AI video coaching for teachers
Video coaching for teachers has worked as a development tool for years: the teacher records a class, a mentor reviews it, and they debrief on what was observed. It is powerful — but expensive. One human coaching session per teacher per month is about the most an institution can sustain.
AI changes that ceiling. The first pass of analysis is done by a platform like TeachView in minutes: talk time, question types, moments of good practice, activity distribution, aligned with the institution’s protocol (CLASS, Danielson, MBE-Chile, COPUS, or a custom one). The human mentor still matters — but now they intervene on evidence, not on memory.
That changes the economics of coaching. Every teacher can get feedback after every class, not only after the monthly observation. The institution gets continuous evidence of classroom practice, not only termly snapshots. And the teacher stays in control: the recording is theirs, and no one else sees it without explicit permission.
This is a placeholder landing page. The full post — with cases, sample protocols and notes on privacy — will publish in the coming weeks.