C. Stephanidis (Ed.): Posters, Part I, HCII 2013, CCIS 373, pp. 169–174, 2013. © Springer-Verlag Berlin Heidelberg 2013 Insights from Eye Movement into Dynamic Decision-Making Research and Usability Testing Benoit R. Vallières, Cindy Chamberland, François Vachon, and Sébastien Tremblay Co-DOT Laboratory, School of Psychology, Université Laval, Québec, Canada benoit.roberge-vallieres.1@ulaval.ca, {cindy.chamberland,francois.vachon, sebastien.tremblay}@psy.ulaval.ca Abstract. This study shows how the use of various measures of eye movement can serve to portray dynamic decision-making (DDM) in a coherent fashion. We extracted eye movement metrics relative to 1) scanpath, 2) eye fixations, and 3) pupillary response, to characterize DDM during the process of risk assessment. Results from Experiment 1 revealed that incorrect classifications were associated with 1) less efficient information search, 2) difficulties in making sense of critical information, and 3) a low level of cognitive load. In Experiment 2, we used eye tracking to assess the impact on DDM of introducing a decision support system. The addition of a temporal-overview display seems to affect processing time in DDM as indexed by shorter scanpaths and fixations during classifications. These findings illustrate how event-based eye movement measures can reveal characteristics and limitations of the ongoing cognitive processing involved in DDM and also contribute to usability testing. Keywords: Eye movements, dynamic decision-making, usability testing, decision support system. 1 Introduction Dynamic decision making (DDM) involves a series of interdependent real-time decisions and actions made in an environment that continuously changes, and evolves according or not to operators’ actions [1]. Air traffic control and military operations are examples of complex dynamic situations in which DDM is difficult to the point that it often taxes operators’ cognitive capabilities [2]. In such situations, decision makers have to process and categorize information coming from multiple sources within a limited time frame [3]. The demands to support DDM are growing rapidly, but providing such support requires a good understanding of the underlying cognitive processes involved in DDM. One avenue that we wish to explore is to reveal these cognitive processes through the use of eye tracking in a manner that is closely linked to the dynamics of the situation [4-5]. Indeed, eye movements can provide non-obtrusive, online indices