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How to Teach Computational Thinking
How to Teach Computational Thinking
How to Teach Computational Thinking
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How to Teach Computational Thinking

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In a world where jobs are continually being outsourced to machines and algorithms, the question of how best to educate the next generation becomes more important with every year. Stephen Wolfram, author of A New Kind of Science and Idea Makers and creator of Wolfram|Alpha, says the answer is computational thinking. Wolfram defi

LanguageEnglish
Release dateApr 19, 2018
ISBN9780965053266
How to Teach Computational Thinking

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    How to Teach Computational Thinking - Stephen Wolfram

    How to Teach

    Computational Thinking

    September 7, 2016

    The Computational Future

    Computational thinking is going to be a defining feature of the future—and it’s an incredibly important thing to be teaching to kids today. There’s always lots of discussion (and concern) about how to teach traditional mathematical thinking to kids. But looking to the future, this pales in comparison to the importance of teaching computational thinking. Yes, there’s a certain amount of traditional mathematical thinking that’s needed in everyday life, and in many careers. But computational thinking is going to be needed everywhere. And doing it well is going to be a key to success in almost all future careers.

    Doctors, lawyers, teachers, farmers, whatever. The future of all these professions will be full of computational thinking. Whether it’s sensor-based medicine, computational contracts, education analytics or computational agriculture—success is going to rely on being able to do computational thinking well.

    I’ve noticed an interesting trend. Pick any field X, from archeology to zoology. There either is now a computational X or there soon will be. And it’s widely viewed as the future of the field.

    So how do we prepare the kids of today for this future? I myself have been involved with computational thinking for nearly 40 years now—building technology for it, applying it in lots of places, studying its basic science—and trying to understand its principles. And by this point I think I have a clear view of what it takes to do computational thinking. So now the question is how to educate kids about it. And I’m excited to say that I think I now have a good answer to that—that’s based on something I’ve spent 30 years building for other purposes: the Wolfram Language. There have been ways to teach the mechanics of low-level programming for a long time, but what’s new and important is that with all the knowledge and automation that we’ve built into the Wolfram Language we’re finally now to the point where we have the technology to be able to directly teach broad computational thinking, even to kids.

    I’m personally very committed to the goal of teaching computational thinking—because I believe it’s so crucial to our future. And I’m trying to do everything I can with our technology to support the effort. We’ve had Wolfram|Alpha free on the web for years now. But now we’ve also launched our Wolfram Open Cloud—so that anyone anywhere can start learning computational thinking with the Wolfram Programming Lab, using the Wolfram Language. But this is just the beginning—and as I’ll discuss here, there are many exciting new things that I think are now possible.But first, let’s try to define what we mean by computational thinking. As far as I’m concerned, its intellectual core is about formulating things with enough clarity, and in a systematic enough way, that one can tell a computer how to do them. Mathematical thinking is about formulating things so that one can handle them mathematically, when that’s possible. Computational thinking is a much bigger and broader story, because there are just a lot more things that can be handled computationally.

    But how does one tell a computer anything? One has to have a language. And the great thing is that today with the Wolfram Language we’re in a position to communicate very directly with computers about things we think about. The Wolfram Language is knowledge based: it knows about things in the world—like cities, or species, or songs, or photos we take—and it knows how to compute with them. And as soon as we have an idea that

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