Experimental skills and investigations in Year 7 Science

Plan a fair scientific investigation

Start with a question that can be answered by observations or measurements. Use scientific knowledge to make a prediction, then identify the variables. The independent variable is the factor deliberately changed. The dependent variable is the result measured or observed. Control variables are the other factors kept the same so that they do not provide a different explanation for the result.

A fair test changes only the independent variable while controlling relevant conditions. The method should name the equipment, quantities, measurement intervals and sequence clearly enough for another person to repeat it. Safety is part of the plan: identify hazards, explain how risk will be reduced and follow the instructions of the supervising adult rather than attempting unfamiliar practical work alone.

• Question: what relationship or difference will the investigation test?
• Prediction: what outcome is expected, and which scientific idea supports it?
• Variables: what will change, what will be measured and what must stay constant?

Measure accurately and record usable data

Choose equipment with a suitable range and resolution. A ruler marked in millimetres can distinguish smaller length differences than one marked only in centimetres. Record every measurement with its unit and use the same method each time. Repeats help reveal natural variation and mistakes; they do not repair a method that changes halfway through the investigation.

Design the results table before collecting data. Put the independent variable in the first column and the dependent variable in the next column, with units in the headings rather than repeated in every cell. Keep observations separate from measurements where that makes the evidence clearer. Do not remove an unexpected result simply because it does not fit the prediction: mark it as a possible anomaly and decide whether there is a justified reason to repeat that reading.

Present patterns and write an evidence-based conclusion

Choose a graph that matches the variables. A line graph or scatter graph is useful when the independent variable is numerical and continuous; a bar chart is suitable when the groups are categories. Plot the independent variable on the horizontal axis and the dependent variable on the vertical axis, use even scales and label both axes with units.

A conclusion should describe the pattern in the data and answer the investigation question. Refer to both variables and use measured values as evidence. Then explain the pattern using relevant science. Supporting the prediction does not prove that an explanation is permanently correct, and a result that contradicts the prediction is still useful if the method and evidence are sound.

Evaluate reliability and improve the method

Evaluation asks how much confidence the evidence deserves. Check whether repeat readings are close together, whether the control variables really stayed constant, whether the equipment could resolve the expected differences and whether enough values were tested to reveal a pattern. Random error causes readings to vary unpredictably; systematic error shifts results in a consistent direction.

Suggest a specific improvement linked to a weakness. For example, use a data logger to measure at fixed intervals, repeat each condition and calculate a mean, test more values across the range, or control temperature with a water bath. Saying only that the investigation should be more accurate is not enough: identify what will change and explain how that change will improve the evidence.