Is connectivism real v 19th

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Connectivism
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Is connectivism real v 19th

  1. 1. Is Connectivism Real? • Why networks? • Is this really “new”? • Can we test it? • How does this help?
  2. 2. Overview Behavioural/Cognitive models are useful for memory and conceptual knowledge Constructivist models develop group skills and trust Connectivist models and tools introduce networked learning and are foundational for lifelong learning in complex contexts 21 Century Literacies and skills demand effective use of all three
  3. 3. Connectivism • 1. Application of network principles to define both knowledge and the process of learning. Knowledge is defined as a particular pattern of relationships and learning is defined as the creation of new connections and patterns well as the ability to maneuver around existing networks/patterns. • 2. Addresses the principles of learning at numerous levels - biological/neural, conceptual, and social/external. This is a key concept that I'll be writing about more during the online course. What I'm saying with connectivism (and I think Stephen would share this) is that the same structure of learning that creates neural connections can be found in how we link ideas and in how we connect to people and information sources. One scepter to rule them all. • 3. Focuses on the inclusion as part of our distribution of cognition and knowledge. Our knowledge resides in the connections we form - where to other people or to information sourcesof technology such as databases • 4. Recognizes the primacy of context. While other theories pay partial attention to context, connectivism recognizes the fluid nature of knowledge and connections based on context. As such, it becomes increasingly vital that we focus not on pre-made or pre-defined knowledge, but on our interactions with each other, and the context in which those interactions arise. The context brings as much to a space of knowledge connection/exchange as do the parties involved in the exchange. • 5. Understanding. Coherence. Sensemaking. Meaning. These elements are prominent in constructivism, to a lessor extent cognitivism, and not at all in behaviourism. But in connectivism, we argue that the rapid flow and abundance of information raises these elements to critical importance • (http://connectivism.ca/blog/2008/08/what_is_the_unique_idea_in_con.html)
  4. 4. Siemens' connectivism incorporates ideas from: • Chaos theory - Recognizing complex patterns and deep sensitivity on small changes in initial conditions are important properties of learning and decision-making as well as key aspects of chaos theory. • Self-organization - This term usually refers to ”the spontaneous formation of well organized structures, patterns, or behaviors, from random initial conditions.”3) Self-organization is according to Siemens a characteristic of knowledge on personal as well as on institutional or corporate level. • Networks - Network models were acquired because of their applicability and simplicity. Networks are sets of relations between elements which integrate those elements into a whole.
  5. 5. Evolution of intelligent systems
  6. 6. Evolution of intelligent systems • Simple networks » Of chemicals
  7. 7. Evolution of intelligent systems • Simple networks » Of chemicals » Of cells • Self organizing
  8. 8. Evolution of intelligent systems • Simple networks » Of chemicals » Of cells • Self organizing
  9. 9. Evolution of intelligent systems • Simple networks » Of chemicals » Of cells • Self organizing • Chaotic
  10. 10. Evolution of intelligent systems • Simple networks » Of chemicals » Of cells • Self organizing • Chaotic • Networks of networks
  11. 11. Evolution of intelligent systems • Simple networks » Of chemicals » Of cells • Self organizing • Chaotic • Networks of networks
  12. 12. Evolution of intelligent systems • Simple networks » Of chemicals » Of cells • Self organizing • Chaotic • Networks of networks
  13. 13. Evolution of intelligent systems • Simple networks » Of chemicals » Of cells • Self organizing • Chaotic • Networks of networks
  14. 14. Evolution of intelligent systems • Simple networks » Of chemicals » Of cells • Self organizing • Chaotic • Networks of networks
  15. 15. Why now?
  16. 16. Why now? Something happened to how we communicate.
  17. 17. Why now? • Unilateral communication
  18. 18. Why now? • Unilateral communication
  19. 19. Why now? • Unilateral communication
  20. 20. Why now? • Unilateral communication
  21. 21. Why now? • Unilateral communication » TV Video Lecture • Bilateral communication
  22. 22. Why now? • Unilateral communication » TV Video Lecture • Bilateral communication
  23. 23. Why now? • Unilateral communication » TV Video Lecture • Bilateral communication
  24. 24. Why now? • Unilateral communication » TV Video Lecture • Bilateral communication » Telephony classroom guild/mentor • Communication with storage
  25. 25. Why now? • Unilateral communication » TV Video Lecture • Bilateral communication » Telephony classroom guild/mentor • Communication with storage
  26. 26. What Does Connectivity Claim? • The network model : – reflects the growth of new emergent properties – is self organizing – Connecting in this different way changes the role of information and how it is used by the student
  27. 27. How can we tell? • emergent properties • self ogranization • information usage • New math analysis tools can measure – Connectivity – Centrality – Information entropy
  28. 28. How can we tell? • emergent properties • self ogranization • information usage • New math analysis tools can measure – Connectivity – Centrality – Information entropy
  29. 29. How can we tell? • emergent properties • self ogranization • information usage • New math analysis tools can measure – Connectivity – Centrality – Information entropy
  30. 30. What to look for • How quickly and easily information disseminates through the net.
  31. 31. What to look for • How quickly and easily information disseminates through the net.
  32. 32. What to look for • An example of a simple system becoming more complex as a single parameter is adjusted slightly
  33. 33. What to look for • Lyapunov exponent is sensitive to the onset of new chaotic behaviour
  34. 34. What to look for Fractals’ complexity scales
  35. 35. What to look for Fractals’ complexity scales – so do networks -
  36. 36. What to look for one test might be to search for the emergence of a fractal scaling factor in the information entropy of communication nets
  37. 37. What to look for Might be easier than looking through these . . .
  38. 38. What to look for • What about self organization?
  39. 39. What to look for • There are network coefficients that can tell the difference between rule based systems like the Dewey decimal
  40. 40. What to look for • There are network coefficients that can tell the difference between rule based systems like MedScape
  41. 41. What to look for • There are network coefficients that can tell the difference between rule based systems like MedScape and self organizing systems like
  42. 42. What to look for • There are network coefficients that can tell the difference between rule based systems like MedScape and self organizing systems like Guess which system has the best info flow?
  43. 43. If these tests prove out the usefulness of this model how can I use this?
  44. 44. If these tests prove out the usefulness of this model how can I use this? Why would I use this?
  45. 45. How can I use this? • Is teaching 4 students the same as teaching 20 • Is teaching 20 students the same as teaching 45? • Is teaching 45 students the same as teaching 1000?
  46. 46. How can I use this? • Is teaching 4 students the same as teaching 20 • Is teaching 20 students the same as teaching 45? • Is teaching 45 students the same as teaching 1000? • Can an increase in complexity of communication nets cause emergent behaviour ->
  47. 47. How can I use this? • Is teaching 4 students the same as teaching 20 • Is teaching 20 students the same as teaching 45? • Is teaching 45 students the same as teaching 1000? • Can an increase in complexity of communication nets cause emergent behaviour -> and perhaps new teaching methods
  48. 48. How can I use this? • How big do you think your class is …
  49. 49. How can I use this? • How big do you think your class is … • Did you count the non-human intelligences in your class?
  50. 50. How can I use this?
  51. 51. How can I use this? • Identifying subnets
  52. 52. How can I use this? • Identifying subnets • Identifying students at risk
  53. 53. How can I use this? • Identifying subnets • Identifying students at risk • Identifying key players
  54. 54. How can I use this? • Identifying subnets • Identifying students at risk • Identifying key players
  55. 55. How can I use this? • Identifying subnets • Identifying students at risk • Identifying key players • Indicator species
  56. 56. Other possibilities may emerge
  57. 57. Is Connectivism Real - Summary
  58. 58. Is Connectivism Real - Summary • Natural evolution of intelligent organisms
  59. 59. Is Connectivism Real - Summary • Natural evolution of intelligent organisms • May have been happening all the time
  60. 60. Is Connectivism Real - Summary • Natural evolution of intelligent organisms • May have been happening all the time • Might be tested with new analysis techniques
  61. 61. Is Connectivism Real - Summary • Natural evolution of intelligent organisms • May have been happening all the time • Might be tested with new analysis techniques • Might use network tools to good effect
  62. 62. Is Connectivism Real - Summary • The best way to teach a single student is different from teaching a network of students » Leacock’s student on a log.
  63. 63. Is Connectivism Real - Summary • The best way to teach a single student is different from teaching a network of students » Leacock’s student on a log. • Learning happens in an individual, but the individual
  64. 64. Is Connectivism Real - Summary • The best way to teach a single student is different from teaching a network of students » Leacock’s student on a log. • Learning happens in an individual, but the individual may be larger than I think…
  65. 65. I have questions
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