“Two school days. That’s all it took. In 2024, I chaperoned field trips two days in a row, for two different grade levels, and came back to roughly 450 ungraded assignments. I knew what to do, I’ve done it before, mark them credit or no credit and move on. Students get something out of that. They did the practice. But if any of them were practicing it wrong, nobody catches it, nobody tells them, and the misunderstanding rides along into the next unit. That pile of work led me to build an AI grading assistant. And this past April, I removed its most automated feature: the one that could return an AI-generated grade and comment to a student before I had reviewed it. Building that feature was easy to justify. Removing it taught me which part of grading a teacher can’t hand off. Most of what students turn in to me isn’t a clean essay. I teach engineering, and my students submit designs, schematics, code, and photos of physical work. That’s part of why many teachers I know still don’t grade with AI. They’ll use it to scaffold a unit or soften an email to a parent, but grading with it usually means pasting work into a chatbot one assignment at a time, which is so slow I can grade it faster myself. So, I built my own tool. I teach mechatronics, and if mechatronics teaches you anything, it’s that efficiency matters. You optimize the system and eliminate friction. I brought that mindset to the product I built, and the logical endpoint was auto-return. The AI could evaluate the work, draft the grade and comment, and send it back to the student without another click from me, late submissions included. I had spent hours tuning it to grade against my assignment, handouts, instructions, and rubric. Then a student came up to me one day, happy about the encouraging comment on an assignment. The comment had motivated him to redo the work and resubmit it. When AI Takes Control The problem was that I didn’t write the comment. I hadn’t even seen it. If it had passed by my eyes and I’d confirmed it, edited it, or decided it belonged there, this would be a different story. But in that moment, the student thought the encouragement came from me, and I wasn’t actually in the exchange. Nothing about the feedback was inaccurate. That almost made it harder to explain. After more than two decades in a classroom, I couldn’t put words to what felt wrong. I just knew it did. The issue wasn’t whether AI could draft useful feedback. It could. The issue was whether a student should receive a teacher’s judgment when the teacher hadn’t made one. So, I removed auto-return, and the automatic grading of late work went with it. What replaced it is a review dashboard: the AI drafts every grade and comment against my rubric and lays it out in front of me. I can edit, override, reject, or return the feedback in one pass. It’s still fast. But now my eyes and my judgment touch every grade before a student sees it. That changed how I think about human review. It can’t mean glancing at a score and clicking approve. It must mean checking the student’s work against the rubric and owning the result. The software can propose a judgment. It cannot own one. Policy is starting to move the same way. New York City’s public school guidance now says AI must not replace educator decision-making, and other states are weighing rules on human review and student data. The rules will keep changing. The principle shouldn’t; a student’s grade needs a person who is accountable for it. When I walked one of my administrators through the tool, what he liked most wasn’t the time savings. It was that it requires a rubric. Teachers write rubrics for big projects, but the daily, low stakes work rarely gets one, and that’s exactly the work that gets marked credit or no credit and never comes back with feedback. The trade runs both ways: students get clearer expectations up front and comments on work that used to get a checkmark. He had two concerns, both fair. Parents and students should know when an AI-assisted tool is grading, so it belongs in the syllabus. And if a student contests a grade, the teacher should re-grade it by hand. We agreed the second should happen anyway, with or without AI. Humans make grading mistakes too. My students know I built the AI tool. What they care about isn’t the technology. It’s whether the feedback is fast, the rubric is clear, and the grade is fair. A few times the tool has docked points for work it missed, almost always because a screenshot cut off the edge of the page or the writing was too faint to read. Those students came up to me, I looked at the work, and I gave the points back. I want that. A grade should be something a student can question. What surprised me is that a student will challenge the AI long before he’ll challenge me. A kid will walk right up and say, “The AI got this wrong, I should have full credit.” That same kid won’t tell me, to my face, that I made the mistake and owe him ten points. Both of us can be wrong, but the machine is easier to push back on than the teacher, and that’s good for the student. The grade still passes through me. The draft between us just makes it easier to speak up. If a grading system makes students afraid to challenge the result, the system is wrong. AI Grading Advice If your school is wrestling with AI grading, start with the disclosure. Don’t say “AI may be used.” Say what that means: comments and grades are drafted by AI and reviewed by the teacher. Then answer the harder questions. Where does student work go? Is it stored, or used to train models? How secure is the platform, and has anyone independent reviewed it? We are teachers, not graders. We grade, yes, but we also sit in IEP meetings, call parents, design lessons, and try to notice the student who is quieter than usual. If a grading assistant hands me back the hours I spent marking daily work, and I spend them on better lessons and better feedback, everyone wins. But when a student asks, “Why did I get this grade?” the answer cannot be, “Because the system said so.” It has to come from me.
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