A generic essay about Ordinary People is easy for a chatbot to produce, and many teachers worry about how to tell authentic student work from generated text. The novel is widely discussed online, so the broad themes of grief, family silence, and recovery appear in countless summaries. Relying on detection software alone is unreliable and can lead to false accusations. A better strategy is to design assignments and grading practices that make real engagement visible.

Process-based assessment collects evidence of thinking at several stages rather than only at the end. Students might submit a thesis proposal, annotated passages, a rough draft, and a short reflection on their revision. Each piece reveals how the final essay developed. A student who understands the novel can usually discuss these choices in detail.

Prompts can also be tailored to class-specific material. Asking students to analyze a scene discussed in a particular lesson, or to connect the novel to an in-class activity, makes generic responses less useful. Requiring page references and specific details from chapters adds another layer of accountability. These design choices reward students who read and attended.

Collect Evidence of Authentic Work

Short in-class writing samples provide a baseline for each student's voice and level. When a take-home essay differs sharply from this baseline, a conversation is warranted. The goal of the conversation is understanding, not accusation. Asking the student to explain their thesis and evidence often clarifies the situation quickly.

• Require a proposal or outline with the chosen thesis and scenes
• Collect annotated pages showing the student's notes on key passages
• Use brief in-class writing to establish a baseline of voice and skill
• Hold short conferences where students explain their argument aloud
• Ask for a revision reflection describing specific changes and reasons

Be Clear About Acceptable AI Use

Ambiguity breeds problems. Teachers should specify whether students may use AI tools for brainstorming, outlining, grammar checking, or not at all, and explain the reasoning. A clear policy stated in the assignment sheet prevents misunderstandings. Students who know the boundaries are more likely to respect them.

If limited use is permitted, ask students to document how they used the tool and what they changed afterward. This turns AI use into a visible part of the process rather than a hidden shortcut. It also encourages critical evaluation of generated suggestions. Many students find that generic output needs substantial revision to meet the rubric.

Grade for Specificity and Insight

Generated essays tend to be fluent but generic, offering broad statements without precise textual detail. Rubrics that reward specific evidence, original interpretation, and accurate references naturally favor authentic work. A row for specificity can explicitly score the use of particular scenes and language. This discourages reliance on generic content.

Feedback can reinforce this expectation. Comments such as "which scene shows this?" or "what exact words support your claim?" push students to engage with the text. Over time, they learn that detail matters. This builds skills that no tool can replace.

Use Tools to Support, Not Police

Teachers can use AI-assisted grading tools to apply rubrics consistently and to flag essays that lack specific evidence, which often correlates with generic writing. These flags are prompts for review, not proof of misconduct. Human judgment remains essential in interpreting them. The emphasis stays on teaching and assessment rather than surveillance.

Building trust with students also matters. When assignments feel meaningful and feedback is helpful, students have less reason to outsource their thinking. A classroom culture that values process over product reduces temptation. Thoughtful design is more effective than any detection method.