Generative AI in Academic Reading: Impacts on Cognitive Load and Student Reading Behaviors
DOI:
https://doi.org/10.24310/ijtei.121.2026.22461Keywords:
GenAI, Academic reading, Cognitive load, Reading behaviors, Reading amount, Reading strategy useAbstract
As generative artificial intelligence (GenAI) tools become increasingly integrated into academic routines, their influence on core learning behaviors, particularly academic reading, warrants critical investigation. Despite growing interest in GenAI’s role in education, limited research has explored its impact on reading behavior. This study adopts a quantitative correlational design to examine how reading with GenAI tools influences university students' reading amount and strategy use, while assessing the mediating role of three types of cognitive load: intrinsic, extraneous, and germane. Data were collected from 274 undergraduate students using convenience sampling and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) in SmartPLS 4.0. Results revealed that reading with GenAI tools significantly increased reading strategy use, extraneous cognitive load, and germane cognitive load, while significantly reducing intrinsic cognitive load. Furthermore, intrinsic cognitive load negatively affected reading strategy use, extraneous load negatively affected reading amount, and germane load positively influenced both reading strategy use and reading amount. These findings provide novel insights into how GenAI tools reshape reading behavior in higher education, highlighting the importance of managing cognitive load in digitally supported learning environments.
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