Table 2 Comparison of science and engineering practices

Begins with a question about a phenomenon.

Begins with a problem, need, or desire that leads to an engineered solution.

Using models to develop explanations about natural phenomena.

Using models and simulations to analyze existing solutions.

Scientific investigation in field or lab using a systematic approach.

Engineering investigation to obtain data necessary for identifying criteria and constraints and to test design ideas.

Analyzing and interpreting data from scientific investigations using a range of tools for analysis (tabulation, graphical interpretation, visualization, and statistical analysis) locating patterns.

Analyzing and interpreting data collected from tests of designs and investigations to locate optimal design solutions.

Mathematical and computational thinking are fundamental tools for representing variables and their relationships. These ways of thinking allow for making predictions, testing theory, and locating patterns or correlations.

Mathematical and computational thinking are integral to design by allowing engineers to run tests and mathematical models to assess the performance of a design solution before prototyping.

Constructing scientific theory to provide explanations is a goal for scientists and grounding the explanation of a phenomenon with available evidence.

Constructing designing solutions using a systematic approach to solving engineering problems based upon scientific knowledge and models of the material world. Designed solutions are optimized by balancing constraints and criteria off existing conditions.

Arguments with evidence is key to scientific practices by providing a line of reasoning for explaining a natural phenomenon. Scientists defend explanations, formulate evidence based on data, and examine ideas with experts and peers understandings.

Arguments with evidence is key to engineering for locating the best possible solutions to a problem. The location of the best solution is based on a systematic approach to comparing alternatives, formulating evidence from tests, and revising design solutions.