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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

Research output: Contribution to journalOriginal Articlepeer-review

1 Scopus citations

Abstract

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.

Original languageAmerican English
Article number1223
JournalEducation Sciences
Volume15
Issue number9
DOIs
StateIndexed - Sep 2025

Bibliographical note

Publisher Copyright:
© 2025 by the authors.

Keywords

  • ChatGPT
  • Job Demands–Resources (JD-R) theory
  • digital fatigue
  • faculty development
  • generative artificial intelligence
  • higher education
  • prompt engineering
  • screen time
  • single-case experimental design
  • technostress

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