Can ChatGPT Ease Digital Fatigue? Short-Cycle Content Curation for University Instructors

Verónica Tomasa Cajas Bravo, Lupe Marilu Huanca Rojas, Andrés Arias Lizares, Juan Cielo Ramírez Cajamarca, Fernando Vasquez Perdomo, Miguel Angel De la Cruz Cruz, Hilario Romero Girón, Ana María Guerrero Millones, Roberto Carlos Dávila-Morán

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Resumen

Digital fatigue is pervasive among university instructors, yet rigorous evidence on whether generative AI improves well-being is scarce. We conducted an eight-week staggered multiple-baseline AB–AB reversal with eight lecturers at a private Peruvian university. In intervention phases, participants replaced full readings with a daily ≤200-word ChatGPT summary plus three discussion questions (“content-curation sprint”). Outcomes were self-reported digital fatigue (FDU-24) and automatically logged screen time; analyses were carried out using trend-corrected Tau-U and paired-phase Cohen’s d. Across two intervention cycles, screen exposure fell by about 122 min per day (~29% of baseline) and digital fatigue scores decreased by ~22%. Effects were large and replicated (aggregate Tau-U = −0.79; d = −1.5 to −2.2). Treatment fidelity averaged 96%, and post-study technology acceptance was high. These findings provide preliminary experimental evidence that a brief, low-friction ChatGPT workflow can simultaneously reduce screen time and alleviate digital fatigue in higher-education faculty, suggesting a dual productivity-and-well-being dividend and positioning generative AI as a Job Demands–Resources “resource” rather than a stressor. Multi-site randomized trials with active controls, longer follow-up, and cost-effectiveness analyses are warranted. Practical implications for faculty development are immediate.

Idioma originalInglés estadounidense
-1223
PublicaciónEducation Sciences
Volumen15
N.º9
DOI
EstadoIndizado - set. 2025

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© 2025 by the authors.

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