What happens when a student submits an essay that suddenly sounds like it was written by a 40-year-old lawyer instead of a 15-year-old sophomore?
For many educators, the first instinct is to run the assignment through an AI detection tool. But here’s the uncomfortable reality: most AI checkers still aren’t reliable enough to confidently accuse a student of cheating. False positives happen, advanced writers get flagged, and multilingual students can be unfairly targeted by algorithms that simply don’t understand the complexity of real classrooms.
In this episode, we explore one of the most challenging questions teachers face today: How do you handle AI-generated work when the tools meant to detect it aren’t trustworthy?
Instructional technology coach and former English teacher Brittanie Payne joins the conversation in an episode recorded live at TCEA 2026 to unpack why AI detection tools continue to struggle, what teachers should actually look for when evaluating student work, and why the future of assessment may require a major shift in mindset.
Instead of focusing only on the final product students submit, educators may need to start paying closer attention to the learning process behind the work. When teachers understand how students brainstorm, draft, revise, and reflect, AI suddenly becomes much easier to navigate.
We also discuss practical strategies teachers can use right now, including redesigning assignments, strengthening classroom relationships, and building AI literacy so students understand when and how these tools should be used responsibly.
AI isn’t going away anytime soon. The real question for educators is this: Are we grading the work students submit, or are we paying attention to how they actually learn?
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About Brittanie Payne
Brittanie Payne is the Instructional Coach for Technology for El Campo ISD in El Campo, Texas. She is a former high school ELA teacher. When she’s not at work, she likes spending time with her family and watching football. Go Chiefs!
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