Twitter and the riots: how the news spread | UK news | guardian.co.uk

Nice article on the role of Twitter in the London riots earlier this year. The simple take-away from the research: almost no negative effects, with calls to riot completely overwhelmed by opposition when they were not totally ignored (which was most of the time), and a great many positive effects such as coordination of the clean-up and support for victims afterwards. 

Address of the bookmark: http://www.guardian.co.uk/uk/2011/dec/07/twitter-riots-how-news-spread?newsfeed=true

Confirmation bias in Great American Cities

One of the notable side effects of not building cities the way Jane Jacobs suggested is that many North American cities are designed not for people on foot but for people in cars. Instead of local neighborhoods which, of necessity, provide for all the basic needs of a population and are thus innately diverse, people drive to places that interest them, to meet people that interest them, and bypass the people and things that don’t interest them. People in the sprawling burbs and zoned areas of great American cities often don’t know their own neighbours but gather in self reinforcing cliques where, in a city of sufficient size, it is possible to find people that share all sorts of interests, including the sinister and unsavory as well as the positive and affirmatory. Intricate social networks of place are replaced by sets of people and things that relate to our needs and interests: networks within those do emerge, but they are networks of affinity. Ghettos in cities hardly matter any more as we can ghettoise our own lives by skipping the limitations of location through the use of vehicular transport. It’s an exaggeration, sure, but it’s a tendency that becomes ever greater, ever more self-reinforcing because of thoughtless planning.

On the Internet have mostly built our networked spaces like those great American cities, but we have added some new flavours to the mix. Confirmation biases arise when we engage in social networks with (mostly) only those we already know (our nets) or those who share an interest (our sets) or those engaged in collaborative activities (our groups). We create sites for our courses, sites for work, sites for hobbies, and so on. On our desktops or other forms of collecting information and feeds, our news sources can and do become more personalised, tailored to our interests and focusing our attention on what we already focus our attention on and, because the Internet is vast, there is always something to meet ever-more more refined and specific interests, usually a Google search away. Much of the time we see what we want to see, engage with whom we want to engage about things we want to engage about. If someone is boring us, we will not cause offence by ceasing to pay attention because, mostly, they will not know we have stopped listening.

I once built a little play space called Dwellings that was an attempt to reintroduce the succession of eyes found in the diverse and thriving neighbourhoods of which Jane Jacobs wrote so eloquently and that can still be found in many parts of the world, and even parts of a fair number of North American cities. A cross between a collaborative browser, a MUD and a shared bookmarking system, it attempted to apply the dynamics of thriving city district to a web site. I was pleased with the concept even though the actual environment worked terribly the moment more than a handful of people came by. However, more than that, I have come to realise that it could not ever work as I had hoped. On the Web, you are a gesture or mouseclick away from anywhere. Constraints of a site are only an issue if you have to engage with it but, on a site that you do not have to navigate your way around, the obvious way to bypass constraints is to go somewhere less constraining. But, if it is a site with which you have to engage then it is just another of those isolated spaces that we go to for some reason, seldom a space that we pass through because we are on our way somewhere, so it is unlikely to result in the rich diversity necessary to break out of a set-oriented or net-oriented self-reinforcing view of the world.

I’m not sure that there are any neat solutions that employ common technologies. Finding ways to reintroduce ourselves to our communities of place would help. Similarly, if we build more virtual spaces that have more diversity, then there is a greater chance of serendipity and movement between social forms and milieus, but it is hard to imagine that will become sufficiently ubiquitous as a design ethic to stop the tide as the whole point of specialised spaces is that people know what to expect and that’s why they are there. I quite like what happens in some popular aggregators like Pulse, that do make it easy for one to filter and shape things to one’s liking, but that also provide pre-built feeds that are more like a traditional newspaper, with consequent opportunities for border-crossing. However, if there is too much variation, then we will probably stop using them: given the choice between something that shows us things we like because they are like us and things that we may occasionally like but mostly don’t, most of us will follow the things we like.

Or perhaps, as one of the literacies of this networked age, we should nurture and cultivate the skill of deliberately opening ourselves to serendipity. For instance, maybe we should all follow one link every day that has no apparent interest to us, or subscribe to a random feed (some sites like Boing Boing are not far from that already). In the long run, to paraphrase Mcluhan’s paraphrasing of Churchill, we are the shapers of the tools that shape our lives.

And so it ends…

Well, actually, I’m very happy to continue the conversation and develop this group space if anyone is interested. However, we are reaching the end of my week at the Change11 MOOC so this is probably the last post in this space for a while, back to my usual blog for the next one.

We had a lively and, I think, fruitful and interesting discussion today to wrap up my week at #change11. Stephen Downes has made the audio available at http://t.co/Tq8C6ZSE. I suppose I should provide some kind of summary of where we got to but all that stuff is there online already and in the audio of the session, so I’m going to finish with some observations about the MOOC itself and some of the self-referential ways it relates to what I’ve been discussing this week.

I’m not the first to observe that a big problem with connectivist-influenced MOOCs like this is that they are, well, chaotic and lacking in centre. People are contributing all over the place in a hundred different ways and certainly not in an orderly fashion. This is not your grandmother’s kind of course and that would be fine, apart from the fact that such a small percentage of people wind up getting fully engaged and so many drop out, one of the main reasons being the complexity of following and keeping up with the course. If we had drop-out rates of this magnitude in our universities there would be some very serious questions asked. But this is not the same kind of thing as a formal institutional course and it would be silly to apply identical standards here. Apart from anything else, the only motivation for most people being here is intrinsic – apart from a very few who are getting some kind of professional or academic credit indirectly or directly as a result, no one is going to punish them for failure to attend, no one is going to reward them with grades for pleasing the teacher or demonstrating knowledge of a fixed set of stuff. But that does make me wonder a little – if we had such an intrinsically motivated crowd in a traditional course we would be pretty pleased and would have very high expectations as a result. And yet, many fall by the wayside.

I don’t think it’s too much of a problem that many people do not write anything public – people learn in different ways at different times and respond in different ways to different things, so (though it greatly helps the learning process to write about it, especially in public, as well as helping to provide one of the pillars of intrinsic motivation, connection with others) it is fine that only some of the participants are visibly ‘there’. And it is equally fine that people pay attention to some sessions and not others – there is no particular narrative in the various presentations and there is no single body of knowledge to absorb (that’s part of the point) so people should only engage with what they find engaging.

But wouldn’t it be great if more people stuck with it? Wouldn’t that show that it was really working?

We wound up talking quite a bit about balance this week – reaching that Goldilocks spot that is not too hard and not too soft in not just our technologies but the whole system of which technologies are a part. i think that the change11 MOOC technology, though decidedly flaky in places (Stephen Downes is brilliant but he only has so much time to build and manage tools along with the rest of his commitments), is evolving nicely, employing precisely the kind of principles I’ve been advocating this week and for many years, of building with small, hard pieces, and aggregating them well. I think I might adapt the interaction design a little here and there but there is now a fairly strong sense of narrative that emerges through the deliberate aggregation of blogs, Tweets and so on, and a good centre to the course on the change11 site, with strong and simple interfaces to other systems so it can itself be reaggregated as we wish. It relies a bit too much on soft technologies – my own sessions this week came close to disaster because Stephen was left having to handle almost the whole thing while George and Dave were away, which meant ‘my’ page labelled me as Erik Duval for most of the week, my sessions didn’t appear in the calendar and today’s session was only linked and announced five minutes before it began. We harden stuff because it makes things less error-prone, faster, more efficient, and there is scope for a little hardening here though, having said that, it was the brittleness of hard technologies that made the announcement of today’s session so late: an automated system had broken down, and a soft technology (Stephen manually running the job) that allowed it to recover.

But, though there is a good bit of top-down structure and some good aggregation of bottom-up content, the scope for emergence is slightly limited because what gets aggregated is presented as a single, flat stream of content, the good and the bad, the useful and the useless, the helpful and the obscurational. It is left almost entirely to soft technologies (ie the reader’s means of constructing structure or recommendations of others) to sort it out. Because it is not easy, this will be demotivating and inefficient. Although a lot of soft cues are available (titles, tags, reputation of the poster, etc) and an extra layer of other social media sits on top (e.g. Tweets from people we respect helping to draw attention to good stuff) and some people are creating their own edited aggregations, there needs to be a lot more texture here. A single view of any course is always going to be a compromise that suits some and not others, but that is even more of a problem when an almost unfiltered stream of stuff comes pouring in with nothing to counterbalance it but the top-down structure of the course leaders. And it’s not enough to subject it to editorial control (e.g. a simple rating system) because different things will be valuable to different people at different times. A number of relatively simple collective-based solutions immediately spring to mind, all of which would require a bit of serious programming somewhere down the line but any of which might make use of existing tools:

  • collaborative filtering – matching people whose interests and tastes seem similar, whether through explicit profiling or mining of implicit preferences, would help to draw attention to things that are more interesting. There are big weaknesses with a CF approach in learning that I and others have written about so it is not the final solution, but it would be a start.
  • tag clouds – this would be especially valuable if it dovetailed with a soft technology, whereby people tagged things not only with #change11 but also other tags to help identify the purpose, theme, pedagogical value of things they post
  • reputation management – perhaps as an adjunct to CF or on its own, a means of helping to distinguish different individuals. I would not be happy with a simple ranking though – my own CoFIND system used an approach that would be useful here, whereby ratings covered a range of dimensions (technically achieved through the use of fuzzy tags with non-binary values) rather than a simple good-bad scale. Slashdot uses similar and many other mechanisms to allow tuning that is highly tailored, a very scrutable user model, but that would be way too complex and nerdy for this purpose 
  • visualisation – combined with other approaches, tools to help show threads, trends, changes, patterns etc
  • adaptive hypermedia – eveyone who joins the course registers on the site and could be encouraged to provide a profile, which could be used as the basis for a simple user model to provide intentional recommendations. 

None of these alone are sufficient but together these, and things like them, might help provide the structures that different people would find useful. Whatever system is used, it is important that it is just employed to provide signposts, not fenceposts. I would resent having things hidden from me, but would value a bit of help in alerting me of things that I might find interesting, or of helping me to find stuff that is most relevant to my current needs.

I think MOOCs are brilliant and I really like what Stephen and George and Dave are doing with this one. It’s an evolving model that is becoming far richer as the years go by but, to be really scalable rather than just big, MOOCs need to begin to mindfully employ some more tools to help different structures and guidance to emerge out that mass of interaction, to really use the crowd. It has been really interesting and a privilege to be involved in this and I look forward to the ongoing conversations and discoveries that will occur over the rest of the course!

Getting to the Goldilocks spot on the soft-hard continuum

There are very few technologies that are wholly hard or wholly soft, at least when viewed as an assembly. It is the proportion of soft/hard parts that make a particular assembly softer or harder. That’s how come replacement can make things harder and aggregation can make things softer. When we replace, we take something from the technology assembly that was formerly flexible and negotiable and make it less so. When we aggregate, we make no changes to the assembly that was there before but we increase the adjacent possible and thus enable more human choice and active shaping of the technology. To help clarify, here is a simple example of how we might harden and soften an assessment activity in a course:

  1. soft: Tell the learners to pass their work to you when they are ready. You will tell them what you think
  2. harder: Tell the learners to pass their work to you when they are ready. You will grade them according to a set of criteria
  3. harder: Tell the learners to pass their work to you on or before a certain date and time. You will grade them according to a set of criteria
  4. harder: Tell the learners to pass their work to you on or before a certain date and time in PDF format. You will grade them according to a set of criteria
  5. harder: Tell the learners to pass their work to you on or before a certain date and time in PDF format, presenting you with no more than 1500 words. You will grade them according to a set of criteria
  6. harder: Tell the learners to pass their work to you on or before a certain date and time in PDF format, presenting you with no more than 1500 words, structured with an introduction, literature review, discussion and conclusion, with correct citations in APA format . You will grade them according to a set of criteria.
  7. harder: Give the learners a templates set of questions that they must answer in essay form with fixed word limits. You will grade them according to a set of criteria.
  8. harder: Put the whole thing in an LMS and use an LSA-based automated marking system to provide feedback and results, according to criteria programmed into the machine. 
  9. Put the whole thing in an LMS and use an LSA-based automated marking system to provide feedback and results, according to criteria programmed into the machine. Late submissions receive an automatic mark of zero. Results are automatically added to a student record sheet without teacher intervention.

Notice that, each time, we replace one flexible part of the technology with another, less flexible part. Logic would suggest that we should simply reverse that procedure to soften things again but, once we start down this kind of path we tend to create a set of path dependencies and  systemic interdepenencies and patterns that affect not only the technology we are looking at but the technologies of which it is a part and those with which it interacts. Typically, this kind of pattern would be accompanied by regulations, processes, tools, learner expectations and policies that would make it trickier to reverse than it was to create. Also, we would seldom want to throw away everything we have gained by hardening and start afresh. If that’s not the case then all is well, we can modify things back to a softer state if that’s what we need. And that would be lovely. But what if we wanted to keep some of the good things from the harder system while enabling alternative and more flexible approaches where needed? Or if other systems (e.g. the pedagogies of the class, the regulations of the course etc) had been built around the harder system? There is another way, using aggregation, that provides a more flexible and simpler-to adapt method of softening. Here is the beginnings of a similar list that reverses parts of the hardness by adding extra technologies:

  1. softer: Put the whole thing in an LMS and use an LSA-based automated marking system to provide feedback and results, according to criteria programmed into the machine. Late submissions receive an automatic mark of zero.  Results are automatically added to a student record sheet without teacher intervention. The results produced by the system are treated as provisional. Students must print their records and take them to the tutor for a signature before they are officially recognised. The tutor may manually amend the marks, and sign the amendment to avoid fraud. The tutor may also manually mark an assignment that has received zero for late submission, if the student provides an acceptable excuse
  2. softer: Put the whole thing in an LMS and use an LSA-based automated marking system to provide feedback and results, according to criteria programmed into the machine. Late submissions receive an automatic mark of zero.  Results are automatically added to a student record sheet without teacher intervention.The results produced by the system are treated as provisional. Students must print their records and take them to the tutor for a signature before they are officially recognised. The tutor may manually amend the marks, and sign the amendment to avoid fraud. The tutor may also manually mark an assignment that has received zero for late submission, if the student provides an acceptable excuseBefore the tutor will sign it, he or she is optionally given a reflective document produced by the student that describes the process. The document gives the student a chance to explain answers in ways that were not possible using the automated form.
  3. softer: Put the whole thing in an LMS and use an LSA-based automated marking system to provide feedback and results, according to criteria programmed into the machine. Late submissions receive an automatic mark of zero.  Results are automatically added to a student record sheet without teacher intervention.The results produced by the system are treated as provisional. Students must print their records and take them to the tutor for a signature before they are officially recognised. The tutor may manually amend the marks, and sign the amendment to avoid fraud. The tutor may also manually mark an assignment that has received zero for late submission, if the student provides an acceptable excuseBefore the tutor will sign it, he or she is optionally given a reflective document produced by the student that describes the process. The document gives the student a chance to explain answers in ways that were not possible using the automated form. If the student wishes, he or she may submit an essay-form version of the answers, formatted according to recognised academic standards. The tutor may choose to treat that as the submission instead of the original automated work.
  4. etc

Note that, though it looks much more complex and full of redundancies this can, with a sufficiently technically advanced component-based system, be at least partially automated  without too much hassle. Using this kind of approach we can selectively soften different parts of the system without necessarily having to roll back the whole thing and lose the hard parts that we value. But soft is indeed hard. The paragraphs describing the technologies are now longer because we are now combining more technologies to achieve the same (but more attuned to our needs) result, and introducing redundancies and complexities for teacher and students that may make it unworthwhile. That’s the trade-off, of course, the reason we need to think about just how soft or hard we would like our systems to be. There are no generalisable right answers here, but our technologies must be sufficiently malleable to allow us to shift the amount of softness and hardness in them according to our ever-changing needs. Without such malleability, we risk being slaves to the machine or floundering in unnecessarily inefficient complexities and substandard tools that are a poor fit with what we want to do

So, we had this meeting and talked about soft and hard things…

I finished the first synchronous sesssion for my bit of the #change MOOC a little while ago. Self referentially, I was a victim of a hard technology of my own devising, a set of slides that formed the background to my talk that, as I talked through them, I realised were in quite the wrong order.

Did that stop me?

Not a bit of it!

Interestingly, however, I could have done so had I had my wits about me. I had found the option where Blackboard Collaborate did give me a menu of available slides to select in addition to the usual back/forward controls. By adding this hard technology to the existing hard technology the makers of the tool had softened it, allowing me to take a non-linear path had I chosen to do so.

But, of course, soft is hard.

The effort of managing the talk, following the chat and grappling with the tools gave me insufficient time to think through a more appropriate path so I took the hard, easy one. As Garrison and Baynton showed in 1987, increasing pacing also increases structure – it is much harder to change the structure in real time than over a longer period. This suggests that ‘hard and fast’ make a better pairing than one might at first think.

It will be interesting to continue the conversation on Friday at 10am MST – see http://change.mooc.ca/cgi-bin/page.cgi?event=45 for announcements about how to get to that.

More woody stuff – how a focus on a tool can blind us to the technology it is a part of

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

Jon holding a stick

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

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

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

Structure, behaviour and wood

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

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

Bradley Messer work in progress

 

 

 

Bradley Messer painting, using the knots in the wood to form eyes

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

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

“Don’t lecture me” (with Twitter track) – Donald Clark at ALT-C 2010 – YouTube

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

Address of the bookmark:

Can Everyone Be Smart at Everything? | MindShift

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

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

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