Date of Award
Thesis - Open Access
Master of Science in Human Factors & Systems
Human Factors and Systems
Dahai Liu, PhD.
First Committee Member
Elizabeth L. Blickensderfer, PhD.
Second Committee Member
Peter N. Squire, PhD.
This study investigated the utility and efficacy of using eye tracking technology as a method for selecting control of a camera within a multiple display configuration. A task analysis with a Keystroke-Level-Model (KLM) was conducted to acquire an estimated time for switching between cameras. KLM estimates suggest that response times are faster using an eye tracker than manual control -indicating a time savings. To confirm these estimates, and test other hypotheses a 2 × 2 within-subjects factorial design was used to examine the effects of Control (Using an eye tracker, or manual) under different Task Loads (Low, High). Dependent variables included objective performance (accuracy and response times during an identification task) and subjective workload measured by the NASA-TLX. The eye tracker under the specific experimental conditions was not significantly better or worse, however, further research may support that the use of the eye tracker could surpass the use of manual method in terms of operator performance given the time saving data from our initial task analysis using a Keystroke Level Model (KLM). Overall, this study provided great insight into using an eye tracker in a multiple display monitoring system.
Scholarly Commons Citation
Popola, Allison, "The Effects of Eye Gaze Based Control on Operator Performance in Monitoring Multiple Displays" (2011). PhD Dissertations and Master's Theses. 116.