Setting Course and Assignment AI Rules
Students need to know what AI use is allowed before they begin an assignment. A useful policy connects the rule to the learning outcome, describes allowed and prohibited actions, explains disclosure, and provides an accessible alternative when a tool is required.
A course statement does not replace institutional academic-integrity, accessibility, privacy, assessment, or research policies. Use institutionally approved tools and follow Responsible AI use when a task involves student data or consequential decisions.
Choose the level for each assignment
A single rule for an entire course is often too vague. Choose the level that matches what each assignment is intended to demonstrate.
| Level | Appropriate when | Example wording |
|---|---|---|
| AI-free | Students must demonstrate unaided knowledge or performance | “Do not use generative AI for any part of this task. The assessment measures your unaided ability to [outcome].” |
| AI-limited | Particular forms of assistance do not replace the target skill | “You may use AI to [allowed actions]. Do not use it to [prohibited actions].” |
| AI-permitted | Students may choose AI, but remain responsible for the work | “You may use AI at any stage, provided you verify the result and disclose how it affected the submitted work.” |
| AI-integrated | Using and evaluating AI is itself part of the learning outcome | “Use the specified AI workflow, retain the required evidence, and evaluate the tool’s contribution and limitations.” |
AI-free assessment remains appropriate when unaided recall, writing, calculation, clinical reasoning, performance, or another independent capability is the intended outcome. Requiring AI can be appropriate when critical AI use is an explicit outcome—not merely because a tool is available.
Write a complete assignment rule
Name the learning purpose
State what the student must learn or demonstrate. Explain why the selected AI level protects or supports that outcome.
Define actions, not labels
Terms such as “responsible use” or “AI-assisted” are open to interpretation. Specify whether students may brainstorm, translate, summarize, find sources, generate prose or code, edit language, produce media, obtain feedback, or debug.
Set evidence and disclosure requirements
Ask only for evidence that supports reflection or assessment. A short use record is usually more useful than an indiscriminate transcript or a collection of screenshots. Do not imply that version history or a detector score proves authorship.
Provide access and privacy conditions
If AI use is required, provide access to an approved tool and an equivalent alternative for students who cannot use it because of accessibility, cost, account, location, language, age, or privacy constraints. Do not require students to surrender personal data or rights to complete an activity.
Explain how the work will be assessed
Align the rubric with the learning outcome. Assess the student’s decisions, evidence, reasoning, verification, and reflection where relevant—not the polish of model-generated text.
State the response to uncertainty
Give a contact point and invite questions before submission. Explain that suspected misuse will be handled through the institution’s normal, evidence- based process and that an AI detector score is not proof.
Copyable course statement
Generative AI is addressed separately for each assignment because the permitted
role depends on the learning outcome. The assignment brief will label the task
AI-free, AI-limited, AI-permitted, or AI-integrated and will list allowed uses.
Unless an assignment says otherwise, do not enter personal, confidential,
licensed, or unpublished course material into an AI service. You remain
responsible for the accuracy, sources, argument, and submitted work. Ask the
course team before using a tool when the instructions are unclear.
When disclosure is required, briefly record the tool, date, purpose, material
retained, and checks performed. Disclosure does not make prohibited assistance,
fabricated evidence, or misrepresentation acceptable.
Students who cannot use a required tool will receive an equivalent way to meet
the same learning outcome without penalty. Contact [role/contact] as early as
possible to arrange this.Copyable assignment block
AI level: [AI-free / AI-limited / AI-permitted / AI-integrated]
Learning purpose:
[What this task is designed to develop or demonstrate]
Allowed:
- [specific action]
- [specific action]
Not allowed:
- [specific action]
- [specific action]
Evidence to submit:
[Short disclosure, annotated changes, source checks, reflection, or none]
Assessment:
[How the rubric rewards the student's knowledge, reasoning, and decisions]
Access and alternative:
[Approved tool/access route and equivalent non-AI route]
Questions or concerns:
[contact and applicable institutional policy]A proportionate disclosure
For many tasks, this is enough:
I used [tool and version, if known] on [date] to [purpose]. I retained [what was used] and checked it by [verification performed]. I remain responsible for the submitted work.
Request a longer process record only when interaction choices are part of the learning outcome. Avoid collecting full conversations by default: they can contain personal information, copyrighted material, false starts, or unrelated content.
Checklist before publishing the rule
- The AI level follows from the learning outcome.
- Allowed and prohibited actions are concrete.
- The rule covers embedded AI features such as translation, rewriting, coding, or image generation where relevant.
- Disclosure requirements are proportionate and assessable.
- The institution approves the tool for the intended data.
- Required use includes access, accessibility, and a genuine alternative.
- The rubric rewards student learning rather than model fluency.
- Students know where to ask questions and how concerns will be handled.
Related guidance
- Assessing learning in the age of AI
- Why AI detection does not work
- Responsible AI use
- Teaching students to evaluate AI outputs
References & Footnotes
- European Commission. (2026). Guidelines on the ethical use of artificial intelligence and data in teaching and learning for educators. https://doi.org/10.2766/9548952Â
- UNESCO. (2024). AI competency framework for teachers. https://unesdoc.unesco.org/ark:/48223/pf0000391104Â