Rene’s Assessment

Authentic

I’ve referred to the idea of authentic assessment before. Most recently in my previous post, in which I promised to delve into the subject again.

In his book The Black Swan: The Impact of the Highly Improbable , the author Nassim Nicholas Taleb mentions an experiment done in 1971 by psychologists Danny Kahneman and Amos Tversky. In the experiment the duo challenged statisticians with basic statistical problems that were presented as normal everyday issues, and not as statistical problems. Interestingly a large number of statisticians failed a significant number of these challenges which illustrates how  our understanding, and especially triggering it’s application, is very domain specific.

Sovjet-jeep

A slightly different anecdote on this issue relates to attempts of the US army to train neural networks in the recognition of enemy  vehicles. After a long training period using pictures of both allied and (at the time) Soviet vehicles the neural network seemed to have learned to flawlessly identify friendly and enemy craft. The next stage of the project involved working with actual vehicles, and the project moved outdoors to a desert where, to the surprise of the military, the neural network suddenly failed to identify any of the collected Soviet machinery as belonging to the enemy. After careful analysis it had turned out that the neural network had actually learned to distinguish the latitude by looking at the length of the shadows on the presented photographs. As the training pictures of the Russian craft were taken in Russia, this worked fine. in stage 1, but stopped working when the actual vehicles were presented on lower US latitudes.

What I’m trying to illustrate here is a few reasons to make assessment, but also learning, as authentic as we can. We want to be sure that our learners have learned something they can apply in a real situation. We also want to ensure that when we assess them, we assess the right constructs, so that the achievement on the assessment will correlate to a ‘real-world’ capability, and not just to an entirely academic one, or worse, one with no relation to the subject at  hand, such as the latitude on which pictures are taken.

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Time for some reflection, and answer the big question for December 2008: what did you learn about learning in 2008? And in doing so, perhaps time to come clean about my own learning disabilities.

Geek Inside

I’m a classical geek: A bit of a recluse, overly rational and sometimes perhaps lacking a bit in some social graces. On most days I read more then my girlfriend talks. I will trust you to correctly apply the stereotypes in that sentence. They are characteristics that, for the most part, have actually served me quite well. Our education system has bestowed the most extraordinary amount of positive action on the minority of people like me. People that can, and are willing to, learn at least some things solely by engaging with the written word.

The problem is of course that this is not how most people learn, and it’s not how the most important things are learned. But it’s easy to stick with something that works, and so it has taken me quite a bit of time to really understand that. To understand that we only really learn by (inter)acting. And while the education system is still accepts, and even favours people with similar disabilities to mine to cling to their narrow learning habits, modern social and professional life make it increasingly hard to be successful with that disposition. Because this disposition is suited primarily for information gathering. And information is of course just another commodity, and an increasingly cheap one.

But aside from this personal realisation, this is something that needs to be translated to our practices, and our institutions and systems, which is not trivial. How are we going stimulate learning, if we are not teaching? How do we verify that learning has taken place, if we aren’t sure how create authentic and valid assessments for the competencies we are now aspiring to instil? And aside from solving these challenges on an intellectual level, how will we actually implement them and change the entrenched system of education in which we work. It’s a worthy challenge, one for after the Christmas holidays…

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The article Learning Networks and Connective Knowledge has been really valuable for me in understanding the ideas behind connectivism a lot better. It is a bit of a read, but in my opinion well worth the time and attention.

What resonated particularly well for me, is the idea of building an emergentist theory of learning. I have always preferred a holistic approach to understanding. One of the major weaknesses in our ‘Western’ view of the world is the idea that we can understanding everything by reducing it to it’s component parts. I suppose it is something that developed with my long term practice of Chinese martial arts and philosophy. More recently I have found tremendous value in ‘system thinking’ as described by Peter Senge in his book ‘The Fifth Discipline‘. In this book Senge criticises the reductionist approach to running businesses such as our obsession with KPI’s and the like. I think I’m starting to realise that connectivism really is based on similar principles, applied to learning.

Reflecting further on connectivism, and in particular on the idea of ‘levels of knowing’, there are several other things falling into place as well. I have been a fan of the SOLO taxonomy ever since being introduced to it by Graham Gibbs about 3 years ago. For me it makes so much more sense then the archaic taxonomy of Bloom. It classifies levels of understanding by the amount of connections that a learner makes, and the broadness of those connections (for instance into other domains of knowledge). It seems to me to be an excellent reflection of how learning would develop according to the connectivist model.

So after a somewhat sceptical start, I must say that I’m beginning to warm to some of the ideas behind connectivism. I do still think some of the theory and arguments behind it need more refinement, and perhaps that is something I should try and articulate over the next few weeks to help this discussion along. For the moment though many of the ideas are still somewhat in the ‘primordial soup’ stage, and so I will give myself a few weeks before venturing down that path further.

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It’s only the first week and I’m already behind schedule, how embarrassing. Either way, here are my reflections on the first week of connectivism:

Levels of analysis
Although not a part of this weeks reading, I did find a lot of value in a video recommended by Clark Quinn: (not Donald Clark as I erroneously said earlier):

It seems to me that a lot of the differences in the various theories and views on learning really boil down to the level of analysis or perspective that you take on the problem. Connectivism in that sense is the result of the analysis of learning within a new level or structure that has been created through new technology.

Analogies
Aside from the level of analysis, analogies can form another perspective on a problem. Often we start employing an analogy because it aids in the representation of an aspect of an idea. However, analogies are always flawed, and so when we start employing our analogy to liberally we inevitably run into problems. Unfortunately our brain seems to like, and need, simplicity and so we often find ourselves stuck in our own analogy.

The brain as a computer is a very obvious analogy. Knowledge as an object that can be internalised is perhaps also the result of a subconscious analogy. In the days where books were not too abundant and the number of views expressed in them relatively limited perhaps it was logical to see the book as a synonym for knowledge. And so reading the book, internalising it, equivalent to learning. the observation had very little to do with what learning really is. It is more an expression of how learning commonly took place.

And so for the blogging, networking and podcasting fanatics amongst us, networked learning has become our preferred mode of learning. And while it serves a lot of us very well, I am not sure it actually makes it a theory of learning, or if it is merely an instantiation of it. And to be very precisely, perhaps it is more a means of sense making, more then learning. Learning, to me, is still something I cannot easily separate from the individual.

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I completely forgot where I found this, as it’s been sitting in my saved Firefox 3 tabs for a few days now, so apologies for the lack of attribution. This excellent talk by Michael Wesch (the guy that brought you the Youtube video “the machine is using us”) gives a great view on what learning and teaching really should be like.

If you don’t have time to watch the whole thing, at least have a look at the first 10 minutes, which will already give you some great ideas on the paradigms in which education seems to be stuck, an dhow to perhaps get beyond those.

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