Cognitive Load and Eye-Tracking
Cognitive load has a significant impact on how we process information and make decisions. When the amount of information exceeds our ability to process it, we may miss important details and/or base our judgments on fewer pieces of information. In this project, we work on developing a predictive model that can predict a user’s experience of cognitive load from his or her eye movement data.
Because fixations serve as a major unit of analysis for cognitive processing, information about density of fixations can be of great value in eye tracking research. In this project, we develop an algorithm that allow researchers to examine nuances in fixations that are typically not detected or accounted for in existing fixation detection algorithms.
Effective communication is a major factor in designing successful websites. In this project, we focus on text simplification and its impact on comprehension, engagement, and performance. We develop a set of plain language guidelines that can be used to create easy to understand textual content.
Improving Mobile Web Experience (Dyn Inc.)
By using optimized responsive web design, this applied research project aimed at enhancing mobile usability of checkout process at Dyn Inc. Two eye-tracking user experience studies were conducted to identify and evaluate mobile-specific drivers of usability and user experience.
Differences in Gen Y’s and Baby Boomer’s viewing patterns (Fidelity Investments)
Two eye tracking studies were conducted to provide insight for design improvements of Fidelity Investments Homepage. Eye tracking proved to be an invaluable tool for detecting behavior. While survey analysis was not able to detect any significant differences between web preferences of Gen Y and Baby Boomers, eye tracking showed that the two groups had significantly different preferences for viewing web pages.
Improving user experience of infinIT (EMC Corporation)
This objective of this project was to redesign the user experience of a globally used internal portal at EMC. Four studies using both qualitative and quantitative analysis (surveys, eye tracking, observations, and interviews) were conducted to assess the portal’s current state and identify improvement opportunities for redesign. A predictive model was developed to help resource allocation for UX projects.