English departments are increasingly asked to consider AI grading tools, and a novel unit such as Breathing Lessons is a useful test case. The essays are long, interpretive, and rubric-driven, which exposes strengths and weaknesses quickly. A tool that handles literary analysis well will likely handle other writing tasks. A structured evaluation helps departments avoid choosing based on marketing alone.

The first question is whether the tool can use the department's own rubric. Tools that force teachers into a fixed template may not reflect local standards or course goals. The ability to import or build custom criteria with clear descriptors is essential. Without it, feedback may feel generic and misaligned.

The second question is the quality and specificity of the feedback. Comments that refer to the student's actual sentences and suggest concrete next steps are far more useful than general praise or criticism. During a trial, departments should read the generated comments carefully and compare them to what a skilled teacher would write. Specificity is a strong indicator of value.

Designing a Pilot That Reveals the Truth

A strong pilot uses a set of essays that teachers have already graded by hand, spanning a range of quality. Running the same essays through the tool allows direct comparison of scores and comments. Differences highlight where the tool is lenient, strict, or inconsistent. Several teachers should participate to capture varied perspectives.

• Use anonymous essays that teachers have already scored
• Compare tool scores to teacher scores across the full quality range
• Read comments for specificity, accuracy, and tone
• Test how the tool handles unusual or creative interpretations
• Gather teacher and student reactions after the pilot

Questions About Privacy and Policy

Student work is sensitive, and departments must understand how any tool handles data. Questions to ask include where data is stored, who can access it, how long it is retained, and whether it is used to train models. Compliance with relevant privacy requirements should be confirmed in writing. Administrators and technology staff should be part of the review.

Departments should also consider their policies on AI in assessment and communicate them to students and families. Being clear about how the tool is used, and that teachers review output, builds trust. Policies should cover appeals and corrections. Preparing this ahead of rollout prevents confusion.

Evaluating Workflow and Usability

A tool that produces good feedback but is cumbersome to use will not be adopted. Teachers should evaluate how easily they can upload essays, adjust rubrics, edit comments, and export results. Time savings should be measured in the pilot rather than assumed. Usability determines whether the tool fits into real classroom routines.

Support and training matter as well. A vendor that provides clear onboarding and responsive help makes adoption smoother. Departments can ask for references from similar schools. These details often decide whether a promising tool succeeds in practice.

Making the Decision and Planning Rollout

After the pilot, departments can weigh the evidence against their priorities, such as accuracy, feedback quality, privacy, and cost. A simple scoring matrix helps compare options. Including teachers who were skeptical at the start can strengthen the decision. A transparent process builds buy-in.

A phased rollout, beginning with a single unit or a few volunteer teachers, reduces risk. Collecting feedback and adjusting before expanding allows the department to refine its approach. Ongoing calibration against teacher scores keeps quality high. The goal is a tool that supports teachers and improves feedback for students.