Decoding reading comprehension from eye movements in narrative and expository texts: A keyword‐ and whole‐text‐level comparison

BACKGROUND: Eye-movement pattern during text reading has been recognized as a functional predictor of reading comprehension proficiency. However, it remains unclear whether and how the coupling between eye-movement pattern and reading comprehension is influenced by text genre and level of analysis. AIMS: This study addresses this question by investigating genre-specific eye-movement patterns during narrative and expository reading, as well as evaluating their predictive power for comprehension proficiency at both the keyword and whole-text levels. SAMPLE: = 21.02, SD = 2.04; 72.3% female) were recruited for this study. METHODS: Eye-movement features were extracted at both the whole-text and keyword levels while participants read narrative and expository texts. Support Vector Machine Recursive Feature Elimination was then utilized to build predictive models for reading comprehension and to select optimal feature subsets. RESULTS: Narrative reading and expository reading were associated with two distinctive eye-movement profiles at both levels. While eye-movement pattern during narrative reading exhibited a 'Dual-Stage Balanced Mode' that might reflect synchronized early lexical access and late-stage integration, eye-movement pattern during expository text reading exhibited a 'Late-Stage Compensatory Mode' that reflected backward integration. Moreover, the keyword level analysis outperformed the whole-text level analysis in terms of comprehension proficiency prediction, suggesting that core semantic nodes were more informative of readers' comprehension proficiency. CONCLUSIONS: Our findings offer a transformative perspective on how eye-movement patterns can be leveraged to assess reading comprehension and provide important heuristics for developing reading assessment and instructional tools.