Dynamic Complex Systems

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Dynamic Complex Systems

  1. 1. D YNAMIC S YSTEMS M ODELING IN E DUCATIONAL S YSTEM D ESIGNSYSTEM DYNAMICS • INTRO • MODELING • USES IN POLICYMODELING IN EDUCATION • SIMPLE EXAMPLESFUTURE WORK • DEVELOPING COMPLEX MODELS • CONNECTIONS TO THINK SCENARIOS J ENNIFER G ROFF 2009
  2. 2. D YNAMIC C OMPLEXITY & U NINTENDED E FFECTSFORRESTER EXAMPLE • CITY OF BOSTON URBAN PLANNINGPARALLELS IN EDUCATION • NCLB “POLICY RESISTANCE” • LINEAR-THINKING • TENDENCY TOWARDS ANALYSIS J ENNIFER G ROFF 2009
  3. 3. D YNAMIC C OMPLEXITY C HARACTERISTICS OF C OMPLEX S YSTEMS• Constantly challenging – Change in systems occurs at many time scales, and these different scales sometimes interact.• Tightly coupled – The actors in a system interact strongly with one another and with the natural world; everything is connected to everything else.• Governed by feedback – Our actions feed back on themselves, giving rise to a new situation as a result of our actions.• Nonlinear – Effect is rarely proportional to cause, and what happens locally in a system often does not apply in distant regions; it arises as multiple factors interact in decision-making.• History-dependent – Taking one road often precludes taking others and determines where you end up; many actions are irreversible.• Self-organizing – The dynamics of systems arise spontaneously from their internal structure, generating patterns in space and time creating path dependence.• Adaptive – The capabilities and decision rules of the agents in complex systems change over time. Adaption also occurs as people learn from experience, especially as they learn new ways to achieve their goals in the face of obstacles. Learning is not always beneficial, however.• Characterized by trade-offs – Time delays in feedback channels mean the long-run response of a system to an intervention is often different from its short-run response. High leverage policies often generate transitory improvement before the problem grows worse.• Counterintuitive – Cause and effect are distant in time and space while we tend to look for causes near the events we seek to explain.• Policy resistant – The complexity of the systems in which we are embedded overwhelms our ability to understand them, resulting in many seemingly obvious solutions to problems that fail or actually worsen the problem. J ENNIFER G ROFF 2009
  4. 4. M ODELING T OOLS FOR S YSTEM D YNAMICSBehavior-Over-Time Graphs - Displays data of change inthe system in a line graph formatCausal Loop Diagrams - Mapping of feedback loops andhow they may interact with one anotherStock/Flow Maps - "Stocks" are the accumulation ofsomething in the system, such as money, people, etc."Flows" are the rates of change of those stocks, such assavings or spending rate. Feedback loops within a systemare what control these flows. Through these threecomponents, one can depict the dynamics of a givensystem.Computer Simulation Models - Once a system isdiagrammed, its accuracy can best be tested throughconstructing a computer simulation of that model. While noone person could simultaneously calculate theinterdependent relationships of system of time thatproduces the troublesome behavior, a computer model can.Numerous tools have been developed to help achieve this,including StarLogo, and NetLogo.
  5. 5. E XAMPLE FROM S CIENCE I NFECTIOUS A CTIVITY J ENNIFER G ROFF 2009
  6. 6. E XAMPLE FROM S CIENCE I NFECTIOUS A CTIVITY J ENNIFER G ROFF 2009
  7. 7. E XAMPLE FROM S CIENCE I NFECTIOUS A CTIVITY J ENNIFER G ROFF 2009
  8. 8. E XAMPLE FROM S CIENCE I NFECTIOUS A CTIVITY J ENNIFER G ROFF 2009
  9. 9. E XAMPLE FROM S CIENCE I NFECTIOUS A CTIVITY J ENNIFER G ROFF 2009
  10. 10. Student : Teacher Ratio J ENNIFER G ROFF 2009
  11. 11. Student : Teacher Ratio J ENNIFER G ROFF 2009
  12. 12. Student AchievementStudent : Teacher Ratio J ENNIFER G ROFF 2009
  13. 13. Student AchievementStudent : Teacher Ratio J ENNIFER G ROFF 2009
  14. 14. Student AchievementStudent : Teacher Ratio J ENNIFER G ROFF 2009
  15. 15. Student AchievementStudent : Teacher Ratio NCLB Funding J ENNIFER G ROFF 2009
  16. 16. Student AchievementStudent : Teacher Ratio NCLB Funding J ENNIFER G ROFF 2009
  17. 17. Student AchievementStudent : Teacher Ratio NCLB Funding J ENNIFER G ROFF 2009
  18. 18. Student AchievementStudent : Teacher Ratio NCLB Funding J ENNIFER G ROFF 2009
  19. 19. Student AchievementStudent : Teacher R Ratio NCLB Funding J ENNIFER G ROFF 2009
  20. 20. Student Achievement Student : Teacher R Ratio NCLB Funding StateFunding J ENNIFER G ROFF 2009
  21. 21. Student Achievement Student : Teacher R Ratio NCLB Funding StateFunding J ENNIFER G ROFF 2009
  22. 22. Content Alignment Rate 8 B Rexposure to test content 8 class time available J ENNIFER G ROFF 2009
  23. 23. Content Alignment Rate Subjects Taught/ Tested 8 B Rexposure to test content 8 class time available J ENNIFER G ROFF 2009
  24. 24. Content Alignment Rate Subjects Taught/ Tested 8 B Rexposure to test content 8 class time available J ENNIFER G ROFF 2009
  25. 25. Content Alignment Rate Subjects Taught/ Tested 8 Subject Not Taught/ Tested B Rexposure to test content 8 class time available J ENNIFER G ROFF 2009
  26. 26. Content Alignment Rate Subjects Taught/ Tested 8 Subject Not Taught/ Tested B Students R Proficientexposure to test content 8 class time available J ENNIFER G ROFF 2009
  27. 27. Content Alignment Rate Subjects Taught/ Tested 8 Subject Not Taught/ Tested B Students R Proficientexposure to test content 8 class time available Students Not Proficient J ENNIFER G ROFF 2009
  28. 28. H IERARCHICAL L EVELS OF E DUCATIONAL S YSTEM P OLICY A NALYSIS Federal State District School Classroom Student Teacher J ENNIFER G ROFF 2009
  29. 29. J ENNIFER G ROFFjennifer_groff@mail.har vard.edu 2009

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