I am very sad that such a useful report as this was intended for military use but this is a very well researched discussion of stigmergy in human systems that provides an excellent grounding for anyone interested in the area. However, it feels a bit like using the results of Nazi eugenics experiments: useful knowledge, immorally obtained.
Address of the bookmark: http://www.dtic.mil/cgi-bin/GetTRDoc?Location=U2&doc=GetTRDoc.pdf&AD=ADA440006
Excellent. One down, a few million to go, it’s time to end this barbaric, anti-learner practice. I exaggerate. Exams per se are not wrong and in some cases may be a very sensible way to accredit people – driving tests, for instance. I can even imagine ways that they might be constructively aligned with the learning intentions (sporting contests, for instance), though very rarely in an academic setting. But, like the lecture, it’s an idea of very limited applicability that has become a plague in our systems and it is high time that we had to provide a real, strong, learner focused justification for using them. And no, not the dumb old argument about knowing it is all their own work (palpable nonsense in most settings in higher education). And not the one about efficiency (whose?).
Address of the bookmark: http://harvardmagazine.com/2010/07/bye-bye-blue-books
I want to love Diaspora, I really do. It is entirely about an open, controllable and free social networking system. It is being created by ‘four talented young programmers’ (their words) who clearly have passion and enthusiasm, and its aspirations are quaint but highly admirable:
“We are 140-character ideas. We are the pictures of your cat. We are blog posts about the economy. We are the collective knowledge that is Wikipedia. The internet is a canvas – of which, we paint broad and fine strokes of our lives with. It is a forward extension of our physical lives; a meta-self comprised of ones and zeros. We are all that is digital: If we weren’t, the internet wouldn’t either.”
Sigh.
I want Diaspora to succeed. I share the ideals. I believe in the right of people to own their own data and data about themselves. I believe that that the only right way forward in this field is in distributed, modular and open technologies. I believe that there are many ways to do this and Diaspora might be able to exploit one or two of them.
And yet, ignoring for the moment the complete absence of anything tangible from the Diaspora team apart from a few chummy videos and vague hints they are working with a few familiar standards and protocols…
Mark Zuckerberg. Apparently he sees younger versions of himself in them and so has funded them. Actually, spooky though that is, I think the explanation is way more sinister than that. If (as I fear it will) it spectacularly fails or runs out of steam, the faithful lose a little more faith and Zuckerberg wins. If, as is also pretty likely, it slowly fragments and Balkanises, the effect is the same – and the opportunity to introduce a little Facebook integration poison to make that even more likely is one Zuckerberg will be unlikely to miss. If it is successful, then he has the ties and leverage to make Facebook an integral part of it all, which will allow him to claim both openness (ha) and revenue.
I think Zuckerberg must know that Facebook in its current form is cruising towards eventual meltdown. The brilliant cold exploitation of Reid’s Law and Metcalfe’s Law that makes it so successful is also what makes it unsustainable in the long term as long as it stays closed and centralised. It may have another half billion users to go before it finally breaks (right now it’s hard to see how without a lot of restructuring, but there are some very smart people working in that company who will probably find ways to forestall the inevitable collapse for some while longer) but, at some point, if it is to grow further it *has* to move to a more variegated and distributed model, to become part of a broader ecosystem with greater diversity and differentiation. If he can influence or maybe even control that ecosystem at the basic level of its virtual physics, he wins. Even if not, in the best case scenario that Diaspora gains traction and comes to compete or even dominate, the opportunity to study the enemy from the point of inception will put Facebook in a far stronger position to react and counter-attack.
I’d also love to know what they signed away to him when they took that money. I hope it was nothing.
There is another possible motivation for Zuckerberg’s apparent generosity though that is maybe the simplest: it diverts attention away from other initiatives that actually have good working code, have communities, have backing and have potential to succeed, such as:
and many others (e.g. 6D, Kopal, DiSo). While a few are only a little more advanced than Diaspora (that barely exists outside the hype), many are way further on and some, like OneSocialWeb, have serious backing.
We need the innovative and open ideas like those that drive these four young programmers. We need the ideas they are borrowing and using even more. We need systems that are both open and controlled by their users at every level. But I fear Diaspora may not be the answer. The only thing that really heartens me about the ludicrously overblown hype it is attracting is that it draws more attention to what is wrong with the centralised cloud models, helping to drive people into more diverse and trustworthy spaces over which they can have some confidence in control of their data and trust in the guardians of them.
Address of the bookmark: http://www.joindiaspora.com/2010/08/26/overdue-update.html
In the past I have written about tags to which we attach some value. Once upon a time in the late 1990s I called these qualities – a means of describing the things that we find valuable in a resource that do not fall neatly into yes-no tag categories: funny, good for beginners, complex, helpful and so on. In recent years I’ve been calling them scalar tags, to reflect the fact that they carry a scalar value or weighting.
We need these things for a variety of reasons. In the first place, as it turns out, many of the binary-category, definitional, taxonomic tags that we use on many social systems are really nothing of the kind – they often relate to our opinions and feelings towards the things we tag which, by and large, are not black and white (they are also often about things that are relative to us and our context – such as ‘my family’ but that’s another issue). On some sites as many as 30% of all tags used can be about subjective qualities of things. Secondly, they have a really great practical value: if tags carry a value then they can be used to rate things in multiple dimensions. Instead of the traditional ‘I like this’ or star ratings that simply suggest something is more or less good or bad, we can use scalar tags to describe in what ways we like them. Thus, we create a kind of disembodied user model of the aspects of ourselves that are important in relation to what we are tagging. This, as it happens, is mighty useful in an educational setting because liking a learning object or rating it highly is not really the problem: we want to know why it is liked, in what circumstances, for what purposes. Standard high-low ratings can be useful for things about which we have fairly consistent feelings such as movies, books, music and so on but the thing about learning is that it changes us. This means that what we valued when we were learning something no longer has any value to us because we have already learnt it (at least, that is often the case).
It occurred to me yesterday as I was blogging about sets that there is a much nicer term for this kind of thing than scalar tags: these are actually fuzzy tags. Fuzzy tags are of course ideally suited to being considered in fuzzy sets. Fuzzy tags are not categorisations as such, they are ways of attaching a value to a tag that reflects its degree of membership within a set of such tags.
Fuzzy tags are not unproblematic. It is fiendishly hard to create an interface for them, they are highly susceptible to the cold start phenomenon, it is difficult to find uses that give people a non-altruistic motive for using them, and it is hard to get the right balance between counting the number of tags and the values attached to them when presenting resources that have been tagged that way. Do you give prime real estate to those with a higher average value and, if so, how do you balance it so that a resource that has been rated highly by one person does not override one that has been rated even higher by some people but lower by others? Not even considering other problems like the fact people rate things relatively differently, issues of tag ambiguity, personalisation factors and much else besides, it’s a wicked problem with many viable solutions.
If we can crack this problem (I have had a fair number of cracks at it already) then it opens the door to some interesting ways of looking at collectives. At the moment, we think of collectives as being a kind of human-machine cyberorganism that is formed from the actions of the crowd which are then processed to create something that has agency in a social system. What comes in the first page or two of a Google search is an implicit recommendation by the collective, because of the ingenious PageRank algorithm that underpins it. The big tags in tag clouds tell us what the collective finds interesting and suggests to us that we might find it interesting too (and we do – we are about 3-4 times more likely to click a big tag in a tag cloud than a small one).
Apart from in a few experimental systems (I think I’ve built most of them) collectives are a combination of machine intelligence and human intelligence, at least when they work well – they can equally combine mob stupidity and machine ignorance when they work badly. I think they can be a lot more useful when they also capture the affective stuff – human feelings and opinions as well as intelligence. This is about more than just good or bad feelings: it is about things that say what it is that affects us and how we are affected, as well as how much we are affected by them. Fuzzy tags can give us richer folksonomies that reflect more of the diversity, hopes, interests and intentions of the crowd than simple taxonomic tags. Plus, ‘fuzzy tag’ is a really catchy name 🙂
Orkut is trying to catch up with Elgg – it looks mighty familiar! Elgg has been doing exactly this for several years. We are creating a toolset that will go much further than this in enabling us to project personas. All Orkut (and Elgg) are doing here is filtering content based on access rights, which is a good start in recognizing the importance of the different facades we portray to others in real life, but not going anywhere like far enough. Our new tools will allow you to customise the look and feel as well – in effect, allowing us to have a different home page for every grouping of people we care about. It’s still in development but, if they pass the tests and trials, the tools will be coming to Athabasca Landing before very long.
Address of the bookmark: http://www.readwriteweb.com/archives/new_version_of_googles_orkut_separates_business_fr.php?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+readwriteweb+%28ReadWriteWeb%29
If you are not involved in social computing, social network analysis, sociology or similarly network-focussed disciplines and interest groups, this is going to seem like a pretty odd thing to make a fuss about (surely this is all common sense) so you might want to look away now…
Of late I have been increasingly concerned that the field of social computing is becoming dominated by a single world-view. To an increasing extent, research in the area has become dominated by various forms of network analysis, almost completely excluding the ‘social’ part of the term and anything else that avoids talking about abstract connections. Sometimes it is taken to ludicrous extremes. The other day I reviewed a paper that purported to show a small world network structure in what were described as ‘communities’ of people whose only connection was that they had used the same tags to describe content they had uploaded. They had not tagged anyone else’s uploads, only their own. There was absolutely no interaction between individuals, even in a mediated or artefactual way. They were as much a network as all the people in the world that like cake.
I think nets are great. Network analysis is incredibly useful: it provides a powerful and flexible tool for understanding interactions between people and objects, lets us gain rich insights into complex interacting and dynamic systems. But nets are only a small part of what makes the field of social computing interesting.
The main part of social computing is, of course, made up of people and all their multifaceted wonderfulness (gotta love em), which should make up the chief object of study in any rational universe but that are generally simply treated as nodes in social computing conferences and journals (which are not rational universes).
However a significant other class of object in a social computing system is made up of sets of things – people, resources, dialogues, groups and so on. Things in sets (interchangeably, collections, aggregations, classes or bags) don’t have a particular order or internal connections between them like networks. They are defined simply by membership (or, in fuzzy sets, degrees of membership). They are just things we lump together for some reason. We could even have sets of nets. Or nets of sets if it makes sense or is useful to do so. Or sets of sets. The point is, sets and nets are useful in different ways and for different purposes.
Sets are powerful tools, especially in an environment (like this one) where people naturally fall into them – classes, research groups, centres, schools and so on. If I am designing a system for learning in an environment like The Landing, it is at least as important to me to know who is in a class as it is to know about the connections between them. It matters that I see myself in a group (set) of people who like to think about online learning. It matters that I can find them, not because they are a network but because they have defined themselves (through tags and profiles) as part of that set. I guess you could, it you wished, see the person-tag-person triad as a second-order net, but why bother when the most natural thing in the world is to call us part of the same set? It’s also computationally way easier and less expensive to do. Of course, once I have found them then first order networks come into play and that’s important too.
Sets are also wonderful for for lumping, averaging, summing, counting, weighting and rating, comparing and sorting.
Sets are perfect when we want to find something and we know what kind of thing it is – in structured data, especially.
Sets are great when we want to model the entities in the world, to find out what kinds of things are out there, how many there are, what they are like, what most interests them as a whole. The vast majority of databases in the world owe their forms to set theory and are composed of sets.
Sets are fabulous tools to filter not just things that are in a set but also the things that are not.
Sets are just made for harnessing collectives: for instance, tag clouds are based on sets, not nets – typically, we count how many times a tag has been used and weight it in the list by popularity. Similarly, sets are far better than nets for voting: it is mighty interesting that a knows b and b knows c but, in some contexts, it is way more important that there were two votes for x and one vote for y.
While we could (if we were particularly obsessive) see nets in everything from atoms to galaxies and model almost all sets as nets, we would lose something important in doing so. The fact that we can even use words like ‘atom’ and ‘galaxy’ means that we have already lumped things into categories – i.e. we have put them in sets. Sets tell us about what matters to us, how we categorise, how we lump things, what the world is like to other people. Sets describe identity. We need sets in order to begin to have nets, as almost every net we are interested in is composed of sets: i.e. things we have no need to analyse as nets and that would have a different meaning and identity if we did.
I am part of the set of people who teach at Athabasca University. I may be part of a similarly named network too, but the fact that I perceive myself as a member, not just joined as a node in a network, matters. Those overlapping sets are as much what defines me as the connections I explicitly or implicitly form.
Nets are cool and most things can be seen in terms of them. But sets are cool, and most things can be seen in terms of them too. Clumping matters as much as connecting.
danah boyd, as ever, pushing the bar on research into social computing, this time with the help of Eszter Hargittai. As it turns out, privacy is not showing any signs of dying soon and it is something people really really want.
If only Facebook took the clear needs of its users seriously it would not be quite as evil. But privacy is not good for Facebook and they make it as hard as possible to achieve, while just about keeping the customers satisfied. Connections make a powerful drug that keeps the customers coming, but the price is high. It would be nice to see Facebook price themselves out of the market on this one.
Address of the bookmark: http://www.uic.edu/htbin/cgiwrap/bin/ojs/index.php/fm/article/view/3086/2589
Reading a PhD thesis today that discusses, amongst many other things, the effects of different kinds of motivation on achievement, I was struck once again by the great weaknesses of many of our traditional methods of measuring achievement. The study finds that intrinsic forms of motivation do not have a great effect on grades when compared with extrinsic forms: people who have high extrinsic motivation and/or the extrinsic end of intrinsic motivation can, as long as they also have a fair degree of intrinsic motivation, achieve the ‘same’ results as those who are more purely intrinsically motivated.
What interests me, and what we seldom measure, is what else those with higher levels of intrinsic motivation achieve. Those for whom learning is relevant, rewarding, connected and meaningful in itself would, I would hypothesise, achieve far greater long-term benefits from the process that are not usually measured in grades. The greater sense of competence that they experience would encourage them to continue confidently learning after the course of study is over. The relatedness that they feel with others would encourage them to continue to engage and extend their learning networks. And their sense of autonomy would give far greater ownership of the knowledge: they would be far more likely to build strong connections that reinforce and extend existing knowledge. None of these things are measured in most traditional institutional approaches to assessment, with their focus on content and subject-specific competences and goals.
I’m not suggesting that content and competences are unimportant – far from it. Such details are what give visible shape and form to the bigger picture, the paints that we use to create it. Without something to make it from, there would be no bigger picture. Also, I would like my doctor to know about medicine when she is treating me. But that’s just the starting point. While the ability to pass a few exams in a short space of time might be an indicator of minimal competence, I would infinitely prefer to be treated by someone who has enthusiastically continued to learn, who understands how to apply and build on her knowledge creatively and insightfully as a continuous process, who sees the connections between the many different subjects she has studied and who contributes actively in learning communities of other doctors.
The stuff we learn about is shifting and changing and, in many fields, not that important. I was once able to pass exams in writing COBOL. I could not do so now and there would be no point in me doing so as it has been close to irrelevant in any context that interests me for about 20 years. In fact, I do very little actual programming nowadays of any sort. I suspect that my teachers mostly believed that they were teaching me to program in COBOL as that’s what they examined me on, but that’s by far the least important part of what I really learned. My continuing ability to think like a programmer and to engage in an ongoing dialogue with others in the profession remains a truly valuable skill. I understand the world in different ways, know why some of those computer things behave the way they do, can abstract concrete systems and concretise abstract systems, can dream bigger because I know what is possible and maybe can dream smaller in some ways because I also think, maybe erroneously, that I know what is impossible. I know the ways that the apparently autistic programmer mind works and can see the beauty and value in that as well as work round some of its limitations. I can express myself in dynamic systems. I can see the simplicity in some superficially complex things, and complexities in the superficially simple. I can reframe knowledge I already possessed in different ways, creating new knowledge, new perspectives. I can see possibilities that I could not see before and they continue to grow as I learn more. My boundaries changed and continue to change as a result of what I learned. Because I learned things that were never assessed in exams I am a more creative, more articulate, more informed person than I would have otherwise been, a better problem-solver and a deeper thinker. And that’s what I really learned, not how to program in COBOL.
A successful education is one that changes the way you think. It is no surprise that extrinsic motivation can (at least with a bit of intrinsic motivation to complement it) produce good ‘achievement’ because the measurement of that achievement concentrates on the visible tip of the iceberg, not the big and mostly hidden mass underneath.
There are some obvious and well-documented things we might (and sometimes do) do to redress this, including:
And plenty more. It’s not that we can’t assess achievement more authentically and richly, as long as we have an awareness of the need, the flexibility and the will to do so.
There are some risks of course. It would be almost as bad if all that our assessments showed were the levels of motivation of our students, their ability to bluff, or their enthusiasm for a particular subject. Given our dual and often conflicting roles as judges as well as educators, we have to be able to assess competence, and that includes the stuff we already do look at as well as the rest of the iceberg. We also have to find ways of avoiding cheating in the system when we are the arbiters of quality in learning but, on the bright side, these sorts of approach render that much more difficult and unlikely: when we take a more holistic approach to assessing achievement then we cannot help but be strongly aware of the human at its centre, rather than the abstract chunk of disembodied skill or information they present us with.
The things that change us, really change us, are the rest of the icebergs below the waterline of formal education that matter most. A sea-change is needed in how we consider achievement, not just in isolated pockets of northern lakes ruled by pedagogues and eduphiles, but across the whole educational ocean.
Interesting if absurdly huge slideshow from Paul Adams of Google, talking about our different overlapping networks. This very closely mirrors and supports what we are doing on the Landing, where we have been developing a context switcher to enable people to present different facets of their identities to different groups of people (as well as switch personal contexts for different needs).
Address of the bookmark: http://www.slideshare.net/padday/the-real-life-social-network-v2
Familiarity vs similarity as means of providing social recommendations
Address of the bookmark: http://portal.acm.org/citation.cfm?id=1639714.1639725