Abstract

This study examines the impact of cognitive load dimensions—mental effort, information overload, and decision fatigue—on academic performance in AI-enabled learning environments, with cognitive offloading as a mediating mechanism and Generative AI as a moderating factor. A quantitative cross-sectional design was employed, with data collected from 1,228 university students in India using a structured questionnaire. The proposed model was tested using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results indicate that mental effort and information overload significantly increase cognitive offloading, while decision fatigue negatively influences it. Cognitive offloading, in turn, positively affects academic performance, highlighting its role as a key adaptive strategy in managing cognitive demands. Additionally, mental effort directly enhances academic performance, whereas information overload and decision fatigue show no significant direct effects. Generative AI was found to increase cognitive offloading and exhibit a context-dependent moderating role, strengthening the relationship between mental effort and offloading while weakening the effect of information overload. The study contributes to the literature by extending cognitive load theory into AI-driven learning contexts, positioning cognitive offloading as a central mechanism and Generative AI as a critical boundary condition shaping learning outcomes.