Using Synchronized Eye Movements to Predict Attention in Online Video Learning
Bibliographic Data
| ID | 22043335 |
|---|---|
| Authors | Caizhen Su (Beijing Normal University), Xingyu Liu (0000-0003-1986-9358, Beijing Normal University), Xinru Gan (Beijing Normal University), Hang Zeng (0000-0002-8836-1032, Beijing Normal University, corresponding author) |
| Year | 2024 |
| Volume | 14 |
| Issue | 5 |
| Pages | 548 |
| Publication date | 2024-05-19 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Education Sciences (JOURNAL) |
| Journal identifiers | ISSN: 2227-7102 • E-ISSN: 2227-7102 |
| Publisher | MDPI AG (PUBLISHER • IT) |
| DOI | 10.3390/educsci14050548 |
| OpenAlex | W4398134729 |
| Language | EN |
| Citations received | 2 |
| References cited | 26 |
Concerns persist about attentional engagement in online learning. The inter-subject correlation of eye movements (ISC) has shown promise as an accessible and effective method for attention assessment in online learning. This study extends previous studies investigating ISC of eye movements in online learning by addressing two research questions. Firstly, can ISC predict students’ attentional states at a finer level beyond a simple dichotomy of attention states (e.g., attending and distracted states)? Secondly, whether learners’ learning styles affect ISC’s prediction rate of attention assessment in video learning? Previous studies have shown that learners of different learning styles have different eye movement patterns when viewing static materials. However, limited research has explored the impact of learning styles on viewing patterns in video learning. An eye tracking experiment with participants watching lecture videos demonstrated a connection between ISC and self-reported attention states at a finer level. We also demonstrated that learning styles did not significantly affect ISC’s prediction rate of attention assessment in video learning, suggesting that ISC of eye movements can be effectively used without considering learners’ learning styles. These findings contribute to the ongoing discourse on optimizing attention assessment in the evolving landscape of online education
Cognitive psychology · Eye movement · Eye tracking · Multimedia · Online learning · Online video · Computer Science · Innovative Teaching and Learning Methods · Online Learning and Analytics · Psychology · Visual and Cognitive Learning Processes · Artificial Intelligence
| Unique citing works | 2 |
|---|---|
| Citations per year | 1 |
| Citation span | 2024 - 2026 (3) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 2 |