Dave Pollard's papers on business innovation & knowledge management

	September 12, 2008

CCK08: Thoughts on Knowledge and Learning -- Week One Map of Massive Open Online Course (MOOC) on Connectivism, by Matthias Melcher. Full size map you can actually read here. I'm currently enrolled in an online course on Connectivism and Connective Knowledge (with 2000 other people) being put on by George Siemens at the University of Manitoba and co-hosted by Stephen Downes. The main course wiki, if you still want to enroll, is here. The course runs about 12 weeks and each week has selected readings, live and taped discussions, and a ton of activity on the collaborative course sites shown on the map above. In keeping with the spirit, I'm tagging this blog post to #CCK08, which means it should show up on the collective everything-that-points-to-CCK08 pageflake page. I've also joined an Ontario discussion group on CCK08. I've read all the prescribed material, and scanned some of the daily highlights and other materials above, but have not yet participated (connectively) in the course conversations, nor did I stick with the tedious multimedia discussions. But I did give the subject considerable thought, and came up with the following Week One Propositions About Knowledge and Learning, a mixture of what the course leaders espouse, what other course participants have proffered that I found interesting or provocative, and how I am making sense of it all. Since Week One is titled "What is Connectivism" these Propositions are, not surprisingly, mostly about definitions. Knowledge = patterns of connections, of three types: neural = know-what,  conceptual = know-how, and social = know-who); Networks = loci of knowledge. Learning = making new connections (of the above types). Understanding / coherence / sensemaking = forms of pattern recognition. Community = those with shared knowledge and shared learning interests; we invite individuals to join communities, when what individuals really want is for the community to come to them (for reassurance and recognition and appreciation that their understanding is valid). Workarounds = the mechanism by which individuals make sense of and apply their own learning, regardless of mandated knowledge (instruction) or accepted knowledge ('conventional' wisdom). Accepted knowledge (wisdom) = what evolves as power shifts, people die and the make-up of communities changes; wisdom is inherently 'conventional' and tyrannical. The 'wisdom of crowds' is not 'wisdom' at all, but rather collective knowledge = the aggregation and appreciation of patterns of knowledge of large numbers of independent people, shared; this is much better than wisdom! Not sure yet what intelligence is in the connectivist context, since its meaning is ambiguous in common usage, so I'm going to avoid using the term if possible, except perhaps ironically. All of this is interesting and informative, but so far not evidently of much practical use. This may seem a bit academic, and perhaps unintuitive, but a lot of it resonates with me for how it reflects knowledge and learning processes I've observed in wild animals, and how, according to what I've read, aboriginal and 'unschooled' people learn. As our problems become more complex, pattern recognition becomes more difficult, and collective knowledge ('the wisdom of crowds') becomes more valuable than individual knowledge. I confess that while I think some of this will prove to be useful, I'm not sure how, and I doubt it will centre around whether or not connectivism is "a legitimate learning theory", which some of this week's discussion has been about. It will be valuable to the extent it helps refine our intuitive knowledge of how people learn, and why they (usually) never do. Stay tuned. Category: Knowledge Management "An important scientific innovation rarely makes its way by by gradually winning over and converting its opponents. It rarely happens that Saul becomes Paul. What does happen is its opponents gradually die out and the growing generation is familiarized with the idea from the beginning." (Max Planck) 11:57:30 PM  trackback []  comment []

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