Revolutionizing higher education: unleashing the potential of large language models for strategic transformation
Issue Date
2024-05-13Subjects
large language modelstask analysis
performance evaluation
higher education
Subject Categories::G760 Machine Learning
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This paper investigates the transformative potential of Large Language Models (LLMs) within higher education, highlighting their capacity to reshape the academic landscape. By examining the complex impact of LLMs across critical areas of Higher Education Institutions (HEIs), including the role of HEIs as gatekeepers of knowledge, providers of credentials, research centres, incubators of innovation, drivers of social change and employers. In addition to academic integrity, the future of higher education, intellectual property, and public perception. The findings of this paper indicate that LLMs can empower transformation in HEIs by revolutionising various aspects of academia. The aim is to unveil the profound implications of integrating these cutting-edge technologies. The comprehensive study in this paper reveals the significant impacts and challenges associated with using LLMs in academic settings, which is achieved through a detailed analysis of current literature. The core findings suggest that LLMs hold the promise to trigger significant advancements in higher education. This paper also discusses the innovative potential of LLMs, and it outlines a path for their effective use in HEIs, emphasising the importance of a thoughtful approach to maximise their educational benefits. HEIs must address these challenges thoughtfully, ensuring that the integration of LLMs aligns with their fundamental objectives of promoting education, critical thinking, and personal growth.Citation
Diab IM, Feng X, Dyo V (2024) 'Revolutionizing higher education: unleashing the potential of large language models for strategic transformation', IEEE Access, 12, pp.67738-67757.Publisher
IEEEJournal
IEEE AccessAdditional Links
https://ieeexplore.ieee.org/document/10529287Type
ArticleLanguage
enISSN
2169-3536EISSN
2169-3536ae974a485f413a2113503eed53cd6c53
10.1109/ACCESS.2024.3400164
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