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ENG1503 Assignment 2 Semester 2 | Due 17 September 2025

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ENG1503 Assignment 2 Semester 2 | Due 17 September 2025

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[TYPE THE COMPANY NAME]




ENG1503 Assignment
2 Semester 2 Memo |
Due 17 September
2025
NO PLAGIARISM

[Pick the date]




[Type the abstract of the document here. The abstract is typically a short summary of the contents of
the document. Type the abstract of the document here. The abstract is typically a short summary of
the contents of the document.]

, Exam (elaborations)
ENG1503 Assignment 2 Semester 2 Memo |
Due 17 September 2025
Course

 Academic Language and Literacy in English (ENG1503)
 Institution
 University Of South Africa (Unisa)

ENG1503 Assignment 2 Semester 2 Memo | Due 17 September 2025. THREE
ESSAYS PROVIDED.

Using the extract above as a point of reference, do you think that the output
generated by LLMs constitute plagiarism? In other words, does the use of
LLMs constitute plagiarism?

. What is plagiarism?
Plagiarism is generally defined as:

 Presenting someone else’s work, ideas, or wording as your own,
 Without giving proper acknowledgement or citation.

In academic contexts, it does not matter whether the source is a book, article, website, or AI
tool—if you pass it off as your original work without acknowledgement, it may be considered
plagiarism.




2. Do outputs generated by LLMs constitute plagiarism?
 Direct output from an LLM is not automatically plagiarism.
LLMs (like ChatGPT) generate new text by predicting word patterns from training data,
not by copying or pasting specific texts verbatim. This means the output is usually
“original” in the sense that it isn’t taken directly from a source.
 However, using it without acknowledgement can be problematic.
If a student copies an LLM’s answer word-for-word and submits it as their own thinking,
that’s considered academic dishonesty. Even if it’s not plagiarism in the traditional sense
(since the text isn’t copied from a published author), it violates the principle of claiming
authorship of work you didn’t produce yourself.
 Risk of hidden plagiarism.
Sometimes LLMs reproduce close paraphrases of training data. In such cases, if you use
that text without checking or referencing the original source, you could unknowingly
plagiarize.

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