<?xml version="1.0" encoding="UTF-8"?><oembed><type>video</type><version>1.0</version><html>&lt;iframe src=&quot;https://www.loom.com/embed/eda3ae4652b84bc0a731c5fbc0ee6ca6&quot; frameborder=&quot;0&quot; width=&quot;1920&quot; height=&quot;1440&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>1440</height><width>1920</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>1440</thumbnail_height><thumbnail_width>1920</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/eda3ae4652b84bc0a731c5fbc0ee6ca6-5aab3bab482d98ca.gif</thumbnail_url><duration>3142.233</duration><title>Ethical AI Prompting for Better Lessons 🎯</title><description>I shared why AI prompt engineering fails in education most often as a clarity and generic output problem, not a language problem. I emphasized that ethics is not optional, covering transparency, data stewardship, and the risk of fluent but inaccurate outputs, and I cited the UNESCO 2024 AI teacher framework and a 2025 survey on teacher workload. I taught five prompting methods, including zero shot, role assignment, chain of thought, critic prompting, and constraints, with a suggested stacking order and live demos for persuasive writing. I requested that you try one method this week. I also invited you to join the AI literacy lab circle or book a consultation for the May cohort.</description></oembed>