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A Case Study of Executive Functions in Real Process Modeling Sessions

  • Ilona WilmontEmail author
  • Erik Barendsen
  • Stijn Hoppenbrouwers
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 349)

Abstract

Cognitive aspects like executive control functions, reasoning and abstraction have a crucial influence on modeling performance. Yet how are executive functions used in real modeling sessions and what individual differences exist? In this case study we analyse observations of three modeling sessions according to a coding scheme for behavioural observation of executive functions, reasoning and abstraction. We complement the findings with a qualitative, thick description of the sessions. We find that the modelers have unique styles in how they use executive control, that there appears to be a hierarchy in when specific executive functions are used, and that the use of executive control alone does not guarantee modeling progress. Greater awareness of the effects of executive control use in real modeling settings can be very helpful in training modelers to optimize their skills.

Keywords

Executive functions Process modeling Individual differences 

References

  1. 1.
    Barreteau, O.: The joint use of role-playing games and models regarding negotiation processes: characterization of associations. J. Artif. Soc. Soc. Simul. 6(2) (2003)Google Scholar
  2. 2.
    Basadur, M.: The Power of Innovation: How to Make Innovation a Way of Life and Put Creative Solutions to Work. Financial Times Management, Upper Saddle River (1995)Google Scholar
  3. 3.
    Brown, A.L.: Metacognition, executive control, self-regulation and other more mysterious mechanisms. In: Weinert, F., Kluwe, R.H. (eds.) Metacognition, Motivation, and Understanding, pp. 65–115. Lawrence Erlbaum Associates, Hillsdale (1987)Google Scholar
  4. 4.
    Christoff, K., Keramatian, K., Gordon, A., Smith, R., Mädler, B.: Prefrontal organization of cognitive control according to levels of abstraction. Brain Res. 1286, 94–105 (2009)CrossRefGoogle Scholar
  5. 5.
    Feltovich, P., Spiro, R., Coulson, R., Feltovich, J.: Collaboration within and among minds: mastering complexity, individually and in groups. In: Koschmann, T. (ed.) CSCL: Theory and Practice of An Emerging Paradigm. Computers, Cognition, and Work, pp. 25–44. Lawrence Erlbaum Associates, Inc., Mahwah (1996)Google Scholar
  6. 6.
    Gazzaniga, M.S., Ivry, R.B., Mangun, G.R.: Cognitive Neuroscience: The Biology of the Mind, 2nd edn. W. W. Norton & Company, New York (2002)Google Scholar
  7. 7.
    Hazzan, O.: Reflections on teaching abstraction and other soft ideas. ACM SIGCSE Bull. 40(2), 40–43 (2008).  https://doi.org/10.1145/1383602.1383631CrossRefGoogle Scholar
  8. 8.
    Lee, D., Trauth, E., Farwell, D.: Critical skills and knowledge requirements of IS professionals: a joint academic/industry investigation. MIS Q. 19(3: Special Issue on IS Curricula and Pedagogy), 313–340 (1995)CrossRefGoogle Scholar
  9. 9.
    Lehrer, R., Schauble, L.: Developing model-based reasoning in mathematics and science. J. Appl. Dev. Psychol. 21(1), 39–48 (2000)CrossRefGoogle Scholar
  10. 10.
    Lincoln, Y.S., Guba, E.G.: Naturalistic Inquiry, SAGE Focus Editions, vol. 75, 1st edn. SAGE Publications, Thousand Oaks (1985)Google Scholar
  11. 11.
    Mendling, J., Strembeck, M., Recker, J.: Factors of process model comprehension—Findings from a series of experiments. Decis. Support Syst. 53(1), 195–206 (2012).  https://doi.org/10.1016/j.dss.2011.12.013CrossRefGoogle Scholar
  12. 12.
    Persson, A.: Enterprise modelling in practice: situational factors and their influence on adopting a participative approach. Ph.D. thesis, Department of Computer and Systems Sciences, Stockholm University (2001)Google Scholar
  13. 13.
    Ross, D., Goodenough, J., Irvine, C.A.: Software engineering: process, principles, and goals. Computer 8(5), 17–27 (1975)CrossRefGoogle Scholar
  14. 14.
    Salles, P., Bredeweg, B.: A case study of collaborative modelling: building qualitative models in ecology. In: Model Based Systems and Qualitative Reasoning for Intelligent Tutoring Systems, pp. 75–84 (2002)CrossRefGoogle Scholar
  15. 15.
    Schwarz, C., et al.: Developing a learning progression for scientific modeling: making scientific modeling accessible and meaningful for learners. J. Res. Sci. Teach. 46(6), 632–654 (2009)CrossRefGoogle Scholar
  16. 16.
    Sins, P.H.M., Savelsbergh, E.R., van Joolingen, W.R.: The Difficult Process of Scientific Modelling: an analysis of novices’ reasoning during computer-based modelling. Int. J. Sci. Educ. 27(14), 1695–1721 (2005)CrossRefGoogle Scholar
  17. 17.
    Sutcliffe, A.G., Maiden, N.A.M.: Analysing the novice analyst: cognitive models in software engineering. Int. J. Man Mach. Stud. 36(5), 719–740 (1992).  https://doi.org/10.1016/0020-7373(92)90038-MCrossRefGoogle Scholar
  18. 18.
    Theodorakis, M., Analyti, A., Constantopoulos, P., Spyratos, N.: Contextualization as an abstraction mechanism for conceptual modelling. In: Akoka, J., Bouzeghoub, M., Comyn-Wattiau, I., Métais, E. (eds.) ER 1999. LNCS, vol. 1728, pp. 475–490. Springer, Heidelberg (1999).  https://doi.org/10.1007/3-540-47866-3_32CrossRefGoogle Scholar
  19. 19.
    Van Der Valk, T., Van Driel, J., De Vos, W.: Common characteristics of models in present-day scientific practice. Res. Sci. Educ. 37(4), 469–488 (2007).  https://doi.org/10.1007/s11165-006-9036-3CrossRefGoogle Scholar
  20. 20.
    Wilmont, I., Hengeveld, S., Barendsen, E., Hoppenbrouwers, S.: Cognitive mechanisms of conceptual modelling: how do people do it? In: Ng, W., Storey, V.C., Trujillo, J.C. (eds.) ER 2013. LNCS, vol. 8217, pp. 74–87. Springer, Heidelberg (2013).  https://doi.org/10.1007/978-3-642-41924-9_7CrossRefGoogle Scholar
  21. 21.
    Wilmont, I., Hoppenbrouwers, S., Barendsen, E.: An observation method for behavioral analysis of collaborative modeling skills. In: Metzger, A., Persson, A. (eds.) CAiSE 2017. LNBIP, vol. 286, pp. 59–71. Springer, Cham (2017).  https://doi.org/10.1007/978-3-319-60048-2_6CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Ilona Wilmont
    • 1
    • 2
    Email author
  • Erik Barendsen
    • 1
  • Stijn Hoppenbrouwers
    • 1
    • 2
  1. 1.Institute for Computing and Information SciencesRadboud University NijmegenNijmegenThe Netherlands
  2. 2.HAN University of Applied SciencesArnhemThe Netherlands

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