Peer review has a reputation for being hit or miss, and anyone who has run a workshop knows why. Students often lack the confidence to critique classmates or default to vague comments such as "good job" and "needs more details." On a novella like Chronicle of a Death Foretold, where interpretation matters and evidence can be scattered, unstructured peer review rarely produces the depth of feedback that drafts need.

AI feedback can fill part of that gap by giving every student a quick, rubric-aligned response before they meet with a peer. If the tool points out that a thesis is descriptive or that a quotation is not explained, the student arrives at the workshop with an informed sense of their own weaknesses. The peer conversation can then focus on ideas and clarity rather than basic issues that a first pass would have caught.

The combination also changes the role of the teacher. Instead of circulating anxiously and trying to give every group a bit of attention, you can spend your time with the students who need help most, guided by the AI report. Workshop days feel calmer, and the feedback students receive is more consistent because it draws on the same criteria from two different directions.

Structuring the Workshop

Start with a short warm-up in which students reread their thesis and highlight the strongest piece of evidence in their draft. Then let the AI feedback arrive, and ask each student to identify one comment they agree with and one they question. This step builds critical reading of the feedback itself, and it prevents students from treating automated suggestions as unquestionable commands.

• Each writer highlights their thesis and the two pieces of evidence they consider strongest.
• Partners read silently and write one sentence summarizing the argument they think the draft is making.
• Partners answer three focused questions about evidence, explanation, and organization.
• Writers compare the peer comments with the AI feedback and note where they agree.
• Each student sets a single revision goal before leaving class.

Training Students to Give Specific Comments

Give students sentence starters that force specificity, such as "I was confused when you wrote..." or "Your strongest quotation is... because..." These frames prevent the empty praise and vague criticism that so often derail peer review. Model a few good comments on a sample paragraph from the novella first, so students see what useful feedback sounds like before trying it themselves.

It also helps to assign roles. One partner might focus on thesis and argument, another on evidence, and a third on clarity and organization. Rotating roles across drafts gives everyone practice with each kind of feedback, and it means no single reader has to catch everything. Over time, students internalize the questions and begin asking them of their own drafts.

Evaluating the AI Feedback Critically

AI feedback is a starting point, not a final authority. Encourage students to test suggestions against the text: if the tool says a claim lacks support, does the student agree, and what passage might strengthen it? This habit protects against blindly accepting advice and reinforces that the writer remains the author with final responsibility for the essay.

Teachers should review the feedback that goes out, at least at first, to confirm it aligns with their expectations. A tool that reads your rubric and draws on your criteria should produce comments that feel familiar, but a quick check helps you catch anything that seems off. With time, you learn which kinds of comments are most reliable and where you want to add your own voice.

Measuring Whether It Works

The simplest way to see if the workshop is effective is to compare first drafts with final versions. Look for growth in thesis clarity, evidence quality, and depth of explanation, and note whether students made changes that reflect the feedback they received. If improvement is uneven, adjust the workshop by giving more time to the areas where students struggle most.

Students can also reflect briefly on what helped. A three-sentence note describing the most useful comment they received and how they used it encourages metacognition and provides you with information about what kinds of feedback land. Those reflections often reveal surprising details, such as peers being more influential than either the teacher or the technology on certain kinds of revision.