Subject: Ways of understanding a dynamic system

Posted by John Gunkler on 5/10/2004
In Reply To:Ways of understanding a dynamic system Posted by Lees Stuntz on 5/10/2004

Message:

Frank Draper, in System Dynamics Review, Vol. 9, no 2 (Summer 1993): 207 - 214, used Barry Richmond's "seven systems thinking skills" as the structure for a 4 - 12 curriculum sequence. I have a PDF file of this article that I'd be willing to send to the person who wrote to ask you how to evaluate the level of understanding of system dynamics. The seven skills are in a kind of order of difficulty so they could become a taxonomy underlying an evaluation (or "categorization") scheme. Here's Draper's version:

1. STRUCTURAL THINKING Figuring out interrelations, what affects what, where things flow, which things accumulate.

Level I: Recognizing what affects what: simple causal relations

Level II: Identifying stocks and flows in phenomena

Level III: Generating detailed flow structures (adding rates, flows, converters) and maintaining dimensional consistency in model

2. DYNAMIC THINKING According to Richmond, “the ability to see and deduce behavior patterns rather than focusing on, and seeking to predict, events.”

Level I : Drawing graphs of behavior over time

Level II: Identifying systems' goals

Level III: Deducing the behavior of stocks and flows

3. GENERIC THINKING Looking beyond specific chains of events to identify which, if any, generic system structures are operating to generate the observed behavior. Going beyond analysis to synthesis to achieve something new. These phenomena are called generic policy structures or system archetypes.

Level I: Understanding and using causal-loop diagrams and archetypes

Level II: Recognizing and using stock-and-flow generic structures

Level III: Creating systems using multiple archetypes and stock-and-flow structures

4. OPERATIONAL THINKING According to Richmond, “thinking in terms of how things really work—not how they theoretically work.”

Level I: Recognizing simple causal relations using real-world variables

Level II: Building paper and pencil stock-and-flow diagrams

Level III: Creating computer models

5. SCIENTIFIC THINKING Being able to quantify relations, accumulations, and decisions (this is not measurement). Being able to hypothesize and test assumptions and models.

Level I : Manipulating and modifying preconstructed computer models

Level II: Creating simple models

Level III: Analyzing models rigorously and testing for robustness

6. CLOSED-LOOP THINKING Recognizing that the internal circular causality of cause-effect feedback, rather than external linear cause-effect relations. is responsible for the behavior of systems.

Level I: Identifying simple internal causal relations

Level II: Running microworld case studies with in-depth debriefing and analysis

Level III: Creating computer models

7. CONTINUUM THINKING Recognizing that continuous processes, rather than discrete events and classes of objects, characterize most real-world phenomena. This is difficult to do, because language and ways of seeing the world habitually emphasize discrete events and relations.

Level I: Identifying simple continuous processes in daily events

Level II: Manipulating, modifying, analyzing, and discussing preconstructed computer models

Level III: Creating computer models

Lees, have her send me an email and I'll be happy to help.

John Gunkler