World literature courses ask students to read works from traditions they may never have encountered, such as Njegoš's Gorski vijenac, and then write about them with confidence. Grading those essays is harder than grading a paper on a canonical American novel, because the instructor must judge interpretation, historical accuracy, and translation awareness at the same time. An AI grading tool is only worth adopting if it can support that complexity. The right questions to ask before choosing one are practical and specific.

First, can the tool grade against your own rubric instead of a generic one? A rubric written for your unit on epic drama will weigh evidence and context differently from a standard five-paragraph essay checklist. Tools that force you into their template will flatten the distinctions you care about. Look for the ability to enter your criteria, level descriptors, and point values directly.

Second, does the feedback reference the student's actual writing? Comments that could apply to any essay are of little use when a student has misread a scene or misdated a historical event. Good feedback quotes or points to specific sentences and explains what to change. You can test this by running two or three sample essays and checking whether the comments would still make sense if you swapped the papers.

Questions to ask during an evaluation

Ask how the tool handles essays that touch on sensitive history, since Gorski vijenac deals with violence and contested memory. The software should assess the quality of argument and evidence without inserting its own moral commentary or refusing to engage. Ask also about transparency, meaning whether you can see why a score was assigned and override it easily. Instructors who cannot inspect the reasoning will not trust the result.

• Does it apply your rubric and point values exactly as written?
• Does the feedback cite specific parts of each student's essay?
• Can you review, edit, and override every score and comment?
• How does it treat essays on violent or contested historical themes?
• What happens to student data, and who can access it?

Matching the tool to your course size

A seminar of twelve students has different needs than a survey course of two hundred. In a small class, you may want the tool mainly for drafting first-pass comments that you personalize heavily. In a large lecture, consistency across graders and sections becomes the primary concern, and rubric-based scoring helps keep teaching assistants aligned. Define which problem you are trying to solve before comparing products.

Consider also how the tool fits your current workflow, including learning management systems and the way students submit work. A tool that requires extensive reformatting will cost you the time it saves. Pilot it on one assignment, such as a short response paper on the opening scenes, before committing to a whole semester. A small trial reveals friction that a demonstration never will.

Measuring whether it is working

After a pilot, compare the tool's scores with your own on a sample of essays and note where they diverge. Large gaps on particular criteria suggest that your rubric descriptors need sharpening or that the tool misreads that skill. Track grading time as well, since efficiency gains should be measurable and not assumed. Ask students whether the feedback was clear enough to guide their revisions.

The goal is not to replace professional judgment but to give instructors more room to use it. When first-pass scoring and comment drafting are handled consistently, you can spend your attention on the students who need a conversation. In a literature course, that attention is best spent on the interpretive risks students take. A tool that protects that time is doing its job.