Learning- it’s all in the connections

Do you know a person who, completely by themselves, can  build a 747? Everything from the metal shell, the comfy (??) seats, upholstered in company fabric, the plastic tray tables, the tyres for landing, not to mention the complex electronics and massive engines required to run it? Of course not – no one on earth could hold all of this knowledge in their heads, nor possess all of the skills required to build it. The same goes for almost all of our transport today – cars contain not just engines but also computers, trains are complex creations, and ocean liners;  where does one begin? 150 years ago, a person could quite conceivably have the skills and knowledge to build a cart, that they could attach to a horse to travel from A to B; however today, the rapid speed of technological change and development means that even bicycles can be quite complicated constructions.

Why am I rattling on about transport? Has the first week of doctoral studies already cracked me? Well…maybe…but –

Over the past few days I’ve been reading Knowing Knowledge, by George Siemens (2006). This text explores how knowledge has changed. Siemens is best known for his theory of Connectivism, which he developed with Stephen Downes.

In Knowing Knowledge, Siemens suggests that although in the past we may have defined, categorised and packaged knowledge, massive change and growth in technology means that now knowledge is best understood as a flow, that can be described at any point in time (within a particular context) but cannot be defined (p.vi). Knowledge changes so rapidly now, and is so abundant, that we can no longer dam it in books and documents; we must now access it as a stream, when and how we need it.

This description of knowledge fits with his theory of connectivism, which I have somewhat clumsily attempted to demonstrate in my opening paragraph on transport. Whereas once, knowledge was limited and defined, and could be held within one person’s head (e.g. the knowledge of how to build a cart for transport), now, knowledge rests in networks. It is more important to know who holds specific knowledge, or where to find it, and to draw these nodes on the network together at point of need. As Siemens says, “we need to adjust our
models to fit the changed nature of “what it means to know.””(2006, p.13).

Therefore, to build a plane, the network requires multiple nodes connecting: the engineer, the computer architect, the mechanic, the interior designer – and each of these will also have their own networks of expertise that will support them.

Connectivism sees learning as something that happens on several levels; on one level, its basis in networks reflects the neural networks in our brains, as connections are made between neurons as we learn, and paths strengthen the more we use them; on another level, it reflects the learning that is the process of continually creating networks from ourselves to other people, resources and sources of information – our personal learning networks (2006, p.29). When we take these sources and remix them to create something new, yet another level of learning appears. The theory suggests that as the content is changing so rapidly, the connections that enable us to learn more are more important than our current state of knowing (p.32). We can use the content how and when we need it, but not spend all our energy cultivating it; it will be out of date in a blink. Instead, spend time cultivating the connections, so that next time we need the same or similar content (now updated), we can access it once again.

The pipe

This (albeit) simple explanation appeals to me very much. As a librarian and a huge fan of Professional/Personal learning networks (PLNs), I acknowledge that I will never ‘know’ everything I need to – and in fact, as soon as I learn something, it changes! Therefore, what I do is ensure I develop the skills to know where to go, and who to contact when I need that knowledge.

When I went to school, learning was considered to be the acquisition of knowledge; when I had ‘learnt’ something, I had it ‘in my head’ and carried it around with me. So when I needed to calculate something, I applied the number facts I had in my head to find the answer, and when someone asked me ‘ in what year did Christopher Columbus sail?’ I combed my memory and drew the answer. This was the content I ‘knew’. For some content, what Siemens calls ‘hardened’ knowledge, this is still relevant – I still calculate number facts in my head, and it is faster than pulling out my phone to access a calculator. However, for much knowledge, I simply cannot carry it all around at , and it’s changing so much it’s really not worth it. So I let it rest somewhere on my network, until I need it. Then I apply my knowledge finding skills to get it when i need it. As I have well developed knowledge finding skills, and a well developed network, this is effective. For those without these things, knowledge is a little more slippery and difficult to locate.

Consider your childhood definition of someone who was ‘smart’ – I bet they were someone who ‘knew’ a lot. Who always had the answers ‘in their head’. Today, a ‘smart’ person may still carry quite a bit of knowledge in their head, but they also know that they don’t know an awful lot – but they know where to find information when they need it.This has tremendous implications for what we value in our school curricula. Do we really need to insist students learn so much content? (I am definitely in favour of basic maths facts, spelling etc; but just how much of our curriculum is just ‘stuff’ being poured into students heads?). Does our pedagogy reflect this changing understanding of knowledge and learning, and model and develop inquiry skills so that students can create and maintain connections? See patterns? Apply meta-cognition to problems?

Years ago, when the doctor saw the patient, they would examine the symptoms and make a conclusion based on observation, measured against their knowledge built up through experience, their medical training and perhaps a text. Today, would you rather this same doctor, or a doctor who could consider not just their own experience, but also the latest, most cutting edge experience and knowledge from everywhere across the globe? If you had a rare disease, Doctor One may not be able to identify it if it is beyond their experience or not in their text. Doctor Two may communicate with a huge international network of doctors, and consult the world’s information online – and has a much better chance of finding you a treatment.

When I construct new knowledge, or ‘learn’ something new, it is not always about making a direct connection; many times it is also about looking across my network, and identifying trends or patterns. If I note that many people are tweeting #RIPfamousperson  then I consider this pattern and begin searching for news of that famous person’s passing. If I note over time that more members of my PLN are speaking about a particular topic, I consider investigating what might be a particular zeitgeist for myself. These simplistic examples are how we move beyond the first level of connective learning, and become more aware of the network as a whole.

While the theory of connectivism is somewhat controversial (see Clara and Barbera, (2014), Kerr (2007) and Verhagen (2006) my early readings of it definitely appeal – and I can see that I will be  stepping more deeply into the waters of Connectivism, as they rush past. The idea of a learner continually encountering new knowledge, and constantly and dynamically updating and rewriting their network as new information and patterns emerge  makes sense to myself as a life long learner, and also appeals to my librarian training.  We do not (indeed cannot) know everything; rather, we maintain connections, that morph and adapt, so that our network provides and suggests information when and where we need it!

References:

Clarà, M., & Barberà, E. (2014). Three problems with the connectivist conception of learning. Journal of Computer Assisted Learning, 30(3), 197-206. doi:10.1111/jcal.12040

Kerr, B. (2007, 18/01/2010). A Challenge to Connectivism. Transcript of Keynote Speech. Retrieved from https://web.archive.org/web/20100118045904/http://ltc.umanitoba.ca/wiki/Kerr_Presentation

Siemens, G. (2006). Knowing knowledge. United States: George Siemens.

Siemens, G. (2004).  Connectivism: A learning theory for the digital age. Elearnspace. org, 14-16.

Verhagen, B. v. P. (2006, 10/12/2009). Connectivism: a new learning theory? Surf e-learning themasite. Retrieved from http://web.archive.org/web/20070113075233/http://elearning.surf.nl/e-learning/english/3793

 

 

 

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