Quality Checking Eye Movement Data for the Covert Detection of Mindless Reading
Conference Year
January 2022
Abstract
While reading and/or doing repetitive tasks attention tends to shift from task-related to task- unrelated thoughts, we call this mind wandering. Past research has shown that mind wandering is anti-correlated with comprehension. We have created an experiment that requires a participant to read a passage while an eye tracker traces their eye movements. We will use the tracked eye movements to calculate a correlation between features of eye movements and comprehension accuracy. To ensure high quality data, we will quality check the data collected, by organizing and plotting it, to conclude if the data merits inclusion in the final analysis.
Primary Faculty Mentor Name
David Jangraw
Graduate Student Mentors
Haorui Sun, George Spearing
Student Collaborators
Blythe Hattenbatch
Status
Undergraduate
Student College
College of Engineering and Mathematical Sciences
Program/Major
Biomedical Engineering
Primary Research Category
Engineering & Physical Sciences
Secondary Research Category
Social Sciences
Tertiary Research Category
Health Sciences
Quality Checking Eye Movement Data for the Covert Detection of Mindless Reading
While reading and/or doing repetitive tasks attention tends to shift from task-related to task- unrelated thoughts, we call this mind wandering. Past research has shown that mind wandering is anti-correlated with comprehension. We have created an experiment that requires a participant to read a passage while an eye tracker traces their eye movements. We will use the tracked eye movements to calculate a correlation between features of eye movements and comprehension accuracy. To ensure high quality data, we will quality check the data collected, by organizing and plotting it, to conclude if the data merits inclusion in the final analysis.