The state of educational programming languages.
In the before time…
While some may mourn BASIC and Pascal, I think people’s estimation of these languages is blinded by nostalgia. Pascal, in particular, overstayed its welcome in the classroom. By the mid 90′s, you might as well have taught C in place of Pascal, for C had sufficiently matured that it was essentially Pascal with pointers, different syntax, and no silly distinction between “procedures” and functions. Moreover, by 2000, the only* easily available implementation of Pascal for students to run on their own computers was (and is) Free Pascal, which actually supports a much changed dialect of Pascal, the result of cross-pollination with Delphi. The added complexity was bad enough, but then the Pascal text books simply didn’t keep up, thereby compounding Pascal’s fate: if new programmers don’t learn the Pascal in actual use, they won’t continue to use Pascal once they’ve learned it, leaving the language stuck in a death spiral.
(*There are actually Pascal implementations other than Free Pascal still available, but they too all significantly diverge from the classic Pascal of classrooms.)
BASIC suffered from an even worse fracturing problem and was eventually wholly overtaken by Visual Basic, which came to be seen as the modern BASIC even though it bore only superficial resemblance to the BASIC of 1980′s nostalgia. Visual Basic saw decent up take in the classroom, but as Microsoft took VB from 3.0 to 6.0, the language got more and more complex until, finally, today’s VB.NET is an almost entirely pointless syntactical variant of C#, a language just as complex as Java and C++.
So it comes down to Ruby and Python. Many will say the choice between the two is just a matter of taste, but I feel Ruby’s latent Perl-isms makes Python obviously better suited for neophytes. However, despite Python’s exemplary cleanliness, it’s still a quite complicated thing from the neophyte’s perspective. There’s a reason O’Reilly’s Learning Python is 746 pages long, and I just don’t think learners should be confronted in any way with subject matter like:
- multiple inheritance
- ‘bound’ vs. ‘unbound’ methods
- old vs. “new” classes
- functions within functions
- list comprehensions
- operator overloading
- exception handling
- creating custom iterators
- internal dictionaries
- a complicated hierarchy of scope with (limited) closure
Of course any sensible introductory Python course will hold off on these topics or avoid them altogether, but simply trying to ignore features of a language has costs, as the complexities and corner cases of a system have a way of intruding into the more pristine areas. For one thing, a student might accidentally write syntax which the compiler interprets as a (successful or unsuccessful) attempt to use a feature the student isn’t even aware exists; the result is mysteriously misbehaving code or a mysterious error message from the compiler. Perhaps worse, learners of a language will not be shielded from features they don’t understand when using their most important learning resource, the internet. Lastly, while Python is certainly a one-way-to-do-it language in comparison to Perl, it still offers conveniences for expert users, conveniences that will only paralyze learners with distracting stylistic decisions.
So perhaps we’d do better starting learners with a language explicitly designed for education. Yes, I did start by saying that the now-dead learner’s languages died because no one wanted to do any actual programming in them, but the main problem there was that Pascal and BASIC grew into complicated languages: they didn’t start life as explicitly learners-only languages and so ended up stuck in a no-man’s land between ‘two-week intro to programming’ and ‘full application-programming tool’. However, there still remains the problem of learners wanting to bypass learning a tool they’re going to immediately drop, so an educational language has a tricky balancing act to perform: the language should be simple enough to be fully learned in one or two lessons so that students don’t complain about learning “all this stuff” they aren’t going to use…but not so simple that the language isn’t enough like a real language to help students understand their first real language…but not too much like a real language that anyone would want to actually use the thing for real work.
Outside the mainstream, we have more educational language options. The most notable among them are:
- Squeak (Smalltalk)
And here’s what’s wrong with these languages:
- Squeak, Scheme, and Haskell are real languages used by real programmers for real work. This is bad. Real means complex. Annoyingly complex in annoying ways. No matter how elegant in conception these languages may be at their core, their corners lurk with ugly realities, and you can’t assume that learners can’t see the corners or can just ignore them. For the learner, more corner cases means more possibilities to consider, more mental dead ends, more detritus to sift through to establish a clear picture. Sure, you could teach a relatively clean subset of Java, but the subset you teach will be scattered here and there in the 1200-page Java book your student picks up. Sure, you could teach Haskell while ignoring its convoluted syntactical conveniences, but the compiler’s warning messages won’t be so friendly to your student. Sure, you could stick to just one dialect of Scheme, but Dr. Scheme will confuse your student with a list of umpteen different dialects from which to choose. For learners, these 1200-page books, cryptic error messages, and fractured sets of dialects are frightening and discouraging.
- Alice and Scratch attempt to sidestep the syntax issue in a novel manner: rather than using text for code, the Alice and Scratch editors have users drag code fragments and fit them together like puzzle pieces: the pieces only fit together in syntactically proper ways, so syntax errors aren’t possible. I actually think this might be a great idea for training students in the syntax and semantics of real languages, such as Java. However, this does mean that the Alice and Scratch dev environments feature a lot more buttons than they otherwise would. More importantly, if these languages’ syntaxes were simple enough in the first place, the benefit of drag-and-drop editing would be negligible.
- Alice, Scratch, and Phogrom all suffer to one degree or another from the “naturalistic language fallacy“: by attempting to have their code read like English, they end up greatly complicating their languages and obscuring the underlying formality, thereby failing in an important regard to prep students for real languages. There’s a reason most English-speakers struggle to learn English grammar: it’s an awkward attempt to fit formal rules on a complex, organic system. Doing the opposite—massaging a formal system into English—doesn’t clarify anything, either. (The biggest offender in terms of naturalism is actually AppleScript, a language some misguidedly hold up as appropriate for learners. Like Dylan, AppleScript, is an example of Apple favoring apparent simplicity over actual simplicity; such bargains are sometimes worth it, and more often than not Apple finds the right balance, but the result with AppleScript is disastrous.)
- Explicitly educational languages present themselves as intertwined to a particular API: Logo is the language in which you do turtle graphics; Alice, Scratch, and Phogrom are languages in which you do simple 3D- or sprite-based graphics and sound. Simple graphics-oriented API’s are a great idea, especially for teaching programming to younger students, yet there’s something wrong when the API is presented as indistinct from the language proper. In real languages, everything useful aside from basic arithmetic and logic is punted into libraries, and this is how it should be. First, multi-module programming brings with it the essential concept of namespaces. Second, without the barrier between core and domain-specific functionality, the distinction gets blurred in students’ minds.
Here there be dragons
Some topics should simply be avoided in a learner’s first exposure to programming, whatever the language. These topics include:
1) Inheritance and other static-y object-oriented features
Java and C++ support OOP the way they do for the sake of compile-time checks and efficiency (relative to languages with dynamic object systems, at least). These features introduce a plethora of rules in those languages, the sum complexity of which distract from the essential ideas in OOP: encapsulation, polymorphism, and inheritance. In a dynamic language, these ideas can be conveyed by convention using regular functions and dictionaries: plain functions are used as constructors and methods; dictionaries are used as the objects; methods take the object as their first parameter; and constructors return a dictionary with the right instance and method members. For example, a method call ends up looking like:
obj.foo(obj, 3) // call the foo method of obj with an argument 3
This may be more verbose, but it’s explicitly constructed out of already existing mechanisms. Inheritance relationships would be ‘faked’ by simply giving one type all the same methods as another, e.g. A is a subtype of B because it has all the right fields and methods. Duck typing, essentially. A student introduced to OOP as a set of conventions rather than new language mechanisms has a better chance of seeing the point of the whole thing and so is less likely to fall into common newbie traps, such as using inheritance for the sake of using inheritance.
Shells seem to be problematic in programming education. For one thing, every shell tutorial I’ve ever seen outright fails to make clear the distinction between shell code and program invocations in the code. For example:
ls -a > foo
While “> foo” is part of Bash syntax, Bash doesn’t see “ls -a” as anything but a command it doesn’t recognize, so it looks for a program named “ls” in its search path, and it loads and executes ls, passing the string “-a” as the argument fed to the char* args parameter of main() of the ls process.
Got that? Well, if you don’t understand this, you don’t understand the first thing about shells. But it’s REALLY FREAKING HARD to start learners off by explaining all this. So we don’t explain it. Rather than really teaching Bash or other shells, we just give students a few example shell commands, wave our hands, and trust that students will eventually figure out what’s really going on. Few students catch on quickly, and many never do, including some that go on to program professionally.
The solution to this situation is to formally cover shell languages as topics in their own right rather than as incidental to instructing students in how to use a compiler. At the very least, then, shells should not be introduced at all until it’s time to give them proper treatment.
(Not only are shells conceptually tricky to explain, the complexity of Bash syntax distracts learners from the essential concepts. The long term solution is to replace Bash as the default shell with something with a proper expression-based syntax—something like Python or Ruby, perhaps—rather than a command-based syntax, even if it means some common tasks would be a bit more verbose to type. Bash is a horribly twisted pile of historical happenstance that is just no longer worth its few minor typing-efficiency advantages.)
3) OS concepts
Key pieces of every language’s standard library deal with operating system matters like files, processes, and threads. Like with shells, these are complicated subjects in their own right: by introducing these OS concepts intertwined with a language, you’re muddling the clear presentation of both.
a = new Hope()
Enough about how to do programming education wrong. What about getting it right? Well, I have a lot of opinions on that front too. So many, in fact, I created my own language, Pigeon. The design philosophy behind Pigeon can be summed up by a few slogans:
- Get in, get out. Pigeon is designed to be fully learnable in 3-4 hours. Once the student fully understands every rule of Pigeon, they should write trivial programs in it for maybe 4-8 days, and then they should move on to learning a real language (especially Python). Pigeon is simple enough that it would be ridiculous to offer a full term course devoted to it, even at a high school or middle school. (At the very least, you should be embarrassed to attend an institution that offers a programming course with Pigeon in the title.)
- The explanation is the design. No other consideration is as important as bare simplicity—both syntactical and semantic—and simplicity is best measured by asking the question, ‘How must this be explained?’ The shorter and clearer the explanation, the simpler the language*. Currently, the Pigeon tutorial is just over 20 pages; I don’t foresee it ever growing past 30.
(*Of course, the simplest possible language would be a minimal notation for a Turing machine, e.g. Brainfuck. While that might actually have educational value, the goal here is to set learners on the path to learning real-world languages.)
Pigeon sticks to the features common to almost all modern languages:
- local and global variables
- branching and looping
- arrays and associative arrays
- modularization across files
(Global variables and recursion are not themselves essential at this point in the learner’s education, but they help establish the concept of local scope.)
The Pigeon program is a bare-bones text-editor window with a sub-window for printing standard output. Clicking ‘Run’ translates the code currently in the text-editor window into a Python module and then executes it. This is all done in about 1,000 SLOC using Python 2.5 with wxWidgets.
Currently, the only output accessible in Pigeon is the standard output window, and the only input is a bare bones pop-up dialog. As explained above, the decision to omit file handling is deliberate. However, one thing I would like to add is a simple interface to wxWidgets’s canvas to allow learners to play with simple 2D drawing. If you’re interested in contributing code to the project, that—or some other kind of simplified input/output mechanism—would be a good place to start.
Another big way to help the project is to concoct simple programming exercises, as I’ve neglected this important area.
If you’d like to contribute, ask for project member status in the comments here so you can edit the wiki. (You must have a gmail account for this.
Learn more about Pigeon:
The current Pigeon download is not usable, so don’t bother with it yet. Something apparently got buggered when I packaged the zip together (hey, it worked on my machine!). I’m putting off a fix until I get the time to add cross-platform filepath support (I developed on Windows without bothering about Unix) and also the time to update the language to match the documentation (I’ve neglected the code since I posted 0.1 in October, for I’ve been focusing on writing docs instead, over which time I changed my mind about a few things). Aside from those few things, I’m sure some things in the code will look hideous from the perspective of a three month hiatus and will demand refactoring. I also haven’t gotten around to putting my svn repository on Google Code, so that will be the first thing I do when I tie up these loose ends sometime this February.