Twitter co-founder on Computational Thinking

Standard

I’ve long been a fan of Jack Dorsey, and I came across this excellent article about an interview on Charlie Rose.

Gary Stager a school reformer and Educational reformer speaks very well about Jack Dorsey. When we speak of using Computing in education, we often forget that in the words of Mitch Reznick ‘the computer is a paintbrush’. I’ve been subjected to some horrendous Powerpoint presentations in my life, and some horrendous ‘false complexity’. Yet I’ve somehow gotten to a Masters level education without being taught how to program.
Programming is something we shouldn’t deny students. In Mathematics for instance we have wonderful tools like Mathematica, Mathlab and Maple. These wonderful tools are interactive and provide all sorts of feedback loops that can greatly enhance learning.

The edtech community’s love affair with social networking has not made it easier for those of us advocating computer science experiences and S.T.E.M. for young people. I do not ascribe a sinister motive to any person or community. It’s just a reality that 1) the education community seems to have great difficulty thinking about two things at once 2) people enjoy talking to their friends and colleagues online 3) schooling is at least 90% focused on language arts 3) too many believe that education is about the transmission of and access to information 3) blogging and tweeting are simply easier than learning to program. New pedagogical strategies and teacher expertise are also required

So just like Professor William T. Shaw pointed out in his article about panic over S.T.E.M. teaching. We probably do need to change our pedagogical strategies which does involve teaching how to ‘get a computer to do it’. This will of course mean some movement away from the typical Gutenberg based technology of ‘teacher at the front of the classroom’, and especially at Universities more focus needs to be on getting students to read and think before lectures. Where the big ideas can be discussed and they’ve already been empowered enough to do computations.

So if in for instance the UK there was a huge movement to give interactive whiteboards to all teachers, and yet there is a denial of programming (something terribly important in S.T.E.M. – very few of my scientifically minded friends can avoid learning to program or needing to program) have we got our priorities as a society completely wrong?
Why do politicians like Michael Grove assume that things like Ancient Greek are somehow more important than teaching the importance of Computer Science, which is certainly already causing a revolution in Theoretical Physics, Mathematics, Biology, Linguistics and numerous other disciplines.
Notice how I use the term ‘Computer Science’ which is not I.T. We do a disservice to students when we fail to teach them the underlying infrastructure of Computers, and the power Computers have to solve problems. Of the various limits imposed by memory storage and the elegance that forces people into. Not to mention the inevitable Mathematics and Physics knowledge that some programming forces people into. As an anecdote, my own love of Mathematics probably goes back to Computer Games programming that I used to do while a teenager. Inevitably when one learns about OpenGL and 3D Graphics, you are forced to learn a few things about rotation matrices, group theory, and projectiles. The advantage of a ‘tinkering’ based system like a computer programming environment is it forces one to realise that knowledge and problem solving aren’t ‘binary’ processes of ‘I get it’ or ‘I don’t get it’ but a more complicated process that involves debugging, and additions. As Seymour Papert said ‘learning is debugging’. The wonderful, charming and well spoken programmer Jack Dorsey certainly understands this process.
Yet we deny students these opportunities, and treat computers in the same way a techo-phobic Accountant does.
This is not the same as learning the ‘false complexity’ of Dreamweaver or Microsoft Excel. Excel is the sort of program that a well trained programmer will just learn if necessary. Why teach the various tabs and windows in an ‘arbitrary’ Microsoft Application? Certainly I’m not saying we shouldn’t teach some HTML, but why not teach something harder? With languages like Scratch, and Logo, (not to mention the more sophisticated programs I mentioned above) students certainly have the ability to develop Computational Thinking and the sort of intellectual self empowerment that we all crave. We speak of ‘self-esteem’ among students, yet we don’t allow them the experiences of ‘making things’. And certainly I agree with Gary Stager that there is very little difference between the intellectual satisfaction that one gets in the Arts and in the Sciences. I don’t see some arbitrary dumb-bell distinction between right brain and left brain, yet many students and even teachers do.
Why not teach students how to program and build things. Lets treat the computer as an extension of ones mind.

Advertisements

Training students for the 21st Century

Standard

Education is a hugely politically loaded issue. I want to write today briefly about education. I’ve two years of experience as a tutor and Teaching Assistant in a Northern Ireland Grammar School, and continue to tutor a range of ages while I undergo my Masters studies in Mathematics. I definitely will focus on STEM subjects, although some of the things I mention will be applicable to other disciplines.

Cal Newport who runs the excellent blog Study Hacks in his teaching statement on his professional page, talks about ‘insight centred pedagogy’. When I teach Calculus myself I feel this is also an important issue. It is impossible to really get a feel for calculus and not to get lost in the details of proofs, without for instance knowing that the tangent to a curve is the first derivative. Similarly in something like Differential Geometry, one needs an insight of what a Lie Derivative is for before learning a long and cumbersome expression.
Perhaps then the focus of lectures should be on the ‘big ideas’ and there is also a huge benefit of the usage of computers in this area. Certainly that sometimes means using Mathlab and Mathematica, perhaps to help ‘debug’ peoples ideas. The wonderful resources that students have including for instance ‘Wolfram Alpha’ and Wikipedia are certainly things that need to be used.
I’m going to think some more about this, and the importance of developing the insights first.
Someone like Cal Newport certainly sees the importance of Theory and Practice in the 21st century, and his blog which focuses on cognitive science supported and study strategies that work, is a very valuable resource to students.
My article today was inspired by a piece on the New Statesman website, by Peter Hyman:

The Tory answer is “students who know more facts”, but the answer from most teachers, students and employers would be “students who know how to apply their knowledge, who love learning, who are creative, analytical and flexible; students who can work independently and show resilience, who are moral and kind to others; students who are high-quality written and oral communicators”.

We don’t know what the jobs of the 21st century will be. It is possible that some of them will involve a huge STEM component, especially as the new Mc Kinsey report which shows that there will be a huge increase in ‘Big Data’ jobs, not to mention the growth industries of Biotechnology, Cryptography and Internet Security.

We don’t know what the jobs of the future will be, so we need students to be ready to change, react and adapt. And we need learning in the classroom to be based less on an outdated notion (disciplinarian teacher at the front) and more on what the neuroscience is telling us: that students learn best when their learning is active (not rote learning or overuse of textbooks), experiential (hands-on), in longer periods (not broken up into 50-minute chunks), developed over a sustained period, and connected to a big picture (making connections between subjects and to larger ideas

This certainly ties in with the ‘big picture’ learning, or inverted classroom approach that someone like Seymour Papert certainly encouraged people to cultivate. Or Robert Talbert’s comments on this inverted classroom approach.
A question I regularly ask is ‘do we teach the correct skills?’
A follow up question is what are the correct skills.
I’m not sure what the answer to that question is. But it is something which needs to be thought out carefully, and with respect for reality, not ideological bias.

Learning as Debugging

Standard

Recently in Luxembourg there was a talk on ‘Mathematics Education’. As always being interested in STEM and the cultivation of learning and thinking, I found this fascinating.
I came across on Robert Talbert’s excellent blog, the following:

Yes! As somebody once said, true learning consists in the debugging process. And that’s where the fun in learning happens to lie, too. Let’s give students as many shots as possible to experience this process themselves.

The ‘someone’ he referred to is Seymour Papert. Such views are also proposed by Marvin Minsky in his OLPC Memos.

Many people are firmly convinced that to have a mechanical image of oneself must lead to a depressing sense of helplessness—because it means that you’re doomed to remain what you are, and there’s nothing that you can do about this. However, I’ll argue exactly the opposite: seeing yourself as a kind of machine can be a liberating idea—because whatever you might dislike about yourself, that might be caused by a bug that you could fix! For example, contrast these pairs of self-images:

I’m not good at math. —There are some bugs in my symbolic processes.
I’m just not very smart —— Some of my programs need improvements.
I don’t like this subject. ———- My current goals need better priorities.
I am confused. ———–Some of my processes may conflict with others.

If you think of yourself in terms of “I”, then you’ll see yourself as a single thing, that has no parts to change or rearrange. But using “My” can help you to envision yourself as composed of parts, which could enable you to imagine specific changes that might improve your ways to think. In other words, if you can represent your mind as made of potentially repairable machinery, then you can think about remedies. For example, you might be able to diagnose some bugs or deficiencies in the apparatus that you use for everyday functions like these:

Time-management. —– Organizing Searches. ——-Splitting problems into parts.
Selecting good ways to represent things. —–Making appropriate cognitive maps.
Allocating short-term memory. ———- Making appropriate Credit Assignments.

It seems clear that some children are better than others are at doing this kind of “self reflection.” Could this be a skill that we could teach? Perhaps, but this might not yet be practical because we don’t yet know enough about our human mental machinery. However, the types of projects this essay recommends could help us to promote that goal, by giving our children more tools to use for constructing better views of themselves!

The notion of viewing yourself as someone who can change, and that ‘debugging’ is part of the learning process is extremely valuable. Perhaps the greatest advantage that computers in STEM education have is to accelerate this process of ‘debugging’. In some sense when one tries to recall information by studying, one is debugging. One writes ones first ideas, and then compares with the correct concepts, and this can be used to develop the ability to for instance learn proofs.
I’ll think some more about this in the future, and probably in other posts, but I think this is an extremely powerful idea. One that ties into the ideas of Carol Dweck on Mindset.
So thinking of oneself as a Machine, is something which can’t be ignored, and may ultimately be empowering

Control theory in Financial Markets

Standard

I unfortunately know very little about Control Theory however what I do understand about it, is that in some sense it deals with feedback in complex systems.
Since the financial markets are complex systems, and very difficult for human beings to regulate. Not to mention the huge explosion of Algorithmic Trading. Certainly it doesn’t seem as if Economics as a whole operates in a state of equilibrium.
So is there a case for control theory being involved in the mathematics of finance? Specifically looking at issues of stability of these complex systems.
I’m by no means an expert, but this seems remotely plausible. Does anyone have anything interesting to add?

On Technology without Borders

Standard

As a naively minded Scientific type, I often make the mistake of imagining that merely developing technology is enough to better the world. As the developing world especially faces huge humanitarian challenges: for instance Malaria, Climate Change, HIV, and diseases such as TB, there are problems with the market conditions of the First World.
Peter Singer once wrote an essay titled ‘Hair Loss pills or Anti-Malaria medication’ pointing out that market conditions may lead to research and development that doesn’t lead to Utilitarian answers. In simple terms Utilitarianism speaks of the ‘greatest happiness for the greatest number of people’, and one can assume implicitly that Malaria and starvation aren’t conductive to human happiness. Except we in the West perhaps don’t know how to quite sympathise with that.
Peter Singer was hinting at the problem of ‘orphan diseases’, i.e. diseases which haven’t been adopted by the pharmaceutical industry due to a lack of financial incentives. A wonderful article in Seed Magazine which I came across today spoke of how to facilitate Biotechnology such as Synthetic Biology to help improve the human condition.
A paragraph that particularly struck me was:

Practically, the phenomenon of orphan diseases points to a broader challenge underlying all innovation and development. Many powerful new technologies migrate slowly, if at all, to developing world populations. More critically, the upstream choice of which technological advances to pursue often depends on market conditions or the wealth of different national governments, which means that the unique needs of developing world populations tend to go unaddressed or are not voiced during the early stages of a technology’s development. Thus, translating the promise of any new field of research, such as synthetic biology, into concrete benefits requires more than technology alone, especially when it comes to helping underserved populations in the developing world. It requires supportive legal, institutional, and commercial environments, and coordination among researchers to pool efforts toward solving shared problems.

We can’t just assume that innovation is the solution, in addressing large scale problems and in attempts to improve the human condition – and if one isn’t trying to do that directly or indirectly then why not? – one needs strong legal frameworks, and more than just referring to the gods of the ‘market forces’. Biobricks is certainly not a perfect solution, but it is interesting nonetheless and I’m very interested in how human resourcefulness in the developing world, in conjunction with Synthetic Biology can produce innovative solutions to some of humanities most pressing problems.