Science & Engineering Practices in the NGSS

The Framework described eight practices in Science and Engineering that all students needed to learn. These are the skills and knowledge needed to do science. We have gathered resources to help you understand all eight practices.

Come back often to this page as we will continue to add more background information to each practice and lesson plans that can be used in your classroom.

Click on each section below to expand and see links to resources.

General Resources for Science and Engineering Practices

  • The Concord Consortium offers a online tool Find Your Path through the NGSS that lets you find lesson ideas based on Core Idea, Crosscutting Concept, and Science and Engineering Practices. Geared towards middle and high school

1. Asking Questions (for science) and Defining Problems (for engineering)

2. Developing and Using Models

3. Planning and Carrying Out Investigations

Scientists and engineers plan and carry out investigations in the field or laboratory, working collaboratively as well as individually. Their investigations are systematic and require clarifying what counts as data and identifying variables or parameters. Engineering investigations identify the effectiveness, efficiency, and durability of designs under different conditions. 

4. Analyzing and Interpreting Data

Once collected, data must be presented in a form that can reveal any patterns and relationships and that allows results to be communicated to others. Because raw data as such have little meaning, a major practice of scientists is to organize and interpret data through tabulating, graphing, or statistical analysis. Such analysis can bring out the meaning of data—and their relevance—so that they may be used as evidence. Engineers, too, make decisions based on evidence that a given design will work; they rarely rely on trial and error. Engineers often analyze a design by creating a model or prototype and collecting extensive data on how it performs, including under extreme conditions. Analysis of this kind of data not only informs design decisions and enables the prediction or assessment of performance but also helps define or clarify problems, determine economic feasibility, evaluate alternatives, and investigate failures. (NRC Framework, 2012, p. 61-62) 

5. Using Mathematics and Computational Thinking

6. Constructing Explanations (for science) and Designing Solutions (for engineering)

7. Engaging in Argument from Evidence

8. Obtaining, Evaluating, and Communicating Information