This large-scale dataset will provide opportunities for researchers to develop more accurate and generalizable detectors of mind wandering. Research shows that when a student misses critical information due to mind wandering, it can inhibit their ability to make further connections as the learning session unfolds. Using an unobtrusive, equitable, and low-cost device, a dataset including interaction data, webcam-based eye-gaze features, and self-reports of mind wandering will be collected.
Caitlin Mills
Assistant Professor of Educational Psychology, University of Minnesota
Caitlin Mills has a PhD in Cognitive Psychology, and her research focuses on constructs related to mind wandering and engagement during learning and in everyday life contexts. She aims to characterize when mind wandering occurs, how it influences learning, and ways to automatically detect it in real-time. Other research interests include the influence of mind wandering in ubiquitous tasks such as driving and how it relates to functional aspects of our lives such as affect, mental health, boredom, and creativity.