LLM's: the backhoe and the bench-press

This is in response to a post at Brad DeLong's "Grasping Reality" blog, From ChatGPT back to clay & cuneiform: A start at rethinking pedagogy for the Age of "AI".

https://wiki.opensourceecology.org/wiki/File:Backhoe.png

He asks himself two questions about broad objectives as a teacher:

• What do I want my students to remember five years from now about this class?
• What do I want my students to know how to do after they have taken this class?

Those seem like absolutely the right questions.

In thinking concretely about his course in economic history, he presents his week-by-week themes and wonders about a weekly structure of three parts:

1. What is our question?
2. How would you go about discovering the best answer to it, at least to your satisfaction?
3. How would you then persuade somebody else that the answer you have come up with is the most likely answer?

He writes,

Could that serve as a scaffolding for education in the age of AI?

I think it could. By focusing on 'how would you discover?' and then 'how would you persuade?', we could avoid all of the traps involved in the overuse of LLMs.

This seems promising to me, though I suppose the first test would be to take items 2 and 3 and ask an LLM to do them.

My broader concerns about the impact of AIs on learning are rooted in how I view the role of memorization and practice. And the difference between short-term and long-term memory.