To follow up on the previous post, here are some notes (from Allison L.) regarding a framework for thinking about how these applications can work together to enable knowledge construction of the sort that we were referring to:
"In my search through ecology texts I have gleaned the following gems. Please read with the understanding that a little knowledge can be a bad/misleading thing :-)
1) Ecology has been desribed as the 'science of case studies' and, as such, could be useful in consideration of a set of scenarios.
2) In the application of ecology to preserve conservation, knowledge of taxa is more important that theory. Bottom up consideration of taxa likely to be more fruitful that the traditional top down. (BTW this is akin to the sort of methodology one would use in scenario planning - so I presume all the pulling together of ecology theory and problem solving theories has already been done....)
3) A central theme of ecology is diversity-stability relationship. Ecologists do not agree about this relationship. The classic theories are based around the notion of diversity for stability (this is an interesting concept in relation to TEL. Should we all use the same applications, or a range of applications. This question is ultimately influenced by interoperabilty and accessibility issues).
4) The classic theory does not hold up in 'rockpool systems' where change in one species can change the whole bio-schema. This is probably the same in learning technology. However, it does surprise me that ecologists could EVER have suggested that such as simple causal relationship would not have exceptions in highly complex systems - now I'm beginning to doubt my source :-)
5) The starting point in examining any system is clarification of concepts including 'community', 'stability' and 'diversity'. However there is an underlying weakness in ecological theories in that the principals and assumptions relating these are not well understood (I find this quite mindblowing. Ecology started a long time ago, with Darwin!).
6) The basic unit of study is a system that reaches 'dynamic stability' . STudying a massive, complex system is difficult, so one solution is to dive the big system into smaller, more managable sub systems(this is 'island biogeography - developed by McArthur and Wilson in the 60s). For us, that probably means we study small, discreet networks of people as a first step, rather than trying to understand the collective. Hmmmm - I do have some doubts about this, though it may be a way forward if - and only if- one understands the relationship between the subsystems. But that adds another layer of complexity.
7) These systems and their interrelationships can be studies through taxa and change in taxanomic composition over time, colonisation and extinction rates. This is an interesting point when one considers that learning technologists tend to look for stable taxa in a rapidly changing field. I'm begiining to think that repository systems could, in theory, be viewed as 'islands' for study. However, the problem is that only some of them grow 'organically'. Most grow due to forced use (ie an LMS system students have to access whether they like it or not; JISC funding influencing use of reps etc). So I'm not sure any study would stand up under these conditions
Ecology can help look at applications and groiups of applications, but the use of these systems by people is another level of our study. We shoud draw on other heuristic methologies, from anthropology. Theories fro anthroploloy must be closely related to general theories of ecology."
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