The blog post for day 2 of my week at the Change11 MOOC…

Yesterday I made a quick and dirty four-minute  video in which I explore the ways that a stick can become a technology because of how it can be combined with soft processes and used as part of an orchestration of phenomena to some use. It can thus become many technologies. On reflection, and looking at the video, I realise that it was a mistake to describe the stick itself as a soft technology it is not. The stick is a part of a great many (probably an infinite number) of soft technologies.

I think that this cuts to the heart of a great many of the mistakes that we make when we talk about learning technologies. We often make the assumption that, because the same thing is involved from one context to the next – a learning management system, a discussion forum, email, a whiteboard, a classroom, a teaching method, etc – that we are talking about the same technology. We are not.

When I use something like this site (the Landing) in different classes or even in different parts of a class, it is just part of an assembly that is, in each case, a different technology. I am orchestrating different phenomena in different ways for different purposes, even though the tool is the same, just like the stick. Similarly, it is a different technology for me, now, writing this, than it is for you, reading this. For me, I am using its ability to share content with a public audience. For you, it is a means to display content. Different uses, different technologies, even though we are both using precisely the same underlying set of tools. It is a very unhelpful generalisation to think of only the tool, not its use and not the things that we are assembling with it for that use to occur.

Churchill said ‘we shape our dwellings and afterwards our dwellings shape our lives’, a sentiment echoed by McLuhan whose take on it was ‘we shape our tools and thereafter our tools shape us’. That’s the starting point for the theme for my bit of the Change11 MOOC. Ignoring the elephant in the room for the moment (because that’s mostly what we do), there are big questions about the kinds of dwellings and tools should we be using and designing to help us to learn, what are the effects of our choices?

It’s partly about softness and hardness. Harder technologies are constraining: learning management systems, for example, work because they deliberately limit the number of choices we have to make, performing some of the orchestration of phenomena on our behalf so that we don’t have to. That’s why they are relatively easy to use, at least when compared with alternatives such as adapting existing tools or building our own programs. There is a strong risk that they can therefore stifle creativity. However, constraints can also drive creativity. I was reminded of this while touring art exhibitions in Vancouver yesterday, where I saw some images that drew their form from the medium on which they were painted, using the natural whorls and knots of the wood grain to structure the picture.

As Stravinsky said, “The more constraints one imposes, the more one frees one’s self. And the arbitrariness of the constraint serves only to obtain precision of execution.” Bradley Messer seems to have taken this message to heart and, though I do not love all of the pictures that result from that, there is no doubt that something creative has emerged from the constraints.

The trouble is, the constraints of our learning technologies are far from arbitrary and are often the result of turning soft and flexible processes observed in traditional teaching practices into something harder. This is not like the knots in the wood, where arbitrary forms can guide our creativity. This is the solidifying of history, the intentional creation of path dependencies that can entrap us in pedagogies and methods used by our forebears that may be less than perfect for our current needs. We need to think far more carefully about those constraints, not to take them as a given, to find ways of using them but not being bound by them. Or maybe we need to build our learning technologies more like wood, more organically, more arbitrarily. 

Excellent talk on the confirmation biases and filter bubbles that make the Internet a less diverse space than it might be.

Address of the bookmark: http://www.ted.com/talks/ethan_zuckerman.html

Donald Clark giving one of his marvellous signature incendiary talks about how to avoid bad ways of teaching (lecturing in particular) with Twitter accompaniment. The tweets are almost as interesting (though not in a good way) as the talk itself. He was well and truly tweckled. A great talk and a fascinating glimpse of the power of backchannels.

Address of the bookmark:

This is a very fine article that provides excellent arguments and evidence about the fundamental dangers of rewarding results rather than effort in learners, and the extreme silliness of learning styles. The notion of a ‘learning quotient’ rather than an ‘intelligent quotient’ is a nice distinction. The idea of fixed abilities and ways of thinking is highly antagonistic to learning – telling people they are good at something or that they are not good at something, or that they learn in one way and not another reduces motivation to become more than they are. We are not static and unchangable beings. To learn is to change, and the best and most rewarding learning is that in which we learn to learn. While there are certainly limits to what an individual can expect to be able to do in a single lifetime and we are all better at some things than others, with enough effort and an appropriate way of going about it, we can almost always learn more, learn to learn differently, and expand our horizons further. 

There are some interesting follow-up comments too: some are predictably dumb, but someone had to make them. There is a particularly heinous opener in which the author claims that rewarding results and punishing failure is what it is like in the real world so learners had better get used to it. This is wrong on so many levels, but mainly because the author completely misses the point that it is about becoming competent, which is not at all the same thing as using that competence once it is achieved. It is possible to learn about reward/punishment systems too, and how to cope with them, but that’s a separate problem, and simply punishing or rewarding every result, without further reflection on and examination of what that means, is definitely not the best way to go about it. However, though there are a few more comments of this nature, the conversation explores a lot of the issues in some depth in a way that extends the depth of the original article considerably. Well worth reading.

Address of the bookmark: http://mindshift.kqed.org/2011/11/can-everyone-be-smart-at-everything/?utm_medium=referral&utm_source=pulsenews

Interesting article overviewing a range of uses of analytics (including learning analytics) raising some slightly fuzzily-articulated but very real concerns about the use of statistics to guide behaviour.

Address of the bookmark: http://www.readwriteweb.com/archives/ipad_apps_for_kids_measure_increase_learning.php?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+readwriteweb+%28ReadWriteWeb%29

Social digital storytelling radio station

Address of the bookmark: http://ds106.us/

I’m sitting here listening to Barbara Means giving the keynote on blended learning in K-12 in the US at E-Learn 2011. The audience is a little thin on the ground this morning as the conference is in Waikiki this year. The people on the beach missed a wonderful traditional chant and greeting – wonderful.

Barbara is telling us that, in meta-studies and in quasi-experimental studies, blended learning is equally or (often) more successful than face to face equivalents. And, the second point, as she observes, is that course completion rates are lower, of course (so the ones that survive are better). For the latter insight it is reasonable to consider the ‘e’ element of it – one absolutely distinctive feature of online learning is that it is much easier to ignore, so less motivated or well-organised students or those who have not learned online learning skills are at a disadvantage (something Barbera rightly observes). For the former, it is not at all.

The problem with these kinds of studies is a failure to understand and cater for the nature of the technologies they are examining. If we are looking at outcomes, it is almost nothing to do with whether people use online teaching or not, it’s about how the technologies (notably including pedagogies as well as organisational systems and the physical and virtual systems) fit together and how it all relates to things like motivation, time on task and the passion of the teacher, which together account for a good 80% of the reason for success or failure in most educational interventions. 

It ain’t what you do, it’s the way that you do it. A bad teacher is a bad teacher no matter what model is used (though good technologies such as sensible pedagogies, amongst others, can reduce the harm), while a good teacher, as long as the physical and organisational constraints are not too limiting, is good no matter what model is used. Technics matter, but caring, art, sensitivity and skill matter more. Good teachers can and often do use bad pedagogies and other bad technologies and yet they still succeed. Similarly, teaching things that people want to learn, when they want to learn them is more useful than almost any other factor. 

Some interesting insights into what happens when technologies are incompatible – like insane state legislation requiring students to sit in class when there is nothing for them to do there because they are working online, or when students learn to learn using one technology but no one notices that the same approach doesn’t work when you use another. Inevitably, she is talking about flipping the classroom (a trendy name for what good face-to-face teachers have done for millenia) with some encouraging stats to suggest that an approach of teaching rather than telling is becoming more fashionable as a result.

This is a bit scary, especially given that some systems put a limit on the size of passwords you may use.  Of course, they need to get hold of the encrypted (or hashed) password in the first place so that should provide a basic line of defence, but it is a remarkable feat, using incredibly cheap hardware. Time to make my passwords longer and stronger, I think. Recent reearch suggests that the strongest are not those that have weird and wonderful mixes of letters and symbols and numbers (easily forgotten), but that use sentences (but not obvious ones that can be found with a web search – poems and song lyrics are not a good choice!)

Address of the bookmark: http://www.computerweekly.com/Articles/2011/10/04/248075/GPU-cracks-six-character-password-in-four-seconds.htm

Stuff about learning, education and teaching