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To get specific feedback from AI on an assignment draft, give it the assignment instructions, the relevant rubric criteria, the draft or excerpt, and a narrowly defined review task. Ask for comments tied to those criteria and practical revision steps—not a grade or a replacement submission. Then check the response against your course rules and use your own judgment to decide what to change.
What should you ask AI to review in your assignment?
Ask about a feature you can revise, such as whether your argument answers the question, whether evidence supports each claim, or whether the organization makes your reasoning clear. Ground the request in the actual assignment brief and rubric: a general request such as “Give feedback on this assignment” gives the tool little basis for distinguishing relevant advice from generic suggestions.
The University of Regina Centre for Teaching and Learning recommends referring to rubric areas or course learning outcomes when seeking feedback. Its September 2025 guidelines state: “Thoughtful prompting and critical review are essential when using GenAI to support feedback.” Read the University of Regina guidelines.
Choose a focused review task
For a first pass, select one or two related criteria. For example, ask whether the thesis makes a clear, arguable response to the question, or whether the evidence is explained in a way that supports the claim. A focused request makes it easier to connect comments to the rubric and decide what to address first. Treat this as a practical workflow, not a guaranteed formula: the official guidance cited here does not establish that any particular prompt produces better results in a measured comparison.
#1 Best Overall
How to write a prompt with enough context
Include the information the tool needs to assess the draft against your task: assignment type and question, essential instructions, relevant rubric criteria, the passage to review, and the feedback focus. Ask it to separate observations from assumptions and identify missing information instead of inventing requirements.
Adapt this prompt to your assignment:
I’m working on [assignment type and question]. The instructions require [brief essentials]. The relevant rubric criteria are [paste or summarize criteria]. Here is my draft or excerpt: [text]. Please give formative feedback only. Focus on [one or two criteria]. For each point, identify the passage or issue, explain how it relates to the stated criterion, and suggest a practical revision step. Separate observations from assumptions; if information is missing, ask me rather than inventing a requirement. Do not write a replacement submission or assign a grade.
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Share only the parts of the brief and draft needed for the review. If you are working with a long assignment, submitting an excerpt tied to one criterion can keep the task manageable. Do not treat the prompt as permission to share material: first check course rules and whether the tool is approved for the information involved.
How to get specific, actionable comments
Ask the tool to point to a passage or issue, explain its connection to a named criterion, and suggest a next step you can carry out. “Explain how the second paragraph supports the criterion for use of evidence, and suggest one way I could clarify the link” is more useful than “Make this better.” Ask for comments, not an automatic rewrite, so you can assess and make the revision yourself.
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- “Which one change would most improve alignment with criterion X, and why?”
- “What part of your previous feedback relies on an assumption not stated in the rubric?”
- “What evidence in this excerpt supports your comment about the argument? If the excerpt is insufficient, tell me what context is missing.”
If the first answer is broad or unhelpful, narrow the task or ask a targeted follow-up rather than treating that response as the final word. The University of Sydney lists seeking feedback on written work as a possible use and advises trying more than one interaction; it does not establish that a particular prompt guarantees useful feedback. See the University of Sydney’s guidance on generative AI in education.
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How to review AI feedback before revising
Check every comment against the assignment instructions, rubric, course materials, and your intended meaning. AI may misunderstand the task or produce inaccurate, fabricated, or biased claims. The University of Wollongong’s student guidance, “Gen AI in assessment,” says: “Fact verification against reliable sources is essential as gen AI outputs can be inaccurate, fabricated or biased.” Read the University of Wollongong guidance.
- Keep feedback that is supported by the stated criteria and helps you improve the draft.
- Question advice that introduces a new requirement, changes your meaning, or conflicts with the brief.
- Verify factual statements and references against reliable sources rather than assuming they are correct.
- Decide yourself which changes to make; feedback is input for your judgment, not an assessment decision.
University guidance cautions against using AI for evaluative decisions. Ask for formative comments you can review, not a definitive grade or judgment of whether the work meets a standard.
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Check permission, disclosure, and privacy first
Permitted uses vary by institution, course, and assessment. The University of Wollongong notes that feedback on an assessment item can be a permitted use, while emphasizing that the assessment instructions determine whether it is allowed. Check your assignment brief, subject outline, or ask your instructor before pasting any work into an AI tool; follow any acknowledgment or disclosure requirements that apply.
Privacy rules also matter. Do not upload personal, sensitive, or confidential information to a tool unless your institution’s rules and the tool’s approved status allow it. The University of Bristol’s guidance addresses its own staff procedures and is not a universal student policy; its cautions about unapproved external tools should not be treated as a substitute for checking your institution’s requirements. Read the University of Bristol’s guidance.
Rules can be specific to an institution. For example, the University of Liverpool’s guidance, updated July 2026, permits AI to help refine feedback when a teacher performs the assessment and identifies unreviewed AI feedback, AI-generated grades or final decisions, and certain public-platform data uploads as unacceptable under its own rules. These are Liverpool-specific requirements, not universal student rules. Read the University of Liverpool guidance.
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