AI in STEM Education

I am studying the book "Dynamics of the Atmosphere" by Zdunkowski and Bott and I have been using ChatGPT to help me do the exercises and verify results as well as confirming my understandings where there has been confusion.

I do not think this book can be read, the way I am doing, by a person untutored in Vector Analysis and Fluid Mechanics, at least at the undergraduate level.

So, there is a need for undergraduate education but the format can change: more problem-solving by the students and fewer derivation on the blackboard by the professor since ChatGPT could display the derivation.

I think the role of Professor now becomes more like that of an Athletic Coach, trying to get the best out of the students.  At the same time, the students must understand that doing and learning the exercises are akin to performing physical exercises of athletes, building brain-muscle, as it were.  In this approach, no marks would be given to exercises.

So how do we evaluate the students?  I suggest two things, team projects and individual thesis (for each course). 

Team projects have been a staple of undergraduate education here in US for decades, preparing students for corporate enterprise life, in Architecture, Computer Science, Mechanical Engineering...

With the advent of AI, some problems that were graduate research level, can now be tackled by undergraduate students since AI can supply the background for them.

The role of professor in both cases would be guidance as well as validating the AI output (or teaching students how to validate that output).

The interesting thing area would be when both approaches are directed at creating physical systems, say a new aerometry instrument, or a chaotic (in the sense of Dynamical Systems) opto-electronic system that generates colors and hues.  LLMs can, potentially, makes suggestions but their heavily text-based algorithms could not generate a design...students must use their brains to so, under the supervision of their Tutor-Professor.