Researching things that don't exist

As the end of my sabbatical is approaching fast, I am still tinkering with a research methodology based on tinkering (or the synonymous bricolage, to make it sound more academic). Tinkering is an approach to design that involves making things out of what we find around us, rather than as an engineered, designed process. This is relatively seldom seen as valid approach to design (though there are strong arguments to be made for it), let alone to research, though it underpins much invention and discovery. Tinkering is, by definition, a step into the unknown, and research is generally concerned with knowing the unknown (or at least clarifying, confirming or denying the partly- or tentatively-known). This is not a direct path, however.

Research can take many forms but, typically and I think essentially, the sort that we do in academia is a process of discovery, rather than one of invention. This is there in the name – ‘recherche’ (the origin of the term) means to go about seeking, which implies there is something to be found. The word ‘discovery’ suggests that there is something that exists that can be discovered, whereas inventions, by definition, do not exist, so they are never exactly discovered as such.

While we can seldom substitute ‘invention’ for ‘discovery’, the borders are blurry. Did Maxwell discover his equations or did he invent them? What he discovered was something about the order of the universe, that his (invented) equations express, but the equations formed an essential and inextricable part of that discovery. R&D labs get around the problem by simply using two terms so that you know they are using both. The distinction is similarly blurry in art: an artwork is normally not, at least in a traditional sense, research because, for most art, it is a form of invention rather than discovery. But sculptors often talk of discovering a form in stone or wood. And, even for the most mundane of paintings or drawings, artists are in a dialogue with their media and with what they have created, each stroke building on and being influenced by those that came before. A relative of mine recently ran an exhibition of works based on the forms suggested by blots of ink and water, which illustrates this in sharper relief than most, and I do rather like these paintings from Bradley Messer that follow the forms of wood grain. Such artists discover as much as they create and, like Maxwell’s equations, their art is an expression of their discovery, not the discovery itself, though the art is equally a means of making that discovery. Discovery is even more obvious in ‘found’ art such as that of some of the Dadaists, though the ‘art’ part of it is arguably still the invention, not the discovered object itself. Duchamp Fountaine And, as Dombois observes  there are some very important ways research and art can connect: research can inform art and be about art, and art can be about research, can support research and can arise from it. Dombois also believes art can be a means of performing research. Komar and Melamid’s ‘most-wanted paintings’ project is a good example of art not only being informed by research itself being a form of research. Their paintings resulted from research into what ‘the people’ wanted in their paintings. The paintings themselves challenge what collective taste means, and the value of it, changing how we know and make use of such information. And the artwork itself is the research, of which the paintings are just a part. 

Inventions (including art works) use discoveries and, from our inventions, we can make discoveries (including discoveries about our inventions). Invention makes it possible to make novel discovery, but the research is that discovery, not the inventions that lead to it. Research perceived as invention means discovering not what is there but what is not there, which is a little bizarre. More accurately, perhaps, it is seeking to discover what is latently there. It is about discovering possible futures. But even this is a bit strange, inasmuch as latent possibilities are, in many cases, infinite. I don’t think it counts as discovery if you are picking a few pieces from a limitless range of possibilities. It is creation that depends entirely on what you put into it, not on something that can be discovered in that infinity. But, perhaps, the discovery of patterns and regularities in that infinite potential palette is the research. This is because those infinite possibilities are maybe not as infinite as they seem. They are at the very least constrained by what came before, as well as by a wide range of structural constraints that we impose, or have imposed upon us. What is nice about tinkering is that, because it is concerned with using things around us, the forms we work on already have such patterns and constraints. 

Tinkering is concerned with exploring the adjacent possible. It is about looking at the things around you (which, in Internet space, means practically everywhere) and finding ways to put them together in new ways to do new things. These new things can then, themselves, create new adjacent possibles, and so it goes on. Beyond invention, tinkering is a tool for making new discoveries. It is a way of having a conversation with objects in which the tinker manipulates the objects and the objects in turn suggest ways of putting them together. It can inspire new ways of thinking. We discover what our creations reveal. Writing (such as this) is a classic example of this process. The process of writing is not one of recording thoughts so much as it is one of making new ones. We scaffold our thoughts with the words we write, pulling ourselves up by our own bootstraps as we do so in order to build further thoughts and connections.

The construction of all technologies works the same way, though it is often hidden behind walls of abstraction and deliberate design. If, rather than design-then-build, we simply tinker, then the abstraction falls away. The paths we go down are unknown and unknowable in advance, because the process of construction leads to new ideas, new concepts, new possibilities that only become visible as we build. Technologies are (all) tools to think with at least as much as they are tools to perform the tasks we build them for, and tinkering is perhaps the purest way of building them. And this is what makes tinkering a process of discovery. The focus is not on what we build, but on what we discover as a direct result of doing so – both process and product. Tinkering is a scaffold for discovery, not discovery itself. This begins to feel like something that could underpin a methodology.

With this in mind, here is an evolving set of considerations and guidelines for tinkering-based research that have occurred to me as I go along.

Exploring the possible

To be able to explore the adjacent possible, it is first necessary to explore the possible. In fact, it is necessary to be immersed in the possible. At a simple level, this because the bigger your pile of junk, the more chances there are of finding interesting pieces and interesting combinations. But there are other sub-aspects of this that matter as much: the nature of the pile of junk, the skills to assemble the junk, and immersion in the problem space. 

1) The pile of junk

Tinkering has to start with something – some tools, some pieces, some methods, some principles, some patterns. It is important that these are as diverse as possible, on the whole. If you just have a pile of engine parts then the chances are you are going to make another engine although, with a tinker-space containing sufficiently diverse patterns, you might make something else. There is a store near me that sells clocks, lights and other household objects made from bits of old electrical equipment and machinery, and it is wonderful. Similarly, some of the finest blues musicians can make infinite complexity out of just three chords and a (loosely) pentatonic scale. But having diverse objects, methods, patterns and principles certainly makes it easier than just having a subset of it all.

It is important that the majority of the junk is relatively complex and self-contained in itself – that it does something on its own, that it is already an assembly of something. Doing bricolage with nothing but raw materials is virtually impossible – they are too soft (in a technology sense). You have to start with something, otherwise the adjacent possible is way too far away and what is close is way too boring. The chances are that, unless you have a brilliant novel idea (which is a whole other territory and very rare) you will wind up making something that already exists and has probably been done better. This is still scrabbling around in the realms of the possible. The whole point is to start with something and assemble it with something else to make it better, in order to do something that has never been done before. That’s what makes it possible to discover new things. Of course, the complexity does not need to be in physical objects: you might have well-assembled theories, models, patterns, belief systems, aesthetic sensibilities and so on that could be and probably will be part of the assembly. And, since we are not just talking about physical objects but methods, principles, patterns etc, this means you need to immerse yourself in the process – to do it, read about it, talk about it, try it. 

2) The tools of assembly

It is not enough to have a great tinker-space full of bits and pieces. You need tools to assemble them. Not just physical tools, but conceptual tools, skills, abilities, etc. You can buy, make, beg, borrow or steal the tools, but skills to use them take time to develop. Of course, one of the time-honoured and useful ways to do that is to tinker, so this works pretty well. Again, this is about immersion. You cannot gain skills unless you apply them, reflect on it, apply them again, in a never-ending cycle.

There is a flip side to this though. If you get to be too skillful then you start to ignore things that you have discovered to be irrelevant, and irrelevant things aren’t always as irrelevant as they seem. They are only irrelevant to the path you have chosen to tread. Treading multiple paths is essential so, once you become too much of an expert, it is probably time to learn new skills. It is hard to know when you are too much of an expert. Often, the clue is that someone with no idea about the area suggests something and you laughingly tell them it cannot be done. Of course it can. This is technology. It’s about invention. You are just too smart to know it.

Being driven by your tools (including skills) is essential and a vital part of the methodology – it’s how the adjacent possible reveals itself. But it’s a balance. Sometimes you go past an adjacent possible on your way and then leave it so far behind that you forget it is there at all. It sometimes takes a beginner to see things that experts believe are not there. It can be done in all sorts of ways. For example, I know someone who, because he does not want to be trapped by his own expertise, constantly retunes his guitar to new tunings, partly to make discoveries through serendipity, partly to be a constant amateur. But, of course, a lot of his existing knowledge is reusable in the new context. You do not (and cannot) leave expertise behind when learning new things – you always bring your existing baggage. This is good – it’s more junk to play with. The trick is to have a ton of it and to keep on adding to it.

3) The problem space

While simply playing with pieces can get you to some interesting places, once you start to see the possibilities, tinkering soon becomes a problem-solving process and, as you follow a lead, the problem becomes more and more defined, almost always adding new problems with each one solved. Being immersed in a problem space is crucial, which tends to make tinkering a personal activity, not one that lends itself well to formally constructed groups. Scratching your own itch is a pretty good way to get started on the tinkering process because, having scratched one itch, it always leads to more or, at least, you notice other itches as you do so.

If you are scratching someone else’s itch then it can be too constraining. You are just solving a known problem, which seldom gets you far beyond the possible and, if it does, your obligations to the other person make it harder for you to follow the seam of gold that you have just discovered along the way that is really the point of it. It’s the unknown problems, the ones that only emerge as we cross the border of the adjacent possible, that matter here. Again, though, this is a balance. A little constraint can help to sustain a focus and doing something that is not your own idea can spark serendipitous ideas that turn out to be good.

Just because it is not really a team process doesn’t mean that other people are not important to it. Talking with others, exchanging ideas, gaining inspiration, receiving critique, seeing the world through different eyes – all this is very good. And it can also be great to work closely with a small number of others, particularly in pairs – XP relies on this for its success. A small number of people do not need to be bogged down with process, schedules, targets, and other things that get in the way of effective tinkering, can inspire one another, spot more solutions, and sustain motivation when the going gets rough. 

The Structural Space

One of the points of bricolage is that it is structured from the bottom up, not the top down. Just because it is bottom-up structure does not mean it is not structure. This is a classic of example of shaping our tools and our tools shaping us (as McLuhan put it), or shaping our dwellings while our dwellings shape our lives (as Churchill put it a couple of decades earlier). Tinkering starts with forms that influence what we do with them, and what we do with them influences what we do next – our creations and discoveries become the raw material for further creations and discoveries. Though rejecting deliberate structured design processes, I have toyed with and tried things like prototyping, mock-ups and sketches of designs, but I have come to the opinion that they get in the way – they abstract the design too much. What matters in bricolage is picking up pieces and putting them together. Anything beyond vague ideas and principles is too top-down. You are no longer talking with the space but with a map of the space, which is not the same thing at all.

Efficiency

One of the big problems with tinkering is that it tends to lead to highly inefficient design, from an engineering perspective. Part of the reason for that is that path dependencies set in early on. A bad decision early can seriously constrain what you do later. One has only to look at our higher education systems, the result of massively distributed large scale tinkering over nearly a thousand years, to see the dangers here. The vast majority of what we continue to do today is mediaeval in origin and, in a lot of cases, has survived unscathed, albeit assembled with a few other things along the way.

Building from existing pieces can limit the damage – at least you don’t have to pull everything apart if it turns out that it is not a fruitful path. It is also very helpful to start with something like Lego, that is designed to be fitted together this way. Most of my work during my sabbatical has involved programming using the Elgg framework, which is very elegantly designed so that, as long as you follow the guidelines, it naturally forms into at least a decent outline structure. On the other hand, as I have found to my cost, it is easy to put enough work into something that it makes it very discouraging when you to have to start again. As the example of educational systems shows, some blocks are so foundational and deeply linked with everything else, that they affect everything that follows and simply cannot be removed without breaking everything.

Working together

Tinkering is quite hard to do in teams, apart from as sounding boards for reflection on a process already in motion. It is instructive to visit LegoLand to see how it can work, though. In the play spaces of LegoLand one sees kids (and more than a few adults) working alone on building things, but they are doing so in a very social space. They talk about what they are doing, see what others are doing and, sometimes, put their bits of assemblies together, making bigger and more complex artefacts. We can see similar processes at work in GitHub, a site where programmers, often working alone, post projects that others can fork and, through pull-requests, return in modified form to their originators or others, with or without knowing them or ineracting with them in any other way. It’s a wonderful evolutionary tinker-space. If programs are reasonably modular, people can work on different pieces independently, that can then be assembled and reassembled by others. Inspiration, support, patterns of thinking and problem solving, as well as code, flow through the system. The tinkering of others becomes a part of your own tinker-space.  It’s a learning space – a space where people learn but also a space that learns. The fundamental social forms for tinkering are not traditional, purpose-driven, structured and scheduled teams (groups), but networks and, more predominantly, sets of people connected by nothing but shared interest and a shared space in which to tinker.

Planning

As well as resulting in inefficient systems, tinkering is not easy to plan. At the start, one never knows much more than the broad goal (that may change or may not even be there at all) and the next steps. You can build very big systems by tinkering (back to education again but let’s go large on this and think of the whole of gaia) but it is very hard to do so with a fixed purpose in mind and harder still to do so to a schedule. At best, you might be able to roughly identify the kind of task and look to historical data to help get some statistical approximation of how long it might take for something useful to emerge.

A corollary of the difficulty of planning (indeed, that it is counter-productive to do so) is that it is very easy to be thrown off track. Other things, especially those that involve other people that rely on you, can very quickly divert the endeavour. At the very least, time has to be set aside to tinker and, come hell or high water, that time should be used. Tinkering often involves following tenuous threads and keeping many balls in the air at once (mixing metaphors is a good form of tinkering) so distractions are anethema to the effective tinkerer. That said, coming up for a breath of air can remind you of other items in the tinker-chest that may inspire or provoke new ways of assembling things. It is a balance.

Evolution, not design

Naive creationists have in the past suggested that the improbability of finding something as complex as even a watch, let alone the massively more complex mechanisms of the simplest of organisms, means that there must be an intelligent designer. This is sillier than silly. Evolution works by a ratchet, each adaptation providing the basis for the next, with some neat possibilities emerging from combinatorial complexity as well. Given enough time and a suitable mechanism, exponentially increasingly complex systems are not just possible put overwhelmingly probable. In fact, it would be vastly more difficult to explain their absence than their existence. But they are not the result of a plan. Likewise for tinkering with technologies. If you take two complex things and put them together, there is a better than fair chance that you will wind up with something more complex that probably does more than you imagined or intended when you stuck them together.  And, though maybe there is a little less chance of disaster than the random-ish recombinations of natural evolution, the potential for the unexpected increases with the complexity. Most unexpected things are not beneficial – the bugs in every large piece of software attest to that, as do most of my attempts at physical tinkering over the course of my lifetime. However, now and then, some can lead to more actual possibles. The adjacent possible is what might happen next but, in many cases, changes simply come with baggage. Gould calls these exaptations – they are not adaptations as such, but a side-effect or consequence of adaptation. Gould uses the example of the Spandrels of St Marco to illustrated this point, showing how the structure of the cathedral of St Marco, with its dome sitting on rounded arches, unintentionally but usefully created spaces where they met that proved to be the perfect place to put images of saints – in fact, they seem made for them. But they are not – the spaces are just a by-product of the design that were coopted by the creators of the cathedral to a useful purpose. A lot of systems work that way. It is the nature of their assembly to create both constraints and affordances, path dependencies and patterns early on deeply defining later growth and change. Effective tinkering involves using such spandrels, and that means having to think about what you have built. Thinking deeply.

The Reflection Space

Just tinkering can be fun but, to make it a useful research process, it should involve more than just invention. It should also involve discovery. It is essential, therefore, that the process is seen as one of reflective dialogue with the creations we make. Reflection is not just part of an iterative cycle – it is embedded deeply and inextricably throughout the process. Only if we are able to constructively think about what we are doing as well as what we have done can this generate ideas, models, principles and foundations for further development. It is part of the dialogue with the objects (physical, conceptual, etc) that we produce and, perhaps even more importantly, it is the real research output of the tinkering process. Reflection is the point at which we discover rather than just invent. In part it is to think about the meaning and consequence, in part to discover the inevitable exaptions, in part to spot the next adjacent possible. This is not a simple collaboration. Much of the time we argue with the objects we create – they want to be one way but we want them to be another and, from that tension, we co-create something new.  

We need to build stories and rich pictures as much as we need to build technologies. Indeed, it doesn’t really matter that much if we fail to produce any useful artefact through tinkering, as long as the stories have value.  From those stories spin ideas, inspirations, and repeatable patterns. Stories allow us to critique what we have done and learn from it, to see it in a broader context and, perhaps, to discover different contexts where the ideas might apply. And, of course, these stories should be shared, whether with a few friends or the world, creating further feedback loops as well as spreading around what we have discovered.

Stories don’t have to be in words. Pictures are equally and often more useful and, often most useful of all, the interactions with our creations can tell a story too. This is obviously the case in things like games, Arduino projects or interactive site development but is just as true of making things like furniture, accessories and most of the things that can be made or enhanced with Sugru.

Here are two brief stories that I hope begin to reveal a little of what I mean.

A short illustrative story

Early in my sabbatical I wrote one Elgg plugin that, as it emerged, I was very pleased with, because it scratched an itch that I have had for a long time. It allowed anyone to tag anything, and for duplicate tags used by different people to be displayed as a tag cloud instead of the normal list of tags that comes with a post. This was an assembly of many ideas, and was a conversation with the Elgg framework, which provided a lot of the structure and form of what I wanted to achieve. In doing it, I was learning how to program in Elgg but, in shaping Elgg, I was also teaching it about the theories that I had developed over many years. If it had worked, it would have given me a chance to test those theories, and the results would probably have led to some refinements, but that was really a secondary phase of the research process and not the one that I was focusing on.

Before any other human being got to use the system, the research process was shaping and refining the ideas. With each stage of development I was making discoveries. A big one was the per-post tag cloud. My initial idea had simply been to allow people to tag one another’s posts. This would have been very useful in two main ways. Firstly, it would give people the chance to meaningfully bookmark things they had found interesting. Rather than the typical approach of putting bookmarks into organized hierarchies, tags could be used to apply faceted categorizations, allowing posts to cross hierarchical boundaries easily and enabling faceted classification of the things people found interesting. Secondly, the tags would be available to others, allowing social construction of an ontology-like thing, better search, a more organized site. Tags are already very useful things but, in Elgg, they are applied by post authors and there are not enough of them for strong patterns to develop on their own in any but quite large systems. One of the first things I realized was that this meant the same tag might be used for the same post more than once.  It was hard to miss in fact, because what I saw when I ran the program was multiple tags for each post – the system I had assembled was shouting at me. Having built a tag cloud system in the 1990s before I even knew the word ‘tag’ let alone ‘tag cloud’ I was primed to spot the opportunity for a tag cloud, which is a neat way to give shape and meaning to a social space. Individually, tags categorize into binary categories. Collectively, they become fuzzy and scalar – an individual post can be more of one tag than another, not because some individual has decided so, but because a crowd has decided so. This is more than a folksonomy. It is a kind of collaborative recommender system, a means to help people recognize not just whether something is good or bad but in what ways it is good or bad. Already, I was thinking of my PhD work which involved fuzzy tags I called ‘qualities’ (e.g. ‘good for beginners’, ‘comprehensive’, ‘detailed’, etc) that allowed users of my CoFIND system not just to categorize but to rate posts, on multiple pedagogical dimensions. Higher tag weight is an implicity proxy for saying that, in the context of what is described by this tag, the post has been recommended. As I write this (writing is great tinkering – this is the power of reflection) I realize that I could explicitly separate such tags from Elgg’s native tags, which might be a neat way to overcome the limitations of the system I wrote about 15 years ago, that was a good idea but very unusable. Anyway…

It worked like a dream, exactly as I had planned, up to the point that I tried to allow people to see the things they had tagged, which was pretty central to the idea and without which the whole thing was pretty pointless: it is highly improbably that individuals would see great value in tagging things unless they could use those tags to find and organize stuff on the site. As it turns out, the Elgg developers never thought tags might be used this way, so the owner of a tag is not recorded in the system. The person that tags a post is just assumed to be the owner of the post. I’m not a great Elgg developer (which is why I did not realise this till it was too late) but I do know the one cardinal rule – you never, ever, ever mess with the core code or the data model. There was nothing I could do except start again, almost completely from scratch. That was a lot of work – weeks of effort. It was not entirely wasted – I learned a lot in the process and that was the central purpose of it all. But it was very discouraging. Since then, as I have become more immersed in Elgg, my skills have improved. I think I can now see roughly how this could be made to work. The reason I know this is because I have been tinkering with other things and, in the process, found a lightweight way of using relationships to link individuals and objects that, in the ways that matter, can behave much like tags. Now that I have the germ of an idea about how to make this pedagogically powerful, hopefully I will have time to do that. 

Another illustrative story

One of my little sabbatical projects (that actually it turned out to be about the biggest, and it’s not over yet) was to build an OpenBadge plugin. This was actually prompted by and written for someone else. I would not thought of it as a good itch to scratch because I happen to know something about badges and something about learning and, from what I have seen, badges (as implemented so far) are at best of mixed value in learning. In the vast majority of instances that I have seen them used, they can be at the very best as demotivating as they are motivating. Much of the time it is worse than that: they turn into extrinsic proxies that divert motivation away from learning almost entirely. They embed power structures and create divisions. From a learning perspective, they are a pretty bad idea. On the plus side, they are a very neat way to do credentials which is great if that is what you are aiming for, opening up the potential for much more interesting separation of teaching and accreditation, diverse learning paths, and distributed learning, so I don’t hate them. In fact, I quite like them. But their pedagogical risks mean that I don’t love them enough to have even considered writing a plugin that implements them.

Despite reservations, I said I would do it. It didn’t seem like a big task because I reckoned I could just lightly modify one of a couple of existing (non-open) badge plugins that had already been written for Elgg.  I also happened to have some parts lying round – my pedagogical principles, the Elgg framework, the Mozilla OpenBadge standard documentation, various code snippets for implementing OpenBadges – that I could throw together. Putting these pieces together made me realize early on that social badging could be a good idea that might help overcome several of my objections to their usual implementations. Because of the nature of Elgg, the obvious way to build such a plugin would be such that anyone could make a badge, and anyone could award one, making use of Elgg’s native fine-grained bottom-up permissions. This meant that the usual power relationships implied in badging would not be such a problem. This was an interesting start.

Because Elgg has no roles in its design (apart from a single admin role for the site builder and manager), and so no explicit teaching roles, this could have been potentially tricky from a trust perspective – although its network features would mean you could trust awards by people you know, how would you trust an award from someone you don’t know and who is not playing a traditional teacher role in a power hierarchy? Even with the native Elgg option to ‘recommend’ a badge (so more people could assert its validity) this could become chaotic. But my principles told me that teacher control is a bad thing so I was not about to add a teacher role.

After tossing this idea around for a few minutes, I came up with the idea of inheritable badges – in other words, a badge could be configured so that you could only award a badge if you had received it yourself. In an instant, this began to look very plausible. If you could trace the badge to someone you trust (eg. a teacher or a friend or someone you know is trustworthy), which is exactly what Elgg would make possible by default, then you could trust anyone else who had awarded the badge to at least have the competence that the badge signifies, and so be more likely to be able to accurately recognize it in someone else. This was neat – it meant that accreditation could be distributed across a network of strangers (as in a MOOC) without the usual difficulties of the blind accrediting the blind that tend to afflict peer assessment methods in such contexts. Better still, this is a great way to signify and gain social capital, and to build deeper and richer bonds in a community of strangers. It is, I think, among the first scalable approaches to accreditation in a connectivist context, though I have not looked too deeply into the literature, so stand to be corrected.

Later, as I tinkered and became immersed in the problem, thinking how it would be used, I added a further option to let a badge creator specify a prerequisite award (any arbitrarily chosen badge) that must be held before a badge could be awarded. As well as allowing more flexibility than simple inheritance, this meant that you could introduce roles by the back door if you wished, by allowing someone to award a ‘teacher’ badge or similar, and only allowing people holding that badge to make awards of other badges.  I then realized this was a generalized case of the same thing as the inheritance feature, so got rid of the inheritance feature and just added the option to make a prerequisite of the current badge itself. It is worthy of note that this was quite difficult to do – had I planned it from the start, it would have been trivial, but I had to unpick what I had done as well as build it afresh.

Social badging, peer assessment, scalable viral accreditation, social capital, motivation  – this was looking cool. Furthermore, tinkering with an existing framework suggested other cool things. By default, it was a lot easier to build this if people could award badges to themselves. The logical next step would have been to prevent them from doing this but, as I saw it working, I realised self-badging was a very good idea! It bothered me for a moment that it might be a bit confusing, at least, not to mention appearing narcissistic if people started awarding themselves badges. However, Elgg posts can be private, so people giving themselves badges would not have to show them to others. But they could, and that could be useful. They could make a learning contract with someone else or a group of people, and allow them to observe, thus not only improving motivation and honesty, but also building bonding social capital. So, people could set goals for themselves and award themselves badges when they accomplished them, and do so in a safe social context that they would be in control of. It might be useful in many self-directed learning contexts. 

These were not ideas that simply flowed in my head from start to finish: it was a direct result of dialogue with what I was creating that this came about, and it could only have done so because I already had ideas and principles about things like portfolios, learning contracts and social learning floating around in my toolkit, ready to be assembled. I did include the admin option to turn off self-awarding at a system level in case anyone disagreed with me, and because I could imagine contexts where it might get out of hand. I even (a little reluctantly) made it possible to limit badge awarding to admins only, so that there could be a ‘root’ badge or two that would provide the source of all accreditation and awarding. Even then, it could still be a far more social approach to accreditation than most, making expertise not just something that is awarded with an extrinsic badge, but also something that gives real power to its holder to play an important role in a learning community.

This is not exactly what my sponsors asked for: they wanted automation, so that an administrator could set some criteria and the system would automatically award badges when those criteria had been met.  Although I reckon my social solution meets the demand for scalability that lay at the heart of that request, I realized that, with some effort, I could assemble all of this with a karma point plugin that I happened to have in my virtual toolshed in order to enable automated badge awarding for things like posting blogs, etc. Because there was no obvious object for which such an award could be given as it could relate to any arbitrary range of activities, I made the object providing evidence to be the user’s own profile. Again, this was just assembling what was there – it was an adjacent possible, so I took it. I could, if I had not been lazy, have generated a page displaying all of the evidence, but I did not (though I still might – it is an adjacent possible that might be worth exploring). And so, of course, now it is possible to award a badge to a user, rather than for a specific post which, though not normally a good idea from a motivation perspective, could have a range of uses, especially when assembled with the tabbed profile we built earlier (what I refer to in academic writings as a ‘context switcher’ and that can be used as a highly flexible portfolio system).

These are just a sample of many conversations I had with the tools and objects that were available to me. I influenced them, they influenced me. There were plenty of others – exaptions like my discovery that the design I had opted for, which made awards and badges separate objects, meant that I had a way of making awards persistent and not allowing badge owners to sneakily change them afterwards, for example, thus enhancing trust in the system. Or that the Elgg permissions model made it very simple to reliably assert ownership, which is very important if you are going to distribute accreditation over multiple sites and systems. Or that the fact that it turned out to be an incredibly complex task to make it all work in an Elgg Group context was a blessing because I therefore looked for alternatives, and found that the pre-requisite functionality does the job at least as well, and much more elegantly. Or that the Elgg views system made it possible to fairly easily create OpenBadge assertions for use on other sites. The list goes on. 

It was not all wonderful though. Sometimes the conversation got weird. My plan to start with an existing badge plugin quickly bit the dust. It turns out that the badge plugins that were available were both of the kind I hate – they awarded badges to individuals, not for specific competences. To add injury to injury, they could be awarded only by the administrator, either automatically through accrued points or manually. This was exactly the kind of power structure that I wanted to get away from. From an architectural perspective, making these flawed plugins work the way I wished would have been much harder than writing the plugin from scratch. However, in the spirit of tinkering, I didn’t start completely from scratch. I looked around for a plugin that would do some of the difficult stuff for me. After playing with a few, I opted standard Elgg Files plugin, because that ought to have made light work of storing and organizing the badge images. In retrospect, maybe not the best plan, but it was a starting point. After a while I realized I had deleted or not used 90% of the original plugin, which was more effort than it was worth. I also got stuck in a path dependency again, when I wanted to add multiple prerequisites (ie you could specify more than one badge as a prerequisite) : by that time, my ingenious single-prerequisite model was so firmly embedded that it would have taken more than a solid week to change it. I did not have the energy, or the time.  And, relatedly, my limited Elgg skills and lack of forward planning meant that I did not always divide the code into neatly reusable chunks. This still continues to cause me trouble as I try to make the OpenBadge feature work. Reflecting on such issues is useful – I now know that multiple inheritence makes sense for this kind of system, which would not have occurred to me if I hadn’t built a system with a single-prerequisite data model. And I have a better idea about what kind of modularity works best in an Elgg system.

Surfing the adjacent possible

Like all stories worthy of the name, my examples are highly selective and probably contain elements of fiction in some of the details of the process. Distance in time and space changes memories so I cannot promise that everything happened in the order and manner presented here – it  was certainly a lot more complicated, messy and detailed than I have described it to be. I think this fictionlizing is crucial, though. Objective reporting is exactly not what is needed in a bricolage process. It is the sense-making that matters, not religious adherence to standards of objectivity. What matters are the things we notice, the things we reflect on and things we consider to be important. Those are the discoveries. 

This is a brief and condensed set of ten of the main principles that I think matter in effective tinkering for research:

  1. do not design – just build
  2. start with pieces that are fully formed
  3. surround yourself with both quantity and diversity in tools, materials, methods, and perspectives
  4. dabble hard – gain skills, but be suspicious of expertise
  5. look for exaptations and surf the adjacent possible
  6. avoid schedules and goals, but make time and space for tinkering, and include time for daydreaming
  7. do not fear dismantling and starting afresh
  8. beware of teams, but cultivate networks: seek people, not processes
  9. talk with your creations and listen to what they have to say
  10. reflect, and tell stories about your reflections, especially to others

As I read these ideas it strikes me that this is the very antithesis of how research, at least in fields I work in, is normally done and that it would be extremely hard to get a grant for this. With a deliberate lack of process control, no clear budgets, no clear goals, this is not what grant awarders would normally relish. Whatever. It is still worth doing.

Tinkering as a research methodology offers a lot – it is a generative process of discovery that builds ideas and connections as much as it builds objects that are interesting or useful. It is far from being a random process but it is unpredictable. That is why it is interesting. I think that some aspects of it resemble systematic literature review: the discovery and selection of appropriate pieces to assemble, in particular, is something that can be systematized to some extent and, just as in a literature review, once you start with a few pieces, other pieces fall naturally into place. It is very closely related to design-based research and action research, with their formal cycles and iterative processes, although the iteration cycle in tinkering is far finer grained, it is not as rigid in its requirements, and it deliberately avoids the kind of abstractions that such methodologies thrive on. It might be a subspecies though. It definitely resembles and can benefit from soft systems methodologies, because it is the antithesis of hard systems design. Rich pictures have a useful role to play, in particular, though not at the early stages they are used in soft systems methods. And, unlike soft systems, the system isn’t the goal.

Finally, tinkering is not a solution to everything. It is a means of generating knowledge. On the whole, if the products are worthwhile, then they should probably feed into a better engineered system. Note, however, that this is not prototyping. Though products of tinkering may sometimes play the role of a prototype at a later stage in a product cycle, the point of the process is not to produce a working model of something yet to come. That would imply that we know what we are looking for and, to a large extent, how we will go about achieving it. The point is to make discoveries. 

This is not finished yet. It might just turn out to be a lazy way to do research or, perhaps, just another name for something that is already well pinned down. It certainly lacks rigour but, since the purpose is generative, I am not too concerned about that, as long as it works to produce new knowledge. I tinker on, still surfing the adjacent possible.

Have we all been duped by the Myers-Briggs test?

Not all of us, no.

But, if you reckon there is any validity at all to personality tests, learning styles and all such pseudo-scientific hokum the answer is ‘yes’, you have been duped. This digestible and brief article presents a small sample of the compelling evidence.

Address of the bookmark: http://fortune.com/2013/05/15/have-we-all-been-duped-by-the-myers-briggs-test/

Three glimpses of a fascinating future

I’d normally post these three links as separate bookmarks but each, which have popped up in the last few days, share a common theme that is worth noting:

http://singularityhub.com/2014/09/04/experimental-rat-brain-fighter-pilot-may-yield-insights-into-how-the-brain-works/

In this, a neural network made out of the brain cells of a rat is trained to fly a flight simulator.

http://news.sky.com/story/1329954/world-first-as-message-sent-from-brain-to-brain

In this, signals are transmitted directly from one brain to another, using non-invasive technologies (well – if you can call a large cap covered in sensors and cables ‘non-invasive’!)

http://singularityhub.com/2014/09/03/neuromodulation-2-0-new-developments-in-brain-implants-super-soldiers-and-the-treatment-of-chronic-disease/

This reports on a DARPA neuromodulation/neuroaugmentation project to embed tiny electronic devices in brains to (amongst other things) cure brain diseases and conditions, augment brain function and interface with the outside world (including, presumably, other brains). This article contains an awesome paragraph:

“What makes all of this so much more interesting is the fact that, unlike all the other systems of the body, which tend to reject implants, the nervous system is incorporative—meaning it’s almost custom-designed to handle these technologies. In other words, the nervous system is like your desktop computer— as long as you have the right cables, you can hook up just about any peripheral device you want.”

I’m both hugely excited and deeply nervous about these developments and others like them. This is serious brain hacking. Artificial intelligence is nothing like as interesting as augmented intelligence and these experiments show different ways this is beginning to happen. It’s a glimpse into an awe-inspiring future where such things gain sophistication and ubiquity. The potential for brain cracking, manipulation, neuro-digital divides, identity breakdown, privacy intrusion, large-scale population monitoring and control, spying, mass-insanity and so on is huge and scary, as is the potential for things to go horribly wrong in so many new and extraordinary ways. But I would be one of the first to sign up for things like augmenting my feeble brain with the knowledge of billions (and maybe giving some of my knowledge back in return), getting to see the world through someone else’s eyes or even just being able to communicate instantly, silently and unambiguously with loved ones wherever they might be. This is transhumanity writ large, a cyborg future where anything might happen. Smartphones, televisions, the web, social media, all the visible trappings of our information and communication technologies that we know now, might very suddenly become amusing antiques, laughably quaint, redundant and irrelevant. A world wide web of humans and machines (biological and otherwise), making global consciousness (of a kind, at least) a reality. It is hard but fascinating to imagine what the future of learning and knowledge might be in the kind of super-connected scenario that this implies. At the very least, it would disrupt our educational systems beyond anything that has ever come before! From the huge to the trivial, everything would change. What would networked humans (not metaphorically, not through symbolic intermediaries, but literally, in real time) be like? What would it be like to be part of that network? In what new ways would we know one another, how would are attitudes to one another change? Where would our identities begin and end? What would happen if we connected our pets? What would be the effects of a large solar flare that wiped out electronic devices and communication once we had grown used to it all? Everything blurs, everything connects. So very, very cool. So very, very frightening.

Social Media and the 'Spiral of Silence'

Fascinating but flawed Pew report finding that people are not inclined to share controversial views (at least about Edward Snowden) on social media, and far less so than when talking face-to-face. Moreover, this carries over into face-to-face interactions. The ‘spiral of silence’ in the title is to do with how social media habits become social habits in our physical lives. It’s an evocative phrase that suggests harm is being caused. At least, that is how it is presented and how the press are reporting on it. I’m not convinced. Not at all.

The obvious findings

 

That people are reluctant to stir controversies on social media is not surprising. Most general-purpose social networking systems (which is the subset of social media that the researchers were looking at) indiscriminately connect us and our posts with everyone in our online social network on a given system. This is quite unlike face-to-face converstations where we are intimately aware of our audience and always addressing a smaller subset of the whole, so of course we are aware that some of our audience may not appreciate or care about those opinions. We therefore tend to express them more circumspectly on social media than we do in places where we can better control who we are talking with. This is especially true now that most of us have learned that things are easily misinterpreted online when expressed as text. Moreover, face-to-face, there is little chance that our comments may be happened upon by people some time in the future who are not yet even in our network. This particular problem equally affects social networking systems like the Landing or Google + that make a big point of the ability of members to selectively choose the circles of individuals with whom they share. Given the diversity of the audience and permanence of the result,  it is natural not only to wish not to offend or spark and argument, but also to not want to appear dumb, and to have that dumbness on (semi) permanent record. Face to face, we can correct ourselves when shown to be fools, and no one thinks the less of us but, online, our original foolishness has the same archival permanence as our correction. It is perfectly reasonable to be wary. Furthermore, the the particular issue that Pew chose to investigate (Snowden’s revelations) is far from neutral to the questions they were asking. Thinking about the Snowden/NSA case would likely encourage subjects to focus on the other shadier and malevolent people that might be looking at their posts without their consent or knowledge, not to mention on concerns about privacy on social media in general. Given the nature of the controversy, the survey questions give a reminder that opinions expressed on the subject online might well be used against us. The fact that the study relied upon self-reporting therefore makes it less reliable than it might have been about a less Internet-related topic.

Where it gets interesting

So far so obvious. However, the study goes further. The findings appear to show that social media users are more sensitive to the opinions and beliefs of others, both online and off, and are reluctant to share beliefs that differ from those of social media contacts offline as well as on. This is interesting. The study goes on to say that:

“This suggests a spiral of silence might spill over from online contexts to in-person contexts, though our data cannot definitively demonstrate this causation. It also might mean that the broad awareness social media users have of their networks might make them more hesitant to speak up because they are especially tuned into the opinions of those around them.” 

So, the suggestion is that engagement in social media sensitizes us to others in what might be seen as quite positive ways – social media users care more about what other people think. The downside of this is the fact that we are therefore less likely to challenge things that we see as wrong, less inclined to express dissent, and this may have deep unforeseen consequences for society as a whole. In effect, social media are making us all a little more Canadian! Well, maybe. The researchers laudably note that they cannot demonstrate this causation though, unfortunately and with far less good conscience, they put ‘spiral of silence’ into the title, suggesting that this is what they have actually found and making sensationalist headlines considerably more likely. Bad move.   

There is another interpretation.

I was surprised to discover that “an internet user is 1.63 times more likely to have obtained even a little news on the Snowden-NSA revelations from radio and television than a non-internet user.” So, not only are Internet users more sociable than non-users in real life, they also pay more attention to broadcast sources. This is particularly true of Twitter and Instagram users (3.67 and 4.02 times more likely than a non Internet user, respectively) and less true (though still true) of Pinterest and LinkedIn users.

Though it does discuss possible reasons for inter-media differences, the report does not provide much speculation on the reasons for the internet-user/non-user divide. I speculate (in Devil’s advocate mode) that it might be because it is increasingly hard to find people that are not Internet users, especially in America where this survey was conducted. In this particular case only 456 of 1801 participants were not Internet users, which is surprisingly high at around 25%, but still sufficiently small to make one suspicious. In a good number of cases the reasons for not being Internet-connected are undoubtedly economic, which in itself makes for a demographic that is far from representative. Also, there is probably some significant skewing due to the fact that those who intentionally (whether through fear or deliberate action) divorce themselves from the world of the Internet, even though they could afford it, may have a different attitude to electronic media in general. Either way, this is not comparing like with like. As an overall demographic, non-Internet users are likely becoming increasingly unusual and non-representative of the population as a whole, so perhaps willingness to discuss political hot potatoes is sympomatic of the same thing or things that prevent them from engaging online in the first place. It might well be that what we see on social media has always been the norm and that the skewing in this case is simply revealing that those who do not use the Internet are, on average, different, and they always have been. Maybe they care less what others think or feel. Or maybe their being offline proves that they are more critically atuned. Maybe (and very likely) the topic chosen is one that reinforces and confirms their deep suspicion of the Internet, about which they feel strongly enough both to avoid it and to make their feelings known to others. Whatever, the chances are that there are some common differences.

Equally, the fact that there are also differences between people that use different social media might be due to the kinds of socialization the systems support, rather than differences caused by the media themselves. For instance, most of us choose LinkedIn for professional contacts and information, while we use other sites for different kinds of social activity. People are almost certainly more drawn to social media that support how they tend to want to behave than those that don’t, notwithstanding the strong peer pressure and network effects that make some of them join in anyway. And, just because they join them, doesn’t mean that they use each of them for the same purposes. Those of us that use multiple social media tend to use them differently, with different (often overlapping) networks and different intents. Different levels of political debate are likely not caused by the social media and the networks that inhabit them: we choose those networks because of those differences.

I am not suggesting that any of my speculations are better than the conclusions drawn by the researchers or commentators on the research in the International press (that are, not unexpectedly, very selective about the findings they report on). The point is that this research does not appear to prove my speculations false.  I’m almost sure that the researchers are correct in thinking that different social media reinforce different behaviours, that we are affected by norms and behaviours of others on social media, and that our behaviour in social media has an effect on our behaviour in the physical world. It would be exceedingly odd if it did not. But I’m not at all sure that these results show that. To prove that point I think it would be a minimal requirement to at least do a longitudinal study that shows behavioural changes when people engage in new social media, rather than a snapshot of how they behave now in the context of a topic that is deeply relevant to social media use. It is irresponsible to suggest causation where all that has been found is correlation, with very good grounds for suspecting other causal factors play a significant role and the methodology itself introduces bias. That’s a crucial flaw and it’s a pity, because there is plenty of good information in this report and some thought-provoking findings. It does not need a gutter-press friendly veneer.

Address of the bookmark: http://www.pewinternet.org/files/2014/08/PI_Social-networks-and-debate_082614.pdf

Komar and Melamid: Most Wanted and Least Wanted Paintings

I don’t know why it took me so long to find this, but I’m very glad I did. This is a wonderful art project dating back to the mid 90s in which Vitaly Komar and alex Melamid asked people about their aesthetic preferences and taste in painting in order to discover what ‘people’s art’ would look like, and then they painted it. They did this for several populations around the world. The paintings, at http://awp.diaart.org/km/painting.html, are remarkable and fascinating, but they are not the art work here. The project challenges analytic approaches to design at a fundamental and quite unsettling level.

The lessons are important to any creative endeavour, including to big ones that matter to me personally and professionally like teaching and education, and computer system and interaction design. They matter every time we base our designs and creative activities on feedback, opinion polls, course evaluations, learning styles, analytics information and similar quantification or classification techniques. The problem is not in finding out such things – that is always interesting. The problem is interpreting and using them to drive design and method, without reflection or critique, especially when we lie to ourselves that our interpretation is therefore in some way objective. But the paintings articulate this and the complex loops of meaning that emerge far more clearly than words ever could. The words are good though, and are as much a part of the artwork as the paintings themselves. As Melamid puts it, provocatively:

It’s interesting: we believe in numbers, and numbers never lie. Numbers are innocent. It’s absolutely true data. It doesn’t say anything about personalities, but it says something more about ideals, and about how this world functions. That’s really the truth, as much as we can get to the truth. Truth is a number.”

Address of the bookmark: http://awp.diaart.org/km/intro.html

Expecting to teach enhances learning and organization of knowledge in free recall of text passages

Very interesting confirmation of something that all teachers know – that the best way to learn is to teach. This uses an experimental method that shows much less than it could and claims much more than it shows.  The researchers have simply shown better memory retention by learners in one particular task due to the expectation of having to teach others. But it’s still useful evidence that is supported by several educational theories and it helps to confirm the value of teachback. As they suggest (though apparently unaware that this is a widespread practice) pedagogies that make use of this phenomenon work well and are highly efficient.

Abstract:

The present research assessed the potential effects of expecting to teach on learning. In two experiments, participants studied passages either in preparation for a later test or in preparation for teaching the passage to another student who would then be tested. In reality, all participants were tested, and no one actually engaged in teaching. Participants expecting to teach produced more complete and better organized free recall of the passage (Experiment 1) and, in general, correctly answered more questions about the passage than did participants expecting a test (Experiment 1), particularly questions covering main points (Experiment 2), consistent with their having engaged in more effective learning strategies. Instilling an expectation to teach thus seems to be a simple, inexpensive intervention with the potential to increase learning efficiency at home and in the classroom.

Address of the bookmark: http://link.springer.com/article/10.3758/s13421-014-0416-z#page-1

Assessment in historical perspective

Fascinating article by Ben Wilbrink (1997) that traces the evolution of assessment approaches, mainly in higher education, from mediaeval times. In the process this offers some intriguing insights into how universities themselves, and the pedagogies with which we are familiar, evolved.

Address of the bookmark: http://benwilbrink.nl/publicaties/97AssessmentStEE.htm

On the Design of Social Media for Learning

A paper by me and Terry Anderson that draws ideas about soft and hard technologies and our model of social forms together.

Abstract: This paper presents two conceptual models that we have developed for understanding ways that social media can support learning. One model relates to the “social” aspect of social media, describing the different ways that people can learn with and from each other, in one or more of three social forms: groups, networks and sets. The other model relates to the ‘media’ side of social media, describing how technologies are constructed and the roles that people play in creating and enacting them, treating them in terms of softness and hardness. The two models are complementary: neither provides a complete picture but, in combination, they help to explain how and why different uses of social media may succeed or fail and, as importantly, are intended to help us design learning activities that make most effective use of the technologies. We offer some suggestions as to how media used to support different social forms can be softened and hardened for different kinds of learning applications.
 

Address of the bookmark: http://www.mdpi.com/2076-0760/3/3/378

I’ve completely moved to social media | Scobleizer

So, Robert Scoble has left the blogosphere. I’m not entirely sure in what sense his blog was not an instance of social media but I do know why this bothers me. It’s not just that he no longer owns his own space but that we don’t either. I am certainly not going to use Facebook to follow him – the company has neither his nor my interests in mind. I might catch the odd post via Twitter or Google+, but it will be lost in a sea of other things and won’t grab my attention, and any attempt I might make to organize and control the tide will be susceptible to the whims of the companies that own the sites, who are playing a much too large role in determining what I get to see in my particular filter bubble as it is.

If I’m going to be in a bubble then I want to be the one that makes it. The great thing about blogs is that they are distributed, not centralized, owned by individuals, not organizations. This is not just important to the individuals that they belong to, but to the individuals that read them, subscribe to them, aggregate them, remix them and learn from them. That’s why things like WordPressElgg (that runs this site) and Known (by Ben Werdemuller, who co-developed Elgg) matter more than all the glitzy social silos put together.

 

Address of the bookmark: http://scobleizer.com/?p=8494

Gordon Pask PDFs

A great collection of papers and even the odd full book by the late great Gordon Pask. His cybernetic theories of learning, especially in the form of conversation theory and the value of teachback in learning, have been very influential (notably through the work of Diane Laurillard) and deserve to be more so. His serialist/holist learning style theory is one of the few that I find even slightly compelling because it actually relates teaching to learning style though, like all the rest of the genre, it makes little sense apart from as a useful reminder that there are infinite different ways to teach the same thing. His systems views of learning are, on the other hand, unequivocally brilliant. Sometimes difficult reading, but the effort pays off.

Address of the bookmark: http://www.pangaro.com/pask-pdfs.html