The Hound of the Baskervilles turns up on syllabi for introductory literature, popular fiction, and Victorian and Edwardian survey courses. It is accessible enough for non-majors and rich enough to support serious analysis. In a lecture course with 150 students, that means a lot of essays.

Professors and graduate teaching assistants know the pattern. The first essays are read carefully, and by the fortieth the comments have shortened and the standards have drifted. Students in the second half of the pile often get less feedback than those at the top.

Grading a large literature class well requires a system. It means a shared rubric, a plan for TA calibration, and an efficient way to give meaningful feedback at volume. Below are approaches that hold up in real courses.

They apply whether you have two TAs or ten. Most of them cost an hour or two of setup and then save time all term. The largest benefit is that students in every section get graded against the same standard.

Build a Rubric That TAs Can Use

A rubric for a college essay on the novel should be short enough to use quickly and specific enough to reduce disagreement. Four or five criteria usually work. Include short descriptors for each level and a note on what earns the top mark.

• Argument: the thesis takes a position that goes beyond the obvious and guides the essay
• Evidence: close reading of specific passages, with attention to language and form
• Analysis: explanation of how the evidence supports the argument, including a sense of Victorian or Edwardian context where relevant
• Engagement with sources: if required, accurate and purposeful use of secondary material
• Writing: clarity, structure, and command of academic style

Calibrate the Team

Before grading begins, have every TA score the same three essays and meet to compare. The disagreements are informative, since they show where the rubric is unclear. Do a short recalibration halfway through, when drift is most likely.

Give TAs a bank of comment stems for common issues, tied to the rubric criteria. Encourage them to personalize each one with a detail from the student's paper. It saves time without producing feedback that feels canned.

Give Students Something Actionable

At scale, students still need to know what to do next. Limit each essay's feedback to the two or three most important things, with an example of how to improve. Long lists of corrections tend to be ignored.

Consider offering an optional revision for the essay. Students who revise learn more, and the revisions show you whether the feedback landed. That can be feasible if the first round of feedback is quick.

Where AI Feedback Helps in Large Courses

In large courses, AI feedback tools can provide a first layer of criteria-based comments for every essay, giving each student meaningful notes even when TA time is limited. GraideMind applies your rubric and drafts feedback that instructors and TAs can review and adjust before release. Courses using this approach can spend TA hours on borderline cases and conferences instead of routine comments.

Whatever the tool, the final grade decision should stay with the instructor. Sample AI-assisted feedback against TA or instructor reads early in the term, and adjust the rubric wording if they diverge. Trust in the process builds when students and staff see that it is checked.