Often times nowadays when people talk about social networks, they actually talk about social media tools or web 2.0 stuff, where it is made easy to express your social ties and make them visible to others (can I friend you?). Underneath all that "stuff" lies the structure of the social network which is of interest to me. I consider a network
as a conduit for the propagation of information or the exertion of influence, and an individual's place in the overall pattern of relations determines what information that person has access to or, correspondingly, whom he or she is in a position to influence. A person's social role therefore depends not only on the groups to which he or she belongs but also on his or her position within those groups. (Watts, 2003, p. 48)
Moreover, Watts goes on to explain yet a different way to view the network, namely through weak ties, "which can be thought of as a link between individual- and group-level analysis in that they are created by individuals, but their presence affects the status and performance not just of the individual who "own" them but of the entire group to which they belong." - and this all leads to the new science of networks.
Duncan Watts's book Six Degrees (2003) is one of my favourite science-tainment (like edutainment) book. I always enjoy picking it up and re-reading it, I seem to understand some of the passages in a new light. Today I re-read the stuff about differences of spreading a virus and "social contagion", like a fab that spreads or cascades throughout the whole social network.
There are some similarities, like the fact that each individual has a different threshold (some get the virus easier than others) and that you have people around to spread it to ("to whom she or he pays attention to"). But "social contagion", unlike biological one, does not take place if the network is too well connected!
So when everyone is paying attention to many others, no single innovator, acting alone, can activate any one of them. ... In social contagion, remember, it is the relative number of "infected" versus "uninfected" - active versus inactive - neighbors that matter. (Watts, 2003, p. 240)
Studying fabs or innovations (e.g. the use of web in ed.context), the question is about the moment when the fab stops being a niche thing among early adapters and when it leaps to the larger general population. I too often have a feeling that eTwinning "preaches to the converted". So, I'm keen on understanding how eTwinning can step out of being a nice of early adapters and get the others "contaminated". Someone aired a good comment in the conference, we should not take eTwinners as a representative sample of educational community in general.
Step one: who is infected?
I ran a few analysis to get a better picture. It's hard to find the number of schools or teachers in all eTwinning countries. After some digging I found OECD's Stat extracts which has lots of good data, and was able to find the number of teaching staff for 23 out of 32 countries (close to OECD's definition for EU19). I think that's a pretty good proxy to go by, however, not sure how accurately our data aligns with them. I used the date as described in the image for 2007.
The data says there was 6 210 411.57 teachers (I love the 0.57 teacher!) working in those countries, out of which 76 367 have registered in eTwinning by this date. On average, each country has 1.83% of their teachers infected by the "eTwinning virus", median was 1.42%. The countries above median in descending order are: Estonia, Iceland, Slovak Republic, Czech Republic, Slovenia, Finland, Greece, Poland (still above average, too!), Spain, Luxembourg, Portugal and Sweden. Are you surprised? I am a bit...
The countries below median were: the United Kingdom, Turkey, Norway, Netherlands, Italy, Ireland, Hungary, Germany, France, Belgium and Austria.
Well, my question is not about the success of eTwinning initiative itself, but it's more about understanding what are the conditions (globally and locally), what are the individual thresholds and when can we expect the cascading effect to take place (it's all about one or more vulnerable neighbors who have one or more vulnerable neighbors who have...).
These are typical questions that people interested in the new science of networks ask, and I want to know more how it happens within educational context. I think eTwinning is a good virus to study that!
We've just stated the TeLLNet project with some top-notch partners, so I'm looking forward to dwell into this problematic later again!
