Exploring Eye-Tracking Data for Detection of Mind-Wandering on Web Tasks

  • Jacek GwizdkaEmail author
Conference paper
Part of the Lecture Notes in Information Systems and Organisation book series (LNISO, volume 29)


Mind-wandering (MW) is a phenomenon that affects most of us; it affects our interactions with information systems. Yet the literature on its effects on human-computer interaction is only scant. This research aims to contribute to establishing eye-tracking measures that could be used to detect periods of MW while a user is engaged in interaction with online information. We conducted a lab study (N = 30) and present an exploratory analysis of eye-tracking data with a focus on finding differences between periods of MW and not-MW. We found 12 eye tracking measures that were significantly different between periods of MW and not-MW. We also show promising classification results of the same variables. Our results indicate plausibility of using eye-tracking data to infer periods of MW.


Mind-wandering Mindless reading Eye-tracking Pupillometry 



This project was supported, in part, by the Temple Teaching Fellowship 2016–2017. We thank Ms. Xueshu Chen, who was a Graduate Research Assistant, for her contributions to this project.


  1. 1.
    Schooler, J.W., Mrazek, M.D., Franklin, M.S., Baird, B., Mooneyham, B.W., Zedelius, C., Broadway, J.M.: The middle way: finding the balance between mindfulness and mind-wandering. In: Ross, B.H. (ed.) Psychology of Learning and Motivation, pp. 1–33. Academic Press, Cambridge (2014)Google Scholar
  2. 2.
    Reichle, E.D., Reineberg, A.E., Schooler, J.W.: Eye movements during mindless reading. Psychol. Sci. 21, 1300–1310 (2010)CrossRefGoogle Scholar
  3. 3.
    Smallwood, J.: Mind-wandering while reading: attentional decoupling, mindless reading and the cascade model of inattention. Lang. Linguist. Compass. 5, 63–77 (2011)CrossRefGoogle Scholar
  4. 4.
    Choi, H., Nam, C.S., Feng, J.: A wandering mind cannot resolve conflicts in displayed information. In: Proceedings of the Human Factors and Ergonomics Society Annual Meeting, Vol. 59, pp. 1397–1401 (2015)CrossRefGoogle Scholar
  5. 5.
    Smallwood, J.: Distinguishing how from why the mind wanders: a process–occurrence framework for self-generated mental activity. Psychol. Bull. 139, 519–535 (2013)CrossRefGoogle Scholar
  6. 6.
    Franklin, M.S., Broadway, J.M., Mrazek, M.D., Smallwood, J., Schooler, J.W.: Window to the wandering mind: pupillometry of spontaneous thought while reading. Q. J. Exp. Psychol. 66, 2289–2294 (2013)CrossRefGoogle Scholar
  7. 7.
    Smallwood, J., Brown, K.S., Tipper, C., Giesbrecht, B., Franklin, M.S., Mrazek, M.D., Carlson, J.M., Schooler, J.W.: Pupillometric evidence for the decoupling of attention from perceptual input during offline thought. PLoS ONE 6, e18298 (2011)CrossRefGoogle Scholar
  8. 8.
    Walcher, S., Körner, C., Benedek, M.: Looking for ideas: eye behavior during goal-directed internally focused cognition. Conscious. Cogn. 53, 165–175 (2017)CrossRefGoogle Scholar
  9. 9.
    Sullivan, Y.: Costs and benefits of mind wandering in a technological setting: findings and implications.
  10. 10.
    Sullivan, Y., Davis, F., Koh, C.: Exploring mind wandering in a technological setting. In: ICIS 2015 Proceedings (2015)Google Scholar
  11. 11.
    Bixler, R., D’Mello, S.: Toward fully automated person-independent detection of mind wandering. In: Dimitrova, V., Kuflik, T., Chin, D., Ricci, F., Dolog, P., Houben, G.-J. (eds.) User Modeling, Adaptation, and Personalization, pp. 37–48. Springer International Publishing, Switzerland (2014)Google Scholar
  12. 12.
    Zhao, Y., Lofi, C., Hauff, C.: Scalable mind-wandering detection for MOOCs: a webcam-based approach. In: Data Driven Approaches in Digital Education, pp. 330–344. Springer, Cham (2017)CrossRefGoogle Scholar
  13. 13.
    Bixler, R., D’Mello, S.: Automatic gaze-based detection of mind wandering with metacognitive awareness. In: Ricci, F., Bontcheva, K., Conlan, O., Lawless, S. (eds.) User Modeling, Adaptation and Personalization, pp. 31–43. Springer International Publishing, Switzerland (2015)Google Scholar
  14. 14.
    Borlund, P.: The concept of relevance in IR. J. Am. Soc. Inf. Sci. Technol. 54, 913–925 (2003)CrossRefGoogle Scholar
  15. 15.
    Freund, L., Kopak, R., O’Brien, H.: The effects of textual environment on reading comprehension: implications for searching as learning. J. Inf. Sci. 42, 79–93 (2016)CrossRefGoogle Scholar
  16. 16.
    Smallwood, J., Schooler, J.W.: The restless mind. Psychol. Bull. 132, 946–958 (2006)CrossRefGoogle Scholar
  17. 17.
    Smallwood, J., Schooler, J.W., Turk, D.J., Cunningham, S.J., Burns, P., Macrae, C.N.: Self-reflection and the temporal focus of the wandering mind. Conscious. Cogn. 20, 1120–1126 (2011)CrossRefGoogle Scholar
  18. 18.
    Feng, S., D’Mello, S., Graesser, A.C.: Mind wandering while reading easy and difficult texts. Psychon. Bull. Rev. 20, 586–592 (2013)CrossRefGoogle Scholar
  19. 19.
    Witten, I.H., Frank, E., Hall, M.A., Pal, C.J.: Data Mining, Fourth Edition: Practical Machine Learning Tools and Techniques. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA (2016)Google Scholar
  20. 20.
    Chawla, N.V., Bowyer, K.W., Hall, L.O., Kegelmeyer, W.P.: SMOTE: synthetic minority over-sampling technique. ArXiv11061813 Cs (2011)Google Scholar
  21. 21.
    Breiman, L.: Random forests. Mach. Learn. 45, 5–32 (2001)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.School of InformationUniversity of Texas at AustinAustinUSA

Personalised recommendations