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Revolutionizing higher education: unleashing the potential of large language models for strategic transformation

  • University of Bedfordshire
Research Output: Contribution to journal Article Peer-review

Open access

Abstract

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.

Publication Information

Output type

Research Output: Contribution to journal Article Peer-review

Original language

English

Article number

10529287

Pages from-to (Number of pages)

Pages 67738-67757 (20 pages)

Journal (Volume, Issue Number)

IEEE Access (Volume 12)

Publication milestones

  • Accepted/In press - 04/05/2024
  • Published - 13/05/2024

Publication status

Published - 13/05/2024

External Publication IDs

  • handle.net: 10547/626309
  • Scopus: 85193271500

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