Advertisement

Eye Tracking Meets the Process of Process Modeling: A Visual Analytic Approach

  • Andrea Burattin
  • Michael Kaiser
  • Manuel Neurauter
  • Barbara Weber
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 281)

Abstract

Research on the process of process modeling (PPM) studies how process models are created. It typically uses the logs of the interactions with the modeling tool to assess the modeler’s behavior. In this paper we suggest to introduce an additional stream of data (i.e., eye tracking) to improve the analysis of the PPM. We show that, by exploiting this additional source of information, we can refine the detection of comprehension phases (introducing activities such as “semantic validation” or “problem understanding”) as well as provide more exploratory visualizations (e.g., combined modeling phase diagram, heat maps, fixations distributions) both static and dynamic (i.e., movies with the evolution of the model and eye tracking data on top).

Keywords

Process of process modeling Eye tracking Modeling phase diagram 

Notes

Acknowledgements

This work is partially funded by the Austrian Science Fund project “The Modeling Mind: Behavior Patterns in Process Modeling” (P26609).

References

  1. 1.
    Becker, J., Rosemann, M., Uthmann, C.: Guidelines of business process modeling. In: Aalst, W., Desel, J., Oberweis, A. (eds.) Business Process Management. LNCS, vol. 1806, pp. 30–49. Springer, Heidelberg (2000). doi: 10.1007/3-540-45594-9_3 CrossRefGoogle Scholar
  2. 2.
    Mendling, J.: Metrics for Process Models: Empirical Foundations of Verification, Error Prediction, and Guidelines for Correctness. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  3. 3.
    Mendling, J., Reijers, H.A., Recker, J.: Activity labeling in process modeling: Empirical insights and recommendations. Inf. Syst. 35(4), 467–482 (2010)CrossRefGoogle Scholar
  4. 4.
    Reijers, H.A., Mendling, J.: A study into the factors that influence the understandability of business process models. IEEE Trans. Syst. Man Cybern. Part A Syst. Hum. 41(3), 449–462 (2011)CrossRefGoogle Scholar
  5. 5.
    Pinggera, J.: The Process of Process Modeling. Ph.D. thesis, Innsbruck University (2014)Google Scholar
  6. 6.
    Pinggera, J., Soffer, P., Fahland, D., Weidlich, M., Zugal, S., Weber, B., Reijers, H., Mendling, J.: Styles in business process modeling: An exploration and a model. Softw. Syst. Model. 14(3), 1055–1080 (2015)CrossRefGoogle Scholar
  7. 7.
    Claes, J., Vanderfeesten, I., Pinggera, J., Reijers, H., Weber, B., Poels, G.: A visual analysis of the process of process modeling. Inf. Syst. e-Bus. Manage. 13(1), 147–190 (2015)CrossRefGoogle Scholar
  8. 8.
    Hoppenbrouwers, S.J.B.A., Proper, H.A.E., Weide, T.P.: A fundamental view on the process of conceptual modeling. In: Delcambre, L., Kop, C., Mayr, H.C., Mylopoulos, J., Pastor, O. (eds.) ER 2005. LNCS, vol. 3716, pp. 128–143. Springer, Heidelberg (2005). doi: 10.1007/11568322_9 CrossRefGoogle Scholar
  9. 9.
    Soffer, P., Kaner, M., Wand, Y.: Towards understanding the process of process modeling: Theoretical and empirical considerations. In: Daniel, F., Barkaoui, K., Dustdar, S. (eds.) BPM 2011. LNBIP, vol. 99, pp. 357–369. Springer, Heidelberg (2012). doi: 10.1007/978-3-642-28108-2_35 CrossRefGoogle Scholar
  10. 10.
    Martini, M., Pinggera, J., Neurauter, M., Sachse, P., Furtner, M.R., Weber, B.: The impact of working memory and the “process of process modelling” on model quality: Investigating experienced versus inexperienced modellers. Sci Rep. 6 (2016)Google Scholar
  11. 11.
    Pinggera, J., Zugal, S., Weidlich, M., Fahland, D., Weber, B., Mendling, J., Reijers, H.A.: Tracing the process of process modeling with modeling phase diagrams. In: Daniel, F., Barkaoui, K., Dustdar, S. (eds.) BPM 2011. LNBIP, vol. 99, pp. 370–382. Springer, Heidelberg (2012). doi: 10.1007/978-3-642-28108-2_36 CrossRefGoogle Scholar
  12. 12.
    Claes, J., Vanderfeesten, I., Pinggera, J., Reijers, H.A., Weber, B., Poels, G.: Visualizing the process of process modeling with PPMCharts. In: Rosa, M., Soffer, P. (eds.) BPM 2012. LNBIP, vol. 132, pp. 744–755. Springer, Heidelberg (2013). doi: 10.1007/978-3-642-36285-9_75 CrossRefGoogle Scholar
  13. 13.
    Blascheck, T., Kurzhals, K., Raschke, M., Burch, M., Weiskopf, D., Ertl, T.: State-of-the-Art of visualization for eye tracking data. In: EuroVis - STARs. The Eurographics Association (2014)Google Scholar
  14. 14.
    Weber, B., Pinggera, J., Neurauter, M., Zugal, S., Martini, M., Furtner, M., Sachse, P., Schnitzer, D.: Fixation patterns during process model creation: Initial steps toward neuro-adaptive process modeling environments. In: HICSS. IEEE (2016)Google Scholar
  15. 15.
    Weber, B., Neurauter, M., Pinggera, J., Zugal, S., Furtner, M., Martini, M., Sachse, P.: Measuring cognitive load during process model creation. In: Davis, F.D., Riedl, R., vom Brocke, J., Léger, P.-M., Randolph, A.B. (eds.) Information Systems and Neuroscience. LNISO, vol. 10, pp. 129–136. Springer, Cham (2015). doi: 10.1007/978-3-319-18702-0_17 CrossRefGoogle Scholar
  16. 16.
    Schrepfer, M., Wolf, J., Mendling, J., Reijers, H.A.: The impact of secondary notation on process model understanding. In: Persson, A., Stirna, J. (eds.) PoEM 2009. LNBIP, vol. 39, pp. 161–175. Springer, Heidelberg (2009). doi: 10.1007/978-3-642-05352-8_13 CrossRefGoogle Scholar
  17. 17.
    Pinggera, J., Zugal, S., Weber, B.: Investigating the process of process modeling with cheetah experimental platform. In: ER-POIS, 13–18(2010)Google Scholar
  18. 18.
    Riedl, R., Léger, P.M.: Fundamentals of NeuroIS. Springer, Heidelberg (2016)CrossRefGoogle Scholar
  19. 19.
    Holmqvist, K., Nyström, M., Andersson, R., Dewhurst, R., Jarodzka, H., Van de Weijer, J.: Eye Tracking: A Comprehensive Guide to Methods and Measures. Oxford University Press, Oxford (2011)Google Scholar
  20. 20.
    Ehmke, C., Wilson, S.: Identifying web usability problems from eye-tracking data. In: British HCI, British Computer Society, pp. 119–128 (2007)Google Scholar
  21. 21.
    Grinstein, G., Trutschl, M., Cvek, U.: High-dimensional visualizations. In: Visual Data Mining Workshop, KDD. Citeseer (2001)Google Scholar
  22. 22.
    Neurauter, M., Pinggera, J., Martini, M., Burattin, A., Furtner, M., Sachse, P., Weber, B.: The influence of cognitive abilities and cognitive load on business process models and their creation. In: Davis, F.D., Riedl, R., vom Brocke, J., Léger, P.-M., Randolph, A.B. (eds.) Information Systems and Neuroscience. LNISO, vol. 10, pp. 107–115. Springer, Cham (2015). doi: 10.1007/978-3-319-18702-0_14 CrossRefGoogle Scholar
  23. 23.
    Hornof, A.J., Halverson, T.: Cleaning up systematic error in eye-tracking data by using required fixation locations. Behav. Res. Methods Instrum. Comput. 34(4), 592–604 (2002)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Andrea Burattin
    • 1
  • Michael Kaiser
    • 1
  • Manuel Neurauter
    • 1
  • Barbara Weber
    • 1
    • 2
  1. 1.University of InnsbruckInnsbruckAustria
  2. 2.Technical University of DenmarkKongens LyngbyDenmark

Personalised recommendations