The Capabilities of Large Language Models for Reducing Learning Fatigue
TL;DR
The study concludes that the responsible, well-regulated integration of LLMs can enhance learning effectiveness while helping to mitigate risks associated with digital fatigue, relevant for educators and institutions seeking to improve student outcomes through the thoughtful adoption of AI-based tools.
Abstract
This article investigates the transformative role of large language models (LLMs), specifically ChatGPT, in contemporary education and their impact on learning fatigue. It examines both the potential benefits of LLMs use as personalized learning, automated content creation, interactive tasks, and real-time feedback from one point of view and the emerging challenges, including increased dependence on digital devices and the risk of digital fatigue - mental, physical, and emotional exhaustion caused by prolonged screen exposure from the other. The results show widespread familiarity with artificial intelligence tools and moderate relationships between AI use and perceived reductions in learning effort. Frequent use of ChatGPT appears to implement improvements in homework, highlighting the need to further develop students’ digital literacy and prompting skills. The study concludes that the responsible, well-regulated integration of LLMs can enhance learning effectiveness while helping to mitigate risks associated with digital fatigue. This research is relevant for educators and institutions seeking to improve student outcomes through the thoughtful adoption of AI-based tools.