Abstract
This study investigates eye movement patterns as indicators of text complexity in Arabic, focusing on the comparative analysis of Classical Arabic (CA) and Modern Standard Arabic (MSA) text. Using the AraEyebility corpus, which contains eye-tracking data from readers of both CA and MSA text, we examined differences in fixation patterns, regression rates, and overall reading behavior between these two forms of Arabic. Our analyses revealed significant differences in eye movement metrics between CA and MSA text, with CA text consistently eliciting more fixations, longer fixation durations, and more frequent revisits. Multivariate analysis confirmed that language type has a significant combined effect on eye movement patterns. Additionally, we identified different relationships between text features and eye movements for CA versus MSA text, with sentence-level features emerging as significant predictors across both language types. Notably, we observed an interaction between language type and readability level, with readers showing less sensitivity to readability variations in CA text compared to MSA text. These findings contribute to our understanding of how historical language evolution affects reading behavior and have practical implications for Arabic language education, publishing, and assessment. The study demonstrates the value of eye movement analysis for understanding text complexity in Arabic and highlights the importance of considering language-specific features when studying reading processes.