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Going Deep and Far: Gaze-Based Models Predict Multiple Depths of Comprehension during and One Week Following Reading
- Source :
-
International Educational Data Mining Society . 2022. - Publication Year :
- 2022
-
Abstract
- What can eye movements reveal about reading, a complex skill ubiquitous in everyday life? Research suggests that gaze can reflect short-term comprehension for facts, but it is unknown whether it can measure long-term, deep comprehension. We tracked gaze while 147 participants read long, connected, informative texts and completed assessments of rote (factual) and inference comprehension (connecting ideas) while reading a text, after reading a text, after reading five texts, and after a seven-day delay. Gaze-based student-independent computational models predicted both immediate and long-term rote and inference comprehension with moderate accuracies. Surprisingly, the models were most accurate for comprehension assessed after reading all texts and predicted comprehension even after a week-long delay. This shows that eye movements can provide a lens into the cognitive processes underlying reading comprehension, including inference formation, and the consolidation of information into long-term memory, which has implications for intelligent student interfaces that can automatically detect and repair comprehension in real-time. [For the full proceedings, see ED623995.]
Details
- Language :
- English
- Database :
- ERIC
- Journal :
- International Educational Data Mining Society
- Publication Type :
- Conference
- Accession number :
- ED624054
- Document Type :
- Speeches/Meeting Papers<br />Reports - Research