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A Catastrophe Model for Motivation and Emotions: Highlighting the Synergistic Role of Performance-Approach and Performance-Avoidance Goal Orientations

  • Georgios Sideridis
  • Dimitrios Stamovlasis
Chapter

Abstract

Mastery and performance type of motivation are crucial to students’ academic behavior, since they might affect their emotion regulation and achievement. The purpose of this study is to investigate the effect of the above motivational variables on students’ arousal levels under achievement situations. Participants were 70 college students who participated in the study for extra credit. Student’s arousal levels were measured prior to and during stressful in-class presentations with a heart rate-monitoring device. Statistical analyses using multilevel modeling and the cusp catastrophe model indicated that a nonlinear effect took place when moving from the baseline condition to the presentation. Performance-avoidance goal orientations were associated with significantly elevated arousal during the baseline and a significant increase with the onset of the presentation. A cusp catastrophe model with performance-approach and performance-avoidance goal orientations as controls proved superior to its linear counterparts, while mastery type of goals have no contribution to the phenomenon under investigation. The cusp effect offers a better explanation of the emotion deregulation observed under those stressful situations and provides the link to NDS and self-organization theory.

Keywords

Catastrophe theory Achievement goal theory Motivation Emotions Performance-approach Performance-avoidance Goal Orientations Cusp catastrophe Bifurcation Bimodality Hysteresis Attractor Self-organization 

References

  1. Arnol’d, V. I. (1992). Catastrophe theory (3rd ed.). Berlin: Springer.CrossRefGoogle Scholar
  2. Atkinson, J. (1964). An introduction to motivation. Princeton, NJ: Van Nostrant Reinholdt Company.Google Scholar
  3. Barron, K. E., & Harackiewicz, J. M. (2001). Achievement goals and optimal motivation: Testing multiple goal models. Journal of Educational Psychology, 80, 706–722.Google Scholar
  4. Brown, C. (1995). Chaos and catastrophe theories. London: Sage.CrossRefGoogle Scholar
  5. Bryk, A., & Raudenbush, S. W. (1992). Hierarchical linear models for social and behavioral research: Applications and data analysis methods. Newbury Park, CA: Sage.Google Scholar
  6. Carver, C. S. (2006). Approach, avoidance, and the self-regulation of affect and action. Motivation and Emotions, 30, 105–110.CrossRefGoogle Scholar
  7. Covington, M. V. (1992). Goal theory, motivation and school achievement: An integrative review. Annual Review of Psychology, 51, 171–200.CrossRefGoogle Scholar
  8. Covington, M. V. (1984). The motive for self-worth. In R. Ames & C. Ames (Eds.), Research on motivation in education (Vol. 1). New York: Academic.Google Scholar
  9. Cury, F., Da Fonséca, D., Rufo, M., Peres, C., & Sarrazin, P. (2003). The trichotomous model and investment in learning to prepare for a sport test: A mediational analysis. British Journal of Educational Psychology, 73, 529–543.CrossRefGoogle Scholar
  10. Darnon, C., Butera, F., Mugny, G., Quiamzade, A., & Hulleman, C. S. (2009). “Too complex for me!” Why do performance-approach and performance-avoidance goals predict exam performance? European Journal of Psychology of Education, 4, 423–434.CrossRefGoogle Scholar
  11. Durant, R. H., Baranowski, T., Davis, H., Rhodes, T., Thompson, W. O., Greaves, K. A., et al. (1993). Reliability and variability of indicators of heart-rate monitoring in children. Medicine and Science in Sports and Exercise, 25, 389–395.Google Scholar
  12. Dweck, C. S. (1986). Motivational processes affecting learning. American Psychologist, 41, 1040–1048.CrossRefGoogle Scholar
  13. Dweck, C. S., & Leggett, E. L. (1988). A social-cognitive approach to motivation and personality. Psychological Review, 95, 256–273.CrossRefGoogle Scholar
  14. Dykman, B. M. (1998). Integrating cognitive and motivational factors in depression: Initial tests of a goal-orientation approach. Journal of Personality and Social Psychology, 74, 139–158.CrossRefGoogle Scholar
  15. Elliot, A. J. (1999). Approach and avoidance motivation and achievement goals. Educational Psychologist, 34, 169–189.CrossRefGoogle Scholar
  16. Elliot, A. J. (2005). A conceptual history of the achievement goal construct. In A. J. Elliot & C. S. Dweck (Eds.), Handbook of competence and motivation (pp. 52–72). New York, NY: Guilford.Google Scholar
  17. Elliot, A. J., & Harackiewicz, J. M. (1996). Approach and avoidance achievement goals and intrinsic motivation: A mediational analysis. Journal of Personality and Social Psychology, 70, 461–475.CrossRefGoogle Scholar
  18. Elliot, A. J., & Church, M. (1997). A hierarchical model of approach and avoidance achievement motivation. Journal of Personality and Social Psychology, 72, 218–232.CrossRefGoogle Scholar
  19. Elliot, A. J., & McGregor, H. A. (1999). Test anxiety and the hierarchical model of approach and avoidance achievement motivation. Journal of personality and social psychology, 76(4), 628–644.CrossRefGoogle Scholar
  20. Elliot, A. J., & McGregor, H. A. (2001). A 2 × 2 achievement goal framework. Journal of Personality and Social Psychology, 80, 501–519.CrossRefGoogle Scholar
  21. Elliot, A. J., & Thrash, T. (2002). Approach-avoidance motivation in personality: Approach and avoidance temperament and goals. Journal of Personality and Social Psychology, 82, 804–818.CrossRefGoogle Scholar
  22. Elliot, A. J., & Murayama, K. (2008). On the measurement of achievement goals: critique, illustration, and application. Journal of Educational Psychology, 100, 613–628.CrossRefGoogle Scholar
  23. Elliot, A. J., Murayama, K., & Pekrun, R. (2011). A 3 x 2 achievement goal model. Journal of Educational Psychology, 103, 632–648.CrossRefGoogle Scholar
  24. Godsen, R., Carroll, T., & Stone, S. (1991). How well does the polar vantage xl heart rate monitor estimate actual heart rate? Medical Sciences in Sports and Exercise, 23, 14.Google Scholar
  25. Gonida, E. N., Voulala, K., & Kiosseoglou, G. (2009). Students' achievement goal orientations and their behavioral and emotional engagement: Co-examining the role of perceived school goal structures and parent goals during adolescence. Learning and Individual Differences, 19(1), 53–60.CrossRefGoogle Scholar
  26. Gonida, Ε., Kiosseoglou, G., & Leondari, A. (2006). Implicit theories of intelligence, perceived academic competence and school achievement: Developmental differences and educational implications. The American Journal of Psychology, 119(2), 223–238.CrossRefGoogle Scholar
  27. Grant, H., & Dweck, C. S. (2003). Clarifying achievement goals and their impact. Journal of Personality and Social Psychology, 85, 541–553.CrossRefGoogle Scholar
  28. Guastello, S. J. (1987). A butterfly catastrophe model of motivation in organization: Academic performance. Journal of Applied Psychology, 72, 165–182.CrossRefGoogle Scholar
  29. Guastello, S. J. (2002). Managing emergent phenomena: Non-linear dynamics in work organizations. Mahwah, NJ: Lawrence.Google Scholar
  30. Guastello, S. J. (2011). Discontinuities and catastrophes with polynomial regression. In S. Guastello & R. Gregson (Eds.), Nonlinear dynamics systems analysis for the behavioral sciences using real data (pp. 252–180). New York: CRC Press.Google Scholar
  31. Guastello, S. J., Johnson, E. A., & Rieke, M. L. (1999). Nonlinear dynamics of motivational flow. Nonlinear Dynamics, Psychology, and Life Sciences, 3, 259–274.CrossRefGoogle Scholar
  32. Guastello, S. J., Boeh, H., Schumaker, C., & Schimmels, M. (2012). Cusp catastrophe models for cognitive workload and fatigue. Theoretical Issues in Ergonomic Sciences, 13, 586–602.CrossRefGoogle Scholar
  33. Guastello, S. J., Boeh, H., Gorin, H., Huschen, S., Peters, N., Fabisch, M., et al. (2013). Cusp catastrophe models for cognitive workload and fatigue: A comparison of seven task types. Nonlinear Dynamics, Psychology and Life Science, 17, 23–47.Google Scholar
  34. Harackiewicz, J. M., Barron, K. E., Pintrich, P. R., Elliot, A. J., & Thrash, T. M. (2002). Revision of achievement goal theory: Necessary and illuminating. Journal of Educational Psychology, 94, 638–645.CrossRefGoogle Scholar
  35. Hardy, L., & Parfitt, G. (1991). A catastrophe model of anxiety and performance. British Journal of Psychology, 82, 163–178.CrossRefGoogle Scholar
  36. Hulleman, C. S., Schrager, S. M., Bodmann, S. M., & Harackiewicz, J. M. (2010). A meta-analytic review of achievement goal measures: Different labels for the same constructs or different constructs with similar labels? Psychological Bulletin, 136, 422–449.CrossRefGoogle Scholar
  37. Kelso, J. A., & Engstrøm, D. A. (2006). The complementary nature. Cambridge: MIT Press.Google Scholar
  38. Koopmans, M. (2015). A dynamical view of high school attendance: An assessment of the short-term and long-term dependencies in five urban schools. Nonlinear Dynamics, Psychology, and Life Sciences, 19, 65–80.Google Scholar
  39. Midgley, C., Kaplan, A., & Middleton, M. (2001). Performance-approach goals: Good for what, for whom, under what circumstances, and at what cost? Journal of Educational Psychology, 93, 77–86.CrossRefGoogle Scholar
  40. Navarro, J., & Arrieta, C. (2010). Chaos in human behavior: The case of work motivation. The Spanish Journal of Psychology, 13, 224–256.Google Scholar
  41. Navarro, J., Arrieta, C., & Balén, C. (2007). An approach to the study of dynamics of work motivation using the diary method. Nonlinear Dynamics, Psychology, and Life Sciences, 11, 473–498.Google Scholar
  42. Navarro, J., Curioso, F., Gomes, D., Arrieta, C., & Cortés, M. (2013). Fluctuations in work motivation: Tasks do not matter! Nonlinear Dynamics, Psychology, and Life Sciences, 17, 3–22.Google Scholar
  43. Nezlek, J. B. (2001). Multilevel random coefficient analyses of event and interval contingent data in social and personality psychology research. Personality and Social Psychology Bulletin, 27, 771–785.CrossRefGoogle Scholar
  44. Nicolis, G., & Nicolis, C. (2007). Foundations of complex systems. Singapore: World Scientific.CrossRefGoogle Scholar
  45. Pekrun, R., Elliot, A. J., & Maier, M. A. (2006). Achievement goals and discrete achievement emotions: A theoretical model and prospective test. Journal of Educational Psychology, 98, 583–597.CrossRefGoogle Scholar
  46. Pekrun, R., Elliot, A. J., & Maier, M. A. (2009). Achievement goals and achievement emotions: Testing a model of their joint relations with academic performance. Journal of Educational Psychology, 101, 115–135.CrossRefGoogle Scholar
  47. Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models. Newbury Park, CA: Sage.Google Scholar
  48. Sideridis, G. D. (2003). On the origins of helpless behavior in students with learning disabilities: Avoidance motivation? International Journal of Educational Research, 39, 497–517.CrossRefGoogle Scholar
  49. Sideridis, G. D., & Stamovlasis, D. (2014). The role of goal orientations in explaining academic cheating in students with learning disabilities: An application of the cusp catastrophe. Ethics and Behavior, 24, 444–466.CrossRefGoogle Scholar
  50. Sideridis, G. D., Antoniou, F., & Simos, P. (2013). The physiological effects of goal orientations on the reading performance of students with dyslexia: A Pilot Study. Procedia, Social and Behavioral Sciences, 96, 1545–1551.Google Scholar
  51. Sideridis, G. D., Antoniou, F., Stamovlasis, D., & Morgan, P. (2013). The relationship between victimization at school and achievement: The cusp catastrophe model for reading performance. Behavioral Disorders, 38(4), 228–242.Google Scholar
  52. Sideridis, G. D., Stamovlasis, D., & Antoniou, F. (2015). Reading achievement, mastery, and performance goal structures among students with learning disabilities: A nonlinear perspective. Journal of learning disabilities (accepted for publication, DOI: 10.1177/0022219415576524). Google Scholar
  53. Skar, P. (2004). Chaos and self-organization: Emergent patterns at critical life transitions. Journal of Analytical Psychology, 49, 243–262.CrossRefGoogle Scholar
  54. Stamovlasis, D. (2006). The nonlinear dynamical hypothesis in science education problem solving: A catastrophe theory approach. Nonlinear Dynamics, Psychology and Life Science, 10, 37–70.Google Scholar
  55. Stamovlasis, D. (2010). Methodological and epistemological issues on linear regression applied to psychometric variables in problem solving: Rethinking variance. Chemistry Education Research and Practice, 11, 59–68.CrossRefGoogle Scholar
  56. Stamovlasis, D. (2011). Nonlinear dynamics and neo-piagetian theories in problem solving: Perspectives on a new epistemology and theory development. Nonlinear Dynamics, Psychology and Life Science, 15, 145–173.Google Scholar
  57. Stamovlasis, D., & Sideridis, G. (2014). Ought approach - ought avoidance: Nonlinear effects under achievement situations. Nonlinear Dynamics, Psychology and Life Science, 18(1), 67–90.Google Scholar
  58. Stamovlasis, D., & Tsaparlis, G. (2012). Applying catastrophe theory to an information-processing model of problem solving in science education. Science Education, 96(3), 392–410.CrossRefGoogle Scholar
  59. Tesser, A. (1980). When individual dispositions and social pressure conflict: A catastrophe. Human Relations, 33, 393–407.CrossRefGoogle Scholar
  60. Thom, R. (1975). Structural stability and morphogenesis. Reading, MA: W.A. Benjamin.Google Scholar
  61. Treiber, F. A., Musante, L., Hartdagan, S., Davis, H., Levy, M., & Strong, W. B. (1989). Validation of a heart rate monitor with children in laboratory and field settings. Medical Science in Sports and Exercice, 21, 338–342.Google Scholar
  62. van der Maas, H. L. J., & Hopkins, B. (1998). Developmental transitions: So what's new? British Journal of Developmental Psychology, 16, 1–13.CrossRefGoogle Scholar
  63. van der Maas, H. L. J., Molenaar, P. C. M., & van der Pligt, J. (2003). Sudden transitions in attitudes. Sociological Methods and Research, 23, 125–152.CrossRefGoogle Scholar
  64. Wajciechowski, J. A., Gayle, R. C., Andrews, R. L., & Dintiman, G. B. (1991). The accuracy of radio telemetry heart rate monitoring during exercise. Clinical Kinesiology, 45, 9–12.Google Scholar
  65. White, R. (1959). Motivation reconsidered: The concept of competence. Psychological Review, 66, 297–333.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Harvard Medical School, Clinical Research Center, Boston Children’s HospitalBostonUSA
  2. 2.Department of Philosophy and EducationAristotle University of ThessalonikiThessalonikiGreecee

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