We argue that learning occurs in networks, and therefore, that the properties of successful networks are also the properties of successful learning environments. We don't 'apply' this in any strict sense - we would never force people to be connectivists. Indeed, within the learning environment, we believe there should be diversity; we believe people should be free to choose their own form of learning.

To me, <span style="font-style: italic;">far more</span> complex - and insightful - forms of reasoning are being created through the interplay among thousands, or millions, of individual content elements. Where each content element may by itself appear to be <span style="font-style: italic;">simple</span>, it is the interconnections between them that creates a much more complex, deep, and <span style="font-style: italic;">rich</span> tapestry of meaning, <span style="font-style: italic;">far more</span> than could be created merely using linguistic devices.

It is substantially <span style="font-style: italic;">harder</span> to work with the disorder and complexity we see within a connectivist network. Because linguistic (syntactical and semantical) descriptions of the concepts and entities in such a network just barely touch the surface, and students must therefore immerse themselves in the process of reasoning in such a system, rather than merely reading about it.

With its inclusion of <a href="javascript:open_win('extra.php?id=3158',650,750,0,0,0,0,0,1,1,0,5,'extra');">game elements</a>, which foster attention, memory, and motivation, SCCS provides a bridge between behaviorist and cognitivist learning theories.

SCCS learning theory focuses on the formation of <a href="javascript:open_win('extra.php?id=3011',650,775,0,0,0,0,0,1,1,0,5,'extra');">schemata</a> in the process of learning, particularly <a href="javascript:open_win('extra.php?id=3206',600,625,0,0,0,0,0,1,1,0,5,'extra');">social-connectedness</a> and <a href="javascript:open_win('extra.php?id=3207',600,375,0,0,0,0,0,1,1,0,5,'extra');">cognitive-connectedness</a> schemata.

Students engage their social-connectedness schema in a set of behaviors that I describe as “link, lurk, and lunge”: Students <em>link</em> up with others who have the knowledge they need; they <em>lurk</em>, watching others who know how do to what they want to do; and they<em> lunge</em>, jumping in to try new things often without seeking guidance beforehand (Brown 2000).

The cognitive-connectedness schema structures a student's ability and desire to know how what they are learning connects to a larger picture.

In other words, cognitivists defend an approach that may be called ‘<a href="http://plato.stanford.edu/entries/folkpsych-theory/">folk psychology</a>’. “In our everyday social interactions we both predict and explain behavior, and our explanations are couched in a mentalistic vocabulary which includes terms like ‘belief’ and ‘desire’.” The argument, in a nutshell, is that the claims of folk psychology are literally true, that there is, for example, an entity in the mind corresponding to the belief that 'Paris is the capital of France', and that this belief is, in fact, what might loosely be called 'brain writing' - or, more precisely, there is a one-to-one correspondence between a person's brain states and the sentence itself.

We may contrast cognitivism, which is a <i>causal</i> theory of mind, with connectionism, which is an <a href="http://en.wikipedia.org/wiki/Emergentism"><i>emergentist</i></a> theory of mind. This is not to say that <a href="http://en.wikipedia.org/wiki/Connectionism">connectionism</a> (see <a href="http://plato.stanford.edu/entries/connectionism/">also</a>) does away with causation altogether; it is not a ‘hand of God’ theory. &nbsp;It allows that there is a physical, causal connection between entities, and this is what makes communication possible. But where it differs is, crucially: <i>the transfer of information does not reduce to this physical substrate</i>. Contrary to the communications-theoretical account, the new theory is a non-reductive theory. The contents of communications, such as sentences, <i>are not isomorphic</i> with some mental state.

For example (and there are <i>many</i> we could choose from), consider Randall O’Reilly on how the brain represents conceptual structures, as described in <a href="http://psych.colorado.edu/%7Eoreilly/papers/OReillyIPap.pdf">Modeling Integration and Dissociation in Brain and Cognitive Development</a>. He explicitly rejects the ‘isomorphic’ view of mental contents, and instead describes a network of distributed representations. "Instead of viewing brain areas as being specialized for specific representational content (e.g., color, shape, location, etc), areas are specialized for specific computational functions by virtue of having different neural parameters...

For example, when I say, "What makes something a learning object is how we <i>use</i> the learning object," I am asserting a functionalist approach to the definition of learning objects (people are so habituated to essentialist definitions that my definition does not even appear on lists of definitions of learning objects).<br><br>It's like asking, what makes a person a 'bus driver'? Is it the colour of his blood? The nature of his muscles? A particular mental state? No - according to functionalism, what makes him a 'bus driver' is the fact that he drives buses. He performs that <i>function</i>.

To illustrate this concept, I have been asking people to think of the concept 'Paris'. If 'Paris' were represented by a simple symbol set, we would all mean the same thing when we say 'Paris'. But in fact, we each mean a collection of different things and none of our collections is the same. Therefore, in our own minds, the concept 'Paris' is a loose association of a whole bunch of different things, and hence the concept 'Paris' exists in no particular place in our minds, but rather, is scattered throughout our minds.

<p><font face="Arial"><font style="font-size: 11pt;" size="2">As we examine the emergentist theory of mind we can arrive at five major implications of this approach for educational theorists:</font></font></p> <p><font style="font-size: 11pt;" size="2"><font face="Arial">- first, knowledge is <a href="http://www.ai.rug.nl/%7Elambert/projects/miami/taxonomy/node99.html">subsymbolic</a>. Mere possession of the words does not mean that there is knowledge; the possession of knowledge does not necessarily result in the possession of the words (and for much more on this, see Michael Polanyi's discussion of '<a href="http://artsci.wustl.edu/%7Ephilos/MindDict/tacitknowledge.html">tacit knowledge</a>' in '<a href="http://www.amazon.ca/Personal-Knowledge-Towards-Post-Critical-Philosophy/dp/product-description/0226672883">Personal Knowledge</a>').</font></font></p> <p><font style="font-size: 11pt;" size="2"><font face="Arial">- second, knowledge is distributed. There is no specific 'mental entity' that corresponds to the belief that 'Paris is the capital of France'. What we call that 'knowledge' is (an indistinguishable) pattern of connections between neurons. See, for example, Geoffrey Hinton, '<a href="http://www.cs.toronto.edu/%7Ehinton/distrep.html">Learning Distributed Representations of Concepts</a>'.</font></font></p> <p><font style="font-size: 11pt;" size="2"><font face="Arial">- third, knowledge is interconnected. The same neuron that is a part of 'Paris is the capital of France' might also be a part of 'My dog is named Fred'. It is important to note that this is a non-symbolic interconnection - this is the basis for non-rational associations, such as are described in the recent Guardian article, '<a href="http://www.guardian.co.uk/life/feature/story/0,13026,1517186,00.html">Where Belief is Born</a>'</font></font></p> <p><font style="font-size: 11pt;" size="2"><font face="Arial">- fourth, knowledge is personal. Your 'belief' that 'Paris is the capital of France' is quite literally different from my belief that 'Paris is the capital of France'. If you think about it, this must be the case - otherwise <a href="http://en.wikipedia.org/wiki/Gestalt_psychology">Gestalt tests</a> would be useless; we would all utter the same word when shown the same picture.</font></font></p> <p><font face="Arial"><font style="font-size: 11pt;" size="2">- fifth, what we call 'knowledge' (or 'belief', or 'memory') is an emergent phenomenon. Specifically, it is not 'in' the brain itself, or even 'in' the connections themselves, because there is no 'canonical' set of connections that corresponds with 'Paris is the capital of France'. It is, rather (and carefully stated), a recognition of a pattern in a set of neural events (if we are introspecting) or behavioural events (if we are observing). We infer to mental contents the same way we watch Donald Duck on TV - we think we see something, but that something is not actually there - it's just an organization of pixels.</font></font></p>

If this is the case, then the concepts of <i>what it is to know</i> and <i>what it is to teach</i> are very different from the traditional theories that dominate distance education today. Because if learning is not the transfer of mental contents – if there is, indeed, no such mental content that exists to be transported – then we need to ask, what is it that we are attempting to do when we attempt to teach and learn.

<p><font face="Arial"><font style="font-size: 11pt;" size="2">we can identify the essential elements of network semantics.</font></font></p> <p><font face="Arial"><font style="font-size: 11pt;" size="2">First, <i>context</i>, that is, the localization of entities in a network. Each context is unique – entities see the network differently, experience the world differently. Context is required in order to interpret signals, that is, each signal means something different depending on the perspective of the entity receiving it.</font></font></p> <p><font face="Arial"><font style="font-size: 11pt;" size="2">Second, <i>salience, </i>that is, the relevance or importance of a message. This amounts to the similarity between one pattern of connectivity and another. If a signal creates the activation of a set of connections that were previously activated, then this signal is salient. Meaning is created from context and messages via salience. </font></font> </p> <p><font face="Arial"><font style="font-size: 11pt;" size="2">Third, <i>emergence,</i> that is, the development of patterns in the network. Emergence is a process of resonance or synchronicity, not creation. We do not <i>create</i> emergent phenomena. Rather emergence phenomena are more like commonalities in patterns of perception. It requires an interpretation to be recognized; this happens when a pattern becomes <i>salient</i> to a perceiver.</font></font></p> <p><font face="Arial"><font style="font-size: 11pt;" size="2">Fourth, <i>memory </i>is the persistence of patterns of connectivity, and in particular, those patterns of connectivity that result from, and result in, salient signals or perceptions.</font></font></p>

For example, in order to illustrate the observation that ‘knowledge is distributed’ I have frequently appealed to the story of the 747. In a nutshell, I ask, “who knows how to make a 747 fly from London to Toronto?” The short answer is that <i>nobody</i> knows how to do this – no one person could design a 747, manufacture the parts (including tires and aircraft engines), take it off, fly it properly, tend to the passengers, navigate, and land it successfully. The knowledge is <i>distributed</i> across a network of people, and the phenomenon of ‘flying a 747’ can exist at all only because of the connections between the constituent members of that network.

<p>“<font style="font-size: 11pt;" size="2"><font face="Arial">What happens,” I asked, “when online learning ceases to be like a medium, and becomes more like a platform? What happens when online learning software ceases to be a type of content-consumption tool, where learning is "delivered," and becomes more like a content-authoring tool, where learning is created?”</font></font></p> <p><font face="Arial"><font style="font-size: 11pt;" size="2">The answer turns out to be a lot like Web 2.0: “The model of e-learning as being a type of content, produced by publishers, organized and structured into courses, and consumed by students, is turned on its head. Insofar as there is content, it is used rather than read— and is, in any case, more likely to be produced by students than courseware authors. And insofar as there is structure, it is more likely to resemble a language or a conversation rather than a book or a manual.”</font></font></p>

The idea behind the personal learning environment is that the management of learning migrates from the institution to the learner.

Learning therefore evolves from being a transfer of content and knowledge to the production of content and knowledge.

In a distributed environment, however, the design is no longer defined as a type of process. Rather, designers need to characterize the <a href="http://www.cetis.ac.uk/content2/20050124115817">nature of the <i>connections</i></a> between the constituent entities.

In effective networks, content and services are <i>disaggregated</i>. Units of content should be as small as possible and content should not be ‘bundled’. Instead, the organization and structure of content and services is created by the receiver.

An effective network is <i>desegregated</i>. For example, in network learning, learning is not thought of as a Separate Domain. Hence, there is no need for learning-specific tools and processes. Learning is instead thought of as a part of living, of work, of play. The same tools we use to perform day-to-day activities are the tools we use to learn.

Knowledge is a network phenomenon. To 'know' something is to be organized in a certain way, to exhibit patterns of connectivity. To 'learn' is to acquire certain patterns.

<tr><td><p align="CENTER"><font face="Arial"><font style="font-size: 11pt;" size="2"><b>Downes Educational Theory</b></font></font></p> </td> </tr> <tr> <td> <p><font face="Arial"><font style="font-size: 11pt;" size="2">A good student learns by practice, practice and reflection.<br>A good teacher teaches by demonstration and modeling.<br>The essence of being a good teacher is to be the sort of person you want your students to become.<br>The most important learning outcome is a good and happy life.</font></font></p></td></tr>

In essence, on this theory, to learn is to immerse oneself in the network. It is to expose oneself to <i>actual</i> instances of the discipline being performed, where the practitioners of that discipline are (hopefully with some awareness) <i>modeling </i>good practice in that discipline. The student then, through a process of interaction with the practitioners, will begin to <i>practice</i> by replicating what has been modeled, with a process of <i>reflection</i> (the computer geeks would say: <a href="http://www.seattlerobotics.org/encoder/nov98/neural.html">back propagation</a>) providing guidance and correction.

These environments cut across disciplines. Students will not study algebra beginning with the first principles and progressing through the functions. They will learn the principles of algebra <a href="http://www.downes.ca/cgi-bin/page.cgi?post=41">as needed</a>, progressing more deeply into the subject as the need for new knowledge is provoked by the demands of the simulation. Learning opportunities - either in the form of interaction with others, in the form of online learning resources (formerly known as learning objects), or in the form of interaction with mentors or instructors - will be embedded in the learning environment, sometimes presenting themselves spontaneously, sometimes presenting themselves on request.

This does not mean that a 'science' of learning is impossible. Rather, it means that the science will be more like meteorology than like (classical) physics. It will be a science based on modeling and simulation, pattern recognition and interpretation, projection and uncertainty.