Systems Thinking 101: A New Way of Understanding Student Risk

In my last post, I raised the need to develop next-generation early-warning systems that better identify students "at-risk" in our schools. I also argue that to do so, we need to expand our conceptualization of the problem of student failure as well as our definition of "at risk." In short, we need a different mindset if we want our early-warning systems to be better able to help schools simultaneously reduce student risk and increase student achievement.

At New Visions, we have adopted systems thinking as a way of re-framing the problem. Unlike other frameworks, systems thinking is closed loop as opposed to open loop; and, it helps bring to light structures that are not easily seen but are often at the root of many vicious cycles. In this post, l'll define what constitutes a system and then bring the art of systems thinking to life using visualization maps created in STELLA, software that allows users to build simulations.

Systems and Systems Thinking

Donella Meadows defines a system as "an interconnected set of elements that is coherently organized in a way that achieves something."  Elements, interconnections, and function are the critical components of a system.  Elements are the easiest components to identify in a system because they tend to be visible.  Interconnections represent the causal relationships among the elements and determine how they will interact.  Function is system behavior -- how the system actually behaves; and, often there is a discrepancy between our conceptualization of system behavior (i.e., vision / mission statements) and reality.   She gives a simple example of system:

"A football team is a system with elements such as players, coach, field, and ball. Its interconnections are the rules of the game, the coach's strategy, the players' communications, and the laws of physics that govern the motions of ball and players. The purpose of the team is to win games, or have fun, or get exercise, or make millions of dollars, or all of the above."

The emergent behavior that characterizes the system (i.e., its outcomes) is a result of the dynamic interplay of the interconnected elements. In other words, a system is more than the sum of its parts.  System behavior encompasses both the interactions and interconnections among a system’s constituent parts, the "small behaviors" (e.g. the fluid exchange and understanding of the signals the coach and quarterback give and receive) as well as the overall functioning of the system, or its "large behavior" (e.g. the win-loss record or divisional standing).

Barry Richmond defines systems thinking as "the art and science of making reliable inferences about behavior by developing an increasingly deep understanding of underlying structure." In other words, if you understand the component parts of a system (its elements and interconnections) – then you can predict the way the system will behave. 

For example, it might be seductive to blame the quarterback for losing the game.  This is the visible.  We saw with our own eyes the interception.  But, perhaps the quarterback was injured going into that game and the team did not have sufficient resources to 1) adequately treat the quarterback or 2) the resources to hire a strong second string quarterback with sufficient skill to relieve the first string quarterback.  And this lack of funding also translates to hiring strong offensive line. Insufficient funds might mean weaker lineman less capable of protecting the quarterback, which resulted in the injuries … and so on.  Understanding the financial structures of the football team and the key decisions related to the allocation of resources is a less visible structure but one that might play a more critical role in a win-loss record than the individual players on the team.

In systems thinking, the structure of the system is mapped or diagramed using the language and visual images of "stocks" and "flows." Stocks represent accumulations of information, material, or psychological states that build up or diminish over time through the actions of flows. Flows are the "filling or draining" process that change the amount of stock over time.

Figure 1: Simple stock-flow diagram

In Figure 1, imagine the "stock" is a bathtub.  Water flows into it through the pipe.  The amount of water flowing in it is dependent upon how much you open or close its faucet – the "rate."  Sometimes systems thinking is referred to as "bathtub dynamics."

Figure 2.  Bathtub dynamics diagram

Let's pull apart Figure 2.  If we have an equal amount of water flowing into and out of the bathtub, then the level of water in the bathtub (its stock) is stabilized.  If we have more water flowing in than out, our bathtub overflows.  If we have more water flowing out than in, we will never being able to fill the bathtub.

By mapping stocks and flows, we begin to see the dynamic complexity (i.e., the filling and draining process) that arises from the interaction of a system's agents over time. 

When we observe consistently low graduation rates at a school over many years, this pattern suggests the presence of a "reinforcing" feedback loop. In the next blog post, I'll focus on the often invisible feedback loops that are more readily observable within a systems thinking map and explain why they are so important to respect, understand, and fear.

Susan Fairchild is director of program analysis and applied research at New Visions. Follow her on Twitter at @SKFchild.
 

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