Scanpath Regularity as an Index of Reading Comprehension

• Published in: Scientific studies of reading Vol. 28; no. 1; pp. 79 - 100
• Main Authors: Mézière, Diane C., Yu, Lili, McArthur, Genevieve, Reichle, Erik D., von der Malsburg, Titus
• Format: Journal Article
• Language: English
• Published: Philadelphia Routledge 02.01.2024; Routledge, Taylor & Francis Group
• Subjects: Achievement tests; Comprehension; Eye movements; Monolingualism; Oral reading; Reading comprehension; Reading processes; Reading tests
• ISSN: 1088-8438; 1532-799X; 1532-799X
• DOI: 10.1080/10888438.2023.2232063

Recent research on the potential of using eye-tracking to measure reading comprehension ability suggests that the relationship between standard eye-tracking measures and reading comprehension is influenced by differences in task demands between comprehension assessments. We compared standard eye-tracking measures and scanpath regularity as predictors of reading comprehension scores. We used a dataset in which 79 participants (mean age: 22 years, 82% females, 76% monolingual English speakers) were administered three widely-used reading comprehension assessments with varying task demands while their eye movements were monitored: the York Assessment of Reading for Comprehension; (YARC), the Gray Oral Reading Test; (GORT-5), and the sentence comprehension subtest of the Wide Range Achievement Test; (WRAT-4). Results showed that scanpath regularity measures, similarly to standard eye-tracking measures, were influenced by differences in task demands between the three tests. Nevertheless, both types of eye-tracking measures made unique contributions as predictors of comprehension and the best set of predictors included both standard eye-tracking measures and at least one scanpath measure across tests. The results provide evidence that scanpaths capture differences in eye-movement patterns missed by standard eye-tracking measures. Overall, the results highlight the effect of task demands on eye-movement behavior and suggest that reading goals and task demands need to be considered when interpreting eye-tracking data.