5. Experimental desgin

Experimental design

The way participants are allocated to the different conditions of an experiment.

Independent groups design (independent measures)

Different participants take part in each condition of the experiment.

Repeated measures design

The same participants take part in all conditions of the experiment.

Matched pairs design

Participants are matched on key characteristics and one from each pair is allocated to each condition randomly (both participants from the pair can be put into a hat and the first one picked out can be put into group B and the second can be put into group A .

Order effects

Changes in performance caused by the order of conditions, such as practice, boredom or fatigue effects.

Participant variables

Individual differences between participants, such as intelligence or motivation, that may affect results.

Random allocation

Using chance to decide which participants take part in each condition of an experiment.

Counterbalancing

An attempt to control order effects by changing the order in which participants experience conditions.

Independent groups – Strength

Avoids order effects because participants only take part in one condition.

Independent groups – Strength

Less chance of demand characteristics as participants are unaware of other conditions.

Independent groups – Weakness

Participant variables may affect results as different people are used in each condition.

Independent groups – Weakness

Requires more participants, which can be time-consuming and costly.

Repeated Measures Design – Evaluation

Repeated measures – Strength

Controls participant variables because the same participants are used in all conditions.

Repeated measures – Strength

Requires fewer participants, making the study quicker and more economical.

Repeated measures – Weakness

Order effects such as practice or fatigue may affect performance.

Repeated measures – Weakness

Demand characteristics may occur because participants may guess the aim of the study.

Matched pairs – Strength

Reduces participant variables by matching participants on important characteristics.

Matched pairs – Strength

Avoids order effects as participants only take part in one condition.

Matched pairs – Weakness

Matching participants accurately is time-consuming and difficult.

Matched pairs – Weakness

Individual differences may still exist if matching is not exact.

How to avoid order effects

• Have a longer period of time between tests

• Use another design such as independent design or matches pairs

• Use counterbalancing so participants experience conditions in a different order.

How to avoid participant variables

• Use repeated measures or matched pairs designs

• Randomly allocate participants to conditions.

Random allocation – Effectiveness

Reduces the impact of participant variables by spreading individual differences evenly across conditions.

Counterbalancing – Effectiveness

Reduces practice and fatigue effects, improving internal validity.

Counterbalancing – Definition

Changing the order of conditions so that different participants complete conditions in a different sequence.

ABBA counterbalancing

One group completes condition A then B, and another completes condition B then A.

Counterbalancing – Strength

Controls order effects, increasing internal validity.

Counterbalancing – Weakness

Does not eliminate all order effects, especially if the effects are permanent.