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Going Deep and Far: Gaze-Based Models Predict Multiple Depths of Comprehension during and One Week Following Reading

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Title: Going Deep and Far: Gaze-Based Models Predict Multiple Depths of Comprehension during and One Week Following Reading
Language: English
Authors: Caruso, Megan, Peacock, Candace E., Southwell, Rosy, Zhou, Guojing, D'Mello, Sidney K.
Source: International Educational Data Mining Society. 2022.
Availability: International Educational Data Mining Society. e-mail: admin@educationaldatamining.org; Web site: https://educationaldatamining.org/conferences/
Peer Reviewed: Y
Page Count: 13
Publication Date: 2022
Sponsoring Agency: National Science Foundation (NSF)
Contract Number: DRL1920510
Document Type: Speeches/Meeting Papers
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Eye Movements, Reading Comprehension, Inferences, Prediction, Computer Software, Reading Processes, Models, Time Factors (Learning), Rote Learning, Accuracy, Intelligent Tutoring Systems, Teaching Methods, Undergraduate Students
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.]
Abstractor: As Provided
Entry Date: 2022
Accession Number: ED624054
Database: ERIC
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  Data: 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.]
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      – Text: English
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        PageCount: 13
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      – SubjectFull: Eye Movements
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      – SubjectFull: Reading Comprehension
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      – SubjectFull: Inferences
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      – SubjectFull: Computer Software
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      – SubjectFull: Teaching Methods
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      – SubjectFull: Undergraduate Students
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      – TitleFull: Going Deep and Far: Gaze-Based Models Predict Multiple Depths of Comprehension during and One Week Following Reading
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