The Eye Movement Pattern and Brain Dynamics indicate successful learning during education video viewing
Abstract
Online education has become a prominent feature of modern learning. However, what determines learning success in online education remains unclear. To explore this, the present study applies Hidden Markov Model to eye-tracking and EEG data in an open dataset containing educational video-viewing task. The model revealed two eye movement patterns: a global pattern where fixations were distributed across the video, and a local pattern where fixations focused on task-relevant features. The model also revealed 6 distinct brain states involving attention and memory. Experiments 1 and 2 explore the impact of task engagement on eye movement. We found that compared to intentional learning condition, more participants use a global pattern and suffer from worse memory performance in incidental learning condition. Experiment 3 explores the impact of video style. We found that only in the presenter-and-animation style, the local eye movement patterns and learning brain states are associated with learning success. Overall, this study explores factors that indicate learning success and offers insights for improving learning efficiency in online education.