article · Discover Education
Large language models such as GPT-4 offer notable opportunities for digital education by mimicking human-like text and altering approaches to teaching and learning. A review of their development and application demonstrates their capacity to automate instructional tasks and support personalised learning experiences for students. Alongside these benefits, the deployment of such models introduces substantial integration challenges and ethical concerns. Successfully embedding artificial intelligence into higher education frameworks relies on addressing data privacy requirements, upholding ethical standards, and maintaining an effective balance between technology and human educators. Developing structured strategies for incorporation can assist institutions in improving overall learning outcomes while safeguarding educational integrity.
Artificial intelligence is rapidly changing how higher education institutions operate. Understanding how to adopt large language models safely ensures that universities can harness automated instruction and tailored student support without compromising data privacy, ethical standards, or the vital personal guidance provided by human teachers.
The findings indicate applications for higher education institutions, educational technology developers, and administrators seeking to automate teaching tasks and deliver personalised tutoring. Because the review focuses on strategic guidance and institutional frameworks rather than a specific commercial product or deployment trial, the work represents early-stage conceptual guidance for organisations designing AI integration policies and digital classroom software.
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Artificial intelligence-driven Chatbots, especially large language models (LLMs) like GPT-4, represent significant progress in digital education. These models excel in mimicking human-like text and transforming learning and teaching methods. This study examines the development, application, and impact of LLMs in education. It highlights their role in automating instructional tasks and promoting personalized learning experiences. Despite integration concerns and ethical debates, LLMs showcase the potential of AI to improve educational practices. Our research concludes that LLMs offer transformative opportunities for education. However, their incorporation requires careful ethical considerations, data privacy measures, and a balance between human educators and AI technologies. The findings suggest strategies for integrating LLMs into educational frameworks to enhance learning outcomes while preserving educational integrity.
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DOI: 10.1007/s44217-025-00424-7
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