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1Repair Windows errors before they cause bigger problems2Fix the driver behind crashes, sound loss and screen glitches3Clear out junk files and repair common Windows errorsCan I use AI for this assignment, and can I ask without being treated as dishonest? Students should be able to get a clear answer before they submit work. Instructors can protect academic integrity without creating a climate in which reasonable questions or good-faith disclosures feel dangerous.
The workable approach is assignment-level clarity: state what AI may and may not do, explain how to acknowledge permitted assistance, preserve evidence of the student’s learning and judgment, and provide a consistent route for questions. Psychological safety means students can raise uncertainty and disclose permitted support; it does not mean prohibited conduct has no consequences.
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Start with the assignment, not a blanket AI rule
Generative AI is not automatically misconduct in every course. Whether it is allowed for assessed work can depend on the institution, program, course and individual assignment. The University of British Columbia states: “At this time, whether the use of AI tools in courses and assessments is or is not allowed is a course or program-level decision.” Its guidance tells instructors to set expectations in the syllabus, advises students to obtain permission before using AI for assessed work, and says students should ask for clarification when rules are missing or unclear. UBC also has a syllabus requirement taking effect on 1 September 2026; that is a UBC policy, not a universal higher-education rule.
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A university-wide statement cannot answer whether a student may use a text generator to brainstorm a topic, a grammar tool to correct punctuation, a coding assistant to suggest functions, or an image model to create a visual for one particular task. The assignment must identify the learning that will be judged and the role, if any, that AI can play.
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Three categories students need to distinguish
| Category | What it means | What the student should do |
|---|---|---|
| Permitted support | The assignment expressly allows a defined use, such as brainstorming, translation, accessibility support or feedback on a draft. | Stay within the stated limits, verify the output and provide the required acknowledgement. |
| Undisclosed or out-of-bounds assistance | AI is used for a task the instructions reserve for the student, or a permitted use is hidden when disclosure is required. | Stop and ask the instructor before submitting. Do not assume that a generally permissive course policy covers every task. |
| Work that no longer demonstrates the student’s learning | The system produces the substance being assessed, while the student has little meaningful role in reasoning, analysis, design or revision. | Do not submit it as personal work. Seek an approved way to demonstrate the outcome yourself. |
Permission is therefore not a blanket licence. A student can use an approved tool and still breach the assignment by exceeding its scope, failing to check inaccuracies, or omitting a required declaration.
What an assignment-level policy should say
Students should not have to infer the rules from a general statement about “responsible AI.” Put the instructions beside the assessment brief, rubric and submission link. A practical policy answers five questions.
- Is AI allowed? Say yes, no or “only for the uses listed below.” If different components have different rules, label each component.
- Which tasks may it support? Name concrete activities: generating questions, explaining a concept in alternative language, finding coding errors, or checking grammar. Avoid the vague phrase “AI may be used appropriately.”
- What must remain the student’s own work? Identify the reasoning, calculations, interpretation, design decisions, source selection, performance or other learning outcome being assessed.
- What acknowledgement is required? Specify whether students must name the tool, date of use, prompts or a short description of how the output influenced the work. Give a word limit or form if one is required.
- Where can students ask? Provide one named contact or discussion channel and a response-time expectation. Tell students that asking before submission is responsible conduct, not an admission of misconduct.
A usable declaration model
The University of Sheffield recommends an “Acknowledge, Describe, Evidence” approach. Adapted to a course, it can require a student to:
- Acknowledge: identify the AI service or other tool used.
- Describe: explain what it did, such as suggesting headings, translating a passage or identifying possible syntax errors.
- Evidence: retain drafts, prompts, output excerpts, revision notes or another record when the assignment requires proof of process.
Students should not be asked to provide sensitive prompts or account data that the course does not need. The declaration should collect enough information to evaluate authorship and process without creating an unnecessary privacy burden.
Sample assignment wording
“You may use an AI tool to generate practice questions and to suggest grammar corrections. You may not use it to write analysis, select sources or produce your final answer. Check every suggestion against course materials. Add a 100-word declaration naming the tool, describing how you used it and identifying one change you made after checking its output. If you are unsure whether a use is allowed, ask the instructor before submission.”
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Compare course approaches against the same six tests
There is no single correct policy for every discipline. A permissive policy may fit a learning outcome that includes evaluating AI output; a restricted policy may be necessary when unaided performance is the outcome. An assignment-specific policy often works when tasks in one course require different kinds of evidence. Compare options using the same questions rather than choosing a label first.
| Test | Permissive approach | Restricted approach | Assignment-specific approach |
|---|---|---|---|
| Learning-outcome alignment | Works when critical use or evaluation of AI is part of the outcome. | Works when independent recall, calculation or performance must be observed. | Matches different outcomes across a course or sequence. |
| Boundary clarity | Requires a detailed list of allowed and prohibited tasks. | Requires a clear definition of what “no AI” covers, including accessibility tools. | Requires students to check the rule for each assessment component. |
| Disclosure | Needs a simple, consistent declaration format. | Should explain whether any incidental or assistive use must still be reported. | Can vary the declaration by task, but terminology should remain consistent. |
| Evidence of authorship | Drafts, annotations, oral explanation or version history can show judgment. | In-class or supervised work may provide direct evidence. | Evidence can be matched to the risk and outcome of each task. |
| Support route | Students need help evaluating fluent but incorrect output. | Students need a safe way to ask before using a prohibited tool. | Students need a single place to resolve conflicting instructions. |
| Access, privacy and equity | Plan for tool costs, accessibility and data handling. | Provide an accessible alternative when a required tool is unavailable or inappropriate. | Review each tool and task separately for data and access risks. |
These six tests are a planning framework synthesized from institutional guidance; they are not a validated scoring instrument. Document why the chosen approach fits the learning outcome and tell students how that decision affects their work.
Psychological safety is a procedure, not a promise of immunity
A psychologically safe course lets students say, “I am not sure whether this counts,” without being shamed. It also makes the response predictable. Safety disappears when one student receives informal permission while another is penalized for the same use, or when a declaration is treated as proof of dishonesty by itself.
The University of Sheffield says, “We provide institutional expectations while respecting disciplinary expertise.” That balance is useful: an institution can establish principles for honesty, privacy and access while instructors explain what those principles mean in a particular assignment.
Use a three-part conversation
- Clarify the facts. Ask what tool was used, for which step, when, and what the student changed or checked. Do not begin with an accusation based only on writing style or a detector score.
- Compare the use with the published rule. Identify the exact boundary: allowed, prohibited, or not specified. If the rule was ambiguous, record that ambiguity and apply the same clarification to the whole class.
- Choose the next action. This may be a declaration, a resubmission, a learning conversation, or a formal academic-integrity process when the evidence and policy support it. Explain the appeal or review route.
Psychological safety does not require promising that every disclosure will avoid consequences. It requires a known boundary, a good-faith question route and a fair process. Tell students that a question before submission is different from a finding that prohibited assistance was used, while avoiding assurances that the outcome is predetermined.
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Normalize questions in ordinary course communication
- Put a recurring “AI use questions” item in the learning-management system.
- Answer common questions in a shared document so the whole class receives the same interpretation.
- Include permitted assistive uses in examples rather than treating disability-related support as an exception that students must privately defend.
- Invite students to disclose uncertainty early, before grades or misconduct procedures are involved.
- Record policy changes with a date and notify every student; do not alter a rule silently after work has begun.
Recent evidence should be interpreted cautiously. A mixed-methods study described in a British Journal of Educational Psychology abstract examined 409 undergraduates at one Singaporean university and explored cognitive, social and emotional factors related to willingness to disclose generative-AI use. A 2026 preprint summary reports that supportive teacher practices and clear guidance may support psychological safety, while ambiguity and reputational concerns may discourage disclosure. These findings are context-specific and do not prove that one script or policy will produce the same response in every course.
Design assessments so learning remains visible
Rules work better when the assessment itself asks for evidence that a text generator cannot easily substitute for. The Tertiary Education Quality and Standards Agency resource collection groups work around detection, assessment design and curriculum integration, signalling that detection is only one part of an integrity strategy.
Specify the human judgment being assessed
Write the rubric around decisions students must justify: why a method fits the problem, how evidence supports a claim, which design trade-off was chosen, or how a result changes under a different assumption. If an AI tool is allowed to produce options, grade the student’s evaluation and revision rather than the polished option alone.
Collect proportionate process evidence
- Require a short rationale, annotated bibliography, calculation trail, code comments or design log where it directly supports the outcome.
- Use staged submissions when feedback and revision are part of the learning.
- Add a brief oral explanation or in-class application when the course needs direct evidence of individual understanding.
- Ask for drafts or version history only when the information will be used and can be stored securely.
Do not turn every assignment into surveillance. Process evidence should have a clear relationship to the learning outcome, a manageable workload and an accessible alternative for students who cannot use a particular platform.
Keep detection in its proper place
An AI detector result is a concern to examine, not a substitute for a clear rule, student conversation and evidence of learning. Detection tools can produce signals that require context; the evidence supplied here does not establish a universal accuracy rate for any detector. A fair process should never treat a score as conclusive proof without considering drafts, citations, course instructions, the student’s explanation and other relevant evidence.
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Keep final decisions human
Liverpool’s July 2026 guidance lists educational uses such as generating multiple explanations of a concept, refining a rubric and drafting teaching materials for review. It also identifies copying unreviewed AI content into briefs or rubrics and using AI to generate grades or final assessment decisions as unacceptable. The practical rule is simple: an educator may use AI to assist preparation under safeguards, but a qualified person remains responsible for the assessment judgment, feedback and final grade.
Use the same principle for student work. An AI system may help surface possible counterarguments, but the student must verify facts, evaluate sources and make the argument that the rubric assesses. AI outputs can be inaccurate, biased or filled with false references; fluent wording is not evidence of truth.
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A policy that assumes every student can use the same commercial tool may create an integrity problem of its own. Sheffield notes that AI can function as assistive technology and may help students who are neurodivergent, anxious or managing invisible barriers. It also calls attention to access costs and accessibility limitations.
Build an equitable option
- State whether a tool is optional or required, and provide an equivalent route when it is unavailable, unaffordable or inaccessible.
- Do not require students to create an account or surrender personal data merely to complete an assessment.
- Explain whether an assistive use must be declared and how that declaration will be handled.
- Coordinate accommodations with disability or accessibility services rather than asking students to disclose sensitive information to the whole class.
- Check that prompts, uploaded files and generated interfaces work with the assistive technologies used in the course.
Decide what data may be entered
Liverpool advises against uploading student work, personal data or confidential information to public AI platforms without completing a Data Protection Impact Assessment and/or seeking guidance from its Data Protection Officer. That is an institution-specific rule, so instructors must follow their own privacy, records-management and contractual requirements.
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UT Austin’s responsible-adoption guidance says, “To use AI responsibly, students and educators must always be in the loop, understand how these technologies work, their ethical assumptions and implications and the influence they will have on their learning, careers and society.” Apply that principle by documenting what a service stores, who can access it, whether data is used for training, how long records are retained and how a student can opt for an alternative.
A practical implementation plan for instructors
Before publishing the assessment
- Write the learning outcome in observable terms and identify which parts require unaided performance or human judgment.
- Choose permitted, prohibited and conditional AI uses for each assessment component.
- Check institutional academic-integrity, accessibility, procurement and data-protection rules.
- Draft the acknowledgement requirement and decide what process evidence is genuinely necessary.
- Test the instructions with a colleague or student representative for ambiguous wording and unequal access.
When releasing the assessment
- Place the AI rule in the brief, rubric and submission instructions, using the same wording.
- Show one permitted example and one prohibited example from the actual task.
- Provide the question channel, expected response time and a reminder that asking is responsible behavior.
- Explain how declarations, drafts or other evidence will be stored and who will see them.
During the work period
- Answer questions publicly when they are relevant to the whole class; preserve private routes for sensitive circumstances.
- Publish clarifications with dates and notify students who have already started.
- Watch for access barriers, tool outages and conflicting instructions from teaching assistants or placement partners.
- Encourage students to verify outputs against course readings, primary sources and their own reasoning.
At marking and review
- Apply the rubric to the learning outcome, not to how polished or machine-like the prose appears.
- Review a detector signal alongside process evidence and the student’s explanation; never use it as the sole basis for a finding.
- Separate a missing declaration from substantive unauthorized assistance when the policy distinguishes them.
- Use the institution’s formal process when a suspected breach cannot be resolved informally, and provide the required notice and appeal rights.
- After the assessment, record recurring questions and revise the next version before students begin it.
A decision path for students: “Should I tell my teacher?”
When the rule is unclear, students can use this sequence:
- Read the syllabus, assessment brief, rubric and any course announcements together. Look for a rule specific to this task.
- Describe the proposed use in plain language: tool, purpose, stage of work and whether it will affect the submitted content.
- Ask before using the tool if the permission is not explicit. Keep the response with the assignment records.
- If use is allowed, follow the exact acknowledgement format and verify every factual, mathematical or cited output.
- If use was outside the rule, stop adding AI-generated material and contact the instructor or designated adviser promptly. Do not conceal the use or invent a citation.
A disclosure gives the instructor information about process; it does not automatically establish misconduct or guarantee an outcome. The relevant question is whether the use complied with the published rule and whether the submitted work demonstrates the required learning.
How program leaders can keep policies consistent
Program and integrity leaders should provide a common vocabulary without forcing every discipline into one template. A central policy can define academic honesty, privacy, accessibility, records and review rights. Course teams can then map those principles to each assessment.
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- Train instructors and teaching assistants to give the same answer to common scenarios.
- Provide an escalation route for ambiguous or high-risk uses, including confidential data.
- Review whether students with accommodations or limited connectivity have an equivalent way to meet each outcome.
- Audit patterns of questions, declarations and appeals for inconsistent treatment, without treating disclosure counts as a measure of guilt.
The goal is not maximum restriction or maximum permission. It is a course environment in which students know what honest work looks like, can ask before they cross a boundary, and are still responsible for the quality and authorship of what they submit.
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