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Personal Learning the Web 2.0 Way


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Presentation to Webheads in Action Online Conference. For audio please see

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Personal Learning the Web 2.0 Way

  1. 1. Personal Learning the Web 2.0 Way Stephen Downes May 20, 2007
  2. 2. Overview• AI and Expert Systems• Learning Design• The Connectivist Alternative• Personal Learning
  3. 3. Expert Systems• Two major aspects: – Representation – Inference engine• Analogy: the wizard
  4. 4. Properties of Expert Systems • Expert systems are goal oriented • Good expert systems are efficient • Expert systems should be adaptive
  5. 5. AI Requires… • Knowledge Acquisition – Subject matter expert • Knowledge Representation – Eg. creation of resources • Knowledge Encoding – Eg. creation of if-then structures
  6. 6. Learning Design• “Much of the work on Learning Design focuses on technology to automatically “run” the sequence of student activities (facilitated by the educator via computers), but an activity in a Learning Design could be conducted without technology.” – James Dalziel arning-design-and-open-source-teaching/
  7. 7. IMS Learning Design• Based on Education Modelling Language (Rob Koper)• Examples… – Programmed instruction – Role play – Competency-based learning• Idea that LDs are “pedagogically neutral”
  8. 8. Competency-Based Learning
  9. 9. LD: Conceptual ModelKoper
  10. 10. LD ToolsNr. Tool Name Link Author Levels1 CopperAuthor OUNL A2 Reload LD Reload A,B,C Editor tml3 ASK LDT University of A,B Piraeus4 Mot+ University of A gp/eng/productions/mot.htm Quebec5 Cosmos www.unfold- University of A,B Duisburg general_resources_folder/co smos_tool.zipBerggren
  11. 11. The Lego Metaphor & Garcia
  12. 12. The Learning Refinery• LD but one element of a larger picture• Includes Learning Objects, repositories, etc• “LDs by themselves are of limited value without a bundle of surrounding documentation, metadata, and taxonomies”Greller
  13. 13. ConnectionismMinsky: Symbolic vs. Analogical Man: Top-Down vs. Bottom Up
  14. 14. Messy vs. Neat
  15. 15. Enter the Network Everything is connected to everything else (Theory-laden data)Lakatos
  16. 16. Pattern Recognition… Gibson
  17. 17. stands for? Hopfield Or is caused by? Distributed Representation = a pattern of connectivity
  18. 18. Where is the PLE?
  19. 19. The way networks learn is the way peoplelearn…
  20. 20. This…Network Learning…• Hebbian associationism • based on concurrency• Back propagation • based on desired outcome• Boltzman • based on „settling‟, annealing
  21. 21. Leads to This…Personal Learning… To teach is to model and to demonstrate To learn is to practice and reflect
  22. 22. What is the PLE?
  23. 23. We can get an idea of what the PLE looks likeby drilling down into the pieces… The question is – how to transport and represent Model models that are actually - conceptual frameworks used? - wiki (wiki API, RSS) - concept maps (SVG, mapping format) - gliffy (SVG?) - reference frameworks - Wikipedia - video / 2L 3D representation – embedded spaces
  24. 24. The question is, how can we connect theDemonstrate learner with the- reference examples community at work? - code library - image samples- thought processes - show experts at work (Chaos Manor)- application - case studies - stories
  25. 25. The question is, how can we enable access toPractice multiple environments- supported practice that support various activities? - game interfaces - sandboxes- job aids - flash cards - cheat sheets- games and simulations - mod kits - mmorpgs
  26. 26. The question is, how can we assist people to see themselves, their practice, inReflection a mirror?- guided reflection - forms-based input - presentations and seminars- journaling - blogs, wikis- communities - discussion, sharing
  27. 27. People talk about „motivation‟ – but the real issue here is ownershipChoice – Identity - Creativity- simulated or actual environmentsthat present tasks or problems- OpenID, authentication, feature orprofile development- Portfolios & creative libraries
  28. 28. http://www.downes.caDownes