S2.1.3—Controlling variables

Control an effect because it could change the outcome

For every control, state the unwanted influence, the practical action and how that action protects the dependent measurement. A variable name alone does not show that the investigation is controlled.

Unwanted influence	Practical control	Why it helps
Instrument offset or sensor drift	Zero and calibrate before use; record any correction	Prevents a fixed offset from being mistaken for a physical effect
Changing environmental conditions	Monitor and maintain the relevant condition	Stops an external change from becoming a second independent variable
Heat exchange	Insulate against heat loss or gain where relevant	Keeps energy transfer outside the intended system small
Friction or unwanted electrical resistance	Reduce it consistently or account for it in the design	Limits unintended energy loss or voltage change
Background radiation	Measure the background under the same conditions and correct the signal	Separates source counts from background counts

Example — pendulum timing

If length is the independent variable and period is measured, keep a measurable release condition such as the initial angle constant; bob mass, diameter or material may also matter to the chosen setup. Explain how the same value is reproduced for every trial.

Control the system, not merely the equipment name

Saying “use the same stopwatch” or “keep gravity constant” does not identify a controllable influence in this design. Name a measurable feature and the method used to maintain it.

How it is assessed

Questions ask for one variable that needs to be controlled in a materials experiment.

Command terms

State

What earns marks

Name a relevant measurable property such as material, dimensions, mass or applied rate, not an unrelated environmental condition.

Watch for

Giving an irrelevant variable such as atmospheric pressure when the method’s material and geometry are the actual controls.

Design from a question

Turn context into a measurable question, hypothesis and prediction with independent, dependent and controlled variables.

Make evidence reliable

Choose a useful range and repeats, calibrate instruments, control relevant conditions and reduce or correct known losses and background.

S2.1.3—Controlling variables

Control Experimental Variables

S2.1.3 Exam Analysis

Assessment in practice

Retrieve Investigation Design