Dijkstra on Haskell and Java (2001)

I learned programming with Scheme, in that course, in 2004. I used, without noticing, many techniques I would later have relearn due to a "prolongued exposure to imperative programming". In my semester I used closures, functions as first class objects and lots of recursion.

The following three semesters I forgot all that, for I had to use C, C++ and Java. When, in the fourth semester, I had my AI course in Lisp, I used "let"s and loops for everything. In the middle of the semester, I remembered recursion, and how it made everything better (in Lisp). Later, by myself, I relearned closures, functions as first-class-objects and other stuff.

Having Scheme as an introductory language is good because it put students that came from a IT-technical high-school education equal to general high-school education students (that have never seen programming before). With the "real world" so drowned in imperative programming languages, there are few courses that can justify using a functional programming language. The things I know about FP, I know because I thought myself.

I'm not saying FP is better than imperative programming, is just that both should be (well) taught. (As some other paradigms too, I believe).

Some years ago my old uni, like MIT, changed from Scheme to Python. Python is my favourite programming language. But I'm still not happy with the decision.

I think CS students should instead start by learning basics of computer architecture at a high level and programming on a level close to the computer architecture that so far has turned out to be practical, the Von Neumann machine. This way they can understand the whole field better, if you never face the challenges of organizing computations in a computer without many existing layers of abstractions designed by other people, you will never understand the development of the field and how the disciplines of algorithms, operating systems, computer architecture, etc came to be the way they are, too many things are taken for granted by people who have only seen very high level languages.

People should know what the stack is, how function calls works, what is an assembler, what linked lists, binary trees, hash maps, ... are and why those had to be invented etc. I think something at the level of Go or C is best for that. Then I think a good moment comes for a course like SICP where people can learn how to take those pieces and build abstraction layers out of them.

1. Teach structure and organisation of programming. - Python is a good for this as it's object oriented, but has very little boilerplate and syntax getting in the way of learning. A few universities have done well using Haskell for this instead, and I think that's quite a good option, particular as it introduces types.

2. Teach from the perspective of how a computer works - C is probably the best one for this as it helps students understand how computers work at a more basic level, being closer to assembly and machine code. It also allows for memory to be thought of as a much more basic resource of the machine that users must manage.

Java would be good for teaching data structures and algorithms, but I don't think that should come until after an introductory class using one of the above methods.

> The idea behind a tiny and cheap computer for kids came in 2006, when Eben Upton, Rob Mullins, Jack Lang and Alan Mycroft, based at the University of Cambridge’s Computer Laboratory, became concerned about the year-on-year decline in the numbers and skills levels of the A Level students applying to read Computer Science. From a situation in the 1990s where most of the kids applying were coming to interview as experienced hobbyist programmers, the landscape in the 2000s was very different; a typical applicant might only have done a little web design.

I joined at about that time and found it noticeable that having experience with C++ and a few other languages marked me out as more advanced than many of the other students.

Also relevant to this discussion is that in the first term we learnt ML, a functional language. This was partially because of advantages in talking about algorithms in it, but also to put everyone on a level playing field and introduce something that even keener students won't have encountered before. We did Java later, which I found much less rewarding.