This afternoon, I watched a you tube video (below) by Ian Robertson titled “An Introduction to Learning Theories“. While it was a high-level introduction, it carried an underlying message of how I feel about learning theories.
Ian provides a definition or brief explanation for a number of learning theories, backed with examples of when they are most effective. It is this point that I have been trying to communicate through my previous blog posts on the topic of context. There is no learning theory to rule them all. They are all largely valid and meaningful – for a given context.
What I believe to be misguided is the purist approach to learning theory – (ie. theory X is right and theory Y is wrong), or that you have to decide which one you use, and discard the others. In fact after reading a forum post by George Siemens, I believe he has similar perspectives on this. George says:
We use ideas and apply them based not only on their merits, but on the context – where we’re at…where our learners are at…tools available, etc. So, sometimes, sloppiness works. Misapplication still teaches. Our theory is pure in thought, messy in application. And, few things are refuted in their entirety. Many aspects of constructivism, cognitivism have value beyond the language construct we have created to house the ideals. Most ideas are messy, run across domains, and even revolutions bear the characteristics of the system they are attempting to replace.
In Week 4, George Siemens has specifically asked the question “… what are the unique ideas in connectivism?” A very pertinent question. I shall frame my response in terms of which contexts suit the connectivist learning theory, which will in itself, differentiate it from others. Well maybe. 🙂
George said of Constructivism:
Constructivism made sense in that it rode on the cultural trends and philosophical viewpoints of the day … it combined existing ideas into a framework that resonated with the needs and trends of the current era.
Largely, a central tenet of Connectivism is the application of network principles to define both knowledge and the process of learning. Something possible in modern society through our advancements in technology. George asks in his seminal work Connectivism: A Learning Theory for the Digital Age:
Some questions to explore in relation to learning theories and the impact of technology and new sciences (chaos and networks) on learning:
- How are learning theories impacted when knowledge is no longer acquired in the linear manner?
- What adjustments need to made with learning theories when technology performs many of the cognitive operations previously performed by learners (information storage and retrieval).
- How can we continue to stay current in a rapidly evolving information ecology?
- How do learning theories address moments where performance is needed in the absence of complete understanding?
- What is the impact of networks and complexity theories on learning?
- What is the impact of chaos as a complex pattern recognition process on learning?
- With increased recognition of interconnections in differing fields of knowledge, how are systems and ecology theories perceived in light of learning tasks?
Naturally, George positions Connectivism to respond to these modern day sciences and challenges, and herein lay Connectivisms effective context. A response to learning in the era of the 21st century – the information age.
But this context is far from global. What of contexts where such networks are unavailable or difficult to access? There are many developing countries for example where such technological advancement is beyond reach. Even in first-world countries, there is not ubiquitous access to technological services generating the types of challenges and environments questioned by George above. We look at students at our University and many still do not have access to broadband Internet. Our institution has many students who work full-time in the mining sector as another example – many of which are located in remote areas of Australia (ie. Western Queensland, and Western Australia). Try obtaining reliable and affordable broadband Internet in remote areas of Australia, such as Western Queensland. How can they consistently engage in a learning network? Even in urban areas of Australia, there are the haves and have nots for high-speed Internet.
So it would be interesting to see whether Ian considers Connectivism as a learning theory in its own right, and add examples of the appropriate context in which to use it.