When eyes wander around: Mind-wandering as revealed by eye movement analysis with hidden markov models
Journal
Sensors
Journal Volume
21
Journal Issue
22
Date Issued
2021
Author(s)
Abstract
Mind-wandering has been shown to largely influence our learning efficiency, especially in the digital and distracting era nowadays. Detecting mind-wandering thus becomes imperative in educational scenarios. Here, we used a wearable eye-tracker to record eye movements during the sustained attention to response task. Eye movement analysis with hidden Markov models (EMHMM), which takes both spatial and temporal eye-movement information into account, was used to examine if participants’ eye movement patterns can differentiate between the states of focused attention and mind-wandering. Two representative eye movement patterns were discovered through clustering using EMHMM: centralized and distributed patterns. Results showed that participants with the centralized pattern had better performance on detecting targets and rated themselves as more focused than those with the distributed pattern. This study indicates that distinct eye movement patterns are associated with different attentional states (focused attention vs. mind-wandering) and demonstrates a novel approach in using EMHMM to study attention. Moreover, this study provides a potential approach to capture the mind-wandering state in the classroom without interrupting the ongoing learning behavior. ? 2021 by the authors. Licensee MDPI, Basel, Switzerland.
Subjects
Eye movement analysis with hidden Markov models (EMHMM)
Fixation
Learning
Mind-wandering
Sustained attention
Eye movements
Eye tracking
Learning systems
Motion analysis
Centralised
Distributed patterns
Eye movement analyse with hidden markov model
Eye movement analysis
Eye movement patterns
Hidden-Markov models
Hidden Markov models
eye
eye movement
human
learning
Eye
Eye Movements
Humans
Type
journal article