An overview of how teacher evaluation works, start to finish: the evaluation cycle (pre-conference, observation, evidence, feedback, summative rating), the frameworks behind it, how ratings are set, and what makes an evaluation fair and defensible.
The post-observation conference is where evaluation becomes growth. How to structure the conversation, the reflection questions to ask, and what to avoid.
Nobody trains you to evaluate teachers. The observation cycle, the conferences, the rookie mistakes, and how to keep up — everything the rubric doesn't tell you.
AI can cut a teacher evaluation in half, but which half? The watching (human judgment) must stay human; the writing (rubric translation) is what AI can safely do. Why that line is the whole question, and why the write-up tool you pick still matters.