Understand experimental and research designs, including strengths and…

The idea

Experimental design dictates how participants are allocated to conditions. In an independent measures design, different participants are used in each condition (e.g., Group A drinks caffeine, Group B drinks water). This avoids order effects but introduces participant variables. A repeated measures design uses the same participants in all conditions. This eliminates participant variables and requires fewer people, but order effects like fatigue or practice can occur. A matched pairs design pairs participants based on key variables (e.g., memory ability) and assigns one from each pair to each condition. This reduces participant variables and avoids order effects, but it is time-consuming and exact matching is impossible.

What earns the marks

• Identifying the experimental design used in a given research scenario.
• Explaining one strength of independent measures, such as the absence of order effects.
• Explaining one weakness of repeated measures, such as the potential for practice or fatigue effects.
• Justifying the choice of a matched pairs design to control for specific participant variables.

Common mistakes and how to put them right

• Confusing independent measures with repeated measures.

  Put it right: 'independent' means separate groups of people, while 'repeated' means the same people repeat the conditions.

• Stating that matched pairs eliminates all participant variables.

  Put it right: State that it only reduces participant variables, as people can never be matched perfectly on every trait.

• Believing that order effects occur in independent measures designs.

  Put it right: Order effects only occur in repeated measures designs where participants take part in more than one condition.

Exam tips

• When evaluating an experimental design, always link the strength or weakness back to the specific context of the study provided in the stem.
• Use the term 'participant variables' rather than 'individual differences' when discussing the weaknesses of independent measures.
• If suggesting a matched pairs design, explicitly name the variable you would match participants on (e.g., age, IQ, or gender) relevant to the study.