CBM: Anchoring Computational Thinking in today’s curriculum

CBM: Anchoring Computational Thinking in today’s curriculum

There is a lot of talk of "Computational Thinking" as a new imperative of education, so I wanted to address a few questions that keep coming up about it. What is it? Is it important? How does it relate to today's school subjects? Is CBM a Computational Thinking curriculum?

Firstly, I've got to say, I really like the term.

To my mind, the overriding purpose of education is "to enrich life" (yours, your society's, not just in "riches" but in meaning) and different ways in which you can think about how you look at ideas, challenges and opportunities seems crucial to achieving that.

Therefore using a term of the form “xxx Thinking" that cuts across boundaries but can support traditional school subjects (eg. History, English, Maths) and emphasises an approach to thinking is important to improving education.

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Enterprise Private Cloud: the core solution for Enterprise Computation

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.

I'll leave my main blogpost to do the talking, but suffice it to say that I'm pleased there's a clean, powerful, modern way to put computation at the heart of the enterprise--what I call Enterprise Computation.

It's important for organisations to start to think now about how they manifest this new opportunity which will rapidly become a necessity--one driven particularly by data science.

How Significant is Significance Arithmetic?

How Significant is Significance Arithmetic?

Central 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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Computers in education: Great machines, Wrong results

Computers in education: Great machines, Wrong results

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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China: from omnipotent to impotent?

China: from omnipotent to impotent?

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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Evidence: let's promote not stifle innovation in education

Evidence: let's promote not stifle innovation in education

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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Computation meets Data Science in London, Thursday 5 March

Computation meets Data Science in London, Thursday 5 March

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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