Citation

Cheong, Jeffrey and Pang, Wai Leong and Goh, Hui Hwang and Soon, Kian Lun and Tee, Wei Hown and Md Rezali, Fazliyatul Azwa and Chan, Kah Yoong (2026) The Opportunities and Impacts of Large Language Models in Higher Education. The Future of Learning: AI, Ethics, and Sustainability in Higher Education. pp. 242-275.

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Abstract

Large Language Models (LLMs) are artificial intelligence (AI) solutions developed to analyze and generate various human languages. There are many LLM solutions available in the market, and they have successfully attracted billions of users globally. LLMs are widely used in various applications and areas such as content creation, presentation script preparation, and data analysis. The education sector widely applies LLMs because of their strong content-creation capabilities, which stem from big data analysis. This chapter will provide a critical review of the opportunities and impacts of using LLMs in higher education. LLMs are widely used in higher education to carry out research work, data analysis, report writing, problem-solving, image processing, and programming code analyses, with their capabilities expanding throughout the day. Well-trained LLMs can create various kinds of interesting topics and continuously improve content according to the user's requirements. However, the misuse and high dependence on LLMs in teaching and learning can significantly impact academic integrity. The addicted users lost their creativity, motivation for study, and problem-solving skills, as well as experienced amplified laziness. The poorly developed LLMs generate bias and wrong information that will have a significantly negative impact on the users in teaching and learning activities. The LLMs are a promising solution that significantly strengthens the students’ learning experience and supports the lecturers in various learning activities. A clear policy or rules and regulations are needed to control the usage of the LLMs with a clear understanding of the risks and limitations.

Item Type:	Article
Uncontrolled Keywords:	Artificial intelligence; Big data; Education computing; Engineering research; Information analysis; Students; Teaching
Subjects:	L Education > LB Theory and practice of education > LB2300-2430 Higher education
Divisions:	Faculty of Artificial Intelligence & Engineering (FAIE)
Depositing User:	Ms Suzilawati Abu Samah
Date Deposited:	01 Oct 2026 02:58
Last Modified:	01 Oct 2026 02:58
URII:	http://shdl.mmu.edu.my/id/eprint/16759

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