Teaching The Trial in a survey course of modernism or European literature can mean a hundred or more papers per assignment. Kafka's ambiguity makes these papers slow to read because no two arguments look alike. Professors need a system that survives the volume.

The first step is deciding what level of feedback each paper needs. A first-year student writing on Kafka for the first time needs different guidance than a junior in a seminar. Treating every paper the same way wastes time on both ends.

Teaching assistants often carry much of the grading in large courses, which introduces another challenge. Two graders can read the same essay very differently. Without calibration, students in different sections end up with different standards.

A shared rubric and a set of anchor papers solve most of that. Before grading begins, everyone reads and scores the same three or four essays and discusses the differences. That hour of alignment prevents weeks of complaints later.

Design assignments that are gradable at scale

Long, open-ended papers on Kafka are intellectually rewarding but expensive to grade. Consider shorter assignments with clear structural requirements. A four-page argument with a defined thesis and specific quotation requirements is far easier to evaluate.

• Require a single-sentence thesis submitted before the full draft
• Limit the number of primary quotations so students choose carefully
• Ask for a brief methodological note on which reading approach they used
• Use a shared rubric with clear point ranges for each row
• Provide an annotated sample paper before the due date

Use technology to handle the first pass

AI grading and feedback tools are increasingly useful in this setting. They can apply a rubric to each paper and produce draft comments that identify missing evidence or unsupported claims. Professors then review, adjust, and add the higher-level commentary only they can provide.

The key is to stay in control of the final judgment. Use the tool for consistency and speed, but read enough papers yourself to catch what it misses. Kafka essays in particular can be quirky in ways that reward a human eye.

Give students a reason to read your comments

Students in large courses often ignore feedback because it arrives late and feels generic. Tie comments to the next assignment so they have an immediate use. A note that says to apply this fix in the next paper is more likely to be read.

Consider returning grades only after students have read the feedback and written a short response. Even two sentences on what they will change encourages reflection. It costs students little and improves the payoff of your grading time.

Protect your time for the papers that need it

Not every paper deserves the same investment. Spend extra time on borderline cases, on students who are struggling, and on standout essays worth discussing. A streamlined process for the rest frees you to do that.

The goal is not to grade less but to grade smarter. A workable system means you can return Kafka papers in a reasonable time while still saying something meaningful to each student. That balance is what large courses demand.