Abstract
Mind wandering, defined as shifts in attention from task-related processing to task-unrelated thoughts, is a ubiquitous phenomenon that has a negative influence on performance and productivity in many contexts, including learning. We propose that next-generation learning technologies should have some mechanism to detect and respond to mind wandering in real-time. Towards this end, we developed a technology that automatically detects mind wandering from eye-gaze during learning from instructional texts. When mind wandering is detected, the technology intervenes by posing just-in-time questions and encouraging re-reading as needed. After multiple rounds of iterative refinement, we summatively compared the technology to a yoked-control in an experimentwith104 participants. The key dependent variable was performance on a post-reading comprehension assessment. Our results suggest that the technology was successful in correcting comprehension deficits attributed to mind wandering (d = .47 sigma) under specific conditions, thereby highlighting the potential to improve learning by “attending to attention.”
| Original language | English (US) |
|---|---|
| Number of pages | 8 |
| State | Published - 2017 |
| Externally published | Yes |
| Event | 2017 International Conference on Educational Data Mining - Wuhan, China Duration: Jun 25 2017 → Jun 28 2017 Conference number: 10 |
Conference
| Conference | 2017 International Conference on Educational Data Mining |
|---|---|
| Abbreviated title | EDM 2017 |
| Country/Territory | China |
| City | Wuhan |
| Period | 6/25/17 → 6/28/17 |
Keywords
- mind wandering
- gaze tracking
- student modeling
- attention-aware