Comment by werizuwe | Hacker News Reader

Comment by werizuwe | Hacker News Reader

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I currently get a teaching degree. The education for that is split in two parts: The academic part in the university and the practical part at a school. I'm currently in the academic part, but some time ago a professor (not actually a professor) of the practical part gave some insights what the expect in the second part.

He said that no matter how good we will be, in CS half of our (high school) students will not learn much, if anything.

I was (and still am) absolutely shocked about this statement.

He claimed that this was a unique property of CS. If such a thing would happen in any other subject the teacher would be a total failure. But it would happen to him in CS, every college and every teacher in education he was ever responsible for.

This person is responsible for the education of teachers, engaged, probably very well thought and I have every reason to believe him to be a very good teacher. I'm don't know what I should think about this.

But The link at the end is really not helpful.

>At Harvey Mudd we’ve focused on changing four things about learning CS: make it fun, make it relevant, make it not scary and make it clear that lots of kinds of people have careers involving CS. We changed the context of the intro course to “creative problem-solving in science and engineering using computational approaches with Python” instead of “learn to program in Java” and made sure that the homework assignments were a lot of fun. We did not reduce the level of rigor or challenge, and we increased the amount of programming.

So, you made CS less like math. That good for some. But you completely ignore that math education does not suffer these problems. Why not making making it more like math? Well, in the end AFAIK neither works. At least for worse half of high school students.

There is a considerable literature on 'the CS1 problem' in education. It is a long-term, robust observation that the marks in first-year computing courses in university are strongly bimodal in a way that is not seen in other, comparably difficult subjects.

Here is a discussion of a paper (with link to the paper itself) that looks at these issues: http://www.tjradcliffe.com/?p=1338

And some follow-on, where I build a simple model that reproduces the biomodal mark distribution under the assumption that there is a single characteristic that is uniformly distributed amongst the population but that exhibits a threshold when it comes to programming: http://www.tjradcliffe.com/?p=1471

My bet is there's one (or a small number) of characteristics that are possessed in different degree by people and that if you fall below some threshold you will have a hard time learning to code. I liken this to height with respect to getting over a wall in an obstacle course: for people who are tall enough, it'll be easy. For people below some threshold it will become increasingly hard. There are two other variables that matter (strength and weight) so it may be difficult to pull out height as a single parameter, but some linear combination of height, weight and strength should be a good predictor of ability to get over the wall.

No one has found such a small set of factors for programming ability yet, but I'm not aware of anyone testing the things that are likely to be important, particularly a) ability to follow instructions; b) ability to create a set of instructions for a task that, when followed by a person unfamiliar with every element of the task will result in its successful completion; and c) ability to arbitrarily use anything to represent anything else.

I think your entire thesis can be boiled down to "if there is a will, there is a way."

Which, I believe, also hold true with learning to program.

Not at all. It's "Some (maybe many) people will require an implausibly large amount of will for learning to code to be a worthwhile use of their time."

Like anyone who has pursued a diversity of interests fairly seriously over decades, I've found that some things are really easy for me, others not. I'm an excellent poet, if I do say so myself, and although I've worked hard at it, it comes easily to me. But after forty years of steady practice I'm pretty sure I will never be much of a prose stylist, no matter how hard I work at it. I can tell a decent story, but when I look at people like Iain Banks or David Mitchell I recognize that they "get it" in a way I probably never will, no matter how much effort I put in.

So the belief that force of will can overcome all obstacles is not one that I subscribe to. It can help, but some obstacles are simply too big. It is an open question if this is often the case with regard to learning to code, and while I think it is, the lack of any independent measure of "getting it" makes my position implausible. As such, all that would take to convince me otherwise would be a way of teaching CS1 that didn't routinely result in the traditional bimodal mark distribution.

> Not at all. It's "Some (maybe many) people will require an implausibly large amount of will for learning to code to be a worthwhile use of their time."

I totally agree with this, and, if fact, it I were totally honest I would say that I took up programming at 15yo because it came easily to me and seemed like a great way to make a living, although performing music was my true love.

I am not saying " force of will can overcome all obstacles", but I am saying if someone wants to overcome their obstacles, there should be no additional ones placed in their way just because they are on the wrong side of the "bimodal mark distribution" curve.

You're missing the point. Imprecise thinking and forgetfulness is not lack of will, it's imprecise thinking and forgetfulness.

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