# data[].attributes.headline
Key Takeaways: (Summarize your group’s final thoughts, lessons learned, and recommendations.)

# data[].attributes.subject
Key Takeaways: (Summarize your group’s final thoughts, lessons learned, and recommendations.)

# data[].attributes.body
She must revisit all AI-generated summaries, read the original papers, and verify the accuracy of each point.

# data[].attributes.headline
Impact Type: (Ethical / Legal / Academic Reputation – justify)

# data[].attributes.subject
Impact Type: (Ethical / Legal / Academic Reputation – justify)

# data[].attributes.body
Source Integrity matters more.

Transparency (declaring AI use) is important, but not sufficient on its own.

Source integrity means ensuring that all citations reflect what the original authors actually said, in context and meaning.

# data[].attributes.headline
Risk Level: (High / Medium / Low – explain why)

# data[].attributes.subject
Risk Level: (High / Medium / Low – explain why)

# data[].attributes.body
High.

this could lead to accusations of academic misconduct, thesis revision or rejection, or even disciplinary action, depending onm the policies.

# data[].attributes.headline
Plagiarism Verdict: (Yes / No / Unclear – explain)

# data[].attributes.subject
Plagiarism Verdict: (Yes / No / Unclear – explain)

# data[].attributes.headline
Risk Level: (High / Medium / Low – explain why)

# data[].attributes.subject
Risk Level: (High / Medium / Low – explain why)

# data[].attributes.headline
Impact Type: (Ethical / Legal / Academic Reputation – justify)

# data[].attributes.subject
Impact Type: (Ethical / Legal / Academic Reputation – justify)

# data[].attributes.headline
Risk Level: (High / Medium / Low – explain why)

# data[].attributes.subject
Risk Level: (High / Medium / Low – explain why)

# data[].attributes.headline
Plagiarism Verdict: (Yes / No / Unclear – explain)

# data[].attributes.subject
Plagiarism Verdict: (Yes / No / Unclear – explain)

# data[].attributes.body
Both.

Plagiarism: Although she paraphrases some AI-generated summaries, she doesn't verify or rephrase them fully in her own understanding. This means she's relying on machine-generated paraphrasing instead of genuine original work — which counts as indirect plagiarism.

Citation fraud: She cites the original sources but based on potentially inaccurate or distorted summaries generated by AI, not from her direct reading and understanding of those sources. This is misrepresentation of source content, hence citation fraud.

Citing a source without confirming that it supports what you're saying is academic dishonesty.

# data[].attributes.headline
Plagiarism Verdict: (Yes / No / Unclear – explain)

# data[].attributes.subject
Plagiarism Verdict: (Yes / No / Unclear – explain)

# data[].attributes.headline
Risk Level: (High / Medium / Low – explain why)

# data[].attributes.subject
Risk Level: (High / Medium / Low – explain why)

# data[].attributes.body
Risk level: High

If detected, this could lead to accusations of academic misconduct, thesis revision or rejection, or even disciplinary action, depending on her university’s policies.

# data[].attributes.headline
Impact Type: (Ethical / Legal / Academic Reputation – justify)

# data[].attributes.subject
Impact Type: (Ethical / Legal / Academic Reputation – justify)

# data[].attributes.headline
Impact Type: (Ethical / Legal / Academic Reputation – justify)

# data[].attributes.subject
Impact Type: (Ethical / Legal / Academic Reputation – justify)

# data[].attributes.body
Impact: Legal (copyright), Academic Reputation, Ethical Trust

Legal: Copyright infringement may occur if the o

# data[].attributes.headline
Key Takeaways: (Summarize your group’s final thoughts, lessons learned, and recommendations.)

# data[].attributes.subject
Key Takeaways: (Summarize your group’s final thoughts, lessons learned, and recommendations.)

# data[].attributes.headline
Key Takeaways: (Summarize your group’s final thoughts, lessons learned, and recommendations.)

# data[].attributes.subject
Key Takeaways: (Summarize your group’s final thoughts, lessons learned, and recommendations.)

# data[].attributes.body
Plagiarism still applies because the core issue is presenting someone else’s ideas as one’s own without permission or credit, regardless of publication status.

Copyright issues might be less clear or less enforceable if the work is unpublished, but ethical breaches remain significant.

Detection and proof might be more difficult without a public record, but academic institutions typically consider unauthorized use of unpublished work as a grave violation of trust and ethics

# data[].attributes.headline
Key Takeaways: (Summarize your group’s final thoughts, lessons learned, and recommendations.)

# data[].attributes.subject
Key Takeaways: (Summarize your group’s final thoughts, lessons learned, and recommendations.)

# data[].attributes.body
Not plagiarism, but it's in an ethical grey area.

Why it’s not plagiarism:

Maya generated the original ideas and structure herself.

The AI served as a language enhancer.

There was no copying of someone else’s work

Why it's ethically grey:

AI-assisted rewriting can go beyond proofreading — it might shape style, tone, and argument flow.

# data[].attributes.body
it is a plagiarism

# data[].attributes.body
1. It could give the impression that originality is not rewarded.

2. It encourages dependency and degrades academic quality.

3. It disrupts knowledge tracing.

# data[].attributes.body
Risk Level: Low

No AI-generated content was passed off as original ideas.

There is no intent to deceive or manipulate citation systems.

However, if institutional policies require AI disclosure, non-compliance could elevate the risk.

# data[].attributes.body
Primary Impact: Ethical

Ethical: Yes, because she did not disclose her use of AI, which some institutions might expect.

Legal: No, there are no legal infringements here.

Academic Reputation: Minor, unless there’s a strict policy requiring disclosure. In such a case, omission could affect perceived academic honesty.

# data[].attributes.body
It is good to adopt the use of AI in academic writing only as an assistant. in addition, ethical guidelines on the AI usage, like full disclosure, must be abided by.

There should be awareness programs in higher institutions on the ethical use of AI.

# data[].attributes.headline
Plagiarism Verdict: (Yes / No / Unclear – explain)

# data[].attributes.subject
Plagiarism Verdict: (Yes / No / Unclear – explain)

# data[].attributes.body
Both.

Plagiarism: Although she paraphrases some AI-generated summaries, she doesn't verify or rephrase them fully in her own understanding. This means she's relying on machine-generated paraphrasing instead of genuine original work which counts as indirect plagiarism.

Citation fraud: She cites the original sources but based on potentially inaccurate or distorted summaries generated by AI, not from her direct reading and understanding of those sources. This is misrepresentation of source content, hence citation fraud.

Citing a source without confirming that it supports what you're saying is academic dishonesty.