Peer review has a mixed reputation among teachers. Done poorly, it produces friendly but useless comments like "good essay, needs more evidence." Done well, it helps students see their own writing more clearly and reduces the number of basic problems that reach you.

A novel like The Master and Margarita is a good candidate for peer review. Students bring different readings, and seeing another interpretation can sharpen their own. The complexity of the book also means drafts benefit from a second set of eyes.

The key is structure. Give reviewers specific questions instead of open-ended prompts. Ask them to find the thesis, mark the strongest piece of evidence, and identify one paragraph that reads like summary.

Keep the review short, around fifteen to twenty minutes. Longer sessions tend to drift. A tight window keeps energy and focus high.

A four-step workflow

This workflow layers AI feedback and peer review so that each does what it does best. AI handles rubric-level observations, while peers offer a reader's reaction. You supervise the process and grade the final draft.

• Students submit a draft and receive rubric-based AI feedback within minutes
• They revise once to address the most obvious issues, such as an unclear thesis
• Peers then review the revised draft using a short structured checklist
• Students write a brief response explaining what they will change and why
• The teacher grades the final version and reviews the revision notes

Training reviewers

Spend one class period modeling good peer feedback. Show a sample essay and demonstrate how to respond with specific, useful comments. Students learn quickly when they see the difference between vague praise and actionable observation.

Provide sentence starters for students who struggle, such as "I was confused when..." or "Your strongest evidence is..." These lower the barrier. Over time, most students stop needing them.

Grading the review process

Consider giving a small credit for thoughtful peer feedback and for revision responses. It signals that the process matters. Keep the scoring light so it does not become another grading burden.

Spot-check reviews rather than reading all of them. You will quickly see which pairs are engaged and which need a nudge. That is enough to keep the process honest.

Where AI fits and where it does not

AI feedback is best for consistent, rubric-based observations, which frees peers to respond to ideas and clarity. It should not replace the human conversation about meaning. Be transparent with students about the role each plays.

Watch for over-reliance. Encourage students to think critically about any feedback they receive, whether from a tool or a classmate. Judgment is the skill you are ultimately trying to build.