# Experiment Planning

> CIE A-Level Physics · AS Practical Skills
> Source: https://www.owlsprep.com/study/cie-9702-u15-experiment-planning/

This module covers how to answer high-weight experiment planning questions for CIE AS Paper 3. You will learn how to structure your plan to hit all marking points, avoid common traps, and maximise your score.

**Prerequisites:** Basic physical measurement principles; [Linear and non-linear graph plotting](https://www.owlsprep.com/study/cie-9702-fundamentals-graph-plotting/)

## Learning objectives

- Identify independent, dependent and control variables correctly
- Select appropriate apparatus and write a replicable experimental method
- Plan data analysis including graph plotting and constant calculation
- Identify sources of uncertainty and relevant safety precautions
- Maximise marks on CIE AS Paper 3 planning questions

## Variables and Apparatus Selection

**Core Experimental Variables** — All valid experiments have three key variable types: independent (changed by the experimenter), dependent (measured for effect), and control (kept constant to avoid confounding results)

*Example:* For testing how extension changes with load, load is independent, extension is dependent

The first step in any plan is explicitly stating your variables — this is almost always worth 2-3 marks, so never skip this step. When selecting apparatus, you need to justify your choice based on measurement resolution, matching the apparatus to the expected range of measurements.

**Worked example:** For an experiment investigating how spring extension depends on added load, identify variables and select appropriate apparatus.

1. Identify all variables clearly:
2. - Independent variable: Load (force) added to the spring
- Dependent variable: Extension of the spring
- Control variables: Spring used, environmental temperature
3. Select appropriate apparatus with suitable resolution:
4. Force is measured with 0.1 N resolution slotted masses, appropriate for the 0-10 N range. Extension is measured with a 1 mm resolution metre rule, suitable for extensions of 1-10 cm. Additional apparatus: clamp stand, boss, set square to reduce parallax.

> **Exam tip:** Always mention the resolution of your apparatus if asked to justify your choice, this is a common hidden marking point.

## Method and Control of Variables

A good method is written as a clear step-by-step procedure that another person could follow exactly. You must explicitly state how you control variables that could affect results, and how you collect repeat data to reduce random error.

**Repeat Measurements** — Multiple measurements of the same dependent variable for a fixed independent variable, used to reduce random error and calculate uncertainty in results.

**Worked example:** Write the method for the spring and load experiment, including control of variables.

1. 1. Clamp the spring vertically to the stand, use a set square to align the rule vertically, measure and record the original unloaded length of the spring.
2. 2. Add the first slotted mass, wait 30 seconds for the spring to reach equilibrium, then measure the new extended length.
3. 3. Calculate extension = new length - original length, record the value. Remove the mass, repeat the measurement twice more for the same load to get three repeats.
4. 4. Repeat steps 2-3 for at least 6 different load values across the 0-10 N range. Keep the same spring and measurement technique for all readings to control all other variables.

> **Exam tip:** Planning to take at least 6 readings for the independent variable and repeats for the dependent variable are almost always guaranteed marks, so never forget these.

## Planning Data Analysis

Most planning questions require you to explain how you will plot a graph and draw a conclusion. You must state what to plot on each axis, how you will test the given relationship, and how to calculate any unknown constant from your graph.

**Exam command terms**

Common command terms for analysis planning have clear expected answers:

- **Confirm the hypothesis is correct** — State what graph will confirm the relationship, what shape/gradient you expect *(For $F=kx$, a linear graph through the origin confirms Hooke's law)*

- **Determine the unknown constant** — Link the gradient or intercept of your graph directly to the constant value

**Worked example:** How do you analyse the spring experiment results to find the spring constant $k$ and confirm Hooke's law $F=kx$?

1. 1. Calculate the mean extension for each load value from your three repeat measurements.
2. 2. Plot a graph with:
3. $$F \text{ (load)} \text{ on the y-axis}, \quad x \text{ (mean extension)} \text{ on the x-axis}$$
4. 3. From Hooke's law $F=kx$, the gradient of the straight line of best fit is equal to $k$:
5. $$k = \frac{\Delta F}{\Delta x} = \text{gradient}$$
6. 4. Confirm Hooke's law if all points lie close to a straight line that passes through the origin.

## Error, Uncertainty and Safety

You will almost always be asked to identify sources of uncertainty and relevant safety precautions. These are easy marks that you should never leave blank.

> **tip**
>
> Safety is usually only 1 mark, but you only need one relevant precaution to get it. Generic irrelevant precautions do not earn marks.

**Worked example:** Identify one major source of uncertainty and one relevant safety precaution for the spring experiment.

1. Major source of uncertainty: Parallax error when reading the end of the spring on the rule. This is reduced by using a set square aligned to the end of the spring to take the reading.
2. Safety precaution: Overloading the spring can cause it to snap and recoil violently. Wear safety goggles to protect your eyes from flying debris if the spring breaks.

## Common pitfalls

- **Wrong:** Failing to explicitly state each variable type, only mentioning what you measure.
  - Why it fails: Mark schemes always award separate marks for correctly identifying independent, dependent and control variables.
  - Correct: Start your plan by clearly stating each variable by type.
- **Wrong:** Planning fewer than 6 different readings for the independent variable.
  - Why it fails: A small range of data cannot produce an accurate graph or conclusion, and loses marks for insufficient data.
  - Correct: Always plan for at least 6 different values across the full available range of the independent variable.
- **Wrong:** Forgetting to state what to plot on each graph axis.
  - Why it fails: This is a common 2-mark requirement that many students miss, even when they understand the relationship.
  - Correct: Always explicitly state which variable goes on each axis, and link the gradient or intercept to any required constant.
- **Wrong:** Stating vague "human error" as a source of uncertainty.
  - Why it fails: Vague sources of error do not earn marks; you need to identify the specific cause.
  - Correct: Name the specific source, e.g. "parallax error when reading the rule" instead of just "human error".
- **Wrong:** Including generic irrelevant safety precautions.
  - Why it fails: Mark schemes only award marks for safety precautions relevant to the specific experiment.
  - Correct: Identify the actual hazard (e.g. snapping spring, falling mass, hot wire) and give a matching precaution.

## Cheatsheet

| Planning Section | Required Marked Points |
| --- | --- |
| Variables | State independent, dependent, 1-2 control variables |
| Apparatus | List all, state resolution to justify choice |
| Method | ≥6 readings, repeat measurements, control variables |
| Analysis | State axes, link gradient/intercept to constant, confirm relationship |
| Uncertainty | Name 1 specific source, explain how to reduce it |
| Safety | 1 relevant hazard + matching precaution |

## What's next

Experiment planning is the foundation of all practical work in CIE A-Level Physics, and the skills you learn here carry over to A2 practical work and analysis questions in written papers. Mastering planning gives you a huge advantage on Paper 3, where it makes up almost half the total marks. The skills of critical thinking about variables, error, and experimental design also help you answer unexpected questions across all physics papers. After mastering core planning, you can move on to deeper study of uncertainty, graph analysis and experiment evaluation.

- [Measurement and Observation](https://www.owlsprep.com/study/cie-9702-u15-measurement-and-observation/)
- [Data analysis](https://www.owlsprep.com/study/cie-9702-u15-data-analysis/)
- [Uncertainty Analysis](https://www.owlsprep.com/study/cie-9702-u15-uncertainty-analysis/)

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