Dec 11, 2016
January 15, 2015
This article looks at the needs and demands of people seeking learning with the models and designs offered by traditional institutions, and in the spirit of reclaiming learning describe a new network-based system of education with the learner managing his or her education. It questions the employment of models to design learning systems or the learning process, and recommends instead that learning be developed on a case-by-case basis by the learners themselves as they work within a network of learning resources within a personal learning environment. Learning design on this model resembles a murmuration, shaping and reshaping itself in a self-organizing manner. The author recommends that students self-organize by ‘reclaiming learning’, that is, developing their own learning systems and working outside traditional institutions of learning.
Keywords: learning, networks, MOOCs, personal learning environment
Introduction: What learners Need
I want to begin with a story that came across the wires recently and I thought was very appropriate for this paper. (Inman, 2014) The story described a manifesto that was authored by economic students demanding that the way their profession be taught be changed. Here’s what they said:
We, over 65 associations of economics students from over 30 different countries, believe it is time to reconsider the way economics is taught. We are dissatisfied with the dramatic narrowing of the curriculum that has taken place over the last couple of decades. This lack of intellectual diversity does not only restrain education and research. It limits our ability to contend with the multidimensional challenges of the 21st century. (International Student Initiative for Pluralism in Economics, 2014)
They made observations about things like the global economic collapse and global climate change and other things not really being addressed by current economic theory. They suggested, not so much that current theory is wrong, although current theory is wrong, but that they should be given alternatives or different ways of being able to look at the world. They wanted, in other words, from my perspective, more control over their education.
Professors, meanwhile, far from embracing this Renaissance of student-led learning, are sticking to the tried-and-true traditional way of lecturing in the classroom to the point where they want laptops banned from the classroom. Dartmouth professor Dan Rockmore said in an article in the New Yorker, "These digital assistance are more suitable for play and socializing." (Rockmore, 2014) This is not getting the point that learning today is about play and socializing. It's interesting to note the study he cites, which says, "Taking notes by hand creates better memory recall than taking notes by typing.'' (Talbert, 2014) This again misses the point of what learning is about. As I shall argue in this paper, learning is not remembering.
Active learning works better (Lederman, 2014) than the lecture used and defended by traditional institutions. “Students in sections characterized by active learning scored 6 percent better on examinations than did their counterparts in lecture-only classrooms, and those who were in lecture-driven sections were 1.5 times likelier to fail than were their peers in active learning classes.” (Freeman, 2014) It may seem odd, then, that I engage in lectures myself. But what I’m really doing to engage in the process of creating a learning resource that I hope will be used, shared, cut, clipped, and otherwise abused by people around the world through the years that follow. This isn't so much about the content of this talk and people remembering what I say as it is about creating the possibility, the potential for dialogue and interaction. As Iyadunni Olubode says, “Everyone knows that learning is growing at an increasing depth and an increasing breadth, so you need people who can constantly learn and bridge that gap, even when they're in their current jobs.” (Olubode, 2014)
This is the shape of learning in the future. It is not learning where you go to a lecture, you remember the gospel wisdom that your professor has told you, and you go out forth in the world and propagate it. It's a world where a person is constantly learning before they get to university, while they're in university, after they're at university. It's a world where the content, the nature, and even the means of learning is changing almost on a daily basis. People are looking for learning that isn't so much the repetition of their professors' ideas, but learning that they can apply, that is a part of their life, whether it's part of their life in work, part of their life in their hobbies or their avocations, or part of their life just in what interests them. (Bolkan, 2014) They expect universities to be flexible. (Zogby Analytics, 2014)
This dichotomy between what universities provide and what students want becomes evident in conversations with faculty and staff. At the London School of Economics, for example, where I gave a talk on this subject, we were talking about how the university is structured Bachelor's, Master's, PhD, maybe a couple of other names for these degrees. That's pretty much it. That's not what people are looking for. In survey after survey, they want learning that is directly and immediately applicable to what they're doing. (AfricanEconomicOutlook.org, 2012) "Students expect universities to be more accessible, flexible and focused on jobs." (Zogby Analytics, 2014)
Figure 1. The shifting burden from government support to tuition revenue. Via The Economist, op. cit.
Economists, on the other hand, have their own view of what academia needs. (The Economist, 2014) We've been hearing a lot about it both in Europe as well as in North America. The economists are talking about these days is the destruction of the university at the hands of the massive open online course. “Universities are up against serious cost and efficiency problems, with little chance of taking more from the public purse.” As one of the people who invented the massive open online course, I feel a little personally involved here. It wasn't our intent. I just want to be clear about that now. It was not our intent to destroy universities. That's not why we did it. We want to change universities, and we want them to work for the better.
Thinking in Models: for Design, for Learning…
A large part of this paper is about that change. It may be tempting to transition from people wanting universities to be relevant immediately to the idea that universities will be replaced without thinking about what we need to do in between, but we need to do this thinking.
What are models?
So what are some of the steps in between? We're told there will be tiered service models at universities. We're told there will be analytics and data-driven management. We're told there will be alternative credentials. (Sandeen, 2014) To a certain degree, all of these three things are true. But to a certain degree, none of these three things are going to work themselves out in the way that the economist or economists or education reformers predict.
When you look at that, basically it's like they have this model or design in their head of how we could rebuild the university system, wipe it all out, start over, and we'll have a new model.
Figure 2 - workflowprocess employed to assist LMS selection
This model of accountability and cost frameworks and all of that will solve all the problems that the current system has. Models are popular in education too. Here's a model (Figure 1) of a workflow-processed employee to assist LMS selection. (Norman, 2014) You can't really read the small writing there but it’s not important. Notice the flow from enrollment to program administration to learner interactions to content creation to assessment. It's a fishbone diagram. If you're in economics or business, you're probably familiar with it.
In addition, we have models describing how to select educational technology using customized lists of LMS features, a way of picking among those 305 features of a learning management system that you might want to solve the educational problems at your institution. (Wright, Lopes, Montgomerie, Reju, & Schmoller, 2014)
Models of how to do learning, learning design patterns: Grainne Conole has done a lot on this. Diana Laurillard, who I really wish had been there yesterday because I really wanted to have a chance to discuss some of this she's been working on. If you get the pedagogy right, that will solve all the learning problems. (The Learning Designer, 2014)
There are models for best practices for typical learning tasks, for example, a reference to a paper that talks about the conditional release of materials, or what we used to call back in the day programmed learning. (Fisher, Gardner, Brinthaupt, & Raffo, 2014) You do some learning, you do a test. If you pass the test, you get to see the next learning. You still see the old professors with their overhead projectors and their slides and their little piece of paper that they slowly work down the slide. Goodness, you can't have people reading the bottom of the slide first. It would be just wrong.
There are even models of how to offer courses. There are numerous discussion like this in the literature, such as the way Brinthaupt (et.al.) breaks the model of online, hybrid or traditional models into things like the types of tools, whether you're using discussion boards or white boards or websites or videos. (Brinthaupt, Clayton, Draude, & Calahan, 2014) There's a selection matrix. Out the other end comes level two decisions. You have all of these inputs and outputs. It's very much a systems theory approach. If you get the system and the process right and everything flows out the bottom the way it should.
In these models, these designs are being implemented as educational technology. This is what education reform is about. “Wow,” as I said yesterday, sarcastically. It's also about making a lot of money for some people. It's about standardizing and rationalizing the educational system to fit into a certain set of models or designs.
There’s more. For example, we have Google coming out with Classroom just as part of Google apps for teachers. (Google, 2014) It does all the really useful stuff that teachers need to do like marking and scheduling and assigning learning tasks and all of that sort of stuff. It's education done by software application, basically. It's being commoditized and being standardized and being packaged and delivered. This is education of the future.
The MOOCs that came out, not the ones that we did, but the ones that came out after us, are, again, very much in that same model. “Carnegie Melon University received a two-year grant for research on and development of MOOCs platforms ‘intelligent enough to mimic the traditional classroom experience.’” (UOIC UNESCO Chair, 2014) Get some videos, get some exercises, get some tests, and step students through the material week by week by week. You don't even need a professor. It's nice to have them to do the videos, but otherwise you just deliver this as a content package. (Caulfield, 2013)
Everybody gets the same thing. That's what works. It's Dan Willingham and Paul Kirschner and they say, "There are no individual differences in how we learn. The way we learn depends on the content, not the learner." (Clark, Kirschner, & Sweller, 2012) (Riener & Willingham, 2010) That's a pedagogical approach that I feel is incorrect. I think it is obvious that people learn differently. Learning styles, as a theory, and especially as a design theory, may be wrong. But people learn differently.
Models are not Reality
The fact is that people learn differently, that they have different objectives, different priorities, different goals, different times that they want to learn, different pets sleeping on their keyboard, all of these impact how people want to learn. That's immediately obvious to anyone who actually looks at people learning. Even as I look around the room, he's on an iPad, she's typing, she's writing on a notepad, he's asleep. Everyone learns differently.
As an example, Google has created a page called ‘Apps for Teachers’. (Google, n.d.) These applications model the work of education, according to Google: creating and collecting assignments, making announcements, asking questions, and, of course, a folder, school folder for each assignment and for each student.
Of course Google will mine[reviewer1] this data. They've said they will no longer mine student data for commercial purposes. (Hustad, 2014) They recently came out with that pledge. They did not say they will no longer mine student data. They just said they won't do it for commercial purposes anymore. Google knows people learn differently. That’s why it’s important to mine the data.
With models, again, maybe I'm talking to economists here, maybe I'm not. I'm not sure, but this was actually the subject of my Master's thesis, which maybe three or four people have read. The model is not the reality. That's my 235-page thesis in one sentence. The model is not the reality. The model has never been the reality, and worse, when you're doing any kind of research, if you use a model, typically the answer to the questions you're researching have been defined by the employment of the model in the first place.
That's what happens here. If we use these models, or other models, the design of the model predetermines the structure that defines how we will understand what learning is[reviewer2] . We've predefined what the outcome will be. But learning needs to be open-ended. Learning needs to be an exploration and a discovery, not the output of predefined, standardized products. The adaptation of these models to computerized learning is no more effective than the use of these models in the classroom.
New Versions of Old Models
If your teacher walked in and spoke from a script and answered every question in the same standardized way, you would not consider that effective education. The same is true if it's done on a computer.
Again, we're told that these MOOCs are a new pedagogy. We're told that what's being done at Stanford, MIT, EdX, the rest of it, is going to change education, but it's a continuation of the same models and the same strategies that have defined education for decades, despite the fact that people are asking for something different. It's not even that the new models are the old models with new names. The new models that we're seeing today being done on a computer are the same models we saw being done on a computer a decade ago and two decades ago.
Audrey Waters, for example, talks about Fathom. (Watterrs, 2014) Fathom had a plan. What their plan was, to take learning materials, put them on a computer, and make them available, even openly, to people who wanted to learn. That was almost 20 years ago. People talk about EdX and Coursera and the rest of them as being new. It's like they've written off the previous experiences.
Interestingly, she notes, the president of Coursera is the former president of Yale who while there had the same wonderful idea of putting courses online and charging money for them. Guess what he's going to do at Coursera. It's the same model being repeated over and over and over again. Universitas 21 was invented something like 15 years ago to monetize online learning. It's one of many initiatives to take a course, charge university‑level tuition for it, and sell it online.
This is not what people want, and these initiatives continuously fail.
The same is the case in other areas of educational technology. The LRMI (Learning Resource Metadata Initiative) (Barker, 2014) is a system of standardizing the descriptions of learning resources, but it's a clone, in many respects (I'll talk about a way in which it's not a clone below) but it's a clone, in many respects, of the standards‑driven efforts that have come before. The AICC, (Aviation Industry Computer‑Based Training Committee) had a set of learning resource metadata standards in the 1990s. So did the IMS, Instructional Management Systems. So did IEEE, which is the IEEE, learning object metadata. So did Advanced Distributed Learning, with SCORM, the Shareable Courseware Object Reference Model. And of coursed all of these are based on card catalogue entries we would have found in libraries in our youth.
Again, over and over and over again we see the same pattern: take standardized resources, create standardized descriptions, and create standardized search mechanisms. The standard is the golden standard of learning, it seems, and it's always thought that [reviewer3] if we could just get this precise standard right, it'll all work.
The results have been, over the years, pretty much what you expect. Looking at LRMI again, Phil Barker can list only six or seven institutions using LRMI. (Barker, Who is using LRMI metadata?, 2014) As with all of these standards initiatives, the easy part is to define the standard. I've designed dozens of standards. The hard part is getting people to use the standard, because everybody does these things differently.
Even the terms within the standards are mostly the same from one standard to the next. Typically there is a URL, a title a description, an author.
Even the mistakes are replicated from one standard to the next. The ‘author field’, for example. You'd think, author, how could you go wrong with author? But in actual use we can see everything from people, lists of people, organizations, associations, sometimes pets, sometimes nothing at all. People put markup in what should be a simple string of characters. They put anything and everything inside the author tag. And this is because there shouldn’t be an author tag; there should be a pointer, link or connection to an external entity.
New versions of old models don't produce new results. (Kelly, 2014) I'd like to go down to Canary Wharf and tack that onto one of the buildings so the economics, who use the same models over and over, can read it. If you do the same thing, even if you do it on a computer, you're going to get the same result. And the same result isn't sufficient.
The Right Model is No Model
I may criticize Coursera and the Stanford MOOCs, but when Norvig and Thrun launched their artificial intelligence MOOC, in the first week, 150,000 people signed up. Overall, I think it was something like 250,000 people signed up for one course, a really hard course that's really difficult to understand, in artificial intelligence. So they were doing something right.
Forget the fact that a lot of them dropped out. A lot of them didn't. Tens of thousands finished. This, by itself, indicates that the old model wasn't working. There was such a pent‑up demand for upper‑level university courses in artificial intelligence that, when one was finally made available, people knocked down the doors trying to get to it.
George Siemens and I launched MOOC on connectivism in 2008. It was focused on a niche subject, about as small a niche as possible. It was about an unknown theory in the field of educational technology. Try going out onto Fleet Street and advertising that. Nobody's interested. We got 2,200 people without advertising. That was our first MOOC, and that was when we realized we were onto something, because again, people were beating down our doors trying to get into it. Not as many people, but they weren't very big doors.
You can see that offering these courses to 10 or 12 people at a time in a seminar, whether it's online or offline, isn't going to work. Following a model – any model – of learning was not going to make our course a success. We had to work beyond models.
The right model is no model. The right model is to do away with the models. (Richards, 2014) Think of non‑standard‑based systems. Think of non‑standard designs. Think of courses where there are no defined learning objectives. Think of a learning environment where there is no common core of content. Think of a conversation where you and I have not first established a shared understanding of the meaning of all of the terms.
That's reality. That's this paper. There is no model for what is being written here. If there is a model, I'm probably breaking it. When you say the paper followed a model, it’s mostly after the fact - look at what I did, and say, "Oh, yeah, that's part of the model," and a new model is born, where there should be no model.
That’s what happened to Sugata Mitra (who has almost been commoditized these days). The concept or the idea behind what he did was turned into a model. And this fact, and not what he did, became the basis for criticism. People went back years later to see these computers, and what they found were nothing but holes in the wall. Computers had been vandalized, the Plexiglas stolen. That happens. It doesn't mean he was wrong. It just means that that experiment for that time was finished. People were looking for a model that would always work, but things don't always work. They work for a time, but then we must move on to something else.
David T. Jones argues that "What's missing," he says, "in the standard‑based models is what we used to think of as BAD." (Jones, 2014) BAD. (Bricolage, Affordances, Distribution). These are all, in a sense, anti-models.
- Bricolage: when IMS Learning Design was introduced they used, in their documentation and in their presentation, the metaphor of actors on a stage, and the teacher, of course, would be the director, and then everybody would play their roles. My objection to Learning Design was to ask, "What about improv?" You can't do improv. That's what's missing with these models. You need to be able to assemble, create and improvise, as we say, on the fly.
- Affordances: When people built the Internet, they did not intend to design a system that would store 680 million cat photos. That was not their purpose, and had anyone anticipated in the 1950s and '60s that they were building a system for storing 680 million cat photos they would have thought, first of all, that it's ridiculous. Then they would have thought, "Who would want such a system?" That's the beauty of the Internet, is that, although it was designed for academic research and to survive nuclear wars and things like that, it turns out to be the perfect place to share your cat photos.
That's what makes it beautiful, the affordances, the possibilities of technology that come up that you didn't plan on ahead of time that you can use for other things. History is full of these things, from the first person to use duct tape for something other than to repair ducts to people using an Apple computer to hold a door open. The misuse of technology is what makes technology great.
- Distribution: The idea that you have to be a certain place to get wisdom is ridiculous. New technology and new learning allow for learning to be not only at the event, but also available online to web video‑streaming people. The idea that things don't have to be in one place anymore, learning in one standard way.
Too much content?
We need to question the presumption ‑‑ and it is a presumption ‑‑ that there's too much content, too much data. So much follows from this presumption. We have information overload. It has to be organized. It has to be standardized. It has to be categorized. Must be delivered in packages[reviewer4] .
David Weinberger says, "We do not, interestingly, feel overloaded by the effects of 1.3 million apple pie recipes or 7.6 million cute cat photos" (maybe he was just referring to the subset of cat photos that is cute, but clearly, it's much larger than that). (Weinberger, 2014) We're not overwhelmed by it at all. We don't walk out in the world, wondering, "What am I going to do? I got so many cat photos."
When we talk about learning, by contrast, it's almost the first thing people say. When we started our MOOC, we got people to bring in content and suggest content to us. We brought in a lot content. And the first thing people said was, "There's too much content. How am I supposed to remember all of this?"
We told our students the same thing we’d say about cat photos today: you're not supposed to remember all of it. You’re not even supposed to view all of it. That's the old way of thinking, the supposition that you're supposed to remember the content that the instructor is delivering. But in this course, we said, you're not supposed to remember it. The whole idea of our course (or any course, this course, this paper) isn't to get you to remember what was said. It is to stimulate in you the sort of mental experience that will create in you the sort of mental structures that will, at some point in the future, be useful to you.
These mental experiences are created through environments and interactions. The goal of the course is to stimulate this environment and this sort of interaction. That's why we want questions and discussions after, and that's why we want the wine and cheese reception after a lecture. We're not expected to master every word of the lecture; we draw from it what we need, each one of us something different, to create the learning environment that follows as we talk about it.
It’s like the pie recipes. We don’t have to remember every one of the 1.3 million apple pie recipes. Mastering one will actually be enough. Mastering three to five will be more than most of us ever do. Actually, mastering one will be more than any of us ever do. The main point is we pick and choose them as we need. The interesting thing is take a room full of 50 people, and 1.6 million apple pie recipes, people will choose, not all the same recipe, but different recipes, because they look different. They seem different.
They appeal to us in different ways. I have a whole talk on this. How you will read "Perfect Apple Pie Recipe" from Pilsbury.com? This will set off one set of mental associations for you, while someone else will read it very differently. Maybe you have a favorable impression of Pilsbury, or maybe you think of the dough‑boy and say, "No, that's not for me." Or maybe a different site, perhaps taste.com.au, appeals to the Australian nationalists in the room.
Personal and Personalized
I want to draw a key distinction here, and it's a distinction that the model builders don't get. It's the distinction between personal learning and personalized learning. It's the same difference as pretty much anything like this: custom tire versus customized tire; chocolate versus chocolatized. Something original versus something that has merely been adapted.
The idea here is that personalized learning is something that's off-the-shelf, where you tweak some variables in it, and you have thereby made it personal. That's what's offered in programmed learning. That's what's offered in customized learning solutions, personalized learning, adaptive learning. (Schuwer & Kusters, 2014) Any of these design‑based systems, they're personalized. They are really all just one one package with a bunch of options that have been set.
Personal learning is made to order. Personal learning can be learning you make yourself. Personal learning is where you build your learning, not from a kit, but from scratch. There’s a difference. People don't want customized, necessarily. Sometimes, they do, but typically they don't. They want something personal. They want something custom.
That's the expensive part of learning. Consider the Oxbridge model. "The Oxbridge model is so much better," said the Deputy vice‑chancellor at Greenwich. Why is it so much better? He has a point. It is better, in many ways, because it's personal. The problem is it’s also really expensive. To provide that for everyone would cost more money than there is in the world.
But it would be nice having learning that's tailored exactly to each person’s needs. If you can build it yourself, that's even better. If you can design your food or choose your food from an infinite array of choices, that's better than going to McDonald's. Even if they offer to take the pickle off for you.
Institutions, I would argue, understand personalized. They don't understand personal. There are so many ways in which this is manifest. Even in some of the discussions about personal websites by institutional staff, the first response that comes up is, "But will they follow institutional standards?" (Hannon, Riddle, & Ryberg, 2014) The answer, of course, is, "Well, no." There's the concern that widespread adoption of social media brings shared interactional practices that do not match university arrangements for learning.
When people from institutions talk about learning, they talk about classes. But when they talk about personal learning, they cannot talk about classes. If the class is like a box, the people who want personalized learning are outside the box. You can have a personalized class, but it's still a thing in a box. Something that's personal must go beyond the box.
Autonomy vs Control
Autonomy, for many reasons, rather than control, is essential in education.
This is a bit of a digression, but I want to be really clear about what I mean here. Autonomy does not mean no structure. It means choice of structure.
Think of touring a city. The way the autonomy‑versus‑control distinction is typically sketched is, if you're visiting a city for the first time, either you wander around with no idea of where anything is or where you are, or you're taken on a guided tour. If you actually want to get someplace in the city, you pretty much have to do the second. You can't do the first, because you'll just wander around aimlessly.
That is not a good distinction. Those are not the choices that are given to people. If you're visiting a city for the first time, you have a number of choices. You could ‑‑ and I do this frequently ‑‑ wander around, aimlessly, not knowing where you are. Or you could wander aimlessly around with a map on your phone. Or you could wander aimlessly around with a dead battery on your phone, but using maps that are put up in the city. Or you could ask someone for directions. Or you could take the train, which will drop you close to where you want to go, although you might have to ask for directions to do that, too. Or you could get on one of those hop‑on, hop‑off buses. Or you could get a friend to drive you around the city and show you things. They offered to do that for me in Greenwich. Or you could join a guided tour. That's choice. That's autonomy. The other option is they kidnap you and take you around the city, no matter where you want to go. That's control. Those are the real choices.
Ironically, we do education the second way. Control, really, is an illusion. (Satell, 2014) Really. When you manage and control a work in order to attain certain outcomes, if the environment is at all complex the outcomes often fail to materialize. The reason is that the designs are really abstractions of the actual process. They are no more accurate than the false dichotomy between autonomy and control that we just sketched above. They're not useful as prescriptions of what should be done. If they're useful at all, they're useful as descriptions of what was done, but only partial representations of what was done.
The personal, by contrast, is not designed. It's based on ‑‑ and the photo of the murmuration shows this ‑‑ based on self‑organization.
Figure 3 - Murmuration.
It's based on the idea that people can manage themselves and manage their interaction with others, including learning, for themselves. Consider the murmuration. (Mastrapa, 2010) They've done studies on the murmuration, and of course, there's no head starling. (Cavagna, 2010) What's interesting is there's no mass communication, either. It's rather more like a mesh network, in which each starling is reacting only to the seven starlings around it. Anytime a starling changes position, the seven starlings around it change position. That's what produces the cohesive movement of the whole.
It's interesting, because when you think of it ‑‑ and that's not even in this article ‑‑ when you think of it, a murmuration is a perceptual system for starlings. It's a way a whole flock of starlings can magnify the perceptions, say, of a hawk, by any individual starling.
Complexity, Cause, and Murmurations
What is interesting in this discussion is the way that design, organization, planning, et cetera, suggests that we can cause these events to happen. For anything that is even slightly[reviewer5] complex, however, there is no cause, properly so-called, of the event.
We award prizes to the person who created a landmark idea, to a person who caused some significant change. But landmark ideas and significant change are created not by individual people, but by societies, by this large murmuration of people interacting with their community. (Mitteldorf, 2014) Not all of them, necessarily, but most of them.
The modern technological world is giving us new examples of that. The hashtag (Kricfalusi, 2014) is a way of creating self‑organizing networks. They turn out to be an excellent way to organize the discussion at a conference. Imagine if we tried to plan the Internet so that we could account for and index and abstract all of the conferences that will happen from now on, before they happened. It'd be ridiculous. Couldn't happen. A new speaker series would be impossible to anticipate. Hashtag networks can be seen as self‑organizing ideas. (Melcher, 2014) The hashtag is a murmuration of tweets.
Mary Meeker ‑‑ if you're not familiar with Mary Meeker, you should be, if you're at all interested in education technology and markets ‑‑ has observed (Meeker, 2014) the proliferation of apps, not just in education, in everywhere. What the app world does is facilitate this kind of network interaction. What she's noticing is that the edge, that is, the link between two nodes, is more important than the node.
In education the node is the person, the computer system, the learner, the starling, whatever. It's the connections that are interesting. That's what's interesting in education, as well. The starlings, in education, are the students. (Hill, 2014) The university, the learning institution, properly conceived, should be organized like a murmuration. Should be a self‑organized assemblage of students. But then, of course, you don't need that institutional structure, at all, and it becomes really difficult to justify a $20,000 or 9,000 pound tuition rate.
A Reclamation Project
It's happening. There was a critic recently who said, "Do you know there are no students involved in these conferences?" I did a search. The search for "student panel" actually yielded 199,000 results on Google. The search for "ed tech student panel" in quotation marks, so it's the union set of those words in that exact order, yielded 2,000 results.
The students are doing this. They are organizing themselves. Audrey Waters says (Watters, 2014) ‑‑ and I think she's quite right ‑‑ "The future of educational technology is a reclamation project." The idea here is that we, the learners, the people who need to learn need to reclaim the management and organization of learning for ourselves.
The same thing is happening on the wider World Wide Web. Facebook, for example, has taken over conversations with our grandparents[reviewer6] : we used to talk to our grandparents in person, but now we require Facebook as an intermediary. The managers of Facebook are using these interactions to run experiments, for example, to see whether they can influence our emotions by adding and removing content [reviewer7] , the results of which will be used for marketing purposes. We need to reclaim our conversations with our grandparents. We need to reclaim our interactions of Plato, Socrates, and the person next door. We have to reclaim control of the data, the content, and the knowledge we create. The idea that this belongs to the university that it belongs to the institution is ridiculous. The idea that the university has any say over what students or even its professors would produce in this Internet is absurd.
Here’s why: Lucy Gray does what I do. She puts her presentations up on Slideshare. One day, Slideshare deleted everything. (Gray, 2014) No explanation. No recourse. She couldn't even contact them. She had to tweet it to get any attention from them. No notice. They were just gone. That's why we have to be the owners of our own education. I read this morning ‑‑ I didn't have a chance to put it in the slides ‑‑ there's a guy who started a course, a Coursera course. Went two weeks into the course, and then he deleted the entire course. (Kolowich, 2014) It was, he said, "An experiment in causing confusion." (It’s not the first time (Kolowich, Professor Leaves a MOOC in Mid-Course in Dispute Over Teaching, 2013) this has happened).
One of my colleagues, Ben Werdmuller, is creating something called Known. (Werdmüller, 2014) Known is an application where, as he says, you can still share selfies, make friends, listen to music, et cetera, or put up cat photos (very important). But in a space that's yours and that you get to have control over. Werdmuller, with Dave Tosh, built a thing called Elgg a while back, which is now widely respected as a social networking environment for learning. They also built something that really should have been much more successful than it was, called Explode, which was a similar sort of thing to Known, except I think Known will be better produced.
David Wiley gushed when he heard of the "publish on your own site, syndicate elsewhere" anti‑model (it's called model in the article but I'm calling it an anti‑model because it's not really a model). (Wiley, 2014) There have been (if you check out the #indieweb hashtag you'll see) indications of this, from Diaspora (disclosure: I invested a hundred dollars in it - that was my only investment; I'll never see a return on it) to App.net, which I actually pay money to as well.
Even to syndication itself, it's this idea that what’s today a silo (which is learning) is going to become the syndication end point. These applications, these services, these resources, are the things we reach out and touch but not where we invest our entire lives.
Reclaimed learning is network learning
Jim Groom has been running something called, "Reclaim your domain." (Groom & Lamb, 2014) There have been various other wordings, "Reclaim innovation, reclaim learning." Starting now, he writes, “a technology that allows for limitless reproduction of knowledge resources, instantaneous global sharing and cooperation. All the powerful benefits of digital manipulation, recombination, and computation.”
That was the potential of the Internet twenty years ago and it was basically stopped by the institutions that decided it should be organized a different way. The idea of "reclaim all of this stuff" is to bring back that idea of the Internet. That begins with personal control over your own resources and your own access to external services including leaning.
I've outlined the model in our discussion earlier today. It used to be the case that you would go to one institution, maybe two institutions and you did all your learning there. It's changing now so that you access learning from multiple institutions. Not just multiple universities, but multiple types of institutions, from colleges and universities, potential employers, current employers, past employers, to pet food stores, to friend networks[reviewer8] , to special interest groups, to hobby groups, to the government, to whatever.
They're all sources of learning. The idea is, you are at the center of this network of learning. Reclaimed learning is network learning. (Laux, 2014) Reclaimed learning is having access to the tools and the mechanisms to freely author and create your own learning and share it with others and to access and use learning that was created by others and shared with you.
It's your mechanism for talking to the starlings that are nearby (I really love that murmuration example. I'll try not to beat it to death, but just happen to be beating a starling).
That's something like what we were building when we were building the first MOOCs. (Levine, 2014) Our MOOCs are called "connectivist MOOCs" or "cMOOCs." What makes them distinct is that the people, the individuals are at the center and the learning resources are all distributed.
You might think, "Well, how do you build a course where the center isn't your course?" What we did is, we pointed students to mechanisms on the current internet where they could each build a network where they are at the centre. We said, "Create a blog on Blogger. Create an account on Delicious and do that. Put photos on Flickr. Add videos to YouTube. Create a Google group." Do any of these things.
In the future we'd say, "Use your own personal web space to organize and coordinate your resources and then tell us what these resources are." You create your space, we'll create a space like this too, and then we'll join them together.
That's what we did. It wasn't a course where we had a pedagogical model in mind where we tried to step people through. It was this ridiculous no‑rules mess that turned into a murmuration, that turned into a MOOC, that turned into something that can attract hundreds of thousands of people.
Technology Behind the Reclaimed Web
Some of the technology(for example, Farhi, 2014) behind the reclaimed web, technology that allows us to have comments on our sites without having to author a comment management system...
There's a tool set these days is called the distributors' developers stack, (Loukides, 2014) where you can build your own website and access external services like storage. The old stack was called LAMP ‑ Linux, Apache, MySQL, and Perl. Perl's programming language. That would be where you manage all your data. Today, the stack is your website, but then all the remote system that you can access with your website.
Making it easier for search engines to index (and this is the promised clarification of LRMI) is Schema dot org, where you manage and create your own metadata. (Barker & Campbell, What is Schema.org?, 2014) You don't have to adopt and adapt IMS or IEEE or whatever. Schema is being set up by the search engines. The search engines are saying, "Here's what you can do. It's almost like tagging with tags for websites.''
Figure 4 - Bitnami Apps
Or this is onecalled Bitnami, it's an app store for server software. (Bitnami, 2014) These are all different apps. Again, they're kind of hard to see. But Word Press, Joomla, Redmine (which I don't know anything about), WAMP stack (Windows something, something, something, probably Python) Moodle, Magneto, for e-commerce, just to name some of them. There are actually 50‑60 different applications.
You want to run a survey. The old way to run a survey on your website is you download and install software like LimeWire, configure it, set it up ‑‑ and hope it works ‑‑ and launch your survey.
The modern way to do it is you get an account with Amazon web services or something that will give you some Cloud hosting. You use the app store you rent a LimeWire for $1.99. It installs in Amazon web services, you put a link to it, you have a survey ready. You're not even using any disk space and Amazon is taking the hit for all the traffic. It cost you a little money but it so much better than Facebook.
Take your data back from Google. (Finley, 2014) This will be a thing, a personal web server, preloaded with open‑source software that lets you run all of your web services from home, your home website.
If you don't think it's going to be a thing, think again. People use to go to the Western Union Wire Office to send messages to each other, then the fax machine was invented, and Western Union installed a fax machine on each one of their offices and figured, "This is great. Now, we can charge people for sending messages, and now they can send facsimile images too."
But what happened instead is, people bought fax machines and put them in their homes. You would think who would put a message sending device in their home? Now, we carry them in our pockets.
This is the future of this technology. The personal learning that I've been talking about isn't just personal learning in a conceptual sense, it is personal learning in a concrete hardware sense. Your university will be a box in your living room.
The modern web (Agarwal, 2014) is distributed, interactive, murmuration of services and people ‑‑ 2RCode, OpenSearch, Windows Live Tiles, touch icons, RSS and even a thing called human dot text. All of these are little pieces. Your flavors will all be different as they should be. The idea that every website must be exactly the same is absurd. Only an economist would come up with that.
Social Networks and Neural Networks
This changes learning. This is what George and I are getting at is of the theory of Connectivism. “Connectivism repositions media as type of content” (Buckreus, 2014) - but content is, remember, the McGuffin; it's the thing that gets us talking to each other.
We use media. We use our own services. We use our interaction with each other to create links with each other. These links with each other, these connections between people, between neurons, between concepts, between ideas. That's the actual learning. I could go on. I have two hour long talks about that, which I won't do.
One question that's always asked is what is the connection between social networks and neural networks? (Matthias, 2014) What is the connection between tweeting each other, or sending email, or skyping, and learning, where learning is the formation of connections between your neurons? Learning is, manifestly, the formation of connections between your neurons. What is the link between this and social networks?
There are two ways of looking at it. Connectivism embraces both ways. These are not alternatives, although they're alternatives, but they're not exclusive alternatives.
George's answer is that it's a multi‑nodal extension. What that means is when you learn it's literally the formation of connections between your neurons. You have a network in your brain. This network extends out of the brain and into devices, into the Internet, and, eventually, through to other people. It's an adaptation of the old McLuhan idea that a communication system is like an extension of the body. An information system is an extension of the mind. Pretty smart.
My answer is just as smart. My answer is pattern recognition. (Vento, 2015) My answer is that neural networks and social networks are, in fact, ontologically different, and one is not an extension of the other, but they're related.
They're related by, first of all, a common set of underlying principles described in the mathematics and the methodology of networks. I talked about underlying network principles like autonomy, diversity, and that sort of thing.
The other aspect of it is that networks learn by pattern recognition. The learning in a network is literally the formation of connections. A society learns by forming connections between its people. A human learns by forming connections between their neurons.
What these connections are actually doing is creating a capacity on the part of the network, as a whole, to recognize characteristic patterns. Just like a murmuration of starlings can recognize a falcon. Not because it has falcon‑like content in its collective mind (when you put it that way, it's pretty absurd, right?) but, because it, as a whole, is a system that can react to the presence of a falcon.
The same principles underlie social networks and personal networks. A social network is a perception mechanism for a society. A neural network is a perception mechanism for a person. Persons can recognize patterns in society. Societies can recognize patterns in persons. The interaction begins to flow.
You can see that the Downes answer and the Siemens answer are really two sides of the same coin. Different ways of seeing the same topic. That's really common in network learning.
Even if we're examining the same thing, we're all looking at it from a different perspective. Our understanding of it is never going to be the content of any individual's mind. Again, that would be ridiculous. Rather, the combination, the pattern created by the multiple perspectives that come into play as we all look at this common object.
If I put a chair in the room, our understanding of the chair is the totality of our perceptions of the chair (which is why Wittgenstein was right and Moore was wrong).
Connectivism can be thought of as a learning theory. (Cain, 2014) Personally, I don't care whether you call it a theory or not. But, it accounts for existing theories, it explains where we are, and it we can make predictions.
One thing I do a lot of is make predictions. The predictions based on connectivism can be tested. I've got a history of making predictions, and I'll continue making predictions. One response of connectivism was the MOOC. (Cain, MOOCs and Connectivist Instructional Design, 2012) We built a course in this network style. What we discovered (and frankly, we did discover this, we did not know this going in this) was that building a course as a network allows you to accommodate a lot of people with very few resources.
We had a budget for our first MOOC of nothing, yet we still managed 2500 people. I shouldn't say nothing - George wrangled the free Elluminate account. What we were doing is we were testing connectivism by using connectivist theory to create a course, and that course resulted in the MOOC. My verdict is the experiment was a success. Participants seemed to agree.
Creating networks, developing professional connections, studies of MOOCs - This one is a study done by a couple of my colleagues, Helene Fournier and Rita Kop. (Fournier, Kop, & Durand, 2014) The people who actually took these MOOCs report that the really important part wasn't the content, because the content was just the stuff that George and I sent, but the creating of networks, the developing of connections, the networking, building on the affordances of this particular network. (Saadatmand & Kumpulainen, 2014)
Where are we going? Here comes the prediction part. Although, it's not just me anymore. I've been talking about personal learning and personal learning environments for a number of years ago.
The Aspen Institute - they're actually one of these right‑wing think tanks, but we'll leave that aside - even they are saying learning has to be personal. (The Aspen Institute Task Force on Learning and the Internet, 2014) Learners have to be empowered to learn any place any time. The idea is to use networks to support and guide learners and, most importantly, build operability across learning networks. Grain of salt: they're thinking of this management design perspective. You can't do exactly what they say, but they have the right in saying learning needs to be personal. Learning needs to be connected. Learning needs to be networked.
Learning control is moving beyond computer‑assisted programs “towards authentic learning context, mediated by technology.” (Buchem, Tur, & Hölterhof, 2014) If you think about it, if learning is a network and not an on‑site event‑based kind of process, it can happen anywhere. It will happen anywhere. It will happen and be managed and controlled by people using their own devices, wherever they happen to be. The devices that are implicated in learning will multiply.
This is an interesting one. (Poynder, 2014) I love this one. Reading and networking will become one and the same thing. This is not exactly what Steve Pettifer is saying. Steve Pettifer developed a program called Utopia. It's an Adobe Reader, but when you read it, a sidebar opens up and gives you all kinds of resources from other services.
We built something similar to that, called Plearn. It was an in‑house proof‑of‑concept project that we did between 2010 and 2012. I've seen similar sorts of things in Microsoft Word. The norm will be to have, if you're consuming (terrible word) consuming content, the norm will be that you have a sidebar experience. Even watching television. It used to be you just sit there (and watch). Remember that? But now, we have what they call the second screen experience.
Reading, watching television, all of these things will be, are becoming networked experiences. In the workplace, connective learning is already changing the workplace. It is going to really change the workplace when our learning becomes present in our devices. (Hinchcliffe, 2014) I used to talk about the fishing rod that teaches you how to fish. Now, recently, I saw an advertisement for a tennis racket that teaches you how to play tennis. Somebody actually built it. It exists. I wish I had the link for it. You have internal sensors. The internal sensors know what a good swing looks like. Feeds back to your device. Your device says, "You really ought to work on that backhand." Or whatever.
Teams and collaborations will be transformed. The old way, the design way, the management way, the control way is to form teams and collaborations, and put people in groups and get them all marching to the same tune, singing the same song, et cetera. The new way is to connect, to interact, but to work autonomously. In software development, they're calling the oscillation principle, (Dixon, 2014) where you get together and connect, and go away and do your thing. Get together and connect, go away and do your thing.
Cooperation is basically defined as a set of interactions in a problem space. (Roschelle & Teasley, 1995) The problem space might be anything. The idea here is that you can achieve results without actually having all the overhead of a collaboration. A murmuration is cooperation. Each starling is autonomous. Each starling decides for itself where it's going to go. There's no shared vision.
"Hey, let's have this really neat kind of amorphous mass." It's like one starling's saying, "That's a falcon," and making its own decision. In cooperation, we don't share models. (Stoner, 2013) We don't share designs. We don't share goals. We don't share objectives. Axelrod talks about cooperation. (Axelrod, 1984) All cooperation requires is a durable relationship.
All the overhead that we typically associate with managing activities on the web, including learning ‑‑ things like centrality, commonality, learning objectives, learning management, controlled outcomes, even trust ‑‑ all of these are unnecessary for self‑organizing systems. They're overhead. They make the institutions rich. They don't do the kind of job that the students need.
Cooperation means working with others. Working with them directly, without the overhead. Doing away with the negotiations, the discussions, the accommodations. All you need is to be able to interact and communicate with people. That doesn't mean you can't have negotiations, discussions, and accommodations. A lot of people like that stuff, and it's OK. But it's like the guided tour. A lot of people like the guided tour. If you want to get on the guided tour and share an experience with people, you can. The point of cooperation is we can run a society where you don't have to[reviewer9] be guided, where you can explore on your own.
The new skills, therefore, both in teaching and learning are network skills. The new skills, pretty much in any discipline now, are network skills. This is a reference to Coding For Journalists so that journalists will understand the real meaning of things like lists, loops, and application programming interfaces. (Bradshaw, 2014) The whole idea here is to understand the concept of how individual entities are related to form patterns, data structures, and entities.
People forget about things like Codeacademy, which have proven, very successfully, through millions of users, that people can do things like learn to program on their own, without being told how to do it. (Griffith, 2014) It's like I mentioned at the beginning of the talk. The model for learning is like socializing and playing games.
A New System of Learning
If you've ever been to the media center, I visited the media center once at MIT, the Media Lab - it was a really interesting experience, because the place is a mess. It's utter shambles. (Resnick, Minsky, Kay, & Negroponte, 2014) It's probably a fire trap. But it's brilliant because people can interact any way they want, using whatever kind of device they want. If you want to build a robot, that's cool. It's all play, but I'm sure it's not all play.
We have these models. One model is called the super‑university. (Cape Breton University, 2014)It's going to respond to government directives or commercial imperatives. It will be designed. It'll produce outcomes. It'll create jobs. Economic development. Employment for graduates. Even manage immigration. Commercialize research. This is a line; people have told me this: "It isn't innovation unless it's been commercialized."
Again, if you're in economics or business, you've probably heard this. I really don't think that's true. You might say it's not innovation unless it's used, but that's something distinct. That's the one model. That's the kind of thinking that (is typical of) the people's that are saying, "There will be 10 universities left in the world." That's the kind of thinking that goes into that sort of model, that sort of design.
They talk about the importance of universities because we need them. They don't talk about what it is, in fact, we need. Think about the topics I've talked about in this presentation. Do we need more models and more designs? Does the world really need another theory of learning, honestly?
Do we need more standards and more measurements? I showed you half a dozen ways of standardizing learning resources. I could go on about standards and measurements. Do we need more centralization and control? Are the people out there yearning, "Control me! I don't know where to go." Do we need, quite frankly, the same mistake repeated again?
We're able now to rebuild our system of learning. Why on earth would we do it the old way? What is it that we need? What we need is the mechanism to support learning itself. When you ask the people what they want, they don't want immediate economic development. They want better lives.
They see things like learning - All of those people who went to the artificial intelligence course, all of those people who flooded into our MOOC, they're doing the same thing that the people of Leiden did when they opted for a university instead of lower taxes. They're doing what the people of Tublingen did, when they said, "We want a university, not industrial development."
We have an alternative. We do have an alternative. There is a model. It's not a model. I shouldn't call it a model. We have an anti‑model. Maybe I should be anti‑anti‑model and call it...Never mind. I won't go there. We can, as they say, reclaim learning.
We can have a way of looking at learning where learning is not structured, designed, and set up to create outputs, but rather run, operated, and controlled as an unorganized, unmanaged system by individuals. I say we're moving beyond institutions in learning, toward a cooperative model, toward a [reviewer10] society based on network knowledge, which we can call a ‘knowing society’, because the society as a whole, as well as the individuals within it, can learn and know new things. That's the model of the future.
It'll be based on software, technology, resources, systems, interactions, communities, and the rest that take learning well beyond formal education. People talked about, "What is the role of formal education and institutions in all of this?" It (the role of formal education and institutions) is to serve that.
Institutions need to adapt and get out of the mindset that they control and manage learning, and now think about how they can serve many different people in many different ways, with the resources, the learning, the coaching, the mentoring, et cetera, that they need when they need it.
We're going to get the opposite of these large, control‑based universities. People say, "This is the death of the university, these MOOCs." It's not. This is the beginning of the university. The shift of the university from something big and large and available only to a few, to something much smaller, much more nimble, much more independent, a lot like community music artists ‑‑ that line was for George Siemens ‑‑ that will cater to specific learning needs. They will number in the hundreds of thousands, not the tens. They will be everywhere.
I thank you for your time and your attention. We do actually have a little time for questions, but I won't say how little. Thank you.
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