ENG1503
Assignment 2
Unique No:737611
Due 17 September 2025
, ENG1503
Assignment 02 (Semester 2, 2025)
Unique number: 737611
Essay: Does the Use of Large Language Models Constitute Plagiarism?
Introduction
The rise of large language models (LLMs) such as ChatGPT has transformed how
students and academics engage with information. These systems, trained on extensive
datasets, generate responses through computational algorithms rather than
independent thought (Naithani, 2025). Their growing use in higher education has
sparked an ongoing debate: does reliance on LLMs in assignments amount to
plagiarism? Plagiarism is commonly defined as presenting someone else’s work or
ideas without appropriate acknowledgment. This essay argues that failing to disclose
the use of LLMs constitutes plagiarism because such outputs lack identifiable
authorship, obscure proper attribution, and violate academic integrity. In addition, the
essay suggests strategies universities can implement to protect the credibility of their
qualifications in the age of artificial intelligence.
LLM outputs and lack of authorship
One reason unacknowledged use of LLM-generated text constitutes plagiarism is the
absence of a clear human author. As Naithani (2025) observes, LLMs create content by
systematically processing large volumes of existing data, not by engaging in critical or
creative thinking. When students submit this output as their own, they misrepresent a
machine’s automated synthesis as their original work. Although the generated text may
be unique, it still does not reflect the independent effort, reasoning, and authorship
expected in academic writing. This practice fits within the definition of plagiarism, which
involves presenting work that is not genuinely one’s own.
Attribution and referencing challenges
Assignment 2
Unique No:737611
Due 17 September 2025
, ENG1503
Assignment 02 (Semester 2, 2025)
Unique number: 737611
Essay: Does the Use of Large Language Models Constitute Plagiarism?
Introduction
The rise of large language models (LLMs) such as ChatGPT has transformed how
students and academics engage with information. These systems, trained on extensive
datasets, generate responses through computational algorithms rather than
independent thought (Naithani, 2025). Their growing use in higher education has
sparked an ongoing debate: does reliance on LLMs in assignments amount to
plagiarism? Plagiarism is commonly defined as presenting someone else’s work or
ideas without appropriate acknowledgment. This essay argues that failing to disclose
the use of LLMs constitutes plagiarism because such outputs lack identifiable
authorship, obscure proper attribution, and violate academic integrity. In addition, the
essay suggests strategies universities can implement to protect the credibility of their
qualifications in the age of artificial intelligence.
LLM outputs and lack of authorship
One reason unacknowledged use of LLM-generated text constitutes plagiarism is the
absence of a clear human author. As Naithani (2025) observes, LLMs create content by
systematically processing large volumes of existing data, not by engaging in critical or
creative thinking. When students submit this output as their own, they misrepresent a
machine’s automated synthesis as their original work. Although the generated text may
be unique, it still does not reflect the independent effort, reasoning, and authorship
expected in academic writing. This practice fits within the definition of plagiarism, which
involves presenting work that is not genuinely one’s own.
Attribution and referencing challenges
