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Assessment and feedback

AI Grading and Feedback Guide for Teachers

AI is safest when it supports feedback preparation rather than making an unreviewed final judgement about a learner. Begin with criteria, anonymised work, and a clear human verification process.

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Updated 2026-08-10JENECONK editorial teamInternational edition

Useful teacher-led applications

Rubric drafting

Turn approved learning outcomes into proposed criteria and performance descriptors, then check progression and language carefully.

Feedback banks

Create editable comments for recurring strengths and misconceptions without assigning them automatically to named learners.

Question review

Check whether practice questions cover recall, application, reasoning, and the intended curriculum content.

Exemplar discussion

Generate fictional examples for class critique, clearly labelling them and checking that they genuinely illustrate the criteria.

A defensible feedback workflow

  1. Set the learning outcome and approved marking criteria before using AI.
  2. Decide whether the tool and data are approved for the task.
  3. Remove names and details that could identify the learner.
  4. Ask AI to reference the supplied criteria and show its reasoning.
  5. Compare suggestions with the actual work and teacher evidence.
  6. Write or approve the final grade and feedback yourself.
  7. Provide a route for questions, correction, or appeal under school policy.

Prompt for criterion-based feedback

Using only the rubric below, identify two demonstrated strengths, one area for improvement, and one actionable next step in this anonymised practice response. Quote brief evidence from the response. Do not assign a final grade, infer personal characteristics, or introduce criteria that are not in the rubric. Flag any judgement that requires subject-teacher review.

Fairness and quality checks

  • The same criteria are applied consistently across learners.
  • The tool has not rewarded writing style when content knowledge is being assessed.
  • Feedback does not infer effort, ability, disability, background, or intent.
  • Teachers can explain and correct the final judgement.
  • Learner work is handled under approved privacy and retention rules.
  • Assessment regulations permit the proposed use of AI.

A grade is a consequential decision. Do not rely on an opaque AI score as the sole basis for a result, intervention, placement, or report.

Frequently asked questions

Can AI grade student work automatically?

A school may use approved systems for limited support, but final grading should remain explainable, policy-compliant, and subject to qualified human review.

Can I paste essays into a public chatbot?

Not when the work or surrounding details identify a learner or when the school has not approved that data use.

What is a safer first use?

Draft a rubric or feedback bank from public curriculum criteria, then review it before applying it to any learner work.