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D YNAMIC S YSTEMS M ODELING IN E DUCATIONAL S YSTEM D ESIGN SYSTEM DYNAMICS INTRO MODELING USES IN POLICY MODELING IN EDUCATION SIMPLE EXAMPLES FUTURE WORK DEVELOPING COMPLEX MODELS CONNECTIONS TO THINK SCENARIOS J ENNIFER GROFF 2009

Dynamic Complex Systems

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Page 1: Dynamic Complex Systems

DYNAMIC SYSTEMS MODELINGIN EDUCATIONAL SYSTEM DESIGN

SYSTEM DYNAMICS• INTRO• MODELING• USES IN POLICY

MODELING IN EDUCATION• SIMPLE EXAMPLES

FUTURE WORK• DEVELOPING COMPLEX MODELS • CONNECTIONS TO THINK SCENARIOS

JENNIFER GROFF 2009

Page 2: Dynamic Complex Systems

DYNAMIC COMPLEXITY & UNINTENDED EFFECTS

FORRESTER EXAMPLE• CITY OF BOSTON URBAN PLANNING

PARALLELS IN EDUCATION• NCLB

“POLICY RESISTANCE”• LINEAR-THINKING• TENDENCY TOWARDS ANALYSIS

JENNIFER GROFF 2009

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DYNAMIC COMPLEXITY CHARACTERISTICSOF COMPLEX SYSTEMS

• 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.

JENNIFER GROFF 2009

Page 4: Dynamic Complex Systems

MODELING TOOLS FOR SYSTEM DYNAMICS

Behavior-Over-Time Graphs - Displays data of change in the system in a line graph format

Causal Loop Diagrams - Mapping of feedback loops and how they may interact with one another

Stock/Flow Maps - "Stocks" are the accumulation of something in the system, such as money, people, etc. "Flows" are the rates of change of those stocks, such as savings or spending rate. Feedback loops within a system are what control these flows. Through these three components, one can depict the dynamics of a given system.

Computer Simulation Models - Once a system is diagrammed, its accuracy can best be tested through constructing a computer simulation of that model. While no one person could simultaneously calculate the interdependent relationships of system of time that produces the troublesome behavior, a computer model can. Numerous tools have been developed to help achieve this, including StarLogo, and NetLogo.

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EXAMPLE FROM SCIENCEINFECTIOUS ACTIVITY

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EXAMPLE FROM SCIENCEINFECTIOUS ACTIVITY

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EXAMPLE FROM SCIENCEINFECTIOUS ACTIVITY

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EXAMPLE FROM SCIENCEINFECTIOUS ACTIVITY

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EXAMPLE FROM SCIENCEINFECTIOUS ACTIVITY

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Student : TeacherRatio

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Student : TeacherRatio

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Student : TeacherRatio

StudentAchievement

JENNIFER GROFF 2009

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Student : TeacherRatio

StudentAchievement

JENNIFER GROFF 2009

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Student : TeacherRatio

StudentAchievement

JENNIFER GROFF 2009

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Student : TeacherRatio

StudentAchievement

NCLBFunding

JENNIFER GROFF 2009

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Student : TeacherRatio

StudentAchievement

NCLBFunding

JENNIFER GROFF 2009

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Student : TeacherRatio

StudentAchievement

NCLBFunding

JENNIFER GROFF 2009

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Student : TeacherRatio

StudentAchievement

NCLBFunding

JENNIFER GROFF 2009

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Student : TeacherRatio

StudentAchievement

NCLBFunding

R

JENNIFER GROFF 2009

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Student : TeacherRatio

StudentAchievement

NCLBFunding

R

State Funding

JENNIFER GROFF 2009

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Student : TeacherRatio

StudentAchievement

NCLBFunding

R

State Funding

JENNIFER GROFF 2009

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8

Content Alignment Rate

class time available

RB

exposure to test content 8

JENNIFER GROFF 2009

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Subjects Taught/Tested 8

Content Alignment Rate

class time available

RB

exposure to test content 8

JENNIFER GROFF 2009

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Subjects Taught/Tested 8

Content Alignment Rate

class time available

RB

exposure to test content 8

JENNIFER GROFF 2009

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Subjects Taught/Tested

Subject Not Taught/ Tested8

Content Alignment Rate

class time available

RB

exposure to test content 8

JENNIFER GROFF 2009

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Subjects Taught/Tested

Subject Not Taught/ Tested8

Content Alignment Rate

class time available

RB

exposure to test content

Students Pro!cient

8

JENNIFER GROFF 2009

Page 27: Dynamic Complex Systems

Subjects Taught/Tested

Subject Not Taught/ Tested8

Content Alignment Rate

class time available

RB

exposure to test content

Students Pro!cient

Students Not Pro!cient

8

JENNIFER GROFF 2009

Page 28: Dynamic Complex Systems

HIERARCHICAL LEVELS OF EDUCATIONAL SYSTEM POLICY ANALYSIS

Student Teacher

Classroom

School

District

State

Federal

JENNIFER GROFF 2009

Page 29: Dynamic Complex Systems

JENNIFER [email protected]

2009