A rather belated post on #rhizo15 week 2! How do we count or measure learning in our networks or learning rhizomatically? How do we begin to “grade Dave”?
“Counting” evolution of our learning networks is very important. How does a network or community form? When does it acquire critical “mass” of conversation? How does it sustain? And when does it wither away and perhaps die, only to come alive again in the future, like a raw nerve left exposed?
The months before CCK08, then during CCK08, and Change11 and many of the early cMOOCs afforded great opportunities to discuss a multitude of ideas.
I think Stephen sparked it off by talking about Learning 2.0 in an early article. Then came a series of posts around how I viewed collaboration and evolution in networked learning (starting here). Essentially power laws were well in evidence when we looked at conversations – a small number of conversations were held together by many people and these threads were reasonably long (if I remember correctly, this was the pre-‘like’ era), while a majority of conversations were ad-hoc and short lived.
The pattern was not unlike what you would expect on the Internet prompting discussions on the long tail or that the world wasn’t flat, it was rather spiky. It also was scale-free in the sense that it could observed in small classrooms as well as the rather large learning networks of these cMOOCs.
This pattern also prompted me to think that the goal of such educational networks should be to flatten the power law, leading to a more participatory, equitable and democratic system rather than the ‘rich get richer’ bias that we have now (and Stephen writes eloquently about this, especially towards the end of that post) in his recent dialogues with George when he talks about the University system).
Which is why counting is really an important subject. We cannot continue to count the way we have been counting. But we cannot change unless we also redefine what we are counting and how we are counting it. In fact, for cMOOCs to be counted as a credible alternative (and not just a supplement like the xMOOCs), we have to devise a friendly and intuitive mechanism for counting learning in these networks.
This type of counting is necessary for people to be able to share a new common vocabulary for representing and differentiating levels of competence or progress. Unless this new vocabulary emerges, we will not have a way to transact within it, to generate economic and social choices of human capital using it and to create policy around it. It will also be difficult to get any adoption at scale.
This, in my opinion, has been the biggest block to making cMOOCs mainstream as well as the biggest reason that xMOOCs have been credible. xMOOCs have taken the same counting terms from the traditional system which is widely understood – institutional brand, expert professors, certificates and degrees, price, blended learning – which makes them intelligible to the world. cMOOCs don’t yet have a vocabulary to do that.
It is not just the vocabulary though. The vocabulary will only emerge through research and compelling evidence. It will need new tools and techniques for measurement. It will need to be able to fit in the modern world and the needs of the people. If we do not evolve such measures, cMOOCs will be marginalized as hype.
The need of the hour is for such learning networks to analyze what constitutes learning in the network and how to count it. It is easy to say that these learning networks are only suitable for certain domains or for certain types of people. But it is more difficult to believe they are a credible alternative to traditional education systems without the accompanying quantifying justifications that make the educational, economic and social value intelligible and visible to everyone.