Humphreys, G. W., & Chen, L. (1999). Uniform connectedness and classical gestalt principles of perceptual grouping. Perception and Psychophysics, 61(4), 661–674.CrossRefGoogle Scholar
  44. Herbert, A. (1978). Perceived causes of difficulty in work situations. Ergonomics, 21(7), 539–549.CrossRefGoogle Scholar
  45. Holyoak, K. J., Koh, K. K., & Nisbett, R. E. (1989). A theory of conditioning: Inductive learning within rule-based default hierarchies. Psychological Review, 96, 315–340.CrossRefGoogle Scholar
  46. Horstmann, G. (2002). Evidence for attentional capture by a surprising color singleton in visual search. Psychological Science, 13(6), 499–505.CrossRefGoogle Scholar
  47. Horstmann, G. (2005). Attentional capture by an unannounced color singleton depends on expectation discrepancy. Journal of Experimental Psychology: Human Perception and Performance, 31(5), 1039–1060.CrossRefGoogle Scholar
  48. Hrubes, D., & Feldman, R. R. (2001). Nonverbal displays as indicants of task difficulty. Contemporary Educational Psychology, 26, 267–276.CrossRefGoogle Scholar
  49. Imbo, I., De Rammelaere, S., & Vandierendonck, A. (2005). New insights in the role of working memory in carry and borrow operations. Psychologica Belgica, 45, 101–121.Google Scholar
  50. Imbo, I., & Vandierendonck, A. (2008). Effects of problem size, operation, and working-memory span on simple-arithmetic strategies: Differences between children and adults? Psychological Research, 72, 331–346.CrossRefGoogle Scholar
  51. Izard, C. E. (1977). Human emotions. New York: Plenum.Google Scholar
  52. Kahneman, D. (1973). Attention and effort. Englewood Cliffs, NJ: Prentice-Hall.Google Scholar
  53. Kahneman, D., & Miller, D. T. (1986). Norm theory: Comparing reality to its alternatives. Psychological Review, 93(2), 136–153.CrossRefGoogle Scholar
  54. Koriat, A. (2007). Metacognition and consciousness. In P. D. Zelazo, M. Moscovitch, & E. Thompson (Eds.), The Cambridge handbook of consciousness (pp. 289–325). Cambridge, UK: Cambridge University Press.CrossRefGoogle Scholar
  55. Koriat, A. (2008). Easy comes, easy goes? The link between learning and remembering and its exploitation in metacognition. Memory and Cognition, 36(2), 416–428.CrossRefGoogle Scholar
  56. Leonesio, R. J., & Nelson, T. O. (1990). Do different metamemory judgments tap the same underlying aspects of memory? Journal of Experimental Psychology: Learning, Memory, and Cognition, 16, 464–470.CrossRefGoogle Scholar
  57. MacLeod, C. M. (2004). The stroop task in cognitive research. In A. Wemzel & D. C. Rubin (Eds.), Cognitive methods and their application to clinical research (pp. 17–40). Washington, DC: American Psychological Association.Google Scholar
  58. Maguire, R., & Keane, M. T. (2006). Surprise: Disconfirmed expectations or representation-fit? Proceedings of the 28th Annual Conference of the Cognitive Science Society (pp. 1765–1770). Hillsdale, NJ: Erlbaum.Google Scholar
  59. Mandler, G. (1975). Mind and emotion. New York: Wiley.Google Scholar
  60. Mandler, G. (1984). Mind and body: Psychology of emotion and stress. New York: Norton.Google Scholar
  61. Meyer, W., Reisenzein, R., & Schützwohl, A. (1997). Toward a process analysis of emotions: The case of surprise. Motivation and Emotion, 21(3), 251–274.CrossRefGoogle Scholar
  62. Moraitou, D., & Efklides, A. (2009). The Blank in the Mind Questionnaire (BIMQ). European Journal of Psychological Assessment, 25, 115–122.CrossRefGoogle Scholar
  63. Nelson, T. O. (1996). Consciousness and metacognition. American Psychologist, 51, 102–116.CrossRefGoogle Scholar
  64. Nelson, T. O., & Narens, L. (1994). Why investigate metacognition? In J. Metcalfe & A. P. Shimamura (Eds.), Metacognition: Knowing about knowing (pp. 1–25). Cambridge, MA: Bradford.Google Scholar
  65. Norman, D. A., & Shallice, T. (1986). Attention to action: Willed and automatic control of behaviour. In R. J. Davidson, G. E. Schwartz, & D. Shapiro (Eds.), Consciousness and self-regulation (pp. 1–18). New York: Plenum.CrossRefGoogle Scholar
  66. Ortony, A. (1991). Value and emotion. In W. Kessen, A. Ortony, & F. Craik (Eds.), Memories, thoughts, and emotions: Essays in honor of George Mandler (pp. 337–353). Hillsdale, NJ: Erlbaum.Google Scholar
  67. Paas, F., Renkl, A., & Sweller, J. (2003). Cognitive load theory and instructional design: Recent developments. Educational Psychologist, 38(1), 1–4.CrossRefGoogle Scholar
  68. Paas, F., Tuovinen, J. E., Tabbers, H., & Van Gerven, P. W. M. (2003). Cognitive load measurement as a means to advance cognitive load theory. Educational Psychologist, 38(1), 63–71.CrossRefGoogle Scholar
  69. Pecchinenda, A., & Smith, C. A. (1996). The affective significance of skin conductance activity during a difficult problem-solving task. Cognition and Emotion, 10(5), 481–503.CrossRefGoogle Scholar
  70. Phaf, R. H., Mul, N. M., & Wolters, G. (1994). A connectionist view on dissociations. In C. Umilta & M. Moscovitch (Eds.), Attention and performance: XV. Conscious and nonconscious information processing (pp. 725–751). Cambridge, MA: MIT Press.Google Scholar
  71. Pintrich, P. R., Wolters, C. A., & Baxter, G. P. (2000). Assessing metacognition and self-regulated learning. In J. C. Impara (Series Ed.) & G. Schraw & J. C. Impara (Vol. Eds.), Issues in the measurement of metacognition (pp. 43–97). Lincoln, NE: University of Nebraska-Lincoln.Google Scholar
  72. Posner, G. J., Strike, K. A., Hewson, P. W., & Gertzog, W. A. (1982). Accommodation of a scientific conception: Toward a theory of conceptual change. Science Education, 66(2), 211–227.CrossRefGoogle Scholar
  73. Posner, M. I., & DiGirolamo, G. J. (1998). Executive attention: Conflict, target detection, and cognitive control. In R. Parasuraman (Ed.), The attentive brain (pp. 401–423). Cambridge, England: Cambridge University Press.Google Scholar
  74. Quinlan, P. T., & Wilton, R. N. (1998). Grouping by proximity or similarity? Competition between the gestalt principles in vision. Perception, 27(4), 417–430.CrossRefGoogle Scholar
  75. Rasmussen, C., & Bisanz, J. (2005). Representation and working memory in early arithmetic. Journal of Experimental Child Psychology, 91(2), 137–157.CrossRefGoogle Scholar
  76. Reber, R., Fazendeiro, T. A., & Winkielman, P. (2002). Processing fluency as the source of experiences at the fringe of consciousness. Psyche, 8. Retrieved October 26, 2007, from
  77. Reisenzein, R. (2000). Exploring the strength of association between the components of emotion syndromes: The case of surprise. Cognition and Emotion, 14(1), 1–38.CrossRefGoogle Scholar
  78. Rescorla, R. A. (2004). Spontaneous recovery. Learning and Memory, 11, 501–509.CrossRefGoogle Scholar
  79. Rumelhart, D. E., Smolensky, P., McClelland, J. L., & Hinton, G. E. (1986). Schemata and sequential thought processes in PDP models. In J. L. McClelland & D. E. Rumelhart (Eds.), Parallel distributed processing: Explorations in the microstructure of cognition. Vol. 2: Psychological and biological models (pp. 7–57). Cambridge, MA: MIT Press.Google Scholar
  80. Schneider, W., Eschman, A., & & Zuccolotto, A. (2002). E-prime user’s guide. Pittsburgh, PA: Psychology Software Tools Inc.Google Scholar
  81. Schultz, W., & Dickinson, A. (2000). Neuronal coding of prediction errors. Annual Review of Neuroscience, 23, 473–500.CrossRefGoogle Scholar
  82. Schützwohl, A. (1998). Surprise and schema strength. Journal of Experimental Psychology: Learning Memory and Cognition, 24(5), 1182–1199.CrossRefGoogle Scholar
  83. Shallice, T., & Burgess, P. W. (1996). The domain of supervisory processes and the temporal organisation of behaviour. Philosophical Transactions of the Royal Society of London B, 351, 1405–1412.CrossRefGoogle Scholar
  84. Stepper, S., & Strack, F. (1993). Proprioceptive determinants of emotional and nonemotional feelings. Journal of Personality and Social Psychology, 64(2), 211–220.CrossRefGoogle Scholar
  85. Sweller, J. (2003). Evolution of human cognitive architecture. The Psychology of Learning and Motivation, 43, 215–265.CrossRefGoogle Scholar
  86. Sweller, J. (2006). Discussion of ‘Emerging topics in cognitive load research: Using learner and information characteristics in the design of powerful learning environments’. Applied Cognitive Psychology, 20, 353–357.CrossRefGoogle Scholar
  87. Teigen, K. H., & Keren, G. (2003). Surprises: Low probabilities or high contrasts? Cognition, 87(2), 55–71.CrossRefGoogle Scholar
  88. van Veen, V., & Carter, C. S. (2002). The timing of action-monitoring processes in the anterior cingulate cortex. Journal of Cognitive Neuroscience, 14(4), 593–602.CrossRefGoogle Scholar
  89. Whelan, R. R. (2007). Neuroimaging of cognitive load in instructional multimedia. Educational Research Review, 2, 1–12.CrossRefGoogle Scholar
  90. Winkielman, P., & Cacioppo, J. T. (2001). Mind at ease puts a smile on the face: Psychophysiological evidence that processing facilitation elicits positive affect. Journal of Personality and Social Psychology, 81(6), 989–1000.CrossRefGoogle Scholar

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© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.School of PsychologyAristotle University of ThessalonikiThessalonikiGreece

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