FULT ePortfolio Blogs#4 week 2

The statement for reflection was “Professor Perkins makes the claim that 90% of what we teach is a waste of time. Do you agree or disagree?”

I disagree, for a few of reasons:

1. you don’t know what you might need to know in the future.There is heaps of stuff that I learnt in various courses that I have used, in all sorts of contexts that I wouldn’t have predicted. And not just in work – but just in being an educated person who can read a newspaper article, talk to soemone from a differnt profession, or contribute to running science classes at my kids primary school. In the work context, I teach engineers – who knows what they may need to tackle in the future, and where, and with what resources? One of my most prized bits of student feedback came in an email from a past student. She was doing aid work in Indonesia, and had set up a basic optics bench so they could measure focal length of second hand spectacle lenses donated by a charity. She said that she never thought she’d need to use the optics I taught in first year physics (and finallt reaslised why I made them figure stuff out for themselves in lab instead of giving them detailed instructions).

2. Learning “stuff” teaches you how to learn, as well the “stuff”. Knowing a lot makes it easier to find more information, and to fit it into existing knowledge structures.It allows you to do plausibility checks on new information, because you have existing knowldege to check it against. That works the other way too – it allows to check your existing knowledge. We all have misconceptions that we go through life with, now and then we get to confront them. There’s also a boostrapping element to learning. The more you know, the more you are able to synthesise  – putting together ideas that initially seem disaparate. I used the same  mathematical ideas in my PhD to think about neural networks as I did some years later working in magnetism.  But I needed to know some biology and some solid state physics to recognise the similarity.
3. the 90% (I think that’s an overestimate anyway) that you don’t use gives context and meaning to the 10% that you do use – this is the idea of knowledge structures as distinct from collections of independent concepts. You need a minimum number of concepts to form a structure – the more concepts you can fit into your structures, the stronger the stuctures. This way of representing knowledge comes from neural networks and ultimately from neurophysiology. When you activate a knowldge structure you strengthen it. So adding new knowledge to existing structures strengthens your existing knowledge.
4. a discipline is not a collection of facts, or even technical skills – it’s a way of thinking, and in particular a type of critical thinking characteristic of the discipline. You only learn this way of thinking by applying it to many, many examples within and outside the discipline. It’s not about that example, it’s about how to think about any example.

I recently finished some chapters for a year 11 physics textbook (Cengage Phyisics in Focus, should be out in 2018). I wrote 6 content chapters, and the introductory chapter on scientific method, the nature of physics and how to do investigations (depth studies as they are now called). I really like the intro chapter because it is the only place where I could show, using a set of concept maps, that the many, many ideas, in the apparently separate topics, all reduce down to examples of a few basic ideas – forces, energy and conservation principles. But could you just teach physics by teaching these only? I don’t think so – you need to see them working in a dozen different ways to really grasp their ubiquity and then be able to recognise and apply them in unfamiliar contexts.

Of course, all this needs to be articulated to students, and teaching needs to promote, assess and reward critical thinking as well as declarative and procedural knowledge. That’s the hard bit.


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