Sunday, September 14, 2008

Types of Knowledge and Connective Knowledge

This is a presentation for Week Two of the Connectivism and Connective Knowledge course. It expands on the ideas in Part a of my paper, An Introduction to Connective Knowledge.


What can we know about an object? Historically, we have had two types of knowledge:

First, 'qualitative' knowledge. What colour the object is, for example. What the object is shaped like. What sort of sound it makes. Qualitative knowledge is knowledge typically derived from the senses. The things we see, the things we feel, the things we hear: these are the qualities of the object.

Second, 'quantitative' knowledge. How many things do we see, for example. How much do they weigh? What are their dimensions? Quantitative knowledge is derived from the practices of counting and measuring. Quantitative knowledge gives us a knowledge that is deeper than that gained merely from the senses. It gives us an insight into the nature of the objects through concepts like mass, atomic number, equations and calculus.

These two types of knowledge account for most of what we know about things that there are out there in the world. These two types of knowledge combine the best of human capacities: our ability to perceive, to sense the world, and our ability to calculate, to think about the world. They form the foundation for language, the foundation for logic, and the foundation for all of the sciences we have had up to today.

Empiricism and rationalism: these are the two great schools of philosophy that have shaped the world in modern times. Empiricism, the philosophy that all knowledge is derived from the senses. Rationalism, the philosophy that all knowledge is derived from calculation and realism. the two great schools of thought in our time.

In the 20th century, things changed. On the one hand, the great philosophers of the Vienna circle and their allies in Great Britain founded a philosophy that joined empiricism and rationalism. This philosophy, known as logical positivism, held that we begin with observations, and then use logic and reason to derive statements about the nature of the world. Any statement not derived in this way, they argued, was literally nonsense. It made no sense.

On the other hand, there was an undercurrent of scepticism about that grand enterprise. The American pragmaticsts - William James, Charles Sanders Pierce and John Dewey, argued that there was a third, practical domain of knowledge. The test that something is known, they said, is that it works. In Europe, meanwhile, philosophers found it difficult to accept that all of religion, art and literature were reduced to nonsense.

There are different types of meaning, said some. Meaning is derived from the text, say people like Heidegger and Derrida. meaning is use, say people like Wittgenstein. And there are different types of knowing. The logical positivists describe only our knowledge about things. But, argues Michael Polanyi, there is also 'knowing how'.

It seems clear, at the beginning of the 21st century, that there is a third type of knowledge, a type of knowledge that exists above and beyond the knowledge derived from the senses, and that exists above and beyond the calculations of logic and mathematics.

But though the existence of this knowledge seems to be beyond dispute, the characterization of this knowledge has been elusive. What is 'practical'? What is 'use'? What is 'literature'? What is 'knowing how'? What is 'ineffable knowledge'?

What is this knowledge? We are subjected to all kinds of theories, some that seem reasonable, some that are patent nonsense. Biorhythms. Astrology. Harmonic convergence. The 100th Monkey phenomenon. The music of the spheres. Intuition.

More to the point, such descriptions were importantly empty. It's one thing to say we should do whatever is practical, but quite another to figure out what the most practical thing is. Or when you say something is 'practical', for example, that it 'works', your description depends on what it was you wanted to do all along. If I don't want to do what you want to do, then what you know isn't what I know.

Connectivism is a theory that described this third type of knowledge. It is a theory that tells us what this third type of knowledge is, where it is, what produces it, how we learn it, and how it can be used.

Summary: Three types of knowledge
- of the senses (empirical)
- of quantity (rationalist)
- of connections (connective)


As we have said earler, connectivism is the thesis that knowledge is distributed across a network of connections. Let me expand on that a bit.

Think about what we know about a simple object, say, a lump of coal.

When we look at it, we can see that it is black in colour, and a bit shiny. It is a rough shape. It isn't that heavy. It is hard to the touch, but we can break it. That's the qualitative knowledge we have of the coal.

When we begin to measure it we can say more. We can say that it has a mass of 500 grams, say. We can say that it has a certain density. Our lump of coal is composed of some billions of individual carbon atoms. Under certain conditions, it combines with oxygen, producing a certain amount of heat and releasing a certain amount of smoke. It is values at 23 cents on the international market. That's the quantitative knowledge we have about coal.

Yet there is a third type of knowledge we have about coal. We can know how many carbon atoms we have. But what makes coal, coal, is not just the fact that it is made up of carbon, but also of the way these carbon atoms are connected together. Take exactly the same atoms and connect them differently and you have graphite. Take the very same atoms and connect them differently again and you have diamonds.

This is a very simple example. Carbon atoms are very simple entities. The connections are simple, and they don't vary very much. They are stable, not changing a whole lot with time. So we can find out about how the atoms are connected indirectly: coal has a particular colour, diamonds have a particular hardness, graphite has a particular weight. Still, knowing about the connections is to know more than to know about the qualities and quantity of the material involved.

So, connective knowledge is knowledge OF the connections that exist in the world. It is knowledge about how such connections are created, and what impact, or effect, such a system of connections has. It is knowledge about how we see such connections, how we observe them, and how we observe their results. It is a theory, in addition, about how we measure such connections, how we count them, what sort of measurable properties they have. This is important: connectivism is a new type of knowledge, but it is not independent of other types of knowledge. We need to be able to see connections, and we need to be able to count them, in order to talk about them.

But I also want to introduce a second aspect of connective knowledge: the idea of connections as a WAY of knowing. This is a bit trickier, but is essential to our understanding of what we know and how we know it.

A network is a set of connections between a collection of things. A diamond, for example, is basically a network: it is a collection of carbon atoms that are very tightly connected to each other. But these connections don't appear out of nowhere; they are not created by magic. If we ask, how did these carbon atoms come to be connected *this* way, we learn something about the history of those carbon atoms, that they were subjected to intense heat and pressure. So information about what happened in the past has been stored in these carbon atoms, in the way they are connected.

With *any* set of connected objects, we can ask how the connections came to be that way. Which means that *any* set of connected objects can contain information. What happened to the individual entities in the network, what sort of *input* did they have, to become connected in this way?

A network, therefore, is like a sense organ. A network is stimulated, it takes a certain shape. Stimulate a network of carbon atoms with intense heat and pressure, and the carbon atoms reorganize; they take the form of a diamond. This is what can happen in any network of connected objects. When you impact that network in some way, the connections between the objects in the network change. And this results in the storage of information.

So we have two types of connective knowledge, the knowledge that we have OF networks, that we obtain by looking at networks, and knowledge that is created and stored BY networks in the world.

Summary: Connective knowledge is both:
- knowledge OF networks in the world
- knowledge obtained BY networks


There are many types of networks, and therefore, many types of connective knowledge. We will look at these in much more detail through this course. For now, though, it is important to identify some different ways of talking about networks.

As we discussed in the introduction to connectivism, there are several types of networks that involve humans. One network, for example, is the human brain. The brain is composed of a collection of neurons that are connected to each other. Another network is society itself. Society is composed of humans that are connected to each other.

Now when we are talking about connectivism it is pretty easy to slip back and forth between these networks without noticing. It's easy to get confused. So it is important to keep in mind one's perspective or point of view when talking about networks.

Let's take, as our starting point, a single person.

This person is a part of a network. He or she is what we would call a 'node' in that network. As a node, he or she is connected to other people; it is this set of connections that make up what we can call a 'social network'.

At the same time, the person in question *has* a network. Or we might even say that the person *is* a network. This person is composed, at least in part, of a neural network, a brain, a complex organ for perceiving the world and storing those perceptions in the form of connections in a network of interconnected neurons.

These make up what may be thought of the person's 'active' participation in the network: the actual interactions that take place, the actual interactions that happen between this person and other people, the actual perceptions that reshape the person's neural network.

There is also a set of what may be called 'passive' or 'reflective' participations in the network.

Consider society. Society is a network of collected individuals. A person can participate in society as a node within the network. But it is also possible, through a variety of mechanisms, to observe society as a whole. To, if you will, detach oneself from society and to study it as though it were an collection of objects out there in the world. The same way you might study a lump of coal.

Similarly, we can (with more or less precision) reflect on our own neural network with some degree of detachment. We can observe, and feel, our sensation and passions, our thoughts, our ideas. We can study our own mind, through introspection. This process of reflection is a way of learning about ourselves.

When we are talking about connectivism and connective knowledge, we are talking about all four of these activities. And it is very easy to get caught up and mistake one for the other, to get confused by them. We need to get into the practice right from the very beginning of being clear about what sort of thing we are doing.

Now connectivism is sometimes characterizes a theory that emphasizes 'knowing who' over 'knowing what' and 'knowing how'. This may be, but only from a particular perspective. Only from a particular point of view. When you are looking to become a part of the network, to be and act as a node in the network, then you are most interested in 'knowing who'. You are interested in creating connections and using connections.

But it would be a mistake to characterize connectivism as a theory that is *only* about 'knowing who'. Understanding how networks work will help support our participation in them, but it will also help use create better networks - *knowing* networks - in ourselves and in our society, and it will help us better understand what we see when we *look* at networks.


Active participation in the network:
- as a node in the network, by participating in society
- as a whole network, by perceiving with the brain (the neiural network)
Reflective participation in the network:
- by observing society as a whole
- by reflecting on our mental states and processes