Survey courses in Victorian literature often enroll a hundred students or more, and each is expected to write about poems like "The Lady of Shalott" at a college level. Professors can rarely give every essay the individual attention they would like. The challenge is protecting the quality of feedback while working within the limits of time and teaching assistant support.

The first step is to design assignments that produce gradable evidence without producing unmanageable volume. A short, focused close reading of one stanza can show more about a student's skill than a long, general essay, and it takes a fraction of the time to evaluate. Shorter tasks also allow more frequent writing, which is where improvement actually happens.

When teaching assistants share the grading, calibration is essential. Have everyone score the same five essays independently, compare results, and discuss each disagreement until the group agrees on what each level looks like. This meeting takes an hour and prevents many of the grade appeals that would otherwise arrive at the end of term.

Matching feedback depth to assignment stakes

Not every assignment needs the same level of commentary. Low-stakes response papers can receive a score and one comment, while a major analytical essay merits detailed notes and possibly a conference. Communicating this plan to students in advance prevents the impression that lighter feedback means less care.

• Low-stakes weekly responses: rubric score plus one short comment
• Mid-stakes close readings: score plus two targeted suggestions
• Major essays: full rubric, margin comments, and an optional revision
• Exams: scored against a shared key with common-error notes
• Final portfolios: reflection-based grading focused on growth

Handling disciplinary expectations

College writing in literature has its own conventions, including thesis-driven argument, careful close reading, and attention to historical context. Many first-year and non-major students have never been taught these expectations explicitly. Spelling them out in the rubric, and modeling them in class, reduces frustration on both sides.

Victorian context deserves particular care, since students often either ignore it completely or overload their essays with generalizations about the period. Ask for specific, sourced connections, such as how contemporary ideas about women and domestic space inform a reading of the Lady's tower. Evaluating those connections is much easier when the rubric defines what counts as good contextual evidence.

Using technology responsibly at scale

AI-assisted grading can lighten the load by producing first-pass feedback aligned to your rubric, which instructors and assistants then review. It offers the greatest value in large courses, where consistency across dozens of graders is otherwise hard to maintain. It must be treated as a support for professional judgment, not a replacement for it.

Be transparent with students about how feedback is generated and reviewed, and follow your institution's policies on data and student work. Students respond well to honesty about the process, particularly when they see that a human is accountable for the final grade. Clear communication also protects you if a grade is questioned.

Closing the loop with students

Feedback in a large course is most effective when it leads to action. Offer a limited revision opportunity on one major essay, and require students to explain what changed. Even with hundreds of students, this policy encourages engagement without doubling your grading time.

Gather student input at the end of term about which forms of feedback helped most. Their answers often surprise instructors, and they can guide improvements to next year's assignments. Over several offerings, the course becomes both more efficient and more educational.