Academic Integrity Workshop
Live workshop on plagiarism, paraphrasing, citation, and generative AI rules, run with polls, branching scenarios, and hands-on paraphrasing exercises.
Who this is for
University and college students, run live by academic skills teams, librarians, or course leaders
Learners will be able to
- Recognise the main forms of plagiarism, including mosaic writing, self-plagiarism, and collusion
- Paraphrase and cite source material properly instead of patch-writing close to the original
- Apply their institution's generative AI policy to realistic assignment situations and declare AI assistance where required
- Describe how misconduct cases arise, how panels work, and the penalties poor academic practice can attract
Template prompt
“Create an interactive workshop on academic integrity covering plagiarism types (copy-paste, mosaic, self-plagiarism), proper paraphrasing techniques, citation responsibilities, AI tool usage policies, and consequences of misconduct. Include polls and scenarios.”
This prompt is fully editable. Customise it to match your audience, regulations, and learning objectives before generating.
What the 8 sections cover
- 1
Opening poll: where's the line?
Live poll on borderline cases — reusing your own past essay, sharing notes with a friend, asking AI to draft an introduction — to surface the room's assumptions before any teaching.
- 2
The plagiarism spectrum
Visual spectrum from sloppy citation through copy-paste, mosaic writing, and self-plagiarism up to contract cheating, with a clear definition and example at each point.
- 3
Scenario: the collaborative assignment
Branching scenario exploring where legitimate collaboration tips into collusion, with consequence feedback showing how each choice would be judged.
- 4
Paraphrasing that actually works
Worked before-and-after examples where participants judge which rewrites are genuine paraphrase and which are patch-writing that would trip a similarity report.
- 5
Scored quiz: citation or violation?
Scored quiz classifying six short cases as acceptable academic practice or misconduct, with explanations for every option.
- 6
Generative AI: policy in practice
Poll and discussion on acceptable AI uses — brainstorming, proofreading, drafting — mapped against typical university rules and declaration requirements.
- 7
What happens when it goes wrong
How cases typically surface (similarity reports, marker referral), what a misconduct panel looks like, and the realistic range of penalties from mark caps to expulsion.
- 8
Commitments and key takeaways
Reflection prompt where each participant commits to one concrete practice change, followed by recap flashcards of the session's key rules.
Structure is representative — the generator adapts sections to your edited prompt and passes every package through interactivity and visual-density quality gates.
See a real generated example
Academic Integrity and Responsible AI: Student Decisions in Practice was generated with a prompt like this one — preview every section live and download the SCORM package.
Preview the live exampleTopics covered
Make it yours
- Upload your academic misconduct regulations so scenarios reference your actual penalty bands and panel process.
- Rewrite the AI section around your institution's current generative AI policy, including any declaration or acknowledgement wording students must use.
- For postgraduate or research cohorts, ask for research-integrity cases such as data fabrication, duplicate publication, and authorship disputes.
Frequently asked questions
Is there a single UK definition of plagiarism?
No — each university defines academic misconduct in its own regulations, though QAA guidance strongly shapes them. One thing is fixed in law: providing or arranging contract cheating services (essay mills) for students in England was made a criminal offence by the Skills and Post-16 Education Act 2022.
How should the workshop handle AI tools like ChatGPT?
Policies vary widely between institutions, so the AI section is written to be adapted. The Russell Group's 2023 principles on generative AI support ethical, transparent use with proper acknowledgement, and most UK universities now distinguish permitted uses (idea generation, proofreading) from prohibited ones (submitting AI-written work as your own). State your institution's position in the prompt.
Is this run live or self-paced?
It is designed as a live interactive session — polls and discussion points assume a facilitator and a room. Host it as an Intle session with a join code, or export it as a SCORM package if you need a self-paced version for your VLE, in which case polls become individual response questions.
When should students complete it?
Before their first assessed submission. Many universities schedule integrity workshops in induction and then require a refresher at dissertation stage, when the stakes and the citation load both rise.
Ready to make it yours?
Customise the prompt, generate a draft, then review the content and SCORM package before delivery.
Related templates
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First-year student induction covering academic integrity, library and support services, and study skills, with an interactive referencing quiz.
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Introductory research methods module covering qualitative and quantitative approaches, study design, sampling, and research ethics, with matching exercises pairing methods to use cases.
Handling a Safeguarding Disclosure
Branching scenario where school staff practise receiving a pupil's disclosure in line with KCSIE — listen, reassure, record, refer — with consequence feedback at every decision point.