Planning — OCR A-Level Physics
Test yourself on Planning with OCR A-Level practice questions.
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Planning explained
Experimental design means turning a question into a workable procedure.
Read the full explanation
Start by defining the independent variable you will change, the dependent variable you will measure, and the quantities held constant. Choose apparatus whose resolution suits the expected values: for example, measuring a 2 cm extension with a millimetre rule gives useful precision, whereas a metre rule alone may not. Plan a sensible range of at least five readings, with repeats, and decide how to reduce random and systematic error. In a practical context you must also judge risks, select suitable instruments, and describe how to process data, such as plotting a graph and finding a gradient. The design must be specific enough that another student could follow it and obtain comparable results.
(b) identification of variables that must be controlled, where appropriate
Controlled variables are the quantities, other than the independent and dependent variables, that could affect the result if they changed. In a practical investigation you identify them from the physics of the situation. For example, when testing how the extension of a spring depends on the load, the spring itself, its original length and the temperature should stay the same, because changing any of them would alter the extension for the same load. Not every variable needs controlling: if a quantity has no measurable effect on the outcome, controlling it wastes effort. The skill is to decide which variables matter, explain why, and state how each will be kept constant. A controlled variable is not the same as a zero or null result; it is a quantity deliberately held fixed.
(c) evaluation that an experimental method is appropriate to meet the expected outcomes.
Evaluating a method means judging whether it can actually produce the expected outcome. Check that the apparatus measures the right quantity with enough resolution, that the range of readings covers the values needed, and that the procedure controls the variables that matter. Consider whether the expected relationship, such as extension proportional to load, would be visible in the data or hidden by uncertainty. Identify weaknesses and suggest specific improvements: for example, replacing a stopwatch with a light gate reduces reaction-time error, and increasing the number of repeats reduces random scatter. A strong evaluation distinguishes random from systematic error and explains how each affects the conclusion. It also judges whether the method is safe and practical, not merely whether it is theoretically possible.
Your focus
- Design a practical procedure that tests a stated relationship in a given context.
- Justify the choice of apparatus, range and number of readings.
- Describe how the collected data will be processed to reach a valid conclusion.
Show all 9 objectives
- Identify which variables must be controlled in a described practical context.
- Explain why each controlled variable could affect the measured outcome.
- Describe a practical method for holding each relevant variable constant.
- Evaluate whether a described method can produce the expected outcome.
- Identify specific sources of error and explain their effect on the data.
- Propose and justify improvements that address identified weaknesses.
Planning exam tips
Marking Points
- States a clear independent variable, dependent variable and the key controlled variables for the practical context given.
- Selects apparatus with appropriate resolution and range for the expected measurements, justifying the choice.
- Describes a suitable number and spread of readings, including repeats where random error matters.
- Explains how measurements will be processed, for example averaging, plotting a graph, or using a gradient or intercept.
- Identifies realistic risks and describes precautions that reduce them without making the experiment unworkable.
- Explains how the design will produce data that can answer the question or test the stated relationship.
- Identifies variables, other than the independent and dependent variables, that could affect the measured outcome.
- Explains the physical reason why each identified variable must be held constant.
- Distinguishes variables that genuinely need control from those that do not affect the result.
- States a practical method for keeping each controlled variable constant.
- Judges whether the apparatus and procedure measure the required quantities with sufficient resolution and range.
- Assesses whether the method controls the variables needed for a valid test of the expected outcome.
- Identifies specific sources of random and systematic error and explains their likely effect on the results.
- Suggests realistic improvements that would make the method better able to meet the expected outcome.
- Distinguishes weaknesses that matter for the conclusion from minor practical inconveniences.
- Reaches a supported judgement about whether the method is appropriate overall.
Examiner Tips
- 💡Write the plan as a sequence another student could follow, naming each instrument and the quantity it measures.
- 💡Justify choices of range and resolution using the expected size of the measurements, not just personal preference.
- 💡State how you will process the data and how that processing will answer the question asked.
- 💡Read the practical context carefully and link each controlled variable to the physics of the measurement.
- 💡For each controlled variable, add a short phrase explaining how it is kept constant.
- 💡Reject variables that cannot plausibly affect the result, and be ready to say why they can be ignored.
- 💡Structure the evaluation around apparatus, range, control of variables and error, then give an overall judgement.
- 💡For each weakness, state the effect on the data and a specific improvement.
- 💡Use the expected outcome to decide whether the method is fit for purpose, rather than judging it in isolation.
Common Mistakes
- Listing apparatus without linking each item to what it measures; correction: state the quantity, the instrument and why its resolution is adequate.
- Changing more than one variable at once; correction: identify the independent variable and keep all other relevant quantities constant.
- Giving a single reading as the whole method; correction: plan a range of values and repeats so a pattern or relationship can be seen.
- Confusing the independent variable with a controlled variable; correction: the independent variable is deliberately changed, while controlled variables are held fixed.
- Assuming every conceivable quantity must be controlled; correction: control only those that could measurably affect the dependent variable.
- Naming a controlled variable without saying how it will be kept constant; correction: give the practical method, such as using the same spring each time.
- Listing generic errors such as human error without linking them to the specific method; correction: name the source, such as reaction time when using a stopwatch, and explain its effect.
- Suggesting improvements that do not address the identified weakness; correction: match each improvement directly to the problem it solves.
- Treating all errors as random; correction: distinguish random scatter from systematic offset and explain how each affects the conclusion.