Abstract
The work described in this paper presents an automated, eye movement-driven approach (EMA) that allows for the identification of time intervals in which a user is experiencing difficulties in locating interface components required for completion of a task. Due to the substantial amount of visual search exhibited during these time intervals, this type of the user behavior is referred to as excessive visual search (ES). In this work we propose and evaluate several ES detection algorithms as part of the EMA. Empirical results indicate that it is possible to identify ES with a certain degree of accuracy (51-61% on average), warranting future research that would allow for increased accuracy in ES identification and reduction of misclassification errors. Practical application of EMA should allow the reduction of the amount of time required for manual detection of usability problems present in graphical user interfaces.
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References
Andre, W.K., Elizabeth, M.B.: Low-Cost Rapid Usability Engineering: Designing and Customizing Usable Healthcare Information Systems. ElectronicHealthcare 5(2), 98–102 (2006)
Andreasen, M.S., Nielsen, H.V., Schroder, S.O., Stage, J.: What happened to remote usability testing?: an empirical study of three methods. ACM, New York (2007)
Duchowski, A.: Eye Tracking Methodology: Theory and Practice. Springer, Heidelberg (2007)
Goldberg, J., H., Stimson, M.J., Lewenstein, M., Scott, N., Wichansky, A.M.: Eye tracking in web search tasks: Design implications. In: Proceedings of the Eye Tracking Research and Application Symposium, pp. 51–58 (2002)
Goldberg, J.H., Kotval, X.P.: Computer interface evaluation using eye movements: methods and constructs. International Journal of Industrial Ergonomics 24(6), 631–645 (1999)
Ivory, M.Y., Hearst, M.A.: The state of the art in automating usability evaluation of user interfaces. ACM Comput. Surv. 33(4), 470–516 (2001)
Just, M.A., Carpenter, P.A.: Eye Fixation and Cognitive Processes. Cognitive Psychology 8, 441–480 (1976)
Komogortsev, O.V., Gobert, D.V., Jayarathna, S., Koh, D., Gowda, S.: Standardization of Automated Analyses of Oculomotor Fixation and Saccadic Behaviors. IEEE Transactions on Biomedical Engineering 57(11), 2635–2645 (2010)
Marshall, S.P.: The Index of Cognitive Activity: measuring cognitive workload. In: Proceedings of the 2002 IEEE 7th Conference on Human Factors and Power Plants, 2002, pp. 75–79 (2002)
Mueller, C., Tamir, D., Komogortsev, O., Feldman, L.: An Economical Approach to Usability Testing. In: IEEE International Computer Software and Applications Conference (COMPSAC), pp. 124–129 (2009)
Thyvalikakath, T.P., Schleyer, T.K.L., Monaco, V.: Heuristic evaluation of clinical functions in four practice management systems: A pilot study. J. Am. Dent. Assoc. 138(2), 209–218 (2007)
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Komogortsev, O.V., Tamir, D.E., Mueller, C.J., Camou, J., Holland, C. (2011). EMA: Automated Eye-Movement-Driven Approach for Identification of Usability Issues. In: Marcus, A. (eds) Design, User Experience, and Usability. Theory, Methods, Tools and Practice. DUXU 2011. Lecture Notes in Computer Science, vol 6770. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21708-1_52
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DOI: https://doi.org/10.1007/978-3-642-21708-1_52
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