Defining AI Fatigue in Academic Contexts: Dimensions, Indicators, and a Stage-Based Model Using Grounded Theory
A new study published on arXiv introduces the concept of "AI fatigue" as a distinct form of strain experienced by university students using AI tools for academic work. Through grounded theory analysis of over a thousand student responses, researchers identified five dimensions of AI fatigue: cognitive overload, motivational disengagement, moral unease, physical strain, and attentional drift. The findings propose a stage-based model illustrating how these pressures accumulate with repeated AI interaction, offering a new framework for understanding and addressing this phenomenon in educational settings. AI
IMPACT Establishes a new conceptual framework for understanding the psychological and physical toll of AI tools on students, potentially informing educational policies and tool design.