District leaders considering AI-assisted essay feedback often face a difficult question about where to begin. Launching across every course at once creates risk, while an unfocused pilot produces data no one can interpret. A single, well-defined unit offers a better test, and a classic drama unit like Tvrdica works well because the assignments are common, the standards are clear, and many schools already teach similar material. The pilot can then inform decisions about wider adoption.

Start by defining what success looks like before the pilot begins. Possible measures include the time teachers spend grading, the speed with which students receive feedback, the consistency of scores across sections, and teacher satisfaction with the quality of comments. Choose a small number of metrics and decide how you will collect them. Without this clarity, it is difficult to judge whether the pilot achieved anything.

Select participating teachers carefully. A mix of enthusiastic early adopters and cautious skeptics provides a more realistic picture than volunteers alone. Include teachers from different schools and grade levels so the results reflect the diversity of your district. Make sure each participant understands that the tool supports their judgment and does not replace it.

Designing the Pilot Unit

Use a shared assignment and rubric for the Tvrdica unit so that results can be compared across classrooms. A common prompt, such as an essay analyzing how Molière uses Harpagon to criticize greed, creates a consistent baseline. Teachers can still tailor instruction, but the final assessment should be similar. This makes it possible to evaluate the tool's effect on scoring consistency and turnaround time.

• Define two to four measurable success criteria before starting
• Select a diverse group of teachers across schools and grade levels
• Use a common assignment and rubric for the pilot unit
• Provide a short training session on reviewing and editing AI feedback
• Collect teacher and student feedback at the midpoint and the end

Addressing Concerns Early

Teachers, parents, and administrators will have legitimate questions about accuracy, privacy, and fairness. Address these directly, explaining how student data is handled, how teachers review all feedback before it reaches students, and how the district will monitor for bias. Transparent communication builds trust and reduces resistance. It also demonstrates that the district takes these concerns seriously.

Be honest about limitations as well. AI feedback may misread an unusual argument or give overly generic comments in some cases, which is why teacher review is essential. Collecting examples of both good and poor outputs during the pilot gives the district a realistic understanding. This evidence helps set appropriate guidelines for future use.

Evaluating Results and Scaling

At the end of the pilot, compare your measures with the baseline, looking at both quantitative data and qualitative feedback. Did teachers save meaningful time, and did they reinvest it in instruction? Did students receive feedback faster, and did their revisions improve? The answers should guide decisions about expansion.

If the results are positive, scale gradually, adding additional units, grade levels, or schools in stages. Share lessons from the pilot teachers with new participants so they can benefit from practical experience. Continue to collect data and refine guidelines as adoption grows. A measured approach protects the integrity of instruction while allowing the district to capture the benefits of efficient, consistent feedback.