Experimental Designs

An independent measures design is where participants only take part  in one condition of the experiment

• This means that different participants will take part in each of the experimental conditions
• The two groups of participants in this type of experimental design will be exposed to one level of the IV only

Strengths:

• Higher validity as the results will not be affected by order effect because each participant will complete the task only once so sure that the outcome of the task is being measured.
• Results are less likely to be affected by demand characteristics as participants will complete the task only once so less likely to guess the aim so won't give expected responses so higher validity.

Weaknesses:

• Need twice as many pps which makes it less practical and more time consuming
• Results may be affected by ID which would be difficult to control so may lower validity.

• A repeated measures design is where participants take part in both (or all) conditions of the experiment
• One way of designing an experiment is to compare the performance of people in one condition with their own performance in another condition

Strengths:

• Fewer pps needed to gather all the data so it is more practical and quicker to create a conclusion about what is affecting behaviour
• Individual differences are controlled as each person is compared with themselves so higher in validity as you are sure that you are measuring the impact of the IV

Weaknesses:

• Results may be affected by demand characteristics as pps may guess the aim of the research is they are completing a similar task twice so they may act unnaturally which lowers validity as not measuring true behaviour
• Results may be affected by order effect as pps' performance can improve with practice so results may not be consistent making the outcomes less reliable

• A matched pairs design involves matching each participant in one of the experimental conditions as closely as possible to another pp in the second condition according to variables that are considered to be relevant to the experimental condition
• e.g pairs may be matched on age, gender, IQ or personality test

Strengths:

• Removes problems caused by order effect as different yet similar pps are used to complete tasks so results should be more consistent across pps making the results more reliable.
• Results are less likely to be affected by demand characteristics as pps will complete the experiment only once so they are less likely to guess the aim of the experiment so more valid.

Weaknesses:

• Need twice as many pps to collect data which makes it less practical and more time consuming
• Very difficult to get an exact match between pps so it could be more time consuming