Transforming Education with Large Language Models: Opportunities, Challenges, and Ethical Considerations
DOI:
https://doi.org/10.54741/ASEJAR/5.1.2026.177Keywords:
adaptive learning, artificial intelligence, large language modelAbstract
Large Language Models (LLMs), such as OpenAI’s GPT-4, significantly advance artificial intelligence, offering transformative potential in education. This paper examines how LLMs can enhance personalized learning, content creation, and real-time tutoring by generating diverse, high-quality educational materials and adapting to individual student needs. While LLMs present considerable opportunities, they also pose challenges related to technology dependency, content accuracy, data privacy, and inherent biases. By reviewing current implementations and case studies, this paper highlights the benefits and ethical considerations of LLMs in education. Recommendations for educators and policymakers include balanced integration, robust content verification, stringent data privacy measures, and bias mitigation strategies. Future research should focus on improving LLM accuracy, emotional intelligence, and ethical frameworks to advance personalized, adaptive learning in an equitable and ethical manner.
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Research Articles in 'Applied Science and Engineering Journal for Advanced Research' are Open Access articles published under the Creative Commons CC BY License Creative Commons Attribution 4.0 International License http://creativecommons.org/licenses/by/4.0/. This license allows you to share – copy and redistribute the material in any medium or format. Adapt – remix, transform, and build upon the material for any purpose, even commercially.
