[dansmyers]

I'm a professor at a small college. I teach intro programming most semesters and we're now moving to using tools like Cursor with no restrictions in upper-level courses.

"How do students learn to code nowadays?" - I think about this pretty much all the time.

In my intro class, the two main goals are to learn about structured programming (using loops, functions, etc.) and build a mental model of how programs execute. Students should be able to look at a piece of code and reason through what it does. I've moved most of the traditional homework problems into class and lab time, so I can observe the students coding without using AI. The out-of-class projects are now bigger and more creative and include specific steps to teach students how to use AI collaboratively.

My upper-level students are now doing more ambitious and challenging projects. What we've seen is that AI moves the difficulty of programming away from remembering details of languages or frameworks, but rewards having a careful, structured development process:

- Thinking hard and chatting about the problem and the changes you need to implement before doing anything

- Keeping components encapsulated and thinking about interfaces

- Controlling the scope of your changes; current AIs work best at the function or class level

- Testing and validation

- Good manual debugging skills; you can't rely on AI to fix everything for you

- General system knowledge: networking, OS, data formats, databases

One of my key theories is that AI might lower the value of "computer science" as a standalone major, but will lead to a lot more coding across fields that currently don't use it. The intersection of "not a traditional engineer" and "can work with AI to solve problems with code" is going to be an emerging skill set that will change a lot of disciplines.

[NeutralCrane]

This is by far the most interesting insight in this thread

[ghaff]

I observe the course catalog at one not small college now has options for a lot of majors—many of which weren’t terribly computer-heavy historically.

[greenchair]

appreciate the insight