Scientific and Engineering Practices / Crosscutting Concepts
Scientific and Engineering Practices / Crosscutting Concepts
This domain tests how scientific knowledge is built and how big ideas connect across topics. You must identify variables, judge whether a test is fair, interpret data and use concepts such as patterns, cause and effect, systems and structure–function.
Investigations
- The sequence is question → prediction → method → data → conclusion. A hypothesis is a testable explanation; a prediction is what you expect to happen.
- In a fair test, change the independent variable, measure the dependent variable, and keep all other variables controlled. Repeat and average to reduce error.
- Observations use the senses or instruments; inferences are explanations of observations.
- Data tables need units; graphs need labelled axes and a suitable scale. A conclusion must be based on the evidence and state whether the prediction was supported.
Crosscutting concepts
- Patterns: day and night, seasons, and properties shared by groups of materials or organisms.
- Cause and effect: forces change motion; heating transfers energy.
- Scale and proportion: cells compared with organs; distances in the solar system.
- Systems: a circuit, a food web or the water cycle. Parts interact, so changing one part affects others.
- Structure and function: root hairs absorb water; wings produce lift; a wide base gives stability.
- Stability and change: ecosystems may resist small changes but can shift after large ones.
Engineering practices
Define the problem, design a solution, test it and optimise it. Use evidence to decide which design best meets the criteria.
Worked example
A pupil tests whether light affects bean growth by placing pots at different distances from a lamp.
Reasoning: the independent variable is distance from the lamp; the dependent variable is growth measured after a set number of days; controlled variables include bean type, soil, water, pot size and time. Measure with a ruler at the same time each day, repeat with several pots and average. If the nearer pot grows more, light intensity is a likely cause - but only if the other variables were controlled.
Traps that cost marks
- Calling any guess a hypothesis; a hypothesis must be testable.
- Changing two variables at once in a fair test.
- Confusing an observation with an inference.
- Reading a graph's highest point as best without checking the units and axis labels.
- Assuming correlation proves cause.
- Treating parts of a system as if they act alone.