Questions teachers ask

It will. AI writes with the same confidence whether it is right or wrong: wrong dates, wrong maths, invented facts, quiz questions with two right answers, readings harder than you asked for.

That is why checking is part of the method, not an extra. Session 8 is entirely about quality assurance, and we build a checklist you can run on everything. You are the editor, and you make the final call.

A first draft usually isn't. The program teaches you how to ask so the draft is closer to what you need, and how to find and fix what is left.

We work from your own units, texts and curriculum, so the result fits your class and not an average one.

Generic requests get generic results. When you give the AI your students, your level, your topic and your examples, the output is far more specific, and then you edit it in your own voice. Most of the skill is in the asking and the editing.

I can't promise a cheat-proof classroom, and nobody can. This program is about your preparation, not about policing students.

In session 10 we do talk about how you set expectations with students, and about task design, such as more work done in class or explained aloud, that makes it harder to hand a task to AI.

I wouldn't. These tools give a probability, not proof, and research has found they can wrongly flag human writing, especially by non-native English speakers. A detector score is a reason to have a conversation, not evidence of cheating.

Unedited AI output can read as flat and generic, which is one more reason we edit. Materials you have checked, edited and fitted to your class are your materials.

Some schools have rules about disclosing AI use, so check yours. And a worksheet with a wrong answer key is a problem whoever wrote it.