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Predicting Properties of Cognitive Pupillometry in Human–Computer Interaction: A Preliminary Investigation

Part of the Lecture Notes in Information Systems and Organisation book series (LNISO,volume 25)

Abstract

This paper aims to investigate the predictive property of pupil dilation in an IT-related task. Previous work in the field of cognitive pupillometry has established that pupil size is associated with cognitive load. We conducted a within-subject experiment with 22 children aged between 7 and 9. For the hard questions, visit duration, pupil size and its quadratic effect were significant predictors. We discuss the potential of using this unobtrusive approach for neuro-adaptive and auto-adaptive applications.

Keywords

  • Eye-tracking
  • Pupillometry
  • Cognitive load
  • HCI—learning

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Fig. 1

Notes

  1. 1.

    http://gizmodo.com/msi-s-eye-tracking-laptop-is-the-future-but-not-the-pr-1758485727.

References

  1. Léger, P.M., Sénecal, S., Courtemanche, F., de Guinea, A.O., Titah, R., Fredette, M., Labonte-LeMoyne, É.: Precision is in the eye of the beholder: application of eye fixation-related potentials to information systems research. J. Assoc. Info. Syst. 15(10), 651 (2014)

    Google Scholar 

  2. Loos, P., et al: NeuroIS: neuroscientific approaches in the investigation and development of information systems. Bus. Info. Syst. Eng. 2(6):395–401 (2010)

    Google Scholar 

  3. Dumont, L., et al., Using transcranial direct current stimulation (tDCS) to assess the role of the dorsolateral prefrontal cortex in technology acceptance decisions: a pilot study. Proc. Gmunden Retreat NeuroIS (2014)

    Google Scholar 

  4. Randolph, A.B., Labonté-LeMoyne, É., Léger, P.M., Courtemanche, F., Sénécal, S., Fredette, M.: Proposal for the use of a passive BCI to develop a neurophysiological inference model of IS constructs. In: Information Systems and Neuroscience, pp. 175–180. Springer, Heidelberg (2015)

    Google Scholar 

  5. Mirhoseini, S.M.M., Léger, P.-M., Sénécal S.: The influence of task characteristics on multiple objective and subjective cognitive load measures. In: Information Systems and Neuroscience pp. 149–156. Springer, Heidelberg, (2017)

    Google Scholar 

  6. Sheridan, T.B., Stassen, H.G.: Definitions, models and measures of human workload. In: Moray, N., (eds.) Mental Workload, pp. 219–234. Plenum; New York (1979)

    Google Scholar 

  7. Riedl, R., Léger, P.-M.: Fundamentals of NeuroIS. Springer, Berlin (2016)

    CrossRef  Google Scholar 

  8. Hess, E.H., Polt, J.M.: Pupil size in relation to mental activity during simple problem solving. Science 143(3611), 1190–1192 (1964)

    CrossRef  Google Scholar 

  9. Kahneman, D., Beatty, J.: Pupil diameter and load on memory. Science 154(3756), 1583–1585 (1966)

    CrossRef  Google Scholar 

  10. Beatty, J.: Task-evoked pupillary responses, processing load, and the structure of processing resources. Psychol. Bull. 91(2), 276 (1982)

    CrossRef  Google Scholar 

  11. Klingner, J., Tversky, B., Hanrahan, P.: Effects of visual and verbal presentation on cognitive load in vigilance, memory, and arithmetic tasks. Psychophysiology 48(3), 323–332 (2011)

    CrossRef  Google Scholar 

  12. Piquado, Tepring, Isaacowitz, Derek, Wingfield, Arthur: Pupillometry as a measure of cognitive effort in younger and older adults. Psychophysiology 47(3), 560–569 (2010)

    CrossRef  Google Scholar 

  13. Paas, F.G., Van Merriënboer, J.J.: Instructional control of cognitive load in the training of complex cognitive tasks. Edu. Psychol. Rev. 6(4), 351–371 (1994)

    CrossRef  Google Scholar 

  14. Paas, F., et al.: Cognitive load measurement as a means to advance cognitive load theory. Edu. Psychol. 38(1), 63–71 (2003)

    CrossRef  Google Scholar 

  15. Paas, F., Van Gog, T., Sweller, J.: Cognitive load theory: new conceptualizations, specifications, and integrated research perspectives. Edu. Psychol. Rev. 22(2), 115–121 (2010)

    CrossRef  Google Scholar 

  16. Clark, R.C., Nguyen, F., Sweller, J.: Efficiency in Learning: Evidence-based Guidelines to Manage Cognitive Load. Wiley (2011)

    Google Scholar 

  17. Kruger, J.L., Doherty, S. Measuring cognitive load in the presence of educational video: towards a multimodal methodology. Australas. J. Edu. Technol. 32(6) (2016)

    Google Scholar 

  18. Sweller, J., Van Merrienboer, J.J., Paas, F.G.: Cognitive architecture and instructional design. Edu. Psychol. Rev. 10(3), 251–296 (1998)

    CrossRef  Google Scholar 

  19. Van Mierlo, C.M., Jarodzka, H., Kirschner, F., Kirschner, P.A.: Cognitive load theory in e-learning. In: Encyclopedia of Cyber Behavior, pp. 1178–1211. IGI Global (2012)

    Google Scholar 

  20. Rubio, S., Díaz, E., Martín, J., Puente, J.M.: Evaluation of subjective mental workload: a comparison of SWAT, NASA-TLX, and workload profile methods. Appl. Psychol. 53(1), 61–86 (2004)

    CrossRef  Google Scholar 

  21. Postman, L., Phillips, L.W.: Short-term temporal changes in free recall. Q. J. Exp. Psychol. 17(2), 132–138 (1965)

    CrossRef  Google Scholar 

  22. Glanzer, M., Cunitz, A.R.: Two storage mechanisms in free recall. J. Verbal Learn. Verbal Behav. 5(4), 351–360 (1966)

    CrossRef  Google Scholar 

  23. Beauvois, J.L. (2003). Judgment norms, social utility, and individualism. Sociocognitive Approach Social Norms, 123–147

    Google Scholar 

  24. Spüler, M., Walter, C., Rosenstiel, W., Gerjets, P., Moeller, K., Klein, E.: EEG-based prediction of cognitive workload induced by arithmetic: a step towards online adaptation in numerical learning. ZDM 48(3), 267–278 (2016)

    CrossRef  Google Scholar 

  25. Klingner, J.: Fixation-aligned pupillary response averaging. In Proceedings of the 2010 Symposium on Eye-Tracking Research & Applications (pp. 275–282). ACM (2010, March)

    Google Scholar 

  26. Littell, R.C., et al.: SAS for Mixed Models, 2nd edn., Cary, NC. SAS Institute, 2006

    Google Scholar 

  27. Berka, C., et al.: EEG correlates of task engagement and mental workload in vigilance, learning, and memory tasks. Aviat. Space Environ. Med. 78(5), B231-B244 (2007)

    Google Scholar 

  28. Charland, P., Williot, A., Léger, P.-M., Mercier, J., Skelling, Y., Lapierre, H.-G. Problem solving in physics: a pupillometric perspective. In: Proceedings of the XVIIIth International Congress of the World Association of Research in Education, Eskisehir, Turkey, 1 June 2016

    Google Scholar 

  29. Léger, P.-M., et al.: Neurophysiological correlates of cognitive absorption in an enactive training context. Comput. Human Behav. 34, 273–283 (2014)

    Google Scholar 

  30. Léger, Pierre-Majorique: Using a simulation game approach to teach enterprise resource planning concepts. J. Info. Syst. Edu. 17(4), 441 (2006)

    Google Scholar 

  31. Léger, P.M., et al.: ERPsim, ERPsim Lab (erpsim.hec.ca). HEC Montréal, QC (2007)

    Google Scholar 

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Léger, PM., Charland, P., Sénécal, S., Cyr, S. (2018). Predicting Properties of Cognitive Pupillometry in Human–Computer Interaction: A Preliminary Investigation. In: Davis, F., Riedl, R., vom Brocke, J., Léger, PM., Randolph, A. (eds) Information Systems and Neuroscience. Lecture Notes in Information Systems and Organisation, vol 25. Springer, Cham. https://doi.org/10.1007/978-3-319-67431-5_14

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