Sunday, January 29, 2012

Passwords on gRSShopper

Last night with all the indignation of the morally righteous someone wrote to me and demanded that I do exactly what they say or they would blog about how awful gRSShopper was to the world.

Let me beat him to the punch: gRSShopper is awful. I have never denied it, or claimed anything else. In fact, the most recent version is a 0.3 pre-release release.

His particular concern was that he had heard passwords were being stored as plain text. No, he didn't actually know this, he had just heard it somewhere.

Passwords are in fact stored in the database, not lying around in some plain-text file, and the database is secure and protected against access. So it's not like passwords were there for the taking, and there is no evidence whatsoever that they have ever been taken.

Despite his rudeness, though, he had a fair point about how they were stored, so last night I rewrote the logins so that passwords are encrypted when they are created, and retroactively encrypted every password in the system. This morning I also rewrote the password retrieval system so now it resets passwords instead of simply sending them (I used to encrypt passwords in the past, but actually changed it back because so many users had problems with the password reset system).

It turns out that this was not enough, and he demanded (yes, demanded, complete with bold-face commands littered thoughout his emails) a better password encryption system, one like the ones used by Drupal and Wordpress.

Because in principle, if someone hacked their way into the database, they could then use a brute-force algorithm to crack the passwords, at which point they would have access to - well, information stored in the database.

The concern of course is that people sometimes use the same password in other systems, and so if some hacker got into the gRSShopper database they could access other accounts that people have unwisely set up using the same password.

I'll tell you what. Here's the login system as it now exists in gRSShopper: click here

When I get some time in the future, I'll use full sha1 encryption and make it crack-proof. I'll also put the whole downes.ca and mooc.ca server onto HTTP Secure (https) so people can't pick your passwords out of wifi transmissions they're eavesdropping on (the https stuff he didn't mention but it has been on my mind for years).

Until then: either send me back the login script with the changes made (and don't forget they have to be backward compatible so they don't mess up user accounts even more than I messed them up yesterday), or give me a bit of a break.

gRSShopper does not have a budget. It's something I do in spite of the wishes of my employers, not at their behest. I've paid for the web server out of my own pocket for years. I've spent a lot of my own personal time (and whatever office time I could get away with) working on it. I went through a long process to get permission to release it as open source so that if people had a problem they could fix it.

It would be great if there were some support for the project, if some foundation were to give me the sort of money they give to the grant-writing experts at Stanford and MIT, if I could devote my time to working on making open learning accessible to people instead of working on private hush-hush projects for the government. But I don't have any of that kind of support, and it's even a violation of public service conflict-of-interest guidelines to apply for it (I can't publish books either, for the same reason) so I can't.

So if you have criticisms, either ask me nicely, help me out, or use something else. Don't write to me as though I'm some sort of subordinate you can demand perform this or that task just because you say so on threat of 'exposing' what a crappy software author I am. I love getting suggestions and help. I pathologically hate being given commands or ultimatums.

Oh yeah, and if you're a foundation or some big company or whatever that would like to fund my work, I'm all ears.

Thursday, January 26, 2012

Advice to Teachers on Online Learning


Here are the answers to your questions:

The EdgeX website says this on your page "This to me is a society where knowledge and learning are public goods, freely created and shared, not hoarded or withheld in order to extract wealth or influence. This is what I aspire toward, this is what I work toward." While online learning would be less expensive and hence make learning accessible to many Indians, are there concerns that learning becomes very one sided with no real (as opposed to virtual) interaction?

Yes, of course there are concerns. I think most everyone working in this field today is aware of those concerns. The main point, however, is that those concerns do not create a case against the adoption of online learning.

In the first instance, while we often compare online learning and traditional learning with the presumption that traditional learning is more interactive, this is not in fact true. First of all, in many cases, traditional learning is simply not available, and learning that is not available is not interactive. Online learning *extends* the reach of learning to many people who could not otherwise access it. And second, many instances of traditional learning are not interactive. When I attended university, for example, I attended some very large classes. I never conversed with my instructor at all. I even had difficulty communicating with the teaching assistant. I was very much on my own. Most online learning offers a greater level of interaction than this.

In the second instance, the concern with respect to interactivity is taken as a general principle to the effect that online learning should enable, and even encourage, interaction. With this principle I am in general agreement, at least to the extend that interaction supports learning. Hence the form of courses I design and deliver - 'Massive Open Online Courses' modeled on a connectivist pedagogy - are based around the idea of connection and interaction. It is important, though, to keep in mind that the core of learning for the learner is essentially practice and reflection. The purpose of interaction is to support practice and reflection by creating an environment for practice and fostering authentic reflection. But again, online learning is *more* supportive of interaction than traditional learning.

How do you believe online learning is best used and could be used by Indian educational institutions?

Without having direct familiarity with Indian educational institutions (not to mention Indian culture and traditions) it is very difficult to describe how online learning is best used.

I think though that as a general principle the advice I give to Canadian teachers may well be equally applicable in India. The advice is this: to employ online learning to support one's own teaching and development before attempting to recommend it and use it for one's students. If I were to speak to an Indian teacher today, I would not offer advice on how to improve his or her classes, I would offer advice on how to use the internet to support his or her own learning.

Now clearly even here my advice would have to be taken with the understanding that there are conditions in India I cannot predict nor describe. So my advice could only be understood as my own description of what *I* have done in the online context to improve my own teaching and learning. I offer my own work, my own experience, as the example to draw from, with the understanding that each person's experience is unique, and what works for me may need to be adapted before it works for someone else. Or, as they say on the internet, "Your Mileage May Vary". YMMV.

When I talk about what works for me, I generally describe my process under three major headings: interaction, usability, and relevance. I foster a wide and diverse network of contacts and connections from around the world, in order to draw from the widest range of experience and feedback. To that end I have created what is sometimes called a 'personal learning network' supported by my own online writing as well as places where I can read blogs and comments. Under the heading of 'usability' I foster consistency and simplicity in my life and in my learning. To this end I strive to be clear about my values and purpose, to organize my knowledge around my own understandings, and to represent my understandings from my own perspective and in my own words. Finally, under the heading of 'relevance' I strive to ensure my learning serves my own needs as well as the needs of those whom I serve. I seek learning that is appropriate to the task at hand and accessible to me in both content and format. See more here: http://www.downes.ca/presentation/138

I think that if I understand that this is what my student will seek as well, it may change the way I teach. But I cannot understand how and why my students will seek this until I have understood my own motivations, and seen the benefits for myself. I can't simply *tell* people that "practice 100 times a day is good" (or whatever) - I have to actually do the practice myself, in order not only to know that it actually is good, but also why I would think so, and why I would find this valuable.

Wednesday, January 11, 2012

The Argument from Theft

The argument from theft once again rears its ugly head, this time in an OER discussion forum.

On 01/11/2012 6:44 PM, Jacky Hood wrote:
There is an alternative: stop forcing people to pay for research, education, etc. How good is something that requires jail sentences and fines to get people to pay for it?
Payment for all goods, not just government goods, is enforced with fines or jail. If you walk into a grocery store and take food without paying, you will be fined or jailed, even though food is necessary for life. Indeed, the establishment of a system of jails and fines is one of the major ways government subsidizes private enterprise; try doing business in a country without a functioning police force or judiciary (Somalia, say) and you get a sense of how expense it would be without this subsidy.



Yes, if something is funded by taxpayers, it should be generally available. However, the backers of the 'awful' bill have a valid point. No free enterprise organization can compete against institutions whose 'investors' must put up the money or face fines and imprisonment. Similarly private enterprise cannot compete against products that are free or priced below cost.
The 'investors' are not forced to invest as though by some arbitrary third party. The 'investors' are the people of the nation who have engaged in a free vote and elected representatives who have enacted the sort of social system they find essential. This investment begins, as mentioned above, with a functioning police and court system. The private sector has also been vocal about its need for an educated workforce, and the people of the nation had additionally supplied this. Another service these investors provide to the private sector is publicly funded research.

I would be happy to see the private sector (aka 'free enterprise organization') 'compete' with the public sector, but only given a level playing field - ie., we can attribute to the public sector the costs that the private sector would be forced to pay in order to obtain free content, but we would require that the private sector pay for what the public sector currently provides it for free: police and courses, an education system, and a research program.

The private sector is not being somehow unfairly treated if the population of a country decides to remove a public good from the realm of free market competition. This is usually done in order to subsidize private enterprise in the first place. In such a case, privatizing the service and ending public investment in the program would end up costing more - that's why people have freely opted through democratic government to invest some of their tax money supporting it.



Someone gets to decide what govenment schools/materials/research gets done and those decisions are not necessarily the ones that the payers would choose.
That's correct. In a democracy, decisions are made on the basis of "one person one vote". In a marketplace, decisions are made on the basis of "one dollar one vote" (and "ten dollars fifteen votes", etc). Naturally, the decisions made by the people with the most money will be different from the decisions made by the people with the most votes. But there is no good argument for favouring the decisions made by the people with the most money, as history shows they will make decisions in such a way as to make themselves even more money, usually at the expense of the public.

I've noticed that many academics favor taxpayer funding of art and science, but would balk at taxpayer funding of NASCAR races and bowling tournaments. The marketplace allows more choice for everyone.
No, the marketplace allows more choice for people with money.

It may be that the people, given the democratic choice (rather than one forced on them by the wealthy) would opt for more NASCAR and bowling. If so, then that is the correct decision. But my observation is that the people can generally be trusted. They are not perfect, but they are more trustworthy than the people with money.


Arguing that it's already been paid for so it should be open is a little like saying "if we already have slaves, we should make sure they do high quality work".  The better we make the results, the more we perpetuate the myth that it is OK to use force.
Again with the force argument. If you wish to work outside the domain of laws and police and courts, please be clear about this. Suggesting that measures put in place for the public good are some sort of slavery while measures put in place to protect the interests of private enterprise are something else is disingenuous.

The argument that 'taxation is theft' is dishonest and pernicious. It is propagated by those very people who have benefited the most from the protections offered by law. Measures that take a little bit of that wealth and spread it more widely are not some sort of slavery.  They are the dividend society receives for investing in, and enabling the profit of, the wealthy.

On that basis the argument that open educational resources are somehow 'unfair competition' is unfounded.

-- Stephen

Knowledge and Recognition

Responding to x28, 'Lower Levels of Connectivism'

First, it is probably more accurate to speak of 'domains' of connectivity rather than layers. The use of 'layers' suggests some sort of ordering (from, eg., small to large) that isn't really a defining characteristic. Using 'domains' allows us to recognize that *any* network, appropriately constituted, can be a learning and knowing system.

Second, this usage, "knowledge is found in the connections between people with each other," was a bit loose. I should have said 'entities' instead of 'people', where 'entities' refers to *any* set of entities in a connective network, not just people in a social network. I used 'people' because it's more concrete, but it was a loose usage.

That said, there are two major issues raised in this post. First, how is the sense of 'knowledge' equivalent in one domain and another. And second, how does knowledge cross between domains.

The first raises a really interesting question: does knowledge have a phenomenal quality? And is the nature of this quality based in the physical properties of the network in which it is instantiated? I can easily imagine someone like Thomas Nagel ('What is it like to be a bat?') saying yes, that there is something that it 'feels like' for a neural network to 'know' something that (say) a computer network or a social network does not.

Related to this is the question of whether such a phenomenal 'feel' would be epipehenomenal or whether it would have a causal efficacy. Does what it feels like to 'know' have any influence on our (other) knowledge states? Of is the 'feel' of knowing something merely incidental to knowing?

What I want to say is that there is something in common in the 'knowing' experienced by a neural network and the 'knowing' experienced by a social network, that this something is described by the configuration of connections between entities, so that we can say that 'knowing' for each of these systems is the same 'kind' of thing in important respects, without also having to say that they are the 'same' thing.

Different mechanisms create connections between people with each other and between neurons with each other (and between crows with each other in a crown network, etc). People use artifacts - words, images, gestures, etc. - to communicate with each other, while neurons use electro-chemical signals to communicate with each other. Though the patterns of connectivity between the two systems may be the same, the physical constitution of that pattern is different. It's like a contrail in the sky and a ski trail in the snow - we can observe the sameness of the parallel lines, and make inferences about them (that they never meet, say), while at the same time observe that they have different causes, and that it 'feels' different to create a contrail than it does to create a ski trail.

The same is true of knowledge. We can make observations about the set of connections that constitutes 'knowing' (that it is a mesh, that it embodies a long tail, that a concept is distributed across nodes, etc) independently of reference to the physical nature of that network. And yet, 'knowing' will 'feel' differently to a bunch of neurons than to a bunch of people (indeed, we can hardly say we know how a society 'feels' at all, except by analogy with how a human feels, which may not be a very accurate metaphor).

The second comment concerns how knowledge is transferred between networks (to put the point *very* loosely). There are different senses to this point - how someone comes to know what society knows, how someone comes to know what someone else knows, how somebody comes to know what nobody knows.

In the first instance - and I think this is really key to the whole theory of connectivism - there is no sense in which knowledge is *transferred* between any of these entities.

This is most obvious in the latter case. Learning something nobody knows *cannot* be a case of knowledge transfer. The knowledge must therefore develop spontaneously as a result of input phenomena (ie., experience) and the self-organizing nature of appropriately designed networks.

The organization that results from these conditions *is* the knowledge. The process of self-organizing *is* the process of learning. There are three major factors involved: the input phenomena, the learning mechanism, and the prior state of the network. There is a huge literature describing how such processes can occur.

In the case of one person learning from another, the major different is that the phenomena being experience consist not just of objects and events in nature, but of the deliberate actions of another person. These actions are typically designed in such a way as to induce an appropriate form of self-organization (and there is a supposition that it encourages a certain amount self-organization that one could not obtain by experience alone - the 'zone of proximal development').

What's important to recognize is that the learning is still taking place in the individual, that the other person is merely presenting a set of phenomena (typically a stream of artifacts) to be experienced, and that one's one learning mechanisms and prior state are crucial to any description of how that person learns.

One of the key elements I'd like to point to here is 'recognition'. This is a phenomenon whereby a partial pattern is presented as part of the phenomena, and where, through prior experience, the network behaves as though the full pattern were present. When we see half the letter 'E', for example, we read it as though the full letter 'E' were present.

To 'know' that 'A is B' is to 'recognize' that 'A is B', that is, when presented with 'A', one reacts as though being presented with a 'B'. Recognition lies at the core of communication, as it allows (for example) a symbol 'tiger' to suggest a phenomenon (a tiger).

What is important to understand here is that the recognition is something the *recipient* brings to the table. It is not inherent in the presentation of the phenomenon, and may not even be intended by the presenter (indeed, as likely as not, the presenter had something different in mind).

This also tells us how a piece of knowledge (so-called; there probably aren't really 'pieces' of knowledge) travels from one network to another network. Observe, for example, a murmuration of blackbirds. We humans (the neural networks) observe a flowing dynamic shape in the sky, like a big blob of liquid. We perceive the other network as a whole, and perceive it *as* something. We &recognize* a pattern in the other network.

When a human observes the behaviour of a social network, the human (ie, the neural network) can recognize and respond to patterns in that social network. The patterns are not actually 'created by' or even 'intended' by the social network; they are what we would call 'emergent properties' of the network, supervenient on the network.

So: a person watches 14 other people use the word 'grue' in such and such a context; when the person sees artifacts corresponding to 'grue' he *recognizes* it as an instance of that context. That is to say, on presentation of the artifact representing 'grue', he assumes an active set of connections similar to what he would assume if presented with that particular context.

As a postscript, it's worth mentioning that there's no sense of 'collaboration' or 'shared goal' inherent in any of this. Indeed, I would argue that the use of such terminology makes assumptions that cannot really be justified.

When we say that 'society knows P', what do we mean? *Not* that a certain number of individuals in society know P. There is no apriori reason to assume that social knowledge is the same as individual knowledge, and indeed, it is arguable, and in some senses demonstrable, that what society knows is *different* from what an individual knows. Why? Because the prior state is different, because the learning mechanisms are different, and most importantly, the input phenomena are different.

A society does not, for example, perceive a forest in the same way a human does. A society cannot perceive a forest directly. A human perceives a forest by looking at it, smelling it, walking through it. A society has no such sensations.

A human does not, for example, perceive a neural activation in the same way a neuron does. A neuron receives a series of tiny electro-chemical signals. A human has no such sensations.

A human can only recognize a neural activation *as* something - a forest, say. A society can only recognize a perception *as* something - en economic unit, say, a tract, or something we don't even have a word for.

A human can experience neural activations only in the aggregate - only as a network - in which it may recognize various emergent properties. This set of network activations (this 'sensation') is associated with 'that' set of network activations (that 'knowledge'). The same with a society. It can never experience the forest through the perspective of only one individual - it can only experience the forest through the aggregate of individual perspectives.

The whole dialogue of 'collaboration' presumes that a set of humans can create a fictitious entity, and by each human obtaining the same knowledge (neural state, opinions and beliefs, etc), can imbue this fictitious entity with that state. And by virtue of this action, the fictitious entity can then be assigned some semblance of agency analogous (but magnified) to a human agency.

Assuming that it makes sense to imagine such a creation (and there are many difficulties with it) such a construct does not have independent cognitive properties; it cannot 'learn' on its own, and it cannot 'know' more (or anything different) than any of its constituent human members.

Tuesday, January 10, 2012

Data

Responding to Cooperative Catalyst, Metrics and "Success"

I think data is important (it's the only evidence we have!) but I think that people take a very narrow view of data, which is unfortunate.

- they think, for example, that data is just numbers, when in fact data can be found in the full range of perceptions, including observations of emotions, visceral reactions, likes and dislikes, and more

- they think the only way to work with data is to count things, while in fact data provide a rich range of possible interpretations - connections, patterns, flows, etc

- they think data is cumulative, suitable only for iterations, when (as Kuhn pointed out) the right sort of data shows a greater and greater need for quantuum leaps of scientific revolutions - data about anomalies, data that needs explaining, problems, unanswered questions, etc

- they think data should show you a single 'objective' perspective, when in fact different sets of data yield different perspectives, where these perspectives taken individually and together amount to more than the mass of data aggregated

The problem is not with the use of data to make decisions - the problem is with the simplistic one-dimensional use of data to make decisions. Instead of attacking the data - which leaves you with no ground to stand upon - it makes more sense to attack the simple-mindedness.

Change the grounds! It's not that their approach is 'data-driven' or 'evidence-based' and yours is not, it's that they have very carefully selected a subset of the evidence that will 'count', while you are using a much broader, richer, and ultimately more accurate base of evidence.

(p.s. on the term 'data' - sometimes I use it as a mass noun, and say things like 'data is important', and sometimes I use it as a plural, and say things like 'data provide'; there isn't a single 'correct' way to use the term; its conjugation travels as your usage travels).

Saturday, January 07, 2012

Memory and Memorization

From my post titled 'Wrong':

I get where Gary Stager is coming from. Learning is not the same as remembering. By the same token, I made myself a set of flash cards this week as an aid to remember my past participles in French. So there's another side to it.

Comments:



Gary missed the whole point of what I was saying in my piece for the New York Times. The flaw with adaptive learning is we have no feedback loop to parents. The fact is that this weekend I have to help my fourth grader learn all of the irregular verbs, his spelling words, and the states and capital review for all 50 stated. many theorists argue we shouldn't be doing rote memorization but the fact is our kids are in a system that rewards it. I find that apps help make the learning happen in less time and with less strain on my relationship with my child but there is no feedback loop to help me know if he is getting it or not. Whether we like it or not, there are times our kids have to memorize.


tephen writing from a bus heading to Dodoma Tanzania from daresaalaam a journey of six hours. Thank you for sharing the flash cards. I find the revised. Blooms taxonomy useful. You can not understand what you cannot remember. You then apply what you understand. The rest follow


My Response:

Vicki that's a fine comment for someone who was tired. :)

Here's my thinking: what we need to foster is not memorization, but remembering. However, in cases where we are unable to foster remembering, we need to turn to memorization.

Let me give an example from the perspective of cognitive load theory (I don't need the theory to make the example work, but it's more fun if I use it).

The traditional perspective is, we can remember only seven items at a time. So, I give you seven digits: 4 5 6 2 1 1 6 6 and that's what you can remember. If I give you more 3 2 1 1 3 4 9 4 3 2 you can't do it. Say.

But if you are good at remembering, you'll manage this with no problem because you'll chunk the numbers. 321 - 134 - 9432. Now we can remember it. It's a phone number. It's easy.

Moving beyond cognitive load theory, we are able to remember better if we are able to discover relations, threads, patterns or regularities between what we're trying to remember and something we already know. That's the (crude) purpose of menomics - we convert the long string of things to remember into a simple thing to remember and a rule to convert it into the long string.

This is what we're doing when we're theorizing (what educators like to misleadingly call 'making meaning'). What we're trying to do is to find the underlying thread that connects everything we're trying to remember. A theory. A perspective, or world view.

Sometimes you can't find these regularities overtly. Sometimes there's no rhyme nor reason, or its buried in complexity or antiquity. That's where practice and memorization comes in. By repeating and rote, your brain (which is a fantastic processing machine) will find the patterns you can't find cognitively, and you'll remember.

People who remember really well reach for these associations cognitively, and do the work required to produce them sub-cognitively. That's why, in learning my French verbs, I'm doing some memorization of the stuff there's no rules for (past participles for the irregular verbs), using a mnemonic to remember a subset ('vandertramp'), rules to understand verb-object agreement, and personal discovery to find the key underlying rule (that isn't in the book) that explains everything.

For those who are curious, here's the rule that underlies everything: the verb (extra 'e' for feminine, extra 's' for plural) always agrees with the direct object (You'll never see that stated in the French text, because most of the language is an exception - you see, you have to know what the direct object is, which means you have to have one, it has to be before the verb, and it is sometimes oneself, in which case you conjugate with ĂȘtre instead of avoir).

What you want is the underlying rule that explains everything (or, more accurately, a sense of what underlies everything, because often it can't be explained as a simple rule, but is just felt as a sense or a feeling (which is why cognitivism is wrong - you can't always 'make' this, you often have to grow it).

It's because when you have that underlying grasp of a thing, you are able to manifest expert behaviour - you can know what the thing should be without even thinking about it (which is a good thing, because when you add it all up, if you have a lot to think about).

So, to summarize: remembering really depends on understanding, which is why all the new-fangled progressive teaching methods work better, but understanding can't always be reliably created or scaffolded. It is better to teach students to be able to understand, but also to ensure that they know that sometimes the best and fastest way to understanding is a brute force process of practice and even memorization.

And I might add: this last bit is the work ethic and expectations part of it, and is the place where parents come in. A teacher is not typically in a position to instil the desire to undertake the effort required to practice and sometimes memorize, because this is something that is the result of socialization and culture - the product of a lifetime, not a one-hour-a-week class. 
 

Friday, January 06, 2012

Creating the Connectivist Course

Originally posted in One Change a Day, January 3

When George Siemens and I created the first MOOC in 2008 we were not setting out to create a MOOC. So the form was not something we designed and implemented, at least, not explicitly so. But we had very clear ideas of where we wanted to go, and I would argue that it was those clear ideas that led to the definition of the MOOC as it exists today.

There were two major influences. One was the beginning of open online courses. We had both seen them in operation in the past, and had most recently been influenced by Alec Couros’s online graduate course and David Wiley’s wiki-based course. What made these courses important was that they invoked the idea of including outsiders into university courses in some way. The course was no longer bounded by the institution.

The other major influence was the emergence of massive online conferences. George had run a major conference on Connectivism, in which I was a participant. This was just the latest in a series of such conferences. Again, what made the format work was that the conference was open. And it was the success of the conference that made it worth considering a longer and more involved enterprise.

We set up Connectivism and Connective Knowledge 2008 (CCK08) as credit course in Manitoba’s Certificate in Adult Education (CAE), offered by the University of Manitoba. It was a bit of Old Home Week for me, as Manitoba’s first-ever online course was also offered through the CAE program, Introduction to Instruction, designed by Conrad Albertson and myself, and offered by Shirley Chapman.

What made CCK08 different was that we both decided at the outset that it would be designed along explicitly connectivist lines, whatever those were. Which was great in theory, but then we began almost immediately to accommodate the demands of a formal course offered by a traditional institution. The course would have a start date and an end date, and a series of dates in between, which would constitute a course schedule. Students would be able to sign up for credit, but if they did, they would have assignments that would be marked (by George; I had no interest in marking).

But beyond that, the course was non-traditional. Because when you make a claim like the central claim of connectivism, that the knowledge is found in the connections between people with each other and that learning is the development and traversal of those connections, then you can’t just offer a body of content in an LMS and call it a course. Had we simply presented the ‘theory of connectivism‘ as a body of content to be learned by participants, we would have undercut the central thesis of connectivism.

This seems to entail offering a course without content – how do you offer a course without content? The answer is that the course is not without content, but rather, that the content does not define the course. That there is no core of content that everyone must learn does not entail that there is zero content. Quite the opposite. It entails that there is a surplus of content. When you don’t select a certain set of canonical contents, everything becomes potential content, and as we saw in practice, we ended up with a lot of content.

Running the course over fourteen weeks, with each week devoted to a different topic, actually helped us out. It allowed us to mitigate to some degree the effects an undifferentiated torrent of content would produce. It allowed us to say to ourselves that we’ll look at ‘this’ first and ‘that’ later. It was a minimal structure, but one that seemed to be a minimal requirement for any sot of coherence at all.

Even so, as it was, participants complained that there was too much information. This led to the articulation of exactly what connectivism meant in a networked information environment, and resulted in the definition of a key feature of MOOCs. Learning in a MOOC, we advised, is in the first instance a matter of learning how to select content.

By navigating the content environment, and selecting content that is relevant to your own personal preferences and context, you are creating an individual view or perspective. So you are first creating connections between contents with each other and with your own background and experience. And working with content in a connectivist course does not involve learning or remembering the content. Rather, it is to engage in a process of creation and sharing. Each person in the course, speaking from his or her unique perspective, participates in a conversation that brings these perspectives together.

Why not learn content? Why not assemble a body of information that people would know in common? The particular circumstances of CCK08 make the answer clear, but we can also see how it generalizes. In the case of CCK08, there is no core body of knowledge. Connectivism is a theory in development (many argued that it isn’t even a theory), and the development of connective knowledge even more so. We were hesitant to teach people something definitive when even we did not know what that would be.

Even more importantly, identifying and highlighting some core principles of connectivism would undermine what it was we thought connectivism was. It’s not a simple set of principles or equations you apply mechanically to obtain a result. Sure, there are primitive elements – the component of a connection, for example – but you move very quickly into a realm where any articulation of the theory, any abstraction of the principles, distorts it. The fuzzy reality is what we want to teach, but you can’t teach that merely by assembling content and having people remember it.

So in order to teach connectivism, we found it necessary for people to immerse themselves in a connectivist teaching environment. The content itself could have been anything – we have since run courses in critical literacies, learning analytics, and personal learning environments. The content is the material that we work with, that forms the creative clay we use to communicate with each other as we develop the actual learning, the finely grained and nuanced understanding of learning in a network environment that develops as a result of our working within a networked environment.

In order to support this aspect of the learning, we decided to make the course as much of a network as possible, and therefore, as little like an ordered, structured and centralized presentation as possible. Drawing on work we’d done previously, we set up a system whereby people would use their own environments, whatever they were, and make connections between each other (and each other’s content) in these environments.

To do this, we encouraged each person to create his or her own online presence; these would be their nodes in the course networks. We collected RSS feeds from these and aggregated them into a single thread, which became the course newsletter. We emphasized further that this thread was only one of any number of possible ways of looking at the course contents, and we encouraged participants to connect in any other way they deemed appropriate.

This part of the course was a significant success. Of the 2200 people who signed up for CCK08, 170 of them created their own blogs, the feeds of which were aggregated a tool I created, called gRSShopper, and the contents delivered by email to a total of 1870 subscribers (this number remained constant for the duration of the course). Students also participated in a Moodle discussion forum, in a Google Groups forum, in three separate Second Life communities, and in other ways we didn’t know about.

The idea was that in addition to gaining experience making connections between people and ideas, participants were making connections between different systems and places. What we wanted people to experience was that connectivism functions not as a cognitive theory – not as a theory about how ideas are created and transmitted – but as a theory describing how we live and grow together. We learn, in connectivism, not by acquiring knowledge as though it were so many bricks or puzzle pieces, but by becoming the sort of person we want to be.

In this, in the offering of a course such as CCK08, and in the offering of various courses after, and in the experience of other people offering courses as varied as MobiMOOC and ds106 and eduMOOC, we see directly the growth of individuals into the theory (which they take and mold in their own way) as well as the growth of the community of connected technologies, individuals and ideas. And it is in what we learn in this way that the challenge to more traditional theories becomes evident.

What we’ve learned – at least to me – is that cooperation is better than collaboration, that diversity is better than sameness, that harmony is better than competition, that openness is better than exclusivity, and that understanding complexity is better than reduction to simplicity. These are, to my mind, the opposite of the bases on which traditional education is designed. Does that make connectivism a theory? In a real sense, that question is irrelevant. ‘Theory’ implies principles and abstraction; connectivism is, in practice, the opposite of that.

If that all we’ve learned, that’s enough. But I think, as we read what follows in this series, that the learning is just beginning.