Survey courses in world literature or European modernity often include Lenz as an accessible example of nineteenth-century prose. When enrollment climbs into the hundreds, the writing assignment that follows can quickly overwhelm a professor and a small team of teaching assistants. The temptation is to reduce writing to nothing but multiple choice. A better answer is to redesign the assignment and workflow so that meaningful feedback remains possible.

Start by narrowing the task. A two-page response to a specific passage is far easier to grade than a six-page essay on a broad theme, and it can test the same core skills. For Lenz, a focused prompt on the opening landscape or the conversation with Kaufmann gives every student the same raw material and makes comparison between papers more reliable.

Next, make the rubric short and precise. Four criteria with clear descriptors are easier to apply consistently than a dozen overlapping ones, especially across multiple graders. Include a brief checklist that graders can use to confirm each criterion, and post it for students so they can self-assess before submitting.

Training Graders and Maintaining Consistency

Consistency is the largest risk in large courses, because a student's grade can depend on which teaching assistant read the paper. Hold a calibration meeting where everyone grades the same three sample essays independently and then compares scores. Discussing the gaps reveals different interpretations of the rubric and lets you resolve them before grading begins.

• Use a short rubric with four or five clearly described criteria
• Hold a calibration session with sample essays before grading
• Spot check a random sample from each grader's batch
• Keep a shared document of common problems and standard comments
• Set a firm turnaround time so students receive feedback while it still matters

Feedback That Scales

A comment bank of common issues can save hours without making feedback generic. Write short, specific notes for problems such as summary instead of analysis, quotations that are not explained, or claims that overstate the evidence, and then adapt them to each paper. Students value comments that refer to their own sentences, even when the underlying advice repeats.

Consider adding a short class-wide debrief after grading, summarizing the most common strengths and weaknesses and showing anonymized examples. This gives every student useful guidance and reduces the number of individual questions you will receive during office hours.

Where Technology Fits

AI grading assistants can provide a consistent first pass across every submission, applying the same rubric to all 150 papers. Instructors and teaching assistants can then review the output, adjust scores, and add personalized remarks where they matter most. This workflow reduces the variability that comes from different people reading at different times of day.

The key is to treat the tool as support for human judgment rather than a replacement for it. Spot checks, clear policies, and transparency with students about how feedback is generated build trust. Done well, the approach lets large courses offer the kind of writing feedback that was once limited to small seminars.