Discussion about supervision will be handy, especially since students will be learning how to supervision in their clinicals.

Agree to the points below

I think it is quite helpful!

AI is just fascinating and I am enjoying the learning

We need to be smart consumers of AI when it comes to integrating student learning.

We need to model solid use of AI, so that our students don’t fall into bad habits.

We need future clinicians who can use AI to complement their practice, not as their go-to tools.

Trusting AI is not losing control. The TRUST method (Transparency, Relevance, User Control, Safety, Tracking) helps me evaluate tools before using them. Independent AI needs weekly oversight. I am still responsible.

I will evaluate one tool using TRUST this week. I will set a 15-minute weekly reminder to review interactions and log errors. I will complete my AI Growth Plan.

I learned that AI is not just for quick tasks like creating quizzes. It can also be a thinking partner for complex, long-term projects, such as redesigning a simulation or a final project. The CRAFT method (Context, Request, Audience, Format, and Tone) gave me a clear structure to communicate better with AI. I also understood that evaluating AI outputs is key: I need to check technical accuracy, appropriateness for my students, and the professional standards of my field. If I wouldn't put my name on the result, it's not ready.

This week I will choose a teaching challenge I've been… >>>

AI is an assistant, not a replacement. The three questions (harm? my expertise? routine?) help me decide what to delegate. If I spend more time fixing than creating, it's not working.

This week I'll delegate one routine, low-risk task (like a vocabulary list). Safety decisions, grades, and empathetic feedback stay with me. I'll measure whether I actually save time without losing quality.