Engagement Measurement During Online Learning

Students’ engagement is a key element in successful learning; however, it is common for students to subconsciously lose focus during reading. Because losing focus happens subconsciously and involuntarily, it is difficult to accurately determine when the person stopped paying attention and for how long. Using computer vision and machine learning algorithms we can extract changes in eye and physiological parameters from a webcam recording. Previous studies have shown that changes in parameters, such as blinking rate, gaze, pupil dilation, heart rate, and skin conductance, may be linked to a person’s engagement level. Currently, researchers rely on participants self-reporting their engagement levels or require expensive equipment, such as professional eye trackers, making these studies not scalable to everyday home use. I worked with Open Stax on developing a system that would automatically measure a person’s engagement level during online learning.