AI Grading Tools: Can AI Really Grade Student Work?

AI grading has been getting a lot of attention as a way to reduce teacher workload. But can it actually replace human judgment in assessing student work? I’ve been experimenting with several options.

For objective assessments like multiple choice, fill-in-the-blank, and simple short answer questions, AI grading is already quite effective. Tools built into learning management systems can handle this reliably. No controversy there.

For written work, it gets complicated. I tested several AI grading approaches on the same set of student essays and compared the results to my own grades and those of two colleagues.

The AI was reasonably good at assessing basic writing quality: grammar, organization, and clarity. It could identify well-structured arguments and flag disorganized ones. For these surface-level criteria, AI grades correlated well with human grades.

But it struggled with nuance. It couldn’t assess the originality of a student’s argument. It missed creative interpretations that didn’t follow standard essay conventions. It couldn’t tell when a student was making a sophisticated but subtle point that required context from class discussions. And it consistently rated formulaic, “safe” essays higher than risky, creative ones.

The equity issue also matters. AI grading tools can embed biases from their training data. Students who write in non-standard English dialects, who come from different cultural backgrounds, or who use unconventional rhetorical strategies may be systematically underscored.

My conclusion: AI grading is useful for the mechanical aspects of writing assessment and for providing rapid formative feedback. But it’s not ready to replace human judgment for summative assessment of complex work. Use it to save time on the routine stuff, but keep human eyes on the work that matters most.

What’s your experience with AI-assisted grading?