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Complexity Science and Physics Teaching and Learning

Complexity Science and Physics Teaching and Learning Rachel F. Moll University of British Columbia, Department of Curriculum Studies An Example Learning Context The Physics Olympics

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Complexity Science and Physics Teaching and Learning

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  1. Complexity Science and Physics Teaching and Learning Rachel F. Moll University of British Columbia, Department of Curriculum Studies

  2. An Example Learning Context The Physics Olympics • Teams of five Grade 11 and 12 students compete in an all day Physics competition with hands on, laboratory based activities • Two pre-built designs that students complete before arriving

  3. Presentation Outline Three Parts: • Why study complexity? • Qualities of Complex Systems • Teaching and Complex Systems

  4. Why study complexity? “What kind of science had to be taught to brilliant scientists in the 1980s and 1990s?” George A. Cowan, 1983 “Science that can deal with the real messy world, which is not elegant” Complexity Science!

  5. Who is using complexity? Phenomena • the collapse of the USSR, • trends in a stock market, • the rise of life on earth, • the evolution of the eye, • creativity and intelligence, • the emergence of ‘mind’ Fields • Cybernetics/Information Science • Economics • Ecology • Biology • Artificial Intelligence • Cognitive Science • Physics

  6. Current Trends in Complexity Science Many of the most popular non fiction books are complexivist in nature. For example: Collapse (2005) Jared Diamond The World is Flat (2005)Thomas Friedman Blink (2005)and The Tipping Point (2000)Malcolm Gladwell Emergence (2001) Steven Johnson Descartes’ Error (1994) Antonio Damasio The Hidden Connections (2002) Fritjof Capra

  7. Complexity Theory and Education Some debates in education: • teacher-centred vs. student-centred classrooms • individual vs. collective • work vs. play • nature vs. nurture • skills vs. conceptual understanding What do these have in common?

  8. Complexity and Education Common Ground • Conception of learner — as solitary, self-contained individual • Conception of teaching — in terms of causal influence • Conception of curriculum — in terms of direct(ed) movement • Conception of formal education — in terms of predetermined outcomes

  9. What is Complexity? Complexity scientists make a key distinction between complicated and complex phenomena.

  10. Complicated Systems

  11. Complex Systems

  12. Complicated vs Complex • Adaptive (Darwin) • Ecosystem metaphors • Cyclical imagery • Feedback loops • Sufficiency oriented • Growth minded • Non compressible • Mechanical (Newton) • Machine metaphors • Linear imagery • Input/output flows • Efficiency oriented • Progress minded • Reducible

  13. Complex Systems… … arise in the interactions of many autonomous agents/elements, which collectively manifest properties not exhibited by the agents/elements independently. …are learning systems.

  14. Qualities of Complex (Learning) Systems self-organizing/emergent, far-from-equilibrium, recursively elaborative, nested, scale independent.

  15. Self-Organizing/Emergent Coherent unities arise without the need for a centralized controller.

  16. Dynamic Equilibrium Disequilibrium Far-From-Equilibrium Complex systems do not operate in balance; equilibrium implies death for such a system.

  17. An illustration of Far-from-Equilibrium Severe Congestive Heart Failure Healthy Heart Severe Congestive Heart Failure Cardiac Arrhythmia, Atrial Fibrillation

  18. Recursively Elaborate • Learning systems do not progress along linear trajectories • They unfold by constantly invoking established and new associations • Curriculum can be thought of as recursively elaborate, not linear or cyclical

  19. Growing a Fractal Tree The Seed

  20. Growing a Fractal Tree The Generator

  21. Growing a Fractal Tree Iteration 1

  22. Growing a Fractal Tree Iteration 2

  23. Growing a Fractal Tree Iteration 3

  24. Growing a Fractal Tree Iteration 4

  25. Growing a Fractal Tree Iteration 12

  26. Recursive Elaboration Activity • Choose a specific atom (seed) • Situate the atom in a molecule • Situate the molecule in a simple organism • Describe a structure the organism is a part of

  27. Complex forms unfold from and are enfolded in one another. Whether magnified or reduced, complex forms maintain a constant bumpiness of detail. Nested and Scale Independent

  28. Complex forms unfold from and are enfolded in one another. Whether magnified or reduced, complex forms maintain a constant bumpiness of detail. An example nested system: Learners

  29. Complexity and Teaching Some qualities of complex systems offer suggestions for pedagogy. • Diversity and redundancy • Neighbour interactions and Decentralization • Feedback Loops • Enabling Constraints

  30. Diversity • All complex collectives have abundant diversity. • Diversity is the source of a system’s flexible response—its intelligence. • It may be necessary to create conditions for the expression of diversity. • Teachers have to think through how diversity will be expressed and preserved. • The diversity of responses from the collective will exceed those of any individual. • Favorite methods to represent diverse interpretations on posters, whiteboards or clickers.

  31. Redundancy • Possibility for collective coherence requires commonalities among participants. • Contributes to a system’s robustness. In the classroom: • The teacher must ask, “What common experiences are needed for this to work?” • Formal schooling turns out to be really good at ensuring redundancy among agents … • … because it’s been the principal (and often the exclusive) focus for centuries.

  32. Neighbour Interactions • The agents of the system need to “bump up” against one another. • In a knowledge-producing system, the “agents” aren’t people, but ideas. • There has to be a “critical mass” of ideas/agents in order to start a reaction.

  33. Decentralized Control Theorists have identified three types of networks: DECENTRALIZED DISTRIBUTED CENTRALIZED

  34. DecentralizedControl Theorists have identified three types of networks: The centralized network has the advantage of efficient communication, but the disadvantage of not being very robust. CENTRALIZED

  35. Decentralized Control Theorists have identified three types of networks: The distributed network has the advantage of being very robust, but the disadvantage of poor communication. DISTRIBUTED

  36. Decentralized Control Theorists have identified three types of networks: … balancing efficient communication with a robust structure … … especially when weak links are figured in. The decentralized network is the “fingerprint” of a complex (learning) system/collective. It’s “just right” … DECENTRALIZED

  37. Feedback Loops • Recursive processes that either amplify (positive) or dampen (negative) • Nonlinear -- i.e., not to be confused with behavioral psychology’s “feedback” conditioning mechanisms • Two examples of positive feedback in classrooms are wait time, emotioning and expectations.

  38. Initial Prompt Positive Feedback Loops – Wait Time Suitable Pause Deeper Question Deeper Response Further Thought

  39. Positive Feedback Loops – Wait Time Suitable Pause Deeper Question Deeper Response Further Thought

  40. Teacher Enthusiasm Teacher Mirroring Student Mirroring Student Enthusiasm Positive Feedback Loops –Emotioning

  41. Enabling Constraints • Pedagogically they are about imposing sufficient limits to orient learners and sufficient freedom to allow for the emergence of the unexpected • Examples: Design activities Physics Olympics Problem Based Learning

  42. Teaching Complexity • Free software available for modeling complex systems • NetLogo • Traffic systems, ants, ecosystems, turbulence, etc… • Can design your own or use existing models.

  43. Complexity and Education • Conception of learner — as solitary, self-contained individual • Conception of learner —an ever adaptive unity • Conception of teaching — in terms of causal influence • Conception of teaching — as consciousness of that unity • Conception of curriculum — in terms of direct(ed) movement • Conception of curriculum — as recursively elaborative • Conception of formal education — in terms of predetermined outcomes • Conception of formal education — expanding the space of the possible

  44. Conclusions • Complexity thinking is different way to look at and think about teaching and learning • Can be used as a research tool • Has pragmatic recommendations for both curriculum and pedagogy

  45. Thank You For more information, references and reading list please pick up a handout. rfmoll@gmail.com www.complexityandeducation.ualberta.ca

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