I’m a great fan of ISTE, and love to get updates and information about things that are happening. In my email today were a few tidbits that made me stop and think.
Wow, that’s crazy is more like the sentiment that crossed my mind.
The buzz word this time was “computational thinking”. Perhaps this is a term that is embedded in curriculum frameworks in North America, but I was a little saddened to see thinking in a digital age being described by such a mechanised term. Seriously – thinking is thinking, and calling it computational thinking seemed to me to reflect that educators are not understanding the immersive nature of 21st century learning environments.
It’s like saying ‘water swimming’ instead of ‘swimming’. How else would you swim except in water? So in 21st century environments, how else would you facilitate thinking except with the power of technology – that may or may not be ‘computational’ by the way! I do understand the need to still talk about digital age skills, because so many teachers are still struggling with being digital. I really don’t want to bury 21st century thinking terms like this.
Computational thinking reminds me of the the Hungarian word for computers (when they don’t use the English word, which is most of the time now). A computer is a számítógép – which literally means adding machine. See how that shows the origins of the term? Computational thinking is like an old term for a new idea – one that is actually NOT new at all anymore!
However, the video is good, and has some great ideas. Wish we just didn’t have the term!
You might also consider that, like “typewriter”, the first uses of the word “computer” were to refer to people who were, yes, paid to compute. Most were women, and most were in military roles.
It’s no stranger than “creative thinking” or “logical thinking” or “divergent thining”
Here’s a couple of computational thinking (CT) resources:
Carnegie Mellon’s take on computational thinking:
– draws on concepts fundamental to computer science
– means creating and making use of different levels of abstraction
– thinking algorithmically and with the ability to apply mathematical concepts
– understanding the consequences of scale
summarised from http://www.cs.cmu.edu/~CompThink/
Google defines CT as a set of problem-solving skills and techniques that software engineers use to write programs that underlie computer applications and refers to these specific techniques: Decomposition, Pattern Recognition, Pattern Generalization and Abstraction and Algorithm Design.
summarised from http://www.google.com/edu/computational-thinking/
I’ve not watched the video yet – but at the #CS4HS (Computer Science for High School) workshops run by google we discussed the idea of computational thinking quite a bit. It was framed as a different kind of thinking to the kind we do everyday immersed in a digital sea.
I understand it to refer to thinking like a programmer. To thinking algorithmically. To thinking in a very abstract why about how best to mechanise tedious tasks. To thinking mathematically about how to find a faster path to completion by dividing a problem into smaller chunks and working on them in parallel. It’s about thinking about how to frame a problem so that it can be solved by a machine.
So perhaps it’s not such a bad thing it made you think of it as a mechanised way to think about thinking. Because it is!
I’ll watch the video now – please ignore the above if I’ve misinterpreted due to not doing my homework first!
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