Four Quartets is the kind of text that students are tempted to outsource, since its abstraction makes it feel difficult to write about and chatbots produce confident-sounding essays on it in seconds. Teachers see the results: polished prose that gestures at time and eternity without engaging a single specific line. Proving that a paper was AI-generated is notoriously difficult, so a purely detective-based approach tends to fail. Better results come from designing assignments and grading practices that make genuine engagement visible.

Generic AI essays share recognizable features. They tend to make broad claims about themes, use evenly structured paragraphs, quote only the most famous passages, and avoid committing to risky interpretations. A rubric that rewards specific evidence, original analysis, and connections to class discussion naturally scores such essays lower, because they lack the particularity that real engagement produces. Strong criteria are therefore a first line of defense that does not depend on accusing anyone.

Assignment design offers the next layer of protection. Prompts that require students to analyze a passage discussed in a specific class session, reference their own annotations, or respond to a classmate's interpretation are much harder to answer with a generic tool. Process-based components, such as an outline, an annotated passage, or an in-class draft, create a record of student thinking that a last-minute AI essay cannot easily replicate.

Grading Practices That Reward Real Engagement

Grading with attention to specificity helps separate authentic work from generic text. Look for evidence that the student has actually read the poem closely, such as references to particular images, observations about sound or structure, or interpretations that reflect a distinctive point of view. Essays that remain at a high level of abstraction, however fluent, should score lower on criteria related to evidence and analysis.

• Require quotations from several different sections of the poem, not just the best known lines.
• Ask students to connect their argument to a specific classroom discussion or annotation exercise.
• Collect brief process materials such as outlines, drafts, or reflections along with the final essay.
• Use short in-class writing to establish a baseline of each student's voice and ability.
• Hold brief conferences where students explain their argument aloud.

Being Careful With Detection Tools

AI detection software has well-documented reliability problems, including false positives that disproportionately affect multilingual writers and students with formal writing styles. Relying on a detector's score as proof of misconduct risks unfairly accusing honest students. Most institutions advise treating such tools as, at most, one piece of evidence that prompts a conversation, never as a verdict that replaces human judgment and due process.

A more reliable approach is to talk with the student. Asking them to explain their argument, describe how they chose their evidence, or discuss a passage they cited quickly reveals whether they understand the work. These conversations are respectful, informative, and far more defensible than a software score. They also give students a chance to explain legitimate uses of tools, which can vary across courses.

Setting Clear AI Policies for Your Class

Ambiguity breeds violations. Students need to know whether AI may be used for brainstorming, outlining, grammar checking, or not at all, and the answer should be written in the syllabus and repeated on each assignment. Explaining the reasoning behind the policy, such as the importance of practicing close reading yourself, helps students understand that the rules serve their learning rather than merely restricting them.

When limited use is permitted, require students to disclose how they used the tool. A short note describing what they asked, what they accepted, and what they changed encourages transparency and gives you insight into their process. This approach acknowledges that AI is part of the writing landscape while preserving the expectation that the final argument belongs to the student.

Using AI Grading Responsibly Alongside Integrity Policies

Teachers who use AI to support grading should apply the same transparency they expect from students. Explain how feedback tools are used, what role the teacher plays in reviewing results, and how student data is protected. This consistency builds credibility and shows that the classroom approach to AI is thoughtful rather than hypocritical.

Rubric-based grading tools can also help identify essays lacking specific evidence, which is often a signal of generic or outsourced writing. Teachers can then follow up with a conversation or a revision opportunity. The aim is not to catch students but to maintain standards that make real learning the easiest path to a good grade.