Defining AI Fatigue in Academic Contexts: Dimensions, Indicators, and a Stage-Based Model Using Grounded Theory
arXiv:2605.23123v1 Announce Type: cross Abstract: The integration of AI tools in academic settings has introduced a distinct form of strain that existing frameworks like technostress and digital fatigue have not yet fully addressed. This study develops a conceptual model and identifies the dimensions that define AI fatigue as a form of strain arising from sustained academic use of AI tools. Using grounded theory analysis of open-ended responses from 1,054 university students across three universities in the Philippines, the study examined the cognitive, motivational, emotional, physical, and a
The rapid and pervasive integration of AI tools across academia and industry has made 'AI fatigue' an increasingly relevant and observable phenomenon for which a definitional framework is now emerging.
Understanding and quantifying AI fatigue is crucial for optimizing human-AI collaboration, designing effective AI training and deployment strategies, and mitigating potential negative impacts on productivity and well-being.
This research provides a foundational conceptual model for AI fatigue, enabling more precise measurement, identification, and the development of targeted interventions within academic and professional settings.
- · AI ethicists
- · Human-computer interaction researchers
- · Educational technology providers
- · Mental health support services
- · Organizations implementing AI without human-centric consideration
- · Students and professionals with unmanaged AI tool exposure
- · AI tool developers ignoring user experience
- · Traditional workload management models
The immediate first-order effect is a clearer diagnostic framework for identifying the strains associated with AI tool use.
A plausible second-order consequence is the development of specific tools and policies designed to measure and mitigate AI fatigue in educational and professional environments.
A speculative third-order consequence could be a shift in the design philosophy of AI tools, prioritizing cognitive load and user well-being alongside utility and efficiency.
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Read at arXiv cs.AI