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Models - Developing and Using Models -
Models include diagrams, physical replicas, mathematical representations, analogies, and computer simulations. Although models do not correspond exactly to the real world, they bring certain features into focus while obscuring others. All models contain approximations and assumptions that limit the range of validity and predictive power, so it is important for students to recognize their limitations.   

In science, models are used to represent a system (or parts of a system) under study, to aid in the development of questions and explanations, to generate data that can be used to make predictions, and to communicate ideas to others. Students can be expected to evaluate and refine models through an iterative cycle of comparing their predictions with the real world and then adjusting them to gain insights into the phenomenon being modeled. As such, models are based upon evidence. When new evidence is uncovered that the models can’t explain, models are modified.  

engineering, models may be used to analyze a system to see where or under what conditions flaws might develop, or to test possible solutions to a problem. Models can also be used to visualize and refine a design, to communicate a design’s features to others, and as prototypes for testing design performance.

 Scientific models are not... Scientific models are...
  • Models should never be created for the sake of creating a model. 
  • Models are also not art projects.
  • Models are not stand-alone representations that are used to help reinforce vocabulary or definitions. 
  • Models are not static, isolated diagrams!
  • Models show relationships in real-world phenomenon
  • Models explain and real-world phenomenon
  • Models are predictive.
  • Models are dynamic—they change depending on the variables 
  • Models have limitations
  • Data and evidence should be used to support the development of models 
  • Models should be revised and updated based on analysis  of data
  • Models help develop further questions
  • Discussion, sharing, presenting, and argumentation should all be included in the modeling process.

 Multiple Representations Developing Models
Middle School - Modeling in 6–8 builds on K–5 experiences and progresses to developing, using, and revising models to describe, test, and predict more abstract phenomena and design systems.
  • Evaluate limitations of a model for a proposed object or tool.
  • Develop or modify a model—based on evidence – to match what happens if a variable or component of a system is changed.
  • Use and/or develop a model of simple systems with uncertain and less predictable factors.
  • Develop and/or revise a model to show the relationships among variables, including those that are not observable but predict observable phenomena.
  • Develop and/or use a model to predict and/or describe phenomena.
  • Develop a model to describe unobservable mechanisms.
  • Develop and/or use a model to generate data to test ideas about phenomena in natural or designed systems, including those representing inputs and outputs, and those at unobservable scales.

High School - Modeling in 9–12 builds on K–8 experiences and progresses to using, synthesizing, and developing models to predict and show relationships among variables between systems and their components in the natural and designed world(s).
  • Evaluate merits and limitations of two different models of the same proposed tool, process, mechanism, or system in order to select or revise a model that best fits the evidence or design criteria.
  • Design a test of a model to ascertain its reliability.
  • Develop, revise, and/or use a model based on evidence to illustrate and/or predict the relationships between systems or between components of a system.
  • Develop and/or use multiple types of models to provide mechanistic accounts and/or predict phenomena, and move flexibly between model types based on merits and limitations.
  • Use a model to provide mechanistic accounts of phenomena.
  • Develop a complex model that allows for manipulation and testing of a proposed process or system.
  • Develop and/or use a model (including mathematical and computational) to generate data to support explanations, predict phenomena, analyze systems, and/or solve problems.

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