Performance-Based Eye-Tracking Analysis in a Dynamic Monitoring Task

The goal of this study is to explore how ocular behavior is different in groups that possessed varying levels of performance in dynamic control tasks with complex visual components. Twenty two university students participated in this study by operating a human-in-the-loop HITL simulator. The participants were asked to identify unknown air tracks and take proper actions to defend a battleship. During the experiment, a head-mounted eye-tracking device was used continuously to record participants' visual attention span regarding the normalized coordinates of their gaze points. In the current study, fixation duration was the main eye-tracking metrics. Air track identification accuracy and the NASA Task Load Index NASA-TLX were also used to measure participants' task performance and overall subjective mental workload.

[1]  Jung Hyup Kim,et al.  The Learning Effect of Augmented Reality Training in a Computer-Based Simulation Environment , 2015, HCI.

[2]  Robert J. K. Jacob,et al.  Eye tracking in human-computer interaction and usability research : Ready to deliver the promises , 2002 .

[3]  Thorsten Joachims,et al.  Eye-tracking analysis of user behavior in WWW search , 2004, SIGIR '04.

[4]  Martha E. Crosby,et al.  How do we read algorithms? A case study , 1990, Computer.

[5]  A. L. I︠A︡rbus.  Eye Movements and Vision , 1967 .

[6]  S. Hart,et al.  Development of NASA-TLX (Task Load Index): Results of Empirical and Theoretical Research , 1988 .

[7]  Jung Hyup Kim.  Simulation Training in Self-Regulated Learning: Investigating the Effects of Dual Feedback on Dynamic Decision-Making Tasks , 2014, HCI.

[8]  Markku Tukiainen,et al.  An eye-tracking methodology for characterizing program comprehension processes , 2006, ETRA.

[9]  Linden J. Ball,et al.  Eye tracking in HCI and usability research. , 2006 .

[10]  F. T. Eggemeier.  Properties of Workload Assessment Techniques , 1988 .

[11]  P. Tsang,et al.  Diagnosticity and multidimensional subjective workload ratings. , 1996, Ergonomics.

[12]  J. Hyönä,et al.  Eye movements during repeated reading of a text. , 1990, Acta psychologica.

[13]  K. Rayner,et al.  Eye Movements as Reflections of Comprehension Processes in Reading , 2006 .

[14]  Huei-Tse Hou,et al.  Visual attention for solving multiple-choice science problem: An eye-tracking analysis , 2012, Comput. Educ..

[15]  Andrew L. Kun,et al.  Estimating cognitive load using remote eye tracking in a driving simulator , 2010, ETRA.

[16]  Dick de Waard,et al.  The measurement of drivers' mental workload , 1996 .

[17]  K. Rayner.  Eye movements in reading and information processing: 20 years of research. , 1998, Psychological bulletin.

[18]  M. Hegarty,et al.  Comprehension of Arithmetic Word Problems: Evidence from Students' Eye Fixations. , 1992 .

[19]  Andrew A. Berlin,et al.  Compiling scientific code using partial evaluation , 1990, Computer.

[20]  M. Young,et al.  Longer fixation duration while viewing face images , 2006, Experimental Brain Research.

[21]  Gretchen A. Macht,et al.  Structural models of extraversion, communication, and team performance , 2014 .

[22]  M. Just,et al.  Eye fixations and cognitive processes , 1976, Cognitive Psychology.

[23]  Katharina Scheiter,et al.  Eye tracking as a tool to study and enhance multimedia learning , 2010 .

[24]  Thomas E. Nygren,et al.  The Subjective Workload Assessment Technique: A Scaling Procedure for Measuring Mental Workload , 1988 .

[25]  Joseph H. Goldberg,et al.  Computer interface evaluation using eye movements: methods and constructs , 1999 .

[26]  S. Liversedge,et al.  Saccadic eye movements and cognition , 2000, Trends in Cognitive Sciences.

[27]  Ornella Robutti,et al.  READING MATHEMATICS REPRESENTATIONS: AN EYE-TRACKING STUDY , 2015 .

[28]  Jung Hyup Kim,et al.  Investigating the Effects of Metacognition in Dynamic Control Tasks , 2011, HCI.