Eye-tracking allows us to capture where users are looking on a computer screen. DOI, a novel eye-tracking experimentation paradigm, relies on mapping users’ gazes to interactive visual content automatically and dynamically. This allows experimenters to track users’ deep interests in particular content, how these interests change over time, and how they support goals and tasks. This can facilitate unprecedented insight into how people rely on rich visual content and data to understand, learn, analyze, and decide.
The project aims to lay the groundwork for DOI experimentation by exploring the types of insights that can be achieved with it, and by designing novel analytical paradigms and tools necessary to interpret the large and complex data that DOI experiments typically produce. These topics will be pursued by applying DOI experimentation to concrete problems, such as exploring how people use visualization to explore and analyze data, or how students learn from visual content.
Design experiments and collect concrete DOI eye-tracking data, possibly in collaboration with researchers in other domains.
Analyze collected DOI data using conventional data science methods (i.e., existing visualization tools and data analysis packages)
- Design and develop (iteratively) novel visual analytics paradigms and tools to explore DOI data in general
User study design
Data handling, analysis, and visualization
Iterative software design and development, rapid prototyping