Intuition

Intuition is fast, uncontrolled, and, most importantly, effortless. Computation, on the other hand, is slow, governed by strict rules, and requires tremendous effort.

One Way

One Way

One way is my way and then

there are other ways that others have

to say or nay say their opinion.

My way is the right way and then

there is their way, the wrong way

others have of doing things that way.

My way is better, has benefits, and then

there are other ways that are false promises,

leading to invalid conclusions, inaccurate decisions.

My way is the way to win the future.

A Learning Story

In the Beginning

From the universe of all possible things, select a few to hold in your mind.  Now bring these things into clear focus and find a way to represent them with a symbol or diagram and write a description about how these things fit together.  Include assumptions, elements, parameters, accumulations, flows and other things.  This is defined as a mental model.

Next, start doing “what-if” simulations, running through the dynamics based on your mental model.  Imagine what would happen if your assumptions are true, the parameters have specific values, your accumulations reach accurate levels and the flows are just right.  Rerun your mental model over and over again in your mind with different assumptions, accumulations and flows.  What are the best outcomes and the worst?

Maybe there are some conclusions and decisions that might come to mind after running lots of simulations.  After all this work you have three raw materials for learning (1) a mental model, (2) simulation outcomes, and (3) conclusions and decisions.  These are the raw materials available for constructing learning.

When these raw materials are transparent or revealed to others, then communication is possible. The quality improves when all parties to the communication make their raw materials available to each other.

With this background of thinking and communicating how does learning fit into this picture?  How do we construct learning?

Two Types of Learning

One type of learning might be called self-reflective learning.  This is when the simulation outcomes are used to determine what things are selected from all the things available in the beginning. For example, we think of “what-if” and from the results of the simulation we decide to change the content of what we are thinking about.  We add or remove elements from our mental model.

We also use the simulation outcomes to determine how to represent the things we have selected.  For example, we might change the relationships between things or change a parameter into an accumulation.  We add or remove relationships and symbols for the things on our list.  We rerun the simulation.  We rethink our mental model. This self-reflective learning results from changes in our mental model.

A second type of learning might be called other-inspired learning.  This is when communication with others inspires us to change the things we select or the way we represent those things.  We add or remove elements or relationships.  We change our mental model.  We rerun the simulation.  We communicate again and revise our mental model again. When we communicate our conclusions and decisions after running lots of simulations this will also change what things we select and the way we represent those things in our mental model.  This other-inspired learning results from changes in our mental model.

In the Real World

Until now our story has been about thinking, communicating and learning activities that are very cerebral in nature.  In reality of course, once we have come to a conclusion and made a decision, we are probably going to take action.  Our actions cause consequences that spread out over space and time creating impacts on people and things.  This creates another raw material we can use in our story about learning.

As the consequences branch out and become known, there is the potential to change what elements we select or how we represent them in our mental model.  Another possibility is that when we communicate the consequences to others and others inspire use to change the elements and relationships in our mental model.  These changes cascade through simulations, our conclusions and decisions, and our actions.

In summary, we have four raw materials to work with and two types of learning. We have a self-reflective loop and other-inspired loop to construct learning.  Learning happens when this self-reinforcing system changes our mental models.

We can create learning, improve learning and accelerate learning by building skills in any one of the raw materials and following the process outlined in this story.  Learning doesn’t happen unless our mental model changes.

System Dynamics

System Dynamics builds skills to work within this self-reinforcing system. The study of System Dynamics includes improving our skills to select and represent things to build a computer model, running quality simulations, and reflecting on the elements and relationships in the model.  Self-reflective learning happens when our mental model aligns with our computer model as we make changes.

The study of System Dynamics also includes building skills for coming to conclusions and decisions based on the computer model and simulation results.  A key part of System Dynamics is communicating the four raw materials to others.  Other-inspired learning happens when our model changes are based on feedback from others.

The Education System

In American schools, very little attention is paid to developing simulation skills. Memorization is the primary way knowledge is acquired for improving test scores. This means a very strong set of reinforcing feedback loops is being ignored.  This means students do not have a way to improve the quality of their mental models.

The American Education System doesn’t measure learning.  Standardized tests measure what a student can remember based on memorization and test taking practice.  The current system of formal education in America does not build student skills that create self-reflective and other-inspired learning feedback loops.  They do not operate with the reinforcing system defined by the two types of learning.

As Barry Richmond wrote about building systems thinking skills:

“Each skill can be readily implemented into today’s school systems.  The primary barrier to doing so is the view that the mission of the education system is to fill the students’ heads with knowledge.  This view leads to sharp disciplinary segmentation and to student performance rubrics based on discipline-specific knowledge recall.  Changing viewpoints – especially when they are supported by a measurement system and an ocean of teaching material – is an extremely challenging endeavor.  But the implications of not doing so are untenable.  The time is now.”

Richmond, Barry. "The Thinking in Systems Thinking: Eight Critical Skills." Introduction. Tracing Connections: Voices of Systems Thinkers. Lebanon, NH: isee Systems, 2010. 3-21.