Exploring how textual complexity affects cognitive load during reading: an eye-tracking study

Reading constitutes a fundamental component of learning, and understanding cognitive load during reading is important both for explaining how learners engage with text and for enhancing the effectiveness of learning. The primary aim of this study is to examine how manipulated text complexity conditions influence eye-movement behavior, in order to better understand how readers' gaze patterns reflect increases or decreases in cognitive load. Specifically, the study investigates whether key metrics (fixations, regressions, pupil area) and the behavioral indicator of reading duration differ systematically between easy and hard texts. The study examines how textual complexity affects cognitive load during reading using eye-tracking. The study included 33 university students (18 female, 15 male; M age = 35.6, SD = 12.4), all native Czech speakers. Participants completed a counterbalanced repeated-measures reading task in Czech in which text complexity was experimentally manipulated across lexical, syntactic, and semantic dimensions. Eye-movement data were collected during reading to capture behavioral patterns typically linked to variations in cognitive load, and participants subsequently provided self-reports of perceived mental effort using the NASA-TLX. Results showed that texts with greater complexity led to more fixations, more regressions, and longer reading durations, indicating higher cognitive load. NASA-TLX ratings likewise indicated greater perceived effort for the higher-complexity condition. However, pupillary metrics showed no meaningful differences between conditions. Overall, the findings suggest that gaze-based eye-tracking metrics are sensitive indicators of cognitive demand, while pupillary responses depend on specific experimental conditions.