Statewide guidance in Illinois describes a trust but verify approach to AI, urging educators to evaluate AI-generated content critically instead of accepting it as given. That phrase is easy to endorse and much harder to practice when a teacher is staring at a hundred essays with draft comments already attached. Without a concrete routine, review turns into a quick glance, and errors slip through to students.

A review checklist turns a good intention into a repeatable habit by telling you exactly what to look at on each paper, how much time to spend, and when a result deserves a closer read. Teachers who use one also find it easier to explain their process to administrators and parents, because the steps are written down and can be shown on request. It also helps new colleagues adopt the same standard instead of inventing their own.

Research on AI feedback in classrooms shows why the effort is worthwhile. In one set of teacher surveys, only about 57 percent of teachers called the AI feedback clear and actionable, while roughly a quarter found it vague and about one in five found it incorrect or misleading. Those figures describe a first draft that is useful but not trustworthy enough to send out unreviewed.

The five-point review

Read the student's essay before reading the draft comment, so that your own impression anchors the review instead of the tool's. Then compare each criterion score to what you saw, and check that every comment refers to something actually present in the student's text. Spend your most careful attention on scores near a boundary, such as the line between passing and not passing, because those are the decisions students care about most.

• Accuracy: does the comment describe what the student actually wrote, with no invented quotations or claims?
• Alignment: does each score match the rubric descriptor for that level rather than a general impression?
• Usefulness: does the comment name a specific next step the student can act on this week?
• Tone: is the language respectful, encouraging, and appropriate for this student's age and confidence?
• Fairness: would a student with a different background or writing style receive the same score for this work?

Match your review time to the stakes

Not every paper needs the same depth of review. A low-stakes paragraph graded on a familiar rubric may need only a thirty-second scan of the scores and comment, while a final essay that counts for a large share of a grade deserves a full read and careful edits. Writing down your own standard in advance, such as a full read for any score within one point of a boundary, prevents shortcuts from creeping in on busy weeks.

Track what you change as you review. If you repeatedly edit the same kind of comment, such as overly generous praise or vague suggestions, adjust your rubric descriptors or settings so the next batch needs fewer corrections. A short log of edits over two or three assignments often reveals patterns that save more time than any single review session, and it gives you concrete evidence of how the tool is performing in your classroom.

Make the review visible to students

Tell students that every comment is reviewed by you before they see it, and show them how a draft comment is edited into a final one. This transparency helps counter the skepticism that pilot research has found among students toward AI-only grading. It also models the habit of checking sources that students will need in their own work with technology, which many of them are already using without any such habit.

Invite students to flag any comment that does not seem to match their essay. A simple question in the margin, such as does this describe my paper, gives them a voice and gives you an extra layer of quality control. Students who feel heard are more likely to engage with feedback in the first place, which is the whole point of writing it.

Build the routine into your week

Block a fixed window for review, such as ninety minutes on the day after submissions arrive, and treat it as protected time. Batch similar tasks together, reading all essays for one criterion before moving to the next if your workflow allows it. A predictable routine keeps review from being squeezed out by other demands, which is exactly when shortcuts become most tempting.

Share your checklist with colleagues and compare notes after the first few assignments. Departments that agree on a common standard for review can say with confidence that no AI-drafted comment reaches a student unverified. That claim, backed by a written process, is the most persuasive answer to families, administrators, and board members who worry about automation in grading. Revisit the checklist each term as tools and policies evolve, so that the written process always matches what teachers actually do.