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What practical skills are assessed in the CCEA Double Award, and how do you score well in them?

The prescribed practicals across Biology, Chemistry and Physics, the working-scientifically skills assessed (planning, variables, measuring, recording, analysing and evaluating), and how the Practical Skills unit is examined.

A CCEA GCSE Double Award Science (Practical Skills unit) overview of the prescribed practicals across Biology, Chemistry and Physics, the working-scientifically skills assessed such as variables, accuracy and evaluation, and how the Practical Skills unit is examined.

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  1. What this dot point is asking
  2. The prescribed practicals
  3. Variables and a fair test
  4. Accuracy, precision and errors
  5. Recording, analysing and evaluating
  6. Examples in context
  7. Try this

What this dot point is asking

CCEA Double Award assesses practical work in a dedicated Practical Skills unit (the seventh unit). You carry out prescribed practicals across Biology, Chemistry and Physics during the course, and the unit tests the working-scientifically skills behind them: planning, identifying variables, measuring accurately, recording and presenting data, and analysing and evaluating results. This overview maps the practicals and the skills so you know what is examined.

The prescribed practicals

CCEA sets a list of prescribed practicals spread across the three sciences. You should know the method, the equipment, the variables and the expected results for each. Typical examples are:

For each practical, be ready to recall what you did, why, and what could go wrong.

Variables and a fair test

A fair test changes only the independent variable while keeping the controls constant, so any change in the dependent variable is caused by the independent variable.

Accuracy, precision and errors

Recording, analysing and evaluating

Record results in a table with clear headings and units, then present them as a graph (a line graph for continuous data) with a line of best fit. To analyse, describe the pattern (for example directly proportional) and read values from the graph. To evaluate, comment on how reliable and valid the data are, identify errors, and suggest sensible improvements.

Examples in context

Example 1. A titration. In an acid-alkali titration, accurate readings of the burette and repeating until concordant (close) results are obtained give a reliable mean titre, showing precision and accuracy together.

Example 2. Measuring density. Measuring an irregular solid's volume by displacement and its mass on a balance, then using density equals mass over volume, tests careful measurement and the right choice of equipment.

Try this

Q1. Define the independent variable. [1 mark]

  • Cue. The variable you deliberately change.

Q2. State one way to reduce a random error. [1 mark]

  • Cue. Repeat the measurement and take a mean.

Q3. What is an anomalous result, and what should you do with it? [2 marks]

  • Cue. A result that does not fit the pattern; identify it and leave it out of the mean.

Exam-style practice questions

Practice questions written in the style of CCEA exam questions on this dot point, with worked answer explainers. The year tag is the paper they imitate, not the source.

CCEA-style4 marksA student investigates how the rate of reaction depends on temperature. Identify the independent, dependent and one control variable, and state one way to make the results more reliable.
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Independent variable (the one changed): the temperature.

Dependent variable (the one measured): the rate (for example the volume of gas in a fixed time, or the time taken).

A control variable (kept the same): the concentration and volume of the acid, or the mass and surface area of the solid.

To improve reliability: repeat each temperature and take a mean (and remove any anomalous results).

Markers reward temperature as independent, the rate measure as dependent, a valid control variable, and repeating and averaging for reliability.

CCEA-style3 marksExplain the difference between an accurate result and a precise result, and state one way to reduce a random error.
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An accurate result is close to the true value.

A precise result is one where repeats are close together (little spread), whether or not they are accurate.

To reduce a random error: repeat the measurement and take a mean (or use more sensitive measuring equipment).

Markers reward accurate as close to the true value, precise as repeats close together, and repeating and averaging to reduce random error.

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