4. Systems and System Models

Below is the progression of the Crosscutting Concept of Systems and System Models, followed by Performance Expectations that make use of this Crosscutting Concept.

4. Systems and System Models

A system is an organized group of related objects or components; models can be used for understanding and predicting the behavior of systems.

Primary School (K-2)

  • Systems in the natural and designed world have parts that work together.
  • Objects and organisms can be described in terms of their parts.

Elementary School (3-5)

  • A system can be described in terms of its components and their interactions.
  • A system is a group of related parts that make up a whole and can carry out functions its individual parts cannot.

Middle School (6-8)

  • Models can be used to represent systems and their interactions—such as inputs, processes and outputs—and energy and matter flows within systems.
  • Systems may interact with other systems; they may have sub-systems and be a part of larger complex systems.
  • Models are limited in that they only represent certain aspects of the system under study.

High School (9-12)

  • When investigating or describing a system, the boundaries and initial conditions of the system need to be defined and their inputs and outputs analyzed and described using models.
  • Models (e.g., physical, mathematical, computer models) can be used to simulate systems and interactions—including energy, matter, and information flows—within and between systems at different scales.
  • Models can be used to predict the behavior of a system, but these predictions have limited precision and reliability due to the assumptions and approximations inherent in models.
  • Systems can be designed to do specific tasks.

This is a table of the Crosscutting Concept of Systems and System Models. If coming from a Standard the specific bullet point used is highlighted and additional performance Expectations that make use of the Crosscutting Concept can be found below the table. To see all Crosscutting Concepts, click on the title "Crosscutting Concepts."

Systems and System Models

Systems and System Models are useful in science and engineering because the world is complex, so it is helpful to isolate a single system and construct a simplified model of it. “To do this, scientists and engineers imagine an artificial boundary between the system in question and everything else. They then examine the system in detail while treating the effects of things outside the boundary as either forces acting on the system or flows of matter and energy across it—for example, the gravitational force due to Earth on a book lying on a table or the carbon dioxide expelled by an organism. Consideration of flows into and out of the system is a crucial element of system design. In the laboratory or even in field research, the extent to which a system under study can be physically isolated or external conditions controlled is an important element of the design of an investigation and interpretation of results…The properties and behavior of the whole system can be very different from those of any of its parts, and large systems may have emergent properties, such as the shape of a tree, that cannot be predicted in detail from knowledge about the components and their interactions.” (p. 92)

“Models can be valuable in predicting a system’s behaviors or in diagnosing problems or failures in its functioning, regardless of what type of system is being examined… In a simple mechanical system, interactions among the parts are describable in terms of forces among them that cause changes in motion or physical stresses. In more complex systems, it is not always possible or useful to consider interactions at this detailed mechanical level, yet it is equally important to ask what interactions are occurring (e.g., predator-prey relationships in an ecosystem) and to recognize that they all involve transfers of energy, matter, and (in some cases) information among parts of the system… Any model of a system incorporates assumptions and approximations; the key is to be aware of what they are and how they affect the model’s reliability and precision. Predictions may be reliable but not precise or, worse, precise but not reliable; the degree of reliability and precision needed depends on the use to which the model will be put.” (p. 93)