Jack Davis's play No Sugar produces some of the most layered student writing in a senior English unit, and that is exactly why grading it is slow. Students have to handle historical context, dramatic technique, and a set of characters who respond to dispossession in very different ways. A teacher with five classes can easily face 120 essays that each need real engagement. Speeding up the process starts with admitting that most of the delay comes from repeated comments, not from reading itself.

When you track your own marking habits for one class set, a pattern usually appears quickly. You write some version of the same note thirty times, such as asking a student to connect a quotation to the argument or to explain how a stage direction shapes meaning. Each of those notes takes a minute or two to phrase well. Multiply that across a class and the hours disappear into retyping advice rather than diagnosing what each writer actually needs next.

AI grading tools help most when they take over that repetition while the teacher keeps control of the judgment. A tool that reads an essay against your rubric can draft criterion-level comments, flag missing evidence, and suggest a first-pass score for you to confirm or change. You still decide what counts as a convincing reading of the Millimurra family's experience at the Settlement. The software simply gets you to that decision faster, with a draft already on the page.

Start With a Rubric Built for the Play

Generic essay rubrics produce generic comments, and No Sugar deserves better. A strong rubric names the things you actually want to see, such as accurate use of historical context, close reading of dialogue, and awareness that Davis wrote as a Noongar playwright for a stage audience. Writing those expectations out in plain language also makes any AI-assisted feedback far more precise. The tool can only measure what the rubric describes, so vague criteria lead to vague output.

• Write four or five criteria tied to the play, not to essays in general
• Describe what a strong, developing, and weak response looks like for each one
• Include a criterion for how well students use textual evidence from specific scenes
• Add one line about respectful, accurate language when discussing Aboriginal history
• Keep a bank of your own sample comments so the tool matches your voice

Sort Essays Before You Read Them Closely

A quick first pass saves more time than most teachers expect. Group essays by obvious needs: those with no clear argument, those that retell the plot, and those that already analyze well. Each group needs a different kind of comment, so you can write one strong response for the plot-retelling group and adapt it slightly instead of starting from nothing every time.

AI can perform that sort in seconds by checking each essay against your criteria and surfacing the weakest area. You then spend your attention where it matters, such as the student who makes a sharp point about the Matron's rations but never explains it. The goal is not to read less. It is to read with a clear question about what each student needs, which makes every minute of attention count.

Keep Your Judgment on the Sensitive Parts

No Sugar deals with removal, forced labor, and institutional cruelty, and student responses can touch painful ground. A tool can check structure and evidence, but it cannot decide whether a student has treated that history with the right care. Reserve your own reading for sections where tone, empathy, and historical accuracy are at stake.

A practical split works well: let the software handle paragraph structure, quotation use, and clarity, while you review how students describe the people and events. If a student writes something careless about Aboriginal people, that is a teaching moment you want to handle personally. Automation protects your time for exactly those conversations rather than replacing them.

Build a Repeatable Grading Routine

Speed comes from routine, and a unit like this one benefits from a consistent process across every essay. Many teachers settle on a sequence: upload the set, review the draft feedback against the rubric, adjust scores on borderline papers, and add one personal comment per student. That final comment is where your relationship with the writer shows up, and it is often the line students remember.

Over a term, this routine also gives you better data. You can see which criteria the whole class struggles with, such as linking evidence to an argument, and plan a mini-lesson before the next essay. Grading stops being only a judgment of finished work and becomes a steady source of information about what to teach next.