Addicted to learning or addicted to grades?

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Figure 1: Skinner’s teaching machine

It is not much of a surprise that many apps are designed to be addictive, nor that there is a whole discipline behind making them so, but I was particularly interested in the delightfully named Dopamine Labs‘ use of behaviourist techniques (operant conditioning with variable ratio scheduling, I think), and the reasoning behind it. As the article puts it:

One of the most popular techniques … is called variable reinforcement or variable rewards. 
It involves three steps: a trigger, an action and a reward.
A push notification, such as a message that someone has commented on your Facebook photo, is a trigger; opening the app is the action; and the reward could be a “like” or a “share” of a message you posted.
These rewards trigger the release of dopamine in the brain, making the user feel happy, possibly even euphoric, Brown says.
“Just by controlling when and how you give people that little burst of dopamine, you can get them to go from using [the app] a couple times a week to using it dozens of times a week.”

For well-designed social media and games, the reward is intrinsic to the activity, and perfectly aligned with its function. If the intent is to create addicts – which, in both kinds of system, it probably is – the trick is to design an environment that builds rewards into the algorithms (the rules) of the system, and to keep them coming, ideally making it possible for the rewards to increase in intensity as the user gains greater expertise or experience, but varying ratios or intervals between rewards to keep things interesting. Though this particular example falls out from behaviourist theory, it is also well supported by cognitivist and brain-based understandings of how we think. Drug dealers know this too, as it happens. If you want to keep people using your product, this is how to make your product particularly addictive.

Learning addicts

Lovers of learning experience addiction too. The more we learn, the more there is to learn, the greater the depth and pleasure there is to be found in doing so, and the sporadic ups and downs, especially when faced with challenges we eventually solve, are part of the joy of it. Increasing mastery of anything is a reward in itself that seems quite intrinsic to our make-up, and to that of many other animals. Doing it in a social context is even better, as we share in the learning of others and gain value (social capital, different perspectives, help overcoming problems, etc) in the process. We gain greater control, greater autonomy, greater capability to live our lives as we want to live them, which is very motivating. As long as the reward comes from the activity itself, and the activity is not harmful, this is good news. It makes sense from an evolutionary perspective. We are innately motivated to learn, because learning is an extremely valuable survival characteristic. Learning generally makes dopamine positively drip from our eyeballs.

So what’s the problem with applying the principle in education?

None at all, until you hit something that you do not wish to learn, that is too difficult to master right now, that is too boring, that has no obvious rewards in and of itself. The correct response to this problem is, ideally, to find what there is to love in it. Good teachers can help with that a lot, inspiring, revealing, supporting, demonstrating, and discussing. Other learners can make a huge difference too, supporting, modelling behaviours, filling gaps, and so on. We very often learn things for other people, with other people, or because of other people. Educational systems offer a good substrate for that.

If intrinsic motivation fails to move us, then at least the motivation should be self-determined. Figure 2 shows a very successful and well-validated model of motivation (from Ryan and Deci) that, amongst other things, usefully describes differing degrees of extrinsic motivation (external, introjected, identified, and integrated) that, as they approach the right of the diagram, increasingly approach intrinsic motivation in value, though ‘external regulation’ is rather different, of which more soon. When intrinsic motivation fails, what we need is some kind of internal regulation to push us onwards. It is not a bad idea to find some internally regulated reason that aligns with your beliefs about yourself and your goals, or that at least fits with some purpose or goal that you find valuable. It’s sometimes useful to develop a bit of ‘grit‘ – to be able to do something that you don’t love doing in order to be able to do things that you do love doing, to find reasons for learning stuff that are meaningful and fit with your personal values, even if the immediately presenting activity is not fun in itself. Again, teachers and other people can help a lot with that, by showing ways that they are doing so themselves, by providing support, by engaging, or by being the reason that we do something in the first place. It’s all very social, at its heart.

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Figure 2: Forms of motivation

That social element is important, and not clearly represented in the diagram, despite being a critical aspect of intrinsic motivation and mattering a lot for the ‘higher’ identified forms of extrinsic motivation. From an evolutionary perspective, I suspect this ability to learn because of the presence of others accounts for our species’ apparent dominance in our ecosystems. We are not particularly clever as independent individuals but, collectively, we are mighty smart. This could not be the case without having an innate inclination to value, and to gain value from, other people, and for this to have the consequence that others very materially contribute towards our motivation to do something. I guess I should mention that ‘innate’ does not mean ‘pre-programmed’ – this is almost certainly an emergent phenomenon. But it is a big part of who we are.

Grade addicts

So far so good. Educational systems are, at least in principle, very effective ways of bringing people together. It all goes horribly wrong, however, when the educators’ response to amotivation (or worse, to motivation to avoid) is to change the rules by throwing in extrinsic rewards and punishments, like grades, say, or applying other controls to the process like forced attendance. Externally regulated extrinsic motivation is extremely dangerous.

Extrinsic rewards and punishments do work, in the sense that they coerce people and other animals into behaving as the giver of the rewards or punishments wishes them to behave. And yes, dopamine is implicated. This immediate effectiveness is what makes them so alluring. But it’s like giving an athlete performance-enhancing but ultimately harmful drugs. Rewards and punishments are also highly addictive and, like other addictions, you need more and more to sustain your addiction because you become inured to the effects, and withdrawal gets more painful the longer you are addicted. This works two ways. Those that get the rewards (the good grades, gold stars, praise, whatever) go on to want more of them, and will do what they need to get them, whether or not there are any further benefits (like, say, learning). Cheating is one popular way to do this. Tactical study, where the student tries to do what will get good grades rather than learn for the love of it, is another. But grading, though extrinsically motivating for the most part, is not always effective: bad grades can achieve the opposite effect, like drugs spiked with something horrible. Those that get grades as punishments often try to avoid them by whatever means they can: dropping out and cheating (a way to bypass the system to get hold of the good stuff) are popular solutions.

The biggest problems, however, come when you take the rewards/punishments away. As a vast body of research has shown and continues to show, this diminishes intrinsic motivation and often eliminates it altogether. If people are not very inclined to do something then you can temporarily boost interest by adding extrinsic rewards or punishments but, when you take them away, people are considerably less inclined to do the thing than they were before your started even when they originally liked to do it. At a high level this can be explained by the fact that, in giving a reward or punishment, you are drawing attention away from (crowding out) the thing itself and, at the same time, sending a strong signal that the activity itself is not rewarding enough in itself to be worth doing. But I am not sure that this fully explains the very strong negative effects on motivation that we actually see when rewards or punishments are withdrawn. I idly speculate that part of the reason for this effect might be the dopamine crash. We come to associate an activity with a dopamine boost and, when that boost is no longer forthcoming, it can be very disappointing, like smoking a nicotine-free cigarette (trust me – that’s awful). Cold turkey is not the best state to be in, especially when you associate it with an activity like learning something. It could really put you off a subject. This is just a thought: I know of no evidence that it is true, but it seems a plausible hypothesis that would be worth testing.

Whatever the cause, the effects are terrible. By extrinsically driving our students, we kill the love of the activity itself for those that might have loved it, and permanently prevent those that might have later found it valuable from ever wanting to do it again. Remarkably few survive unscathed, and a disproportionate number of those that do go on to become teachers, and so the cycle continues. I don’t think this is how education should be, and I don’t think it is what most of us in the system intend from it.

Getting out of the loop

The only really effective way to ensure lifelong interest and ongoing love of learning is to find the reward in the activity itself, not in an extrinsic reward. The games and social applications described in this article do that very well but it is important to remember that the intent of the designers of the applications is to increase addiction to them in order to sell or promote the product, and that there is perfect alignment between the reward and the activity itself. This is built into the rule system. In an education system that is driven by marks, we are making grades (not learning) the product, and making those the source of the addiction. This is very different. It has nothing to do with the activity of learning itself: it is extrinsic to the process. It might be even more effective give our students addictive drugs (higher concentrations equate to higher grades) to increase the incentive. I’m surprised no one has tried this.

But, seriously, what we really need to be doing is to make learning the addiction.

We can reduce the harm to an extent by removing grades from the teaching process and focusing on useful feedback and encouragement instead. If forced to judge, we can use pass/fail grades that are still harmful but not quite as controlling. If we are inexplicably drawn to grading, then we can build systems similar to those of ‘likes’ and badges of social media where, instead of rewards we give awards – in other words, we remove the expectation of a grade but, where merit is found, sometimes show our approval – and we can make that a social process, so that it is not dominated by a teacher and therefore does not involve exercise of arbitrary power. We can use pedagogies that give teachers and students the chance to model and demonstrate their passion and interest. We can encourage students to reflect on why they are doing it, ideally shared so they can gain inspiration from others. We can help students to integrate work with other things that matter to them. We can help them personalize their own learning so that it is appropriately challenging, not too dull, not to hard, and so that it matches the goals they set for themselves. We can help them to set those goals, and help them to figure out how to attain them. We can make them participants in the grading process, picking outcomes and assessments that match their interests and needs. We can build communities that support and nourish learning through sharing and mutual support. This is just a small sample of ways – there are really quite a few things that we can do, even within a broken system, to make learning addictive, to find ways to make it rewarding in and of itself, even when there is little initial interest to build upon. But we are still stuck in a system that treats grades as rewards, so we are still faced with a furious current pushing against all of our efforts.

Really, we need to change the system, but just  a bit: our current educational systems have evolved for pragmatic reasons, mainly because alternatives are too expensive or inconvenient for teachers to manage, not because they are any good for learners. One of the consequences of that is that it is almost impossible to run an institutional course or program without at least some form of grading, even if only at pass/fail level, even if only at the end.

An obvious big part of the solution is to decouple learning and grading. Some more advanced competency-based approaches already do that, as do things like challenge assessments and assessment of prior experience and learning, to some extent project/essay/thesis paths, outcomes-based programs, and even some kinds of professional exams (the latter not in a good way, for the most part, because they tend to drive the process). However, there are risks that universities might turn into an up-market version of driving schools, teaching how to pass the tests and doing just as they are doing now, rather than enabling more expansive learning as they should. To avoid that, it is critical that learners are involved in helping to determine their own personalized outcomes, and very much not to have those learning outcomes ‘personalized’ for them – personal, not personalized, as Alfie Kohn puts it and as Stephen Downes agrees. Grades that learners control, for activities that they choose to undertake, are many times better than grades that someone else imposes. It would also be a good idea either to split teaching activities into assemblable chunks, or into open narratives, without alignment with specific awards or qualifications. Students might build competences from smaller pieces – often from different sources – in order to seek a specific award, or might gain more than one award from a single learning narrative (or perhaps from a couple that overlap). It would be a very good idea to provide ways to mentor and help learners to seek appropriate paths, perhaps through personal tuition, and/or through automated help, and/or through membership of supportive communities (I am a fan of action learning sets for this kind of thing). Such mechanisms might also assist in the preparation of portfolios of evidence that would be an obvious way to manage the formal assessment process. I’m not in any way suggesting that we educators (especially for adult learners) should get rid of our accreditation role, merely that we should stop using it to drive our teaching and to enforce compliance in our students.

I think that such relatively small tweaks to how we teach and assess could have massive benefits further upstream. In one fell swoop it would change the focus of educational systems from grades to learning, and change the reward structure from extrinsic to intrinsic. Instead of building fixed-length courses with measurable outcomes that we the teachers control, we could create ecosystems for learning, where cooperation and collaboration would have greater value than competition, where learners are really part of a club, not a cohort, where teachers are perceived as enablers of learning, not as causes, and certainly not as judges. The words ‘learner-centred’ have been much over-used, often being a shorthand for ‘a friendlier way of making students comply with our demands’ or ‘helping students to get better grades’, but I think they fairly accurately denote what this sort of system would entail when taken seriously. Some of my friends and colleagues prefer ‘learning-centred’ and that works for me too. But really this is about being more human and more humane. It’s about breaking the machines that determine what we do and how we do it, and focusing instead on what we – collectively and individually – want to be. We can do this by thinking carefully about what motivates people, as opposed to attempting to motivate them. As soon as our attitude is one of ‘how can we make our students to this?’ rather than ‘how can we help our students to do this?’ we have failed. It’s easy to create addicts of extrinsic motivation. It is hard to make addicts of learning. But, sometimes, the hard way is the right way.

 

Address of the bookmark: http://www.cbc.ca/news/technology/marketplace-phones-1.4384876

Originally posted at: https://landing.athabascau.ca/bookmarks/view/2816324/addicted-to-learning-or-addicted-to-grades

Signal : now with proper desktop apps

Signal is arguably the most open, and certainly the most secure, privacy-preserving instant messaging/video or voice-calling system available today. It is open source, ad-free, standards-based, simple, and very well designed. Though not filled with bells and whistles, for most purposes it is a far better alternative to Facebook-owned WhatsApp or other near-competitors like Viber, FaceTime, Skype, etc, especially if you have any concerns about your privacy. Like all such things, Metcalfe’s Law means its value increases with every new user added to the network. It’s still at the low end of the uptake curve, but you can help to change that – get it now and tell your friends!

Like most others of its ilk it hooks into your cellphone number rather than a user name but, once you have installed it on your smartphone, you can associate that number (via a simple 2D barcode) with a desktop client. Until recently it only supported desktop machines via a Chrome browser (or equivalent – I used Vivaldi) but the new desktop clients are standalone, so you don’t have to grind your system to a halt or share data with Google to install it. It is still a bit limited when it comes to audio (simple messaging only) and there still appears to be no video support (which is available on smartphone clients) but this is good progress.

Address of the bookmark: https://signal.org/download/

Originally posted at: https://landing.athabascau.ca/bookmarks/view/2813683/signal-now-with-proper-desktop-apps

The Ghost in the Machines of Loving Grace | Library Babel Fish

An article from Barbara Fister about the role and biases of large providers like Google and Facebook in curating, sorting, filtering their content, usefully contrasted with academic librarians’ closely related but importantly different roles. Unlike a library, such systems (and especially Facebook) are not motivated to provide things that are in the interests of the public good. As Fister writes:

“The thing is, Facebook literally can’t afford to be an arbiter. It profits from falsehoods and hype. Social media feeds on clicks, and scandalous, controversial, emotionally-charged, and polarizing information is good for clicks. Things that are short are more valuable than things that are long. Things that reinforce a person’s world view are worth more than those that don’t fit so neatly and might be passed over. Too much cruft will hurt the brand, but too little isn’t good, either. The more we segment ourselves into distinct groups through our clicks, the easier it is to sell advertising. And that’s what it’s about.”

These are not new points but they are well stated and well situated. I particularly like the point that lies and falsehoods are not a reason to censor a resource in and of themselves. We need the ugliness in order to better understand and value the beauty, and we need the whole story, not filtered parts of it that suit the criteria of some arbitrary arbiter. As Fister writes:

“There’s a level of trust there, that our students can and will approach a debate with genuine curiosity and integrity. There’s also a level of healthy distrust. We don’t believe it’s wise to leave decisions about truth and falsehood up to librarians.”

Indeed. She also has good things to say about personalization:

“If libraries were as personalized, you would wave your library card at the door and enter a different library than the next person who arrives. We’d quickly tidy away the books you haven’t shown interest in before; we’d do everything we could to provide material that confirms what you already believe. That doesn’t seem a good way to learn or grow. It seems dishonest.”

Exactly so.  She does, though, tell us about how librarians do influence things, and there’s only a fine and fuzzy (but significant) line between this and the personalization she rejects:

“Newer works on the topic will be shelved nearby that will problematize the questionable work and put it in context.”

I’m not sure that there is much difference in kind between this approach to influencing students and the targeted ads of Google or Facebook. However, there is a world of difference in the intent. What the librarian does is about sense making, and it accords well with one of the key principles I described in my first book of providing signposts, not fenceposts. To give people control, they have to first of all have the choices in the first place, but also they need to know why they are worth making. Organizing relevant works together on the shelf is helping students to make informed choices, scaffolding the research process by showing alternative perspectives. Offering relevant ads, though it might be dishonestly couched in terms of helping people to find the products they want, is not about helping them with what they want to do, but exploiting them to encourage them to do what you want them to do, for your own benefit, not theirs. That’s all the difference in the world.

That difference in intent is one of the biggest differentiators between a system like the Landing and a general-purpose public social media site, and that’s one big reason why it could never make any sense for us to replace the Landing with, say, a Facebook group (a suggestion that still gets aired from time to time, on the utterly mistaken assumption that they duplicate each other’s functionality). The Landing is a learning commons, a network of people that, whatever they might be doing here, share an intent to learn, where people are valued for what they bring to one another, not for what they bring to the owners and shareholders of the company that runs the site. Quite apart from other issues around ownership, privacy and functionality, that’s a pretty good reason to keep it.

 

Address of the bookmark: https://www.insidehighered.com/blogs/library-babel-fish/ghost-machines-loving-grace

Wisdom of the Confident: Using Social Interactions to Eliminate the Bias in Wisdom of the Crowds

A really interesting paper on making crowds smarter.  I find the word ‘confident’ in the title a bit odd because it seems (and I may have misunderstood) that the researchers are actually trying to measure independent thinking rather than confidence. As far as I can tell, this describes a method for separating sheep (those more influenced by others) from goats (those making more independent decisions), at least when you have a sequence of decisions/judgments to work with. The reason it bothers me is that sheep can be confident too (see the US election or Brexit, for example).

We know that crowds can be wise if and only if the agents in the crowd are unaware of the decisions of other agents. If there’s a feedback loop (more accurately, I believe, if there is an insufficiently delayed feedback loop) then you wind up with stupid mobs, driven by preferential attachment and similar dynamics. This is a big problem in many political systems that allow publication of polls and early results. However, some people are, for one reason or another, less influenced by the crowd than others. It would be useful to be able to aggregate their decisions while ignoring those that simply follow the rest, in order to achieve wiser crowds. That’s what the method described here seeks to do.

The paper is more concerned with describing its model than with describing or analyzing the experiment itself, which is a pity as I’d like to know more about the populations used and tasks performed, and whether it really is discriminating confident from independent behaviour. I’ve also done some work in this area and have written about how useful it would be to automatically identify independent thinkers, and to use their captured behaviour instead of that of the whole crowd to make decisions, but I have never implemented that because, in real life, this is quite hard to do. In this experiment, it seems quite possible that the ‘independent’ people might simply have been those that knew more about the domain. That’s great if we are using a sequence of captured data from the same domain (in this case, length of country borders) because we get results from those that know rather than those that guess. But it won’t transfer when the domain changes even slightly: knowing the length of the Swiss border might not well predict knowledge of, say, the length of the Nigerian border, though I guess it might improve things slightly because those that care about such things would be better represented in the sample.

It would take a fair bit of evidence, I suspect, to identify someone as a context-independent independent thinker though, given enough time, it could be done, it would be well worth doing, and this model might provide the means to identify that. I’d like to see it applied in a real context. There are less lengthy and privacy-invading alternatives. For instance, we might capture both a rating/value/judgement/whatever and some measure of confidence. Some kinds of prediction market capture that sort of data and, because of the personal stake in it, might achieve better results when we do not have a long history of data to analyze. Whether and to what extent confidence is related to independence, and whether the results would be better remains to be discovered, of course – there’s a good little research project to be done here – but it would be a good start.

Address of the bookmark: https://arxiv.org/abs/1406.7578

Commons In A Box

Landing-like software from CUNY, based on Buddypress, intended to provide a learning commons with relatively little effort or configuration. It’s a nice bit of packaging, slick, with good collaboration tools and a simple, activity-stream-oriented social network. Commons in a Box is definitely worth looking at if you need a site to support a bottom-up social community or network, and you don’t have a wealth of resources to put into building your own. 

I came across this software because it is being used in the University of Brighton’s newly reborn community site at https://community.brighton.ac.uk which, until it was killed off last year, used to run on Elgg.  I remain a fan of Elgg for building such things, which has a lot more options than BuddyPress available by default, richer access control, and a much more elegant technological design that makes customization more robust and flexible, but this seems to be a great simple solution that just works without demanding much effort, and that, thanks to its WordPress foundations, could be customized to do pretty much anything you’d want a bit of social software to do. 

Address of the bookmark: http://commonsinabox.org/

Google’s new media apocalypse: How the search giant wants to accelerate the end of the age of websites – Salon.com

A sad article, if ever there was one. This is about Google’s in-kind response to Facebook’s depressingly successful attempts to be a bigger and better AOL/Compuserve (amongst other things, through its ‘philanthropic’ internet.org arm, that people in developing countries afflicted with it sometimes think of as the Internet). The general idea is that Google will host content, rather than linking to it.

This is not the way the Internet should go, and this is not in line with Google’s avowed intent to not be evil. On the bright side, in real life, though poisonous and virulent, it is not the way the Internet really is going: the Internet is, ultimately, self healing, both in technical and in social terms. It might look like a fairly closed system to people that generally interact with it through Facebook or Google Search (or any of hundreds of thousands of other less successful attempts to lock people in) but it is heartening that WordPress dwarfs all of them put together in terms of sites and people that visit them (more than a quarter of all sites), and Worpress sites are, to a very large extent, controlled and owned by the people that run them. And that’s just the most popular content management system: the Web is many times bigger and more distributed than that, and the Internet is vastly bigger still. And, of course, Google is not the only search engine. You can find the rest of the Web in many other ways.

So, though the article claims doom and gloom all round, I remain optimistic that common sense and decency (or indecency if that happens to be your thing) will triumph in the end, and the game will never be over. A few successful parasitic corporations/applications – Facebook (including its subsidiaries like Instagram, Whatsapp, etc), Google, Apple, Amazon, Twitter, Snapchat, LinkedIn, Yahoo, Microsoft, Pinterest, etc – are doing their darnedest to wreck the open Internet, and are definitely shaping much of it, killing open standards, and sucking billions of people into their locked-in lairs, but those billions of people are just a click away (often, from within those systems themselves) to what the Internet is actually composed of, especially the Web side of it. Sure, these are parasites that suck the life out of openness and diversity but, like all parasites, they would be more than foolish to kill their host. And, hearteningly, the network effect (especially the rich get richer Matthew Effect) works just as effectively in reverse, as any former MySpace or Friendster afficionado will tell you. Or AOL, for that matter.

Address of the bookmark: http://www.salon.com/2016/05/01/googles_new_media_apocalypse_how_the_search_giant_wants_to_accelerate_the_end_of_the_age_of_websites/

Recording of my TCC2016 keynote: The Distributed Teacher

This is the recording of my keynote at the TCC2016 online conference, on the nature of learning and teaching: the inherently social, distributed nature of it, why e-learning is fundamentally different from p-learning, and how we harmfully transfer pedagogies and processes from physical classrooms to online contexts in which they do not belong. If you want to watch it, skip the first 5 minutes because there was a problem with the sound and video (I hate you, Adobe Connect): the talk itself begins at a few seconds after the 5 minute mark.

Downloadable slides and details of the themes are at https://landing.athabascau.ca/file/view/1598774/the-distributed-teacher-slides-from-my-tcc-2016-keynote

Address of the bookmark: http://squirrel.adobeconnect.com/p1bvy7grca7/

Reactions to Facebook's reactions

I quite like the word ‘reactions’ that Facebook is using to describe their new options to express feelings about a post. I wish I’d thought of it. This is a matter of much more than passing interest to me as it relates closely to something that occupied a lot of my time over some years of my life. In my own CoFIND social bookmarking system (that first saw the light of day about 18 years ago and underpinned my PhD work) I used to refer to something quite similar as ‘qualities’ – metadata (tags) to show not just that something is good or interesting but how it is good or interesting, that could then be used to rate and thus help to filter and rank a feed of bookmarked resources. CoFIND is an acronym – Collaborative Filter in N Dimensions – that refers to this n-dimensionality of ratings. Facebook’s Reactions feature is a simplified version of this: it’s about categories more than tags, but the thinking behind it is broadly similar. The differences, though, are interesting.

Fuzzy ratings

One of the things that is most notable about Facebook Reactions is that ratings are, like its Likes before them, binary: a simple ‘yes’ or ‘not-rated’.  In most versions of CoFIND (it iterated a lot), users could choose to what extent something was good/loved/annoying/interesting/etc through a Likert scale. Giving the option to choose the strength of a feeling seems much more sensible when talking about fuzzy values like this. I want to be able to signify that I quite like something, or that is is mildly amusing, especially if my intent is to communicate my feelings to others. Facebook’s Reactions are a coarse as a means of expression: it is quite appropriate that its emoticons are literal caricatures.  In all the methods I tried – radio buttons, clickable links, etc – introducing scalar ratings turned out to be way too complex to be usable, but web interfaces were not as rich in those days: I think things like popup draggable sliders (not dissimilar to Facebook’s interface) might make it more feasible nowadays.

Evolving metadata

Facebook Reactions are not just binary but fixed. CoFIND – I think, still uniquely – allowed individuals to create new qualities (reactions), which could then be used by anyone else. It was an n-dimensional rating system where ‘n’ could be any number at all. Qualities quite literally evolved for each community, with more used qualities surviving (being immediately available for use) and less used ones being relegated to backwaters of the system (effectively dying, albeit with the possibility of resurrection if added again). This allowed for such metadata to provide a mirror of the values that mattered most within a given community or network, rather than being imposed uniformly on everyone, and for those values to evolve as the community itself evolved. While I appreciate the simplicity of Facebook’s interface (CoFIND’s most fatal flaw was always that its interface was far too complex to be usable) I still think that user-created ways of emoting – what I have since called ‘fuzzy tags‘ – lead to much more useful reactions that matter within a given community, especially when users can choose the degree to which a fuzzy tag applies. When CoFIND was used in an educational setting, qualities like ‘good for beginners’, ‘authoritative’, or ‘comprehensive’ tended to emerge – they were pedagogical metadata. When used in other contexts, such as to discover what HCI students considered important in a website, site-ranking qualities like ‘slow’, ‘boring’, ‘artistic’ and ‘informative’ appeared.

CoFIND qualities

 

Parcellation

One of the things I hate most vehemently about Facebook is that it same-ifies everything: a person in Facebook has a single unchanging (and permanently reified) identity, with a single network, a single facade, a single caricatured way of being in the world, notwithstanding the odd nod to diversity like pages and lists. Facebook’s business model relies on this, because any clustering or parcellation reduces the potential to connect, and connections are everything to Facebook. This makes me highly sceptical of its claimed ‘discovery’ that people are actually separated by only 3.57 degrees rather than six. Given that the system very deliberately drives them to friend as many others as much as possible, on most tenuous grounds of connection, this is hardly surprising. It shows not that previous studies are mistaken but the extent to which Facebook has manipulated human networks for profit. Apart from evolving to fit a single community, another of the things CoFIND did was to deliberately parcellate the environment, allowing different sets of values to evolve in different contexts. What is ‘good’ in the context of learning to read is not likely to be ‘good’ in the context of learning geometry, so different topics each evolved a (largely) separate set of qualities. This might not have been the best way to drive the growth of large networks, but it was a much better way to enable the self-organized emergence of meaningful communities. It also allowed individuals to express and embrace different facets of themselves, which in turn made it easy to accommodate changing needs and interests: essential in the context of learning, which is (if nothing else) about change.

You can read about the tortuous process of CoFIND’s development and the thinking behind it in my PhD thesis. I continued to develop CoFIND into the mid 2000s but, though the final version was a bit more usable and scalable (I rewrote it in PHP and changed a lot of the mechanisms, simplifying a fair number of things, including losing the fuzzy ratings) I’m still most fond of the final version that is described in the thesis.

Address of the bookmark: http://www.huffingtonpost.com/entry/facebook-reactions-update_us_56ccb128e4b0ec6725e42861?ir=Weird+News&section=us_weird-news&utm_hp_ref=weird-news

When 300 Million Active Users Isn't Enough | Library Babel Fish

Interesting reflections from librarian Barbara Fister on Twitter’s precarious position, turning a ‘mere’ $191m profit on 300m users and not growing fast enough to assure survival. Turning away from the customer-as-product model, she instead makes a case for small, vertical market, paid-for social (but not too social) services, like Pinboard (tagline: ‘social bookmarking for introverts’) and LibraryThing (“MySpace for bookworms”).

I don’t see these as any more viable than Twitter. If successful, they will be purchased by one of the big few (giving the predator access to my data and social connections) or, if unsuccessful, they will eat my data and my social connections made with them. If they weather all that, the chances of them continuing to grow to meet my ever changing demands are minimal. Vanishingly few will continue to meet my needs for the foreseeable future and it would be foolhardy to bet money that any will survive indefinitely.

And indefinite survival is what is needed, not of the service itself but of the data, processes and social connections that support those data. It is bad enough having elderly files on my own computer that I cannot access at all thanks to proprietary formats. Having such data on a cloud service I may not even be able to access next week is much worse. And, of course, for a social system it is not just about my data but about the network with other people that, when the service dies or I wish to leave it, will be lost.  It’s better to be more of a customer and less of a product, but the endgame is the same either way. Cloud services are susceptible to a thousand and one woes, including unwanted service changes, renogatiated service contracts (seldom beneficial to the customer, once the data are locked in), acquisition, disappearance, failure to grow when needed, and a host of other things beyond my control. The proprietary, locked-in cloud is not the way to go, whether ‘free’ or directly paid-for. It gives the illusion of being open while actually being closed. We need open, portable, distributable and distributed standards for all of this: RSS, OPML, OpenSocial, trackbacks, pingbacks, WebMention and so on. And we need the ability to create, change, move and develop virtual spaces that belong to us, not to a service provider. This is why systems like Known, Elgg and WordPress (with appropriate plugins to support federation) are so important. I find it very encouraging that WordPress (open source and hosted versions) continues to grow and to dominate the social media landscape, powering over 26% of the entire Web. It makes usage of the likes of Facebook, Twitter and YouTube seem like a rounding error, and it is just one of many social systems owned by those that use them.

Address of the bookmark: https://www.insidehighered.com/blogs/library-babel-fish/when-300-million-active-users-isnt-enough

Metcalfe's Law is Wrong – IEEE Spectrum

Compelling argument, 10 years old now, that Metcalfe’s Law and Reed’s Law are wrong, and that the correct value for a network should be n log (n). The reasoning is good: the problem with Metcalfe’s and Reed’s laws is that not all nodes in a network are equal. An analogy is made with Zipf’s Law (“if we order some large collection by size or popularity, the second element in the collection will be about half the measure of the first one, the third one will be about one-third the measure of the first one, and so on”) which reflects the uneven distribution of value in a network.

This makes sense to me, but could be taken further. It seems to me that there is no such thing as an ‘average’ network, so we must always examine the actual patterns in any given network to see what value individuals add, and we must always be prepared for some serious outliers that can greatly affect the overall network. If, say, a prime minister or president started to use the Landing, the effect would be quite spectacular (and likely catastrophic, for all sorts of technical and non-technical reasons). There are great risks in averaging things out and looking for statistical effects when observing any human system.

Address of the bookmark: http://spectrum.ieee.org/computing/networks/metcalfes-law-is-wrong