Integrity Checklist
File: tertiary-guide/07-integrity-checklist.md
Academic integrity is the foundation of higher education. Universities expect students to produce work that reflects their own thinking, reasoning, and judgement, supported by credible sources. These expectations apply across all disciplines — including healthcare, engineering, computer science, sciences, law, business, accounting, and the arts.
Misusing Generative AI — whether by copying outputs, masking lack of understanding, or failing to verify sources — undermines learning and can lead to serious consequences. More importantly, it weakens the habits of responsibility and accountability that universities aim to develop.
This checklist is designed to help you use AI ethically, transparently, and responsibly, while protecting both your academic progress and your professional integrity.
◆ 1. Understand Plagiarism
Plagiarism is not limited to copying text from books or websites. It also applies to AI-generated content when it is presented as your own work.
▸ Copying text directly from AI or other sources without acknowledgement is plagiarism.
▸ Paraphrasing AI output without adding your own analysis, synthesis, or judgement may still be considered plagiarism.
▸ Using AI to produce work you cannot explain or defend undermines the purpose of assessment.
Across disciplines, integrity matters because:
▸ clinicians must justify decisions
▸ engineers must stand behind designs
▸ programmers must understand the code they submit
▸ researchers must defend interpretations
▸ artists must demonstrate original engagement
◆ 2. Check Institutional Policies
AI use policies vary between universities, faculties, and even individual courses.
▸ Some institutions allow AI for brainstorming, planning, or feedback.
▸ Others restrict or prohibit its use in assessed work.
▸ Expectations may differ between coursework, exams, and group projects.
Always consult:
▸ official university policy documents
▸ course outlines or assessment briefs
▸ guidance from lecturers or tutors
When in doubt, ask — transparency protects you.
◆ 3. Use AI as a Partner, Not a Substitute
AI should support your thinking, not replace it.
▸ Use AI to clarify concepts, organise ideas, generate practice questions, or review drafts.
▸ Write final content yourself, using your own reasoning, structure, and voice.
▸ Avoid prompts that ask AI to “write”, “complete”, or “solve” assessed tasks for you.
A useful self-check:
If AI disappeared tomorrow, could I still explain and justify this work?
If the answer is no, AI has crossed from support into substitution.
◆ 4. Verify References
AI tools may generate references that are:
▸ incomplete
▸ incorrectly formatted
▸ misattributed
▸ or entirely fabricated
▸ Always verify sources using library databases, Google Scholar, or official publisher sites.
▸ Ensure in-text citations and reference lists follow the required style (APA, MLA, Harvard, etc.).
▸ Check details such as authors, publication year, journal title, volume, issue, and page numbers.
Accurate referencing is essential not only for academic honesty, but for scholarly credibility.
◆ 5. Keep a Record of Your Process
Maintaining evidence of how your work developed protects you and strengthens reflection.
▸ Save drafts, notes, and planning documents.
▸ Keep track of when and how you used AI tools.
▸ Be prepared to explain your process if asked by a lecturer or examiner.
This mirrors professional practice, where documentation, traceability, and accountability are essential.
◆ 6. Practise Responsible Paraphrasing
Good paraphrasing demonstrates understanding, not just rewording.
▸ Integrate ideas with your own interpretation and examples.
▸ Combine multiple sources rather than relying on a single explanation.
▸ Add disciplinary context, case studies, or applications that show engagement.
Aim for synthesis, not substitution.
◆ 7. Ask Yourself Before Submitting
Before you submit any assessed work, pause and reflect:
▸ Does this work genuinely reflect my own thinking and learning?
▸ Have I cited all sources accurately and appropriately?
▸ Could I explain and defend this content without AI support?
▸ Would I feel confident discussing this work with my lecturer or peers?
These questions are as relevant to professional life as they are to university study.
◆ Final Reminder
Academic misconduct carries serious consequences, but the deeper issue is trust. Universities assess your work to understand your capability, judgement, and readiness to progress.
Generative AI can be a powerful learning tool when used responsibly. By prioritising integrity, transparency, and reflection, you protect your education, your reputation, and your future professional credibility.