An Introduction to Connective Knowledge ~ Stephen's Web ~ by Stephen Downes

03 Jun 20

apf54nau

ETC547 Connectivism Learning Theories

the nature of distributed knowledge.
property of one entity must lead to or become a property of another entity in order for them to be considered connected; the knowledge that results from such connections is connective knowledge.
Connective knowledge requires an interaction. More to the point, connective knowledge is knowledge of the connection.
Emergence is a hard concept, but at this point I can gloss it with a simple characterization: emergence is interpretation applied to connections.
e may perceive an actual set of connections linking a group of entities as a distinct whole.
we may perceive something as a distinct whole and interpret this as a set of connections.
Emergence is fundamentally the result of interpretation
We generally think of knowledge as being about facts, and about facts in turn as being grounded in an independent reality, a physical reality
Physicality provides us with a substrate on which to hang our interpretations, as Kant would say, a necessary condition for the possibility of perception. Physicality moreover offers us a means of sorting between what might be called 'correct' interpretations and 'misperceptions', between reality and a mirage.
interpretations are 'constructed' - that is, they are the result of some mental or cognitive process, rather than something that comes delivered to us already assembled.
nference is, broadly speaking, the manipulation of these bits of knowledge, in the abstract, to produce new bits of knowledge.
All such inferences, however, are the result of a complex process of selecting what might be called the most 'salient' data.
salience may be thought of as the importance, relevance or vivacity of some property or perception.
some connections are more salient than others.
Inference is the observation of salient similarities among thoughts and perceptions. It is the recognition of common properties - qualities, quantities and connections - among varied perceptions, and the consequent drawing of connections between those entities, and between other properties of those entitites.
This process of inference has a history in philosophy under the heading of 'associationism', a type of reasoning associated with (until the advent of logical positivism)
The central idea of associationism is this: two things that are relavantly similar become connected in the mind. This connection or association in turn allows knowledge about one to be inferred of the other.
At this point we reach a central concept of distributed knowledge, that of distribution itself.
Strictly speaking, every entity in the world is a distributed entity
there could be no private language, that meaning is possible only if it is shared publicly.
The principles of organized networks of connections have received much attention in recent years, and deservedly so.
Social knowledge is to a society what personal knowledge is to a person. It is a result of the connections between the individual members of society, resident in no single one of them, but rather a property of the society working as a whole.
Social knowledge has recently attained recognition (and value) under the heading of Surowiecki's 'wisdom of crowds'.
Connective knowledge is supported through similar mechanisms. It is important to recognize that a structure of connections is, at its heart, artificial, an interpretation of any reality there may be, and moreover, that our observations of emergent phenomena themselves as fragile and questionable as observations and measurements
connective knowledge is fundamentally the same as that of attaining reliability in other areas;
connective knowledge - it is an attempt to capture, as public knowledge, what can be observed via the interactions of numerous instances of private knowledge.
Connective knowledge is no magic pill, no simple route to reliability.

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01 Dec 18

lfresquez

EbookFA18 Chap1 Connectivism Reference Resource

06 May 16

riggster

"Connective knowledge requires an interaction. More to the point, connective knowledge is knowledge of the connection. If Janet votes a certain way because I told her to, an interaction has taken place and a connection has been established. The knowledge thus observed consists not in how Janet and I will vote, nor in how many of us will vote, but rather, in the observation that there is this type of connection between myself and Janet."

learning theory connectivism networks webpage downes

Social knowledge is to a society what personal knowledge is to a person. It is a result of the connections between the individual members of society, resident in no single one of them, but rather a property of the society working as a whole.
Numerous instances of such connections occur; where certain of those connections become salient, and are frequently activated through use, they are recognized as forming a distinct entity, producing a distinct type of knowledge.
many instances of social knowledge go unobserved and unremarked
Social knowledge is not merely the aggregation and averaging of individual knowledge
'Public knowledge' is the explicit representation of social knowledge in language or some other concrete form.
personal knowledge, does not externalize, because there is either no need or no mechanism with which to place it in the public domain.
Knowledge that is, for example, subsymbolic defies communication (it is not imposible to communicate, through a shrug, a sigh, a knowing look).
In order for private knowledge to become public knowledge, it must have some means of connecting with everything else that is considered public knowledge - through commonly understood utterances or actions.
It must be interpreted as such, recognized as such, in the public domain. In order for this to happen, the set of utterances ('Paris is the capital of France', say) must form a part of of the communications, of the interactions, in the social network as a whole. Then this pattern of communication must in turn be recognized by some perceiver (or group of perceivers) as constituting a relevant underlying organization of communication informaing (say) the behaviour of a society as a whole.
It becomes evident that one's demonstration of having acquired 'knowledge' is very different in the case of public knowledge than it is for private knowledge, even when the instance known is the same.
It involves being able not only to produce specific behaviours, but in providing evidence of sharing in the same network of associations and meanings as others in the community, sharing a language, methodologies, riverbed assumptions.
Failure to know publicly carries a greater risk: that of not being considered to be a part of the knowing community, of being, therefore, excluded from its interactions, and of being misunderstood when attempting to communicate.
personal knowledge is distinct from public knowledge, but the two go hand in hand, and a person who is considered 'highly learned' is one who has internalized, to an expert degree, a great deal of public knowledge.

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09 Nov 14

Jeff Pinto

It should be clear and obvious at the outset that this is not some process whereby individual points of view are aggregated and averaged - such mechanisms are more evident in entities such as Google and Technorati and Digg. Rather, Wikipedia, through iterations of successive editing, captures the output of interactions between instances of private knowledge. The majority, typically, does not rule on Wkipedia; what matters is what is produced through the interaction.
diversity
autonomy
interactivity
openness
allows
The scale-free networks contemplated above constitute instances in which these criteria are violated: by concentrating the flow of knowledge through central and highly connected nodes, they reduce diversity and reduce interactivity.
Moreover, as we enter the connected age, we live with remnants of the previous eras, years when connectivity in society was limited, control over perspective maintained by the beneficiaries of scale-free communications networks. History is replete with examples of the mind of one man, or one group in power, distorting the mechanisms of media to their own ends.
The history of repression walks hand in hand with the history of the distortion of connective knowledge.
our understanding of the existence of connections, and the nature of the networks they form, is something we bring to the table, an interpretation of what we think is salient.
Meaning, for Wittgenstein, is established in the act of communicating.
Much less has been said about what is probably the most important implication of this work: if a human mind can come to 'know', and if a human mind is, essentially, a network, then any network can come to 'know', and for that matter, so can a society.
Just as the meaning of a word can be both personally based and culturally based, so also can knowledge itself be both personally and culturally based. Moreover, because we know that people can learn, we can now also that societies can learn, and conversely, through the study of how a society can learn, we can understand more deeply how a person can learn.
meaning is an emergent phenomenon, arising from the connections between underlying entities.
of 'how to fly a person from England to Canada in a 747'. No single person possesses this knowledge, because it is the result of combining numerous instances of personal knowledge - from how to make tires to how to navigate a 747 to how to execute a landing while keeping the airplane intact. What makes these individual bits of knowledge combine to form an instance of social knowledge is that they are connected; knowing how to land an aircraft depends on, and makes sense, only in the context of knowing how to fly an aircraft, or to build an aircraft.
of 'how to fly a person from England to Canada in a 747'. No single person possesses this knowledge, because it is the result of combining numerous instances of personal knowledge - from how to make tires to how to navigate a 747 to how to execute a landing while keeping the airplane intact. What makes these individual bits of knowledge combine to form an instance of social knowledge is that they are connected; knowing how to land an aircraft depends on, and makes sense, only in the context of knowing how to fly an aircraft, or to build an aircraft.
connective perspective, is a consideration of the interaction between all statements concerning 'value' and all statements concerning 'wheat', and an interpretation of those statements.
A scale-free network is (as people like Barabasi have shown) distinct from a random network in that some entities in the network have a much higher degree of connectedness than others
But to understand how this could be so, we need to look at networks, not as physical systems, but as semantical constructs, where the organization of links is determined as much by similarity and salience than by raw, epistemologically neutral, forces of nature.
This is a very different model of what it means to 'know' - for one thing, because it is beased on organization and connectedness in the brain, the concept of justification and even of belief are nowhere present.
Contrast this to a cognitivist model of knowledge, where once jutification is presented, something is 'known', and cannot in later life be 'more known'.
There is no 'magic' to obtaining knowledge, no secret short-cut, save for practice and reflection - Hebbian and Boltzman connectivism.
'Public knowledge' is the explicit representation of social knowledge in language or some other concrete form. Public knowledge is what most people think of as 'knowledge' per se, it is what we attempt to teach our children, it is what is embodied an a canon and passed on to successive generations.
Knowing privately that 'Paris is the capital of France' may consist merely of writing the appropriate word on a piece of paper, but knowing the same thing publicly involves a complex of interactions and behaviours, consisting essentially of immersion (becoming a part of, and entity within the organization) in the knowing community, so that utterances of the word 'Paris' reflect, and are seen to reflect, an instance of the (generally recognized fact that) 'Paris is the capital of France'.
Failure to know publicly carries a greater risk: that of not being considered to be a part of the knowing community, of being, therefore, excluded from its interactions, and of being misunderstood when attempting to communicate.
Interaction in a community of practice is to a significant degree an alignment of (certain parts of) one's personal knowledge with public knowledge - immersion produces a salience of certain utterances, certain practices, and thus promotes the developement of corresponding (but probably not isomorphic) structures in the mind. It
People are as inclined to internalize the dysfunctional as the utile, the self-descructive as the empowering.
Cascade phenomena occur when some event or property sweeps through the network.
Terminating all the connections would prevent cascade phenomena. However, it would also prevent any possibility of human knowledge, any possibility of a knowing society.
Quantitative knowledge, the cathedral of the twentieth century, fares no better. Though errors in counting are rare, it is a fragile a process. What we count is as important as how we count, and on this, quantitative reasoning is silent
We can measure grades, but are grades the measure of learning? We can measure economic growth, but is an increase in the circulation of money a measure of progress? We can easily mislead ourselves with statistics, as Huff shows, and in more esoteric realms, such as probability, our intuitions can be exactly wrong.
It is important to recognize that a structure of connections is, at its heart, artificial, an interpretation of any reality there may be, and moreover, that our observations of emergent phenomena themselves as fragile and questionable as observations and measurements - these days, maybe more so, because we do not have a sound science of network semantics.
a network with no connections has no capacity to generate knowledge, a fully connected network has no defense against jumping to conclusions.
Knowledge in the mind is not a matter of mere numbers of neurons being activated by a certain phenomenon; it is an ocean of competing and conflicting possible organizations, each ebbing and subsiding with any new input (or even upon reflection). In such a diverse and demanding environment only patterns of organization genuinely successful in some important manner achieve salience, and even fewer become so important we cannot let them go.
While the human brain exhibits some scale-free properties, it is nonetheless not as imbalanced as even things like the economic system or the World Wide Web. Some neurons (or neural clusters) play important and central roles in the brain, but they are not millions of times more connected than most of the others. The brain is densely connected, but the connections are more equitably distributed.
The extremes in human social behaviour, wrought on a smaller scale by chieftans and kings, and on a global scale by mass media, should serve as ample evidence of this. With nothing to counteract an irrational impulse, the charateristic of the one becomes the characteristic of the whole, and the society spirals into self-destruction.
As Rousseau observed, when the mechanisms of the whole are put into the hands of the few, the very nature of the whole is interpreted in such a way as to serve the needs of the few.
In order therefore to successfully counterbalance the tendency toward a cascade phenomenon in the realm of public knowledge, the excesses made possible by an unrefrained scale-free network need to be counterbalanced through either one of two mechanisms: either a reduction in the number of connections afforded by the very few, or an increase in the denisity of the local network for individual entities. Either of these approaches may be characterized under the same heading: the fostering of diversity.
For, indeed, the mechansism for attaining the reliability of connective knowledge is fundamentally the same as that of attaining reliability in other areas; the promotion of diversity, through the empowering of individual entities, and the reduction in the influence of well-connected entities, is essentially a way of creating extra sets of eyes within the network.

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19 Aug 14

joyce L

connectivism learning knowledge web2.0 collaboration

the nature of distributed knowledge.
Distributed knowledge adds a third major category to this domain, knowledge that could be described as connective
A property of one entity must lead to or become a property of another entity in order for them to be considered connected; the knowledge that results from such connections is connective knowledge.
interaction. A relation - such as 'taller than' or 'next to' - is a type of quality. It describes a property of the object in question, with reference to a second object. But the fact that I am, say, 'taller than' Fred tells us nothing about how Fred and I interact. That is something different.
A connected system will exhibit probabilistic characteristics, but it is not itself probabilistic.
Probabilistic knowledge is a type of quantitative knowledge. It is based on the counting of things (or events, or whatever) and of comparisons between one count and another (one needs only to read Carnap to see this clearly). A poll, for example, gives us probabilistic information; it tells us how many people would vote today, and by inference, would vote tomorrow. But the fact that Janet would vote one way, and I would vote one way, tells us nothing about how Janet and I interact.
connective knowledge is knowledge of the connection. If Janet votes a certain way because I told her to, an interaction has taken place and a connection has been established. The knowledge thus observed consists not in how Janet and I will vote, nor in how many of us will vote, but rather, in the observation that there is this type of connection between myself and Janet.
Connective knowledge requires an interaction.
What we 'know' about the world is irreducibly interpretive. That is to say, we do not through our senses and cognition obtain any sort of direct knowledge about the world, but rather, interpret the sensations we receive. T
It's not that a new colour came into existence when I was twenty, it's that our nomenclature changed.
when we say that 'the apple is red' we are drawing on our prior linguistic ability to use the words 'apple' and 'red' correctly and apply them to appropriate circumstances. Indeed, our prior knowledge often shapes our perceptions themselves
here are twenty schoolchildren in the yard' is a basic fact, but this all depends on how you classify schoolchildren. Suppose, unknown to us all, one of the children had just been expelled; is our statement now false? Not obviously so. Perhaps one of them is over sixteen - is this person still a child (and hence, a schoolchild)? It depends on your point of view.
So such membership is based on interpretation, and hence, so is counting.
Nothing but our observations prevents us from saying that one plus one is three, and in some contexts such a statement makes perfect sense.

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07 Aug 14

parsley

looks at
types of knowledge
interpretation
emergence
physicality
Salience and Inference
Associationism
Distribution
Meaning
Shared meaning
organization
social knowledge
Power Laws and Inequalities
Knowledge
Public Knowledge
Knowing
Structure and process
reliable networks
network structure
Truth
knowing networks
remnants"

07 Jul 14

javier castillo

inglés

TFM conectivismo

24 Dec 13

Yves Simon

You probably grew up learning that there are two major types of knowledge: qualitative and quantitative. These two types of knowledge have their origin in major schools of history and philosophy, the former in the works of the ancient Greeks, and the latter in Arabic and then later Renaissance philosophy.
Distributed knowledge adds a third major category to this domain, knowledge that could be described as connective. A property of one entity must lead to or become a property of another entity in order for them to be considered connected; the knowledge that results from such connections is connective knowledge.
This is more than just the existence of a relation between one entity and another; it implies interaction
This is why it is incorrect to represent distributed knowledge merely as a type of probabilistic knowledge. The logic of probability implies no connection between correlated events; it merely observes a distribution. A connected system will exhibit probabilistic characteristics, but it is not itself probabilistic
Probabilistic knowledge is a type of quantitative knowledge. It is based on the counting of things (or events, or whatever) and of comparisons between one count and another (one needs only to read Carnap to see this clearly). A poll, for example, gives us probabilistic information; it tells us how many people would vote today, and by inference, would vote tomorrow. But the fact that Janet would vote one way, and I would vote one way, tells us nothing about how Janet and I interact.
Connective knowledge requires an interaction.
More to the point, connective knowledge is knowledge of the connection
b. Interpretation
What we 'know' about the world is irreducibly interpretive. That is to say, we do not through our senses and cognition obtain any sort of direct knowledge about the world, but rather, interpret the sensations we receive. This is true not only of connective knowledge, but of all three types of knowledge.
Consider qualities, for example. We take it as basic or atomic (see people like Ayer for example) that a statement like 'this apple is red' represents a pure and unadjusted fact. However, looking at this more closely tells us how much we have added to our original sensation in order to arrive at this fact:
First of all, the apple itself has no inherent colour. Colour is a property (specifically, the wavelength) of light reflecting off the apple. In different coloured light, the apple will appear to us differently - it appears white in red light, for example, or grey in diminished light
Second, our perception of the apple as 'red' depends on our organizing light patterns in a certain way. When I was a child, the spectrum had six colours - red, orange, yellow, green, blue and purple. As an adult, I find that a seventh - indigo - has been added. It's not that a new colour came into existence when I was twenty, it's that our nomenclature changed
And third, when we say that 'the apple is red' we are drawing on our prior linguistic ability to use the words 'apple' and 'red' correctly and apply them to appropriate circumstances.
Less intuitively so, but equally clearly, interpretation applies to quantitative knowledge as well.
Quantification is essentially the enumeration of members of a category or set. Consequently, it depends crucially on how that set is defined. But membership in a set, in turn, is (typically) based on the properties or qualities of the entities in question. So such membership is based on interpretation, and hence, so is counting.
One might be tempted to say that even though applied instances of counting are based on interpretation, mathematics itself is not
For one thing, as people such as Mill and Kitcher argue, the rules of mathematics depend on empirical verification for their importance: we say that one plus one is two, not out of some innate sense of goodness, but because when we put one sheep together with another, we observe that there are two
Emergence is a hard concept, but at this point I can gloss it with a simple characterization: emergence is interpretation applied to connections.
First, we may perceive an actual set of connections linking a group of entities as a distinct whole.
Second, we may perceive something as a distinct whole and interpret this as a set of connections.
Emergence is fundamentally the result of interpretation. As mystics (and Spinoza) are fond of arguing, everything is connected. At a certain point, as the old saying goes, when a butterfly flaps its wings in China, the result is a thunderstorm in Halifax. But broadcasters in Halifax do not watch butterflies in China in order to predict the weather, because this connection will be of no use to them. Typically, they will look at more intermediate events, themselevs emergent properties, such as waves of air moving through the atmosphere (known locally as 'cold fronts')
In the same way, the observation of sets of connections between entities depends a great deal on what we already believe. That is why we see swans in clouds or faces on Mars when, manifestly, there are none. We have brought our prior knowledge of connected entities to bear on our interpretations of these phenomena. As Hume would say, our 'perception' of a causal relationship between two events is more a matter of 'custom and habit' than it is of observation.
d. Physicality
We generally think of knowledge as being about facts, and about facts in turn as being grounded in an independent reality, a physical reality
Certainly, were we not to think of things this way, we would be hard pressed to say anything about anything. Physicality provides us with a substrate on which to hang our interpretations, as Kant would say, a necessary condition for the possibility of perception. Physicality moreover offers us a means of sorting between what might be called 'correct' interpretations and 'misperceptions', between reality and a mirage
All this may be the case, but nonetheless, there is nothing in our interpretations that is inherently based in physical reality, and hence, nothing that precludes our discussion of them without reference to this foundation
Moreover, non-physical entities may have (or be attributed) properties that are themselves (on this theory) based in physical properties
What is to be learned from this? That the entities in the various categories of knowledge - be they properties or numbers - are themselves not real. When we talk about 'redness', we are not talking about something that has an independent, concrete existence in the world, but rather, in something that exists (insofar as it exists at all) only in our own minds. When we talk about the number 'four', we are not describing some Platonic entity, but rather, nothing more than our own thoughts or sensations.
It is merely to distinguish between the perception, which results from a complex of factors, from the physical entity, which ostensively caused it.
In a similar manner, our interpretations of connections is distinct from the actual set of interactions that may exist in the world
There is a tendency on the part of readers, whether of <="" a=""> talking about crickets, or of Shirky talking about power laws, to represent connections as something 'natural' and 'real' that is simply 'out there' - as though what is said about networks of connections represents some immutable law of nature. Quite the converse is the case; our understanding of the existence of connections, and the nature of the networks they form, is something we bring to the table, an interpretation of what we think is salient.

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28 May 13

Brendan Murphy

Connective knowledge requires an interaction
emergence is interpretation applied to connections.
observation of sets of connections between entities depends a great deal on what we already believe
it is only your most active and your most consistent thoughts that intrude on your consciousness,
In the absence of external influences to cause Hebbian connections, the brain settles into a (thermodynamically) stable configuration.
it is a property that exists (in our minds) solely by virtue of it having been recognized or interpreted as such
meanings, in the truest sense, exist only when they are shared by a community of speakers.
'knowing' anything is of a similar nature. To 'know' something is not to be possessed of a certain fact.
. To 'know' is to be organized in a certain way
Failure to know publicly carries a greater risk: that of not being considered to be a part of the knowing community, of being, therefore, excluded from its interactions, and of being misunderstood when attempting to communicate.
Just as a network with no connections has no capacity to generate knowledge, a fully connected network has no defense against jumping to conclusions.
reducing the scale of the inequality between neurons also slows the propoagation of impulses through the brain. It allows sub-organizatuons to develop
when the mechanisms of the whole are put into the hands of the few, the very nature of the whole is interpreted in such a way as to serve the needs of the few.
The majority, typically, does not rule on Wkipedia; what matters is what is produced through the interaction.
The expert serves as a dedicated interpreter of that knowledge, an interpretation that is additionally subject to subsequent interactions with proof-readers and editors.

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23 Jan 13

Scott Meunier

connectivism MOOC designing learning knowledge education downes collaboration

29 Oct 12

Jacqueline Morris

connectivism Education

10 Sep 12

angi_lewis

Discussion by one of the founders of connectivism, Stephen Downes. A thorough explanation of some cautions to be heeded by individuals within a network, like resisting the pull to jump to conclusions. Groups should be connected but not cave to any assumptions as those will naturally ebb and flow. Part of that flexibility is staying open to a diverse community in order to be open to information.

connectivism learning education downes elearning collaboration

15 May 12

pateducacao

connectivism knowledge learning education elearning web2.0

26 Oct 11

Ben Turner

Maed connectivism

22 Aug 11

Jane Wilde

dissertation oer

29 May 11

Melissa Newhouse

By Stephen Downes

knowledge learning downes connective connectivism

16 Feb 11

Linda Jotham

Downes on nature of knowledge - very philosophical and abstract, but stimulating

Learning and Teaching models

15 Dec 10

Rita Kop

connectivism knowledge

14 Dec 10

stefaan vande walle

education technology connectivism web2.0 pedagogy downes

30 Nov 10

Maria Leal

MESTRADO MED ARTIGO Conectivismo

24 Oct 10

Heinz Krettek

Herzsportgruppe Weik mahara view connectivism learning education web2.0 elearning downes collaboration e-learning mamb modul1

15 Oct 10

seturri

#PLENK2010 connectivism knowledge learning education web2.0 pedagogy elearning Downes

05 Oct 10

Equipe CTAE

Founded in 1995, Stephen's Web is best described as a digital research laboratory for innovation in the use of online media in education. More than just a site about online learning, it is intended to demonstrate new directions in the field for practition

Inovação Tecnológica educação

15 Sep 10

Cris Crissman

#PLENK2010 downes connective knowledge

24 Aug 10

cesarfp73

conectivismo e-learning web2.0 conocimiento

08 Aug 10

Viplav Baxi

Connective Simulations

22 May 10

edgaraltamirano

connectivism knowledge learning education web2.0 pedagogy elearning downes

10 May 10

Giorgio Bertini

This paper provides an overview of connective knowledge. It is intended to be an introduction, expressed as non-technically as possible.

learning change

13 Mar 10

Claire

savoirs social_web knowledge_management

17 Feb 10

pedroprincipe

redes_sociais aprendizagem downes

16 Feb 10

carlocolumba

emergence knowledge downes article theory pedagogy stephendownes constructivism elearning learning e-learning education

15 Feb 10

Jorge Barretof

conocimiento conectivo

24 Jan 10

Christopher Rice

education teaching ideas

19 Nov 09

Honor Moorman

connectivism

28 Sep 09

Victor Hugo Rojas B.

Distributed knowledge adds a third major category to this domain, knowledge that could be described as connective

connectivism downes knowledge web2.0 learning collaboration elearning education

23 Sep 09

Lisa Durff

20 Sep 09

Ana Loureiro

connectivism downes knowledge

Isabel Barbosa

09 Sep 09

eci831 blogpost connectiveknowledge connectivism

05 Sep 09

Ramón Aragón

Conectivismo

Ramon Aragon

Conectivismo

28 Jul 09

Fernando Checa

Artículo de Downessobre conectivosmo

elearning e-learning

08 Jul 09

Dallas McPheeters

education learning_theory pedagogy delicious

30 Jun 09

midmarketplace_

connectionism stephendownes

Mike Nall

connectionism stephendownes

Tania Sheko

an introduction to connective knowledge by Stephen Downes

connective knowledge connective knowledge Stephen Downes downes

16 Jun 09

Luis Pedro

conectivismo conhecimento redes

28 Apr 09

Howard Rheingold

Distributed knowledge adds a third major category to this domain, knowledge that could be described as connective. A property of one entity must lead to or become a property of another entity in order for them to be considered connected; the knowledge that results from such connections is connective knowledge.

This is more than just the existence of a relation between one entity and another; it implies interaction. A relation - such as 'taller than' or 'next to' - is a type of quality. It describes a property of the object in question, with reference to a second object. But the fact that I am, say, 'taller than' Fred tells us nothing about how Fred and I interact. That is something different.

This is why it is incorrect to represent distributed knowledge merely as a type of probabilistic knowledge. The logic of probability implies no connection between correlated events; it merely observes a distribution. A connected system will exhibit probabilistic characteristics, but it is not itself probabilistic.

networks knowledge

Distributed knowledge adds a third major category to this domain, knowledge that could be described as connective. A property of one entity must lead to or become a property of another entity in order for them to be considered connected; the knowledge that results from such connections is connective knowledge.

This is more than just the existence of a relation between one entity and another; it implies interaction. A relation - such as 'taller than' or 'next to' - is a type of quality. It describes a property of the object in question, with reference to a second object. But the fact that I am, say, 'taller than' Fred tells us nothing about how Fred and I interact. That is something different.

This is why it is incorrect to represent distributed knowledge merely as a type of probabilistic knowledge. The logic of probability implies no connection between correlated events; it merely observes a distribution. A connected system will exhibit probabilistic characteristics, but it is not itself probabilistic.
Emergence is a hard concept, but at this point I can gloss it with a simple characterization: emergence is interpretation applied to connections.
Social knowledge is to a society what personal knowledge is to a person. It is a result of the connections between the individual members of society, resident in no single one of them, but rather a property of the society working as a whole.
Where structures of connections (ie., networks) differ from sets of observations or measurements is that there is in principle no external entity to which we can appeal in order to check our understanding. In a networked society, every person is a member of the network, and all things being equal, there is not some other networked society against which we can test our conclusions (prior to the days of global communications, societies did test themselves one against the other, but unfortunately though war and other conflict, a solution that was worse than the problem and which clouded their ability to interpret connections in a rational and dispassionate way).
As mentioned above, a scale free network is characterised by a small number of entities is numerous connections, and a large number of entities with much fewer connections. It is worth noting that such networks are very tightly connected - in a scale free network a piece of information can reach an entire network very quickly.

While the human brain exhibits some scale-free properties, it is nonetheless not as imbalanced as even things like the economic system or the World Wide Web. Some neurons (or neural clusters) play important and central roles in the brain, but they are not millions of times more connected than most of the others. The brain is densely connected, but the connections are more equitably distributed.

This is no doubt a result of the physical limitations of neurons. But even more importantly, reducing the scale of the inequality between neurons also slows the propoagation of impulses through the brain. It allows sub-organizatuons to develop - the alternative interpretations we can experience when observing a Gestalt phenomenon, for example. Were the structure of human thought to be replicated at the social level, what we would see is essentially a community of communities - the part of us (society) that likes knitting, the part of us that is a hedonist, the part of us that enjoys a good novel.

Networks that exhibit extreme power law distributions are untable. Because, though the mechanism of highly connected nodes, a single impulse can be broadcast and accepted by the entire network all at once, there is no constraint should the impulse prove to be destructive or dysfunctional. The extremes in human social behaviour, wrought on a smaller scale by chieftans and kings, and on a global scale by mass media, should serve as ample evidence of this. With nothing to counteract an irrational impulse, the charateristic of the one becomes the characteristic of the whole, and the society spirals into self-destruction.

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23 Mar 09

downes connectivism web2.0 elearning

11 Mar 09

Bob Irving

Stephen Downes on Connectivism

connectivism downes

24 Feb 09

Jonathon Richter

Stephen Downes work on "Connective Knowledge" is a good addition to the larger conversation of Org Theory and Management in a Web2.0 world

connectivism downes web2.0 collaboration

Rebecca Hatherley

This paper provides an overview of connective knowledge. It is intended to be an introduction, expressed as non-technically as possible.

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09 Feb 09

Neuhauser Patrick

25 Jan 09

Guillaume Janssen

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Connectivism

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lara g.r.

Más sobre conectivism (principios enumerados)

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Petra Grell

knowledge text

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Keith Hamon

connectivism learning collaboration education elearning Web 2.0 Stephen Downes

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connective knowledge

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23 Jul 08

Cheng Gang

A property of one entity must lead to or become a property of another entity in order for them to be considered connected; the knowledge that results from such connections is connective knowledge.
interaction
Probabilistic knowledge
emergence is interpretation applied to connections.
We 'pick out' those perceptions that will be of use to us, and disregard the rest.
In the same way, some connections are more salient than others.
simple associationism
the network attempting to settle into a 'balanced' or 'harmonious' state
share connections with the same set of entities
connectively similar
share similar sets of connections
The emergent properties of a distributed entity exist solely as a consequence of the organization of its parts,
Every entity is composed of additional entities, and the properties of the entity in question are not all mere reflections of the smaller entities, but rather, unique properties, that come into existence because of the organization of those entities.
The concept of 'redness' is an example of distributed meaning.
To 'know' something is not to be possessed of a certain fact. There is no 'instance' of a piece of knowledge in our head. To 'know' is to be organized in a certain way, to have, if you will, a certain regularly occurring pattern of neural activity
market value' of wheat
Social knowledge
'wisdom of crowds
scale-free' networks.
organization of links is determined as much by similarity and salience than by raw, epistemologically neutral, forces of nature.
it is what we attempt to teach our children, it is what is embodied an a canon and passed on to successive generations.
it is an ocean of competing and conflicting possible organizations, each ebbing and subsiding with any new input

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Stephen Downes article on connective knowledge

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mike nodding

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João Fernandes

This paper provides an overview of connective knowledge. It is intended to be an introduction, expressed as non-technically as possible.

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22 Feb 07

maitri27@mac com

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02 Feb 07

linda wright

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David Delgado

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27 Dec 06

José Mota

This paper provides an overview of connective knowledge. It is intended to be an introduction, expressed as non-technically as possible.

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22 Nov 06

Marshall Taxer

This paper provides an overview of connective knowledge. It is intended to be an introduction, expressed as non-technically as possible.

itec800 social_learning from_delicious

14 Nov 06

Mike Hetherington

connectivism imported:del.icio.us knowledge

01 Oct 06

Christian Kreutz

An Introduction to Connective Knowledge

learning wissen networks

10 Sep 06

Ole C Brudvik

connective_knowledge

it is incorrect to represent distributed knowledge merely as a type of probabilistic knowledge. The logic of probability implies no connection between correlated events; it merely observes a distribution. A connected system will exhibit probabilistic characteristics, but it is not itself probabilistic.
b. Interpretation

What we 'know' about the world is irreducibly interpretive. That is to say, we do not through our senses and cognition obtain any sort of direct knowledge about the world, but rather, interpret the sensations we receive. This is true not only of connective knowledge, but of all three types of knowledge.
Connective knowledge requires an interaction. More to the point, connective knowledge is knowledge of the connection. If Janet votes a certain way because I told her to, an interaction has taken place and a connection has been established. The knowledge thus observed consists not in how Janet and I will vote, nor in how many of us will vote, but rather, in the observation that there is this type of connection between myself and Janet.
c. Emergence

Emergence is a hard concept, but at this point I can gloss it with a simple characterization: emergence is interpretation applied to connections.
This is more than just the existence of a relation between one entity and another; it implies interaction. A relation - such as 'taller than' or 'next to' - is a type of quality. It describes a property of the object in question, with reference to a second object.
Distributed knowledge adds a third major category to this domain, knowledge that could be described as connective. A property of one entity must lead to or become a property of another entity in order for them to be considered connected; the knowledge that results from such connections is connective knowledge.
a. Types of Knowledge

You probably grew up learning that there are two major types of knowledge: qualitative and quantitative. These two types of knowledge have their origin in major schools of history and philosophy, the former in the works of the ancient Greeks, and the latter in Arabic and then later Renaissance philosophy.