[Joel_Mckay]

The libglib-dev with gcc is very handy for toy projects, but only _after_ students try to write their own versions:

https://docs.gtk.org/glib/data-structures.html

It could be fun to do a lab summary after the lists and hashes introduction.

Have a wonderful day, =)

[uecker]

I absolutely I agree that learning to create you own abstractions is an incredible useful skill. It depends though. For a programming course this makes absolutely sense. But for applied problems in, say, biomedical engineering, this does not work. Many students know only a bit of Python, and then it is too much and "too inconvenient" to start from scratch in C. With Python they have a lot of things more easily available, so they make quick progress. This does not lead to good results though! For most of the Python projects, we end of throwing away the code later. Another problem is that students often do not know what they are doing, e.g. the use some statistical package or visualization package and get nicely looking results, but they do not know what it means and often it is entirely wrong. For machine learning projects it is even worse. So much nonsense and errors from copying other people Python code....

[Joel_Mckay]

Python like Basic abstracted far to many details away from students, and trying to convince people they need to know how a CPU works later is nearly impossible.

In general, digging deep enough down a stack, and it drops back into the gsl:

https://www.gnu.org/software/gsl/

Indeed, first month attrition rates for interns at some companies is over 46%. =3