I was a latecomer to the formal theories of education and learning; in my formative years I never read Dewey, Piaget, or Bloom. I am still convinced that I coined the term “problem-finding” one afternoon in 1985 as I ran our two dogs on a sage-covered hillside; certainly I had never heard it used before as a critical skill in the classroom. I, like many others, have grown my understanding of how great learning occurs by observing students and adults over decades, and connecting those observations and outcomes.
So now I am playing catch-up to the rest of you, growing as a professional educator, learning more about educational theory. This blog by “writer, philosopher, educator, journalist” Stephen Downes connected many dots using formal terms that may resonate with the educational theorists. (Thanks to Will Richardson and Angel Kytle for Tweeting out the link.) Downes argues that “connectivism” is the modality of learning most attuned to our students’ current and future needs:
According to connectivism, learning is the formation of connections in a network. The learning theory, therefore, in the first instance, explains how connections are formed in a network.
When I say of connectivism that ‘learning is the formation of connections in a network’ I mean this quite literally. The sort of connections I refer to are between entities (or, more formally, ‘nodes’). They are not (for example) conceptual connections in a concept map. A connection is not a logical relation. It is something quite distinct.
A connection exists between two entities when a change of state in one entity can cause or result in a change of state in the second entity.
Many of us are arguing that connectivity has never been more important in learning than it is now…now that connectivity is utterly integrated into our lives in ways it has never been before. Connectivity not only provides a medium and mechanism for the efficient exchange of knowledge, but for the very fabric of our ability to change and innovate. From the systems work of Adrian Bejan to a dozen prominent authors of innovation management, to my description of the evolving neural network of the cognitosphere, we understand how learning and organizational evolution are grounded in the development of shared connections.
The question of how learning occurs is therefore the question of how connections are formed between entities in a network.
This is a very different model of learning from that proposed by other learning theories.
- In behaviourism, learning takes place through operant conditioning, where the learner is presented with rewards and consequences.
- In instructivism, the transfer of knowledge takes place through memorization and rote. This is essentially a process of presentation and testing.
- In constructivism, there is no single theory describing how the construction of models and representations happens – the theory is essentially the proposition that, given the right circumstances, construction will occur.
Downes lays out how connections are formed between entities in a network; it is a roadmap for teachers to use in constructing highly effective learning environments:
- Hebbian rules – ‘what fires together wires together’ – neurons that frequently share the same state then to form connections between each other
- Contiguity – neurons that are located near to each other tend to form connections, creatinhg a clustering effect
- Back Propagation – signals sent in reverse direction through a network, aka ‘feedback’, modify connections created by forward propagated signals
- Boltzmann – networks seek to attain the lowest level of kinetic energy
The actual physical descriptions of these theories vary from network to network – in human neurons, it’s a set of electrical-chemical reactions, in social networks, it’s communications between individual people, on computer networks it’s variable values sent to logical objects.
Downes ends with a loud reminder: connectivism has “nothing to do with ‘looking up the answer on Google’ or any of the surface characteristics commonly associated with it.” Yes, we are connected via search engines to a vast learning environment. But what I drew from Downes’ post is that the role of connections in learning is deeply rooted in foundational theory that was valid way before the advent of the Internet.
Interesting read! I am in the thick of teaching a seminar (students are senior undergrads) where we are taking a close and critical look at cognitive science principles. The AI/Cog Psy interface of using “neural network” technology as an analogue for human learning is both tricky (and sometimes dicey) but also potentially quite informative. In terms of parallel constructions, there is no human equivalent to “back propagation” and the way in which weights are updated in the ANN programs — programmers do indeed admit that these elements of the programming make the output look “human-like” but they don’t claim that the process itself is “human-like,” at least not in a literal parallel construction sort of way. That said though, when ANNs are given bodies to operate in real environmental contexts, then we do start to learn something intriguing about the possibilities of human learning that take us far beyond the simplicity of Hebbian notions and idea of mere contiguity. If Hebbian circuitry is to become a pattern of thought in a human learner, then not only do the ideals in the network need to be connected in space & time, but there also has to be some meaningful link among all the elements, in terms of an “organism-environment-problem-solution” connection. Breathing the same air doesn’t ensure learning, but making meaningful connections among elements of a challenge that exist in a rich context does. And that’s where educational application comes in — meaning, in all senses of the word, is what leads to learning.
Fascinating stuff, and I am just learning the theory behind what I have known, even though I lacked all formal description. As you say: meaning, in all senses of the word, is what leads to learning. So much of what takes place in schools is utterly devoid of meaning for the students. We have managed to get this completely upside down, and now it is proving very hard to get right again!
On another thread, if you don’t mind, I have a comment too about historical learning theories? I often see “Behaviorism” presented as you do it here, with the implication that learning occurs through reward (i.e., EL Thorndike’s Law of Effect). But in my reading of Thorndike’s work, the mechanism he thought influenced by rewards was motivation, not learning per se. Said another way, the ideal he had in mind at the turn of the last century was that motivation to learn could be improved with a reward system, but the learning itself – the cognitive part of it – was governed by a different mechanism. Indeedm in a paper I read (long ago) he used math education as an example, because that’s a situation where students often dig in their heels when the learning gets hard, and Thorndike recognized that students needed a reason to persevere (as did many other theorists in that era, Vygotsky included). In modern contexts, I often feel like this point is glossed over and that Behaviorist ideals are, rather, set up as straw-man arguments, easily blown over. What are you thoughts on this?
I am not an expert on any of this! What resonated with me in Downes’ post were two things: the emphasis on connectivity, and the idea of constructing learning from some foundational experience. To me, young people (heck, all of us) frequently change our view of what rewards are valuable, so that cannot be the reason we learn. “Getting into a good college” is not a reason to spend 12 years of 10 hour days, at least once we give students a chance to really think about it. It is only by constructing our own worldview, and placing within it the reasons to learn that we see real engagement.
Like I said, I am just learning this myself! Thanks for the comments.