Draft-and-revise workflows are widely recommended for teaching writing, but they are hard to sustain in a poetry course with many students. Teachers cannot comment extensively on every draft, and peer review without structure often produces vague praise. Combining peer review with AI-generated feedback can fill the gaps in both.

Peer review offers a human audience and teaches students to read critically. Reading a classmate's essay on a Wordsworth poem, for example, helps a student notice what makes an argument convincing. Unfortunately, untrained reviewers often say little more than that the essay is good or needs more detail.

AI feedback, by contrast, can be detailed and tied to a rubric but lacks the personal perspective of a fellow student. Used together, the two approaches complement each other. The AI provides structured, criteria-based observations, and peers add reactions from a reader's point of view.

Structure the Peer Review

Effective peer review requires clear guidance. Provide reviewers with specific questions tied to the rubric, such as whether the thesis makes an arguable claim and whether each quotation is explained. Structured questions produce more useful comments than open-ended requests for feedback.

• Give reviewers three or four rubric-based questions to answer
• Ask reviewers to highlight one strong sentence and one unclear one
• Require reviewers to suggest a specific next step for the writer
• Provide the AI feedback to writers before or after peer review
• Have writers summarize what they plan to change and why

Sequence the Feedback

The order matters. Some teachers prefer to share AI feedback first so students can address basic issues before peers read the draft. Others prefer peer review first, followed by AI feedback as a check against the rubric. Either sequence can work, and teachers can test both to see which fits their class.

Whatever the order, students should reflect on how they use the feedback. A short revision plan, listing the changes they will make and why, ensures they engage with the comments rather than ignoring them. This reflection also gives the teacher insight into the student's thinking.

Keep the Teacher in the Loop

The teacher's role shifts from line-by-line commentator to coach and final assessor. Reviewing the revision plans and a sample of the feedback ensures that the process is working and that students are not receiving misleading guidance. Teachers can step in when a student seems stuck or when AI feedback needs correction.

This approach also frees time for more meaningful interventions. Instead of writing the same comments on dozens of first drafts, the teacher can hold short conferences with students who need personalized help. The result is a more efficient and more effective use of teaching time.

Evaluating the Workflow

To see whether the combined workflow helps, compare final essay scores with those from earlier assignments that lacked structured feedback. Look for improvement in specific criteria, such as thesis strength or use of evidence. Student surveys can also reveal which parts of the process they found most useful.

Adjust the process based on what you learn. If peer review comments remain vague, add more specific questions or brief training. If students ignore the AI feedback, build in a requirement to respond to it. Small refinements over a term can make the workflow far more productive.