When you're on top of the world, it's the perfect time to start kicking the little people who lifted you up. At least, that's the only conclusion I can draw from Bret Victor's newest post on teaching code. After he did his presentation on "Inventing on Principle" a while back, the tech community went nuts for Victor's (admittedly impressive) visualization work and approach to live programming. This admiration culminated in Khan Academy's computer science curriculum, which integrates a live Processing environment very similar to Victor's demos. In response, he's written a long post bashing the crap out of it.
Instead, he has a plan to redesign programming itself in a new, education- oriented direction. I'm generally a fan of Victor's presentation work (his touch-based animation UX is phenomenal), but I find that his ideas for teaching tend to be impractical when they're examined closely, and I suspect that's the case here. I don't think it's a coincidence that Victor doesn't seem to spend a lot of time asking if anyone else has solved these problems. A little research should have turned up that someone already wrote the language he's proposing: Scratch.
Scratch isn't terribly pretty--it's designed for kids, and it shows--but it provides almost everything Victor claims he wants. Variables are provided in context, with an instant visual environment that lets users examine routines at any time. The syntax is all drag-and-drop, with clear indications of what is nested where, and there's a stepping debug mode that visually walks through the code and provides output for any variables in use. And as much as Victor wants to push the comparison to "pushing paint," Scratch's sprite-based palette is probably as good as that'll get for programming. That no mainstream programming languages have followed its lead doesn't necessarily indicate anything, but should at least give Victor pause.
In his essay, however, Scratch is nowhere to be found. Victor draws on four other programming paradigms to critique Processing: Logo, Smalltalk, Hypercard, and Rocky's Boots. To say that these references are dated is, perhaps, the least of their sins (although it does feel like Victor's research consisted of "stuff I remember from when I was a kid"). The problem is that they feel like four random things he likes, instead of coherent options for how to structure a learning program. They couldn't possibly be farther from each other, which suggests that these lessons are not easy to integrate. Moreover, using Logo as a contrast to Processing is ironic, since the latter's drawing instructions are strikingly similar (I typically use the Logo turtle to introduce people to canvas graphics). And in Smalltalk's case, the syntax he's applauding is deceptively complicated for beginners (even I find the message rules a little confusing).
Meanwhile, where are the examples that aren't twenty years old? The field hasn't stood still since the Apple IIGS, but you wouldn't know it from Victor's essay. Scratch is the most well-known educational programming environment, but there's no shortage of others, from the game-oriented (Kodu, Game Maker) to actual games (The Incredible Machine, SpaceChem). Where's the mention of the vibrant mod community (UnrealScript is many a coder's first language, and I've had several students whose introduction to coding was writing Lua scripts for World of Warcraft)? Like his Braid-inspired live coding demonstration, Victor's essay gives the impression that he's proposing some incredible innovation only by ignoring entire industries working on and around these problems. It's unclear whether he thinks they're not worth examining, or if he just can't be bothered to use Google.
There's also a question of whether these essays solve problems for anyone but Bret Victor. His obsession with visual programming and feedback is all well and good, but it ignores the large class of non-visual problems and learning styles that exist. As a result, it's nearly all untested, as far as I can tell, whereas its polar opposite (Zed Shaw's Learn Code the Hard Way) has a huge stream of actual users offering feedback and experience.
Let me clarify, in case it seems like I'm simply blaming Victor for failing to completely reinvent computing in his spare time. These essays repeatedly return to visualization as the method of feedback: visualization of time, visualization of data, and code that itself performs visualization. Unfortunately, there's an entire field of programming where a graphical representation is either impossible or misleading (how much of web programming is just pushing strings around, after all?).
Frankly, in actual programming, it's counterproductive to try to examine every value by stepping through the code: if I reach that point, I've already failed all other approaches. My goal when teaching is explicitly not for students to try to predict every value, but to think of programming as designing a process that will be fed values. In this, it's similar to this Quora answer on what it's like to be an advanced mathematician:
Your intuitive thinking about a problem is productive and usefully structured, wasting little time on being aimlessly puzzled. For example, when answering a question about a high-dimensional space (e.g., whether a certain kind of rotation of a five-dimensional object has a "fixed point" which does not move during the rotation), you do not spend much time straining to visualize those things that do not have obvious analogues in two and three dimensions. (Violating this principle is a huge source of frustration for beginning maths students who don't know that they shouldn't be straining to visualize things for which they don't seem to have the visualizing machinery.) Instead... When trying to understand a new thing, you automatically focus on very simple examples that are easy to think about, and then you leverage intuition about the examples into more impressive insights.
"Show the data" is a fine mantra when it comes to news graphics, but it's not really helpful when coding. Beginning coders should be learning to think in terms of data and code structure, not trying to out-calculate the computer. Working with exact, line-by-line values is a distraction at best--and yet it's the primary focus of Victor's proposed learning language, precisely because he's so graphically-focused. The idea that the goals of a visualization (to communicate data clearly) and the goals of a visualization programmer (to transform that data into graphics via abstraction) are diametrically opposed does not seem to have occurred to him. This is kind of shocking to me: as a data journalist, my goal is to use the computer to reduce the number of individual values I have to see at any time. A programming language that swamps me in detail is exactly what I don't want.
I'm glad that people are pushing the state of tech education forward. But changing the way people learn is not something you can do in isolation. It requires practical research, hands-on experience, and experimentation. It saddens me that Victor, who has some genuinely good feedback for Khan Academy in this essay, insists on framing them in grandiose proclamations instead of practical, full-fledged experiments. I don't know that I could honestly say which would be worse: if his ideas were imitated or if they were ignored. Victor, it seems, can't decide either.