|Domains of major fields of physics (Photo credit: Wikipedia)|
David Wiley recently made a comment on his blog, in response to a very succinct posting by Stephen Downes, that the learning theory Connectivism, though he is sympathetic to it, was incomplete. I am not sure what to make of that. I understand David’s point that terms need to be carefully defined. A solid theory needs operationally defined key terms. But I am not sure that Connectivism is really incomplete. There are a lot of great theories out there that work well and are very useful but are not “complete” in every sense. Einstein thought that his theories of relativity would lead to a Universal Field theory and because his work does not account sufficiently for quantum mechanics, in that sense his theory is incomplete. But it is still quite useful and irreplaceable in many fields of study and in practical application.
When Einstein first published his theory it had to go through years of refinement and testing. That is the process. There are still things being worked out with Darwin’s Theory of Evolution but the days of wondering if it is valid are long behind us. It has been proven, observed, and tested. There are still evolutionary mechanisms to be worked out and the history of evolution will take more field work.
Looking at the history of theories, I am beginning to think that the discipline a given theory arises from is often the one least capable of evaluating it. But that is where all of the experimental and observational evidence is going to come from. Most of the criticisms I have read of Connectivism boil down to the new theory is not like the old theories. A theory is meant to provide a conceptual framework for viewing and understanding phenomena. As an instructional designer, I have a purely practical approach. I am only interested in a theory’s usefulness, but for me, a theory must
- account for current theories (either through refutation or inclusion)? A theory shouldn’t just account for a given phenomena, it should do so in some measurably better way (more complete, elegant, etc.).
- sufficiently explain where we are now.
- make predictions. Any theory that can’t predict anything is basically a conjecture at best.
- be subject to testing. Here I would emphasize that the theory should change what we do based on experiment and empirical data.
In my experience, Connectivism has met those four conditions. Those shouldn’t be the only ones but as an instructional designer, the theory accounts for current issues in my work in ways that other theories do not.
With that said, I am no ideologue either. I have my own bones to pick with Connectivism. It is still unclear to me how learning “may reside in a non-human appliance.” It should either be the case or not. My definition of learning requires someone to actually do the learning. I see non-human appliances storing information, processing information, even mimicking pattern-making (chess computers). I don’t understand how learning resides there. That is my “why a duck?” moment with the theory. It also feels like a left over principle from another theory that is not necessary for Connectivism to be a strong theory on its own.
But Connectivism is not just an explanatory or descriptive theory. As an instructional designer, I can use it to help analyze the success and failure of a particular course. So how would I test it? There are a number of ways. First, we build a course design rubric based on the tenets of Connectivism, and compare the success and retention rates, and course satisfaction (for students and teachers). Second, we repeat the experiment, and share the finding so others can reproduce the results.
The jury is still out for Connectivism. This is as it should be! The jury should always be out for all theories if we are going to engage in the scientific method and reason together.