Just a quick entry to say we released a product I've been involved with--Enterprise Private Cloud--a few days ago. It's a dramatic feat of engineering, built on the uniquely extensive base of the Wolfram Technology Stack.
Read MoreA brief post to say how sad I was to wake up this morning to news of the death of Seymour Papert--the great visionary for the use of computers in education, inventor of the coding language Logo and its associated Turtle (as a route to computational thinking) and instigator of the "constructionism" approach to learning.
I am also sad that I never met Seymour. I even can't say when I consciously became aware of him or different strands of his work either. But his name has seemingly for ever been familiar, cropping up with increasing regularity and force in so many of the interests I've pursued, particularly fundamentally reforming maths education (our computerbasedmath.org or CBM project). So many routes in so many areas lead back to Seymour. I can't help but notice with some wry amusement this morning how constructionist an approach I have taken to learning about Seymour's life and work!
Read MoreCentral to our mission at computerbasedmath.org is thinking through from first principles what's important and what's not to the application of maths in the real, modern, computer-based world. This is one of the most challenging aspects of our project: it's very hard to shake off the dogma of our own maths education and tell whether something is for now and the future, or if really it's for the history of maths.
This week's issue is significance arithmetic, similar to what you might know from school as significant figures. The idea is when you do a calculation not just a single value but bounds that represent the uncertainty of your calculation too are calculated. You can get an idea of how accurate your answer is or indeed if it has any digits of accuracy at all.
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I am not the slightest bit surprised at the recent OECD report that use of computers in education hasn't improved PISA results − and indeed that many countries with the best technology provision have mediocre performance.
Why? Because the world's most transformative machines have been used for entirely the wrong purpose in most classrooms: automating pedagogy not changing the subject taught.
Countries with the most attentive teaching are also likely countries where there is least pressure to computerise pedagogy for teaching today's school subjects. They do best in PISA because they are best at helping students through those subjects.
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I've been struck in the last couple of weeks by China's apparent fall from global economic wonder-kid to the latest problem child.
Neither characterisation is true in my view.
What really seems to have spooked people is the psychological turnaround from apparently omnipotent Chinese government, able to command and fix at will, to a government that's apparently largely as financially impotent as any other.
Haven't we seen this same "country on a pedestal" culture that saw Japan fall from grace in the 1990s, the US in 2000s (along in a small way with the UK) and now China?
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Earlier this week I was part of a high-level discussion about maths and computer science education, how we could improve their reach and effectiveness. Rather quickly the question of evidence came up, and its role in driving innovation.
It's taken me a few days to realise that there were actually two very different "importance of evidence" conversations--one with which I completely concur, and one with which I vehemently disagree. In the end, what I believe this exposes is a failure of many in charge of education to understand how major innovation usually happens--whether innovation in science, technology, business or education--and how "evidence" can drive effective innovation rather than stifle it. In an age of massive real-world change, the correct and rapid reflection of this in education is crucial to future curricula, their effective deployment, and achieving optimisation for the right educational outcomes.
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I'm usually going on about "computation" or in education, "maths". But I've come to appreciate just how much of computation's utility in modern life centres around data (rather than, say, algebraic modelling).
Clearly data science is a major, growing and vital field—one that's relatively new in its current incarnation. It's been born and is driven forward by new technology, our abilities to collect, store, transmit and "process" ever larger quantities of data.
But "processing" has often failed to elucidate what's important in the data. We need answers, not just analytics, we need decisions not just big data.
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Traditional areas of maths like algebra, calculus or trig don't seem a good way to think about subdividing the subject in the modern world. You might ask, why subdivide at all? In a sense, you shouldn't. The expert mathematician utilises whichever maths areas helps them solve the problem at hand. Breadth and ingenuity of application is often key.
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Today's maths PISA results are predictable in the successes that many Asian countries show and the mediocrity of many of the traditional Western countries--like the UK.
I believe PISA is meticulous in conducting its tests and reflects a good evaluation of standards of today's maths education. And yet I think if countries like the UK simply try to climb up today's PISA assessment, they'd be doing the wrong thing.
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I was very excited at our CBM summit this morning with Eben Upton to announce that Mathematica will be bundled on the Raspberry Pi computer for free, and so will the new Wolfram Language--also announced today.
This really has at least 4-dimensions of consequence:
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Fixing maths education is becoming ever more central to individual life-chances and our societal needs.
So I am very pleased that we're able to collaborate with UNICEF on our 3rd CBM summit, holding it at their headquarters in New York City on November 21-22.
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I was debating Computer-Based Maths education (CBM) with a sceptic before the summer and he brought up the analogy of music education to support various claims he was making of maths.
As I understood his central point it was that practising hand calculations is akin to practising music pieces--it's simply the way to learn to play. Also there was some attempt to draw the analogy between listening to music and CBM, whereas playing was like traditional hand-calculating maths.
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I'm very excited to announce that computerbasedmath.org has found the first country ready for our completely new kind of maths education: it's Estonia. (...and here's the press release).
I thought Estonia could be first. They are very active on using technology (first to publish cabinet decisions immediately online, first to include programming in their mainstream curriculum), have ambition to improve their (already well respected) STEM aptitude and lack the dogma and resistance to change of many larger countries. There aren't so many countries with all those characteristics.
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