Peer review has long been a staple of writing instruction, and AI feedback is now becoming common. Teachers working through Unterm Rad essays often wonder whether to use one, the other, or both. The most effective approach treats them as complementary stages in a revision process rather than competing options.

Peer review gives students an authentic audience and teaches them to evaluate writing critically. However, classmates are not experts on Hesse, and their comments can be vague or inaccurate. AI feedback offers quick, rubric-aligned observations but lacks the human reaction of a real reader.

Sequencing them thoughtfully allows each to do what it does best. Peers can respond to clarity and persuasiveness from a reader's perspective, while AI checks the draft against specific criteria. The teacher then focuses final attention on the interpretive depth of the argument.

A workable sequence for the unit

Start with a draft of the essay, then run a structured peer review focused on thesis and evidence. After revising, students submit the draft for AI feedback that checks rubric criteria such as explanation of quotations and counterarguments. Finally, the teacher reads the improved draft, with fewer basic problems to address.

• Students draft an essay about Hans, Heilner, or the Rector using a shared rubric
• Partners complete a guided peer review focused on thesis and evidence
• Students revise and submit the draft for rubric-based AI feedback
• Students write a short note explaining which suggestions they used and why
• The teacher grades the final draft and comments on interpretation

Making peer review productive

Unstructured peer review often produces comments like "good job" or "fix your grammar." Provide a short guide with specific questions, such as "What is the writer's claim about Hans, and do you agree?" and "Which quotation is most convincing?" Specific questions produce specific answers.

Train students briefly by modeling a good review of an anonymous paragraph. Show how to praise something concrete and suggest one improvement. Even ten minutes of modeling raises the quality of peer comments noticeably.

Where AI feedback adds value

AI tools like GraideMind can check each draft against the rubric and point to missing elements, such as quotations without explanation or a thesis that lacks a clear position. This feedback is consistent and fast, which makes multiple rounds of revision realistic. Students receive guidance in minutes rather than days.

Remind students that suggestions are not commands. They should consider each comment, decide whether it fits their argument, and be prepared to explain their choices. This keeps ownership with the writer and prevents passive acceptance of every suggestion.

Evaluating the process, not just the product

Collect the reflection notes in which students describe how they responded to each form of feedback. These notes reveal who is revising thoughtfully and who is just clicking through. They also show which comments proved most useful, helping you refine your approach.

Consider awarding a small portion of the grade for evidence of revision. That signals that improvement matters as much as the first attempt. Over time, students come to see feedback as part of writing rather than an afterthought.