Scott, and All ...
A few thoughts ...
- Emergent learning can be repeated for each (next) individual (like the process of parallel evolution - of eyes, for instance, which I think on current data have evolved on at least four unrelated occasions - so far). Emergent learning for a community (an adademic or professional community) might on the other hand become part of the received wisdom, and not be repeated, although even then, it can always be challenged by the next emergent paradigm.
- Autopoeisis does seem to be a threshold process for evolution, and Deacon (New Scientist last year some time) wrote a piece on a variation of auotpoesis, autocatalysis (in which a chemical is the product of a chemical reaction simultaneously with being a catalyst for the same reaction) as a possible mechanism for early forms of life. (See references to related material here ...)
- I love the scenario of oxygen and hydrogen not 'admitting' to know anything about' the formation of water - because that is totally unexpected (although not necessarily unpredictable) from their point of view. Many of the properties of water are even more unexpected, and many of them are still unpredicatable (from our theoretical framework, which clearly still has a long way to go).
- Mathematics is a wonderful example of people imagining new connections and transformations, and describing them in great depth, before anything has been discovered that exhibits those properties - which sometimes only occurs years later.
- Emergence in evolution is based on interaction, variation, and mistakes (mutations) some of which are serendipitously beneficial, most of which are total failures. So, as part of biological life, our existence and our evolution is premised on millions of failures, among which are a few beneficial adaptations. Emergence (and the 'creation' of life and new ideas) is not for the faint hearted.
- Emergence in learning, as a concept, draws on emergence in evolution, within an overall conceptual schema of complexity (complex adaptive systems theory - CAST), but it is not the 'same as' - we need to take the parts that are useful and applicable, and we still have work to do to assemble and configure those aspects of CAST that might be useful to us in understanding emergent learning, particularly learning within social media.
