Scientific Inquiry, Engineering, and Crosscutting Concepts
What this domain tests
Scientific Inquiry, Engineering, and Crosscutting Concepts tests how scientists and engineers build reliable knowledge and solutions. Expect experimental design, variables, data interpretation, graphing, evidence-based claims, engineering constraints, tradeoffs, and crosscutting concepts such as patterns, cause and effect, scale, systems, energy and matter, structure and function, and stability and change.
Core rules
- A testable hypothesis predicts a relationship between an independent variable and a dependent variable.
- Controlled experiments keep other variables constant and include a comparison or control group.
- Repeated trials and larger samples improve reliability; they do not guarantee validity.
- Correlation does not establish causation.
- Engineering design defines a problem, specifies criteria and constraints, builds a prototype, tests it, and iterates.
- Crosscutting concepts connect explanations across domains.
Worked example
A student claims a new biodegradable mulch increases tomato yield. Design a test and identify the variables. Reasoning: The independent variable is mulch type: biodegradable mulch versus no mulch or standard mulch. The dependent variable is tomato yield, measured as mass or number per plant. Constants include soil, water, light, plant variety, and planting date. Randomly assign many plants to each treatment and repeat the season. A difference in mean yield supports the claim only if the comparison is fair and variation is considered. If the student also measures soil moisture, that is a possible confounding variable, not the dependent variable.
Traps
- Calling any difference a “significant” result without considering sample size or variation.
- Changing more than one variable and still attributing the result to one cause.
- Using a line graph for categorical groups; bar graphs usually fit categories.
- Treating a prototype as final; engineering design is iterative.