Writing-intensive courses at universities have grown in size, while expectations for individualized feedback have remained high. A professor with 150 students and a single teaching assistant cannot deliver the kind of detailed comments that smaller seminars allowed. Continuing the old approach in this new environment leads to delays, inconsistency, and exhaustion.

Nick Tasler's Your Year of Wonders argues that embracing change is how people continue to grow, and that principle applies directly to teaching in large classes. Professors who adapt their feedback methods to fit current conditions can maintain quality while preserving their own energy. Adaptation is not a concession; it is a professional skill.

The first adjustment is to be selective about what feedback is for. Not every paper needs line-by-line commentary, and students often benefit more from a few high-priority observations than from a flood of marginal notes. Deciding in advance what each assignment is meant to teach helps focus the comments.

Prioritizing Feedback That Changes Writing

Research and experience both suggest that students act on a small number of clear, actionable comments. A note that a paper lacks a defensible thesis, along with a suggestion for how to revise it, is more useful than ten notes about sentence-level style. Professors can design rubrics that make these priorities explicit.

• Limit written comments to the top two or three issues per paper
• Use rubric descriptors to explain scores without rewriting them each time
• Provide class-wide feedback on common problems in a short video or handout
• Train teaching assistants with calibration sessions on sample papers
• Offer revision opportunities so feedback leads to actual improvement

Calibrating Graders for Consistency

When multiple graders are involved, inconsistency becomes a fairness issue. Calibration sessions, in which graders score the same papers and discuss differences, help align interpretations of the rubric. Repeating these sessions midway through the term catches drift before it affects large numbers of students.

AI-assisted grading can provide a consistent first read across hundreds of papers, which graders can then review and refine. This does not remove human judgment, but it can reduce variation in how the same rubric criteria are applied. Professors can compare AI-generated scores with their own samples to check alignment.

Using Technology Thoughtfully

Technology is most useful when it handles repetitive tasks and leaves interpretive work to instructors. Automated rubric scoring, comment drafting, and score exports can save hours per assignment. The professor's time is better spent on holistic review and on responding to students whose writing needs closer attention.

Be transparent with students about how feedback is generated and reviewed. Explaining that an instructor reviews every score builds confidence, and it clarifies that the rubric, not the software, defines expectations. Students tend to accept feedback more readily when they understand how it was produced.

Sustaining the Approach Across Semesters

Improvements to large-class feedback compound over time. Reusable rubrics, comment banks, and grading workflows reduce setup for each new term. Professors who invest in these assets early often find that teaching writing at scale becomes less draining each year.

Collect brief student feedback on how useful the comments were and adjust accordingly. Student input can reveal which types of feedback lead to better revisions and which are overlooked. A cycle of reflection and adjustment keeps the course responsive to the people it serves.