Peer review is a staple of writing instruction, and it often disappoints. Students trade drafts, write "good job" in the margins, and correct a few commas. The exchange feels productive and changes very little.

A Heart of Darkness draft is a difficult thing to review. The novella is dense, and a peer who does not understand a passage cannot tell whether the writer has interpreted it well. Students hesitate to challenge a classmate's reading of Marlow when they are unsure of their own.

One way to improve the process is to give each draft a first round of feedback before peers ever see it. That first round can catch the basic issues, such as a missing thesis or an unexplained quotation, so that the peer conversation can be about ideas.

AI feedback fits well in that role. When the tool applies the teacher's rubric to a draft and returns comments on each criterion, the student arrives at peer review with a clearer sense of what to work on.

A workflow for the draft stage

The sequence matters. Students revise once on the basis of the initial feedback, then exchange the revised draft with a partner. The partner's job is to respond to the argument, not to repeat what the tool already said.

• Students submit a full draft against the class rubric
• Rubric-based AI feedback is generated and reviewed by the teacher
• Students revise using that feedback before any peer exchange
• Peers respond to the argument with two questions and one suggestion
• Students submit a final version with a short note on what they changed

Giving peers a focused job

Vague instructions produce vague reviews. Give peers a specific task, such as finding the sentence that states the thesis and saying whether they could disagree with it. Or ask them to mark the strongest and weakest use of evidence and explain why.

Questions are better than corrections. "What did you mean by this claim about Marlow's restraint?" prompts the writer to clarify. It also spares the reviewer from having to be an expert.

Keeping the teacher in control

AI-generated comments are drafts, and the teacher decides what students see. A tool like GraideMind provides rubric-aligned suggestions, and the teacher edits, removes, or adds to them before release. That review step keeps the feedback accurate and matched to the class.

It is also a chance to learn where the class is struggling. If the same comment appears on thirty drafts, you know the next mini-lesson.

Measuring whether it works

Compare the quality of final essays with and without the process. Look at whether theses are sharper, whether evidence is better integrated, and whether students can describe what they changed. Those signs matter more than the number of comments exchanged.

Ask students what they found useful. Their answers will tell you which parts of the workflow to keep, and which to trim for the next unit.