Experiments: Experimental Design (AQA GCSE Psychology)

• Experimental design refers to how the participant sample is used in combination with the different levels of the independent variable (IV) e.g. if there are two conditions of the IV, the participants may experience both conditions or only one
• There are three main types of experimental design
  • Independent groups design 
  • Repeated measures design 
  • Matched pairs design 

• In an independent groups design participants only experience one condition of the IV e.g: 
  • Participant A learns a poem with music playing (condition 1)
  • Participant B learns the same poem in silence (condition 2)

• Participants are randomly allocated to each condition to avoid researcher bias  
• Independent groups design generates unrelated data (because the two groups are separate from one another)
• The performance of the group in condition 1 is compared to the performance of the group in condition 2, e.g:
• Participant A learns a poem with music playing (condition 1) and is asked to write down as much of the poem as they can recall in 5 minutes
• Participant B learns the same poem in silence (condition 2) and is asked to write down as much of the poem as they can recall in 5 minutes
• The dependent variable (DV) is measured as the number of words correctly recalled from the poem
• The number of words correctly recalled by participants in condition 1 is compared to the number of words correctly recalled by participants in condition 2

Evaluation of independent groups design

Strengths

• As the participants take part in only one condition there is no possibility that order effects could affect their performance in the task
• Participants are less likely to succumb to demand characteristics as they take part in only one condition i.e. they don’t get a ‘second bite of the cherry’ as it were

Weaknesses

• Individual differences/participant variables may interfere with the findings e.g. in a memory test one group may have naturally better memory than the other group (which could happen when participants are randomly allocated to conditions)
• More participants are required with this design which can sometimes be problematic

• In a repeated measures design participants experience all conditions of the IV e.g: 
• Participant A learns a poem with music playing (condition 1)
• Participant A learns a different poem in silence (condition 2)

• The same participants complete each of the experimental conditions
• Repeated measures design generates related data (because the two scores come from the same participant)
• Participants act as their own control group as their performance in condition 1 can be compared to their performance in condition 2, e.g:
• Participant A learns a poem with music playing (condition 1) and is asked to write down as much of the poem as they can recall in 5 minutes
• Participant A learns a different poem in silence (condition 2) and is asked to write down as much of the poem as they can recall in 5 minutes
• The dependent variable (DV) is measured as the number of words correctly recalled from the poem
• The number of words correctly recalled by the participant in condition 1 is compared to the number of words they correctly recalled in condition 2
• To avoid order effects researchers should use counterbalancing 

Dealing with order effects: Counterbalancing 

• Counterbalancing is relevant to repeated measures designs and is implemented as follows:
  • The researcher splits the participants in half e.g. 20 in one group, 20 in the other group
  • One group completes the conditions in this order: condition A followed by condition B
  • The other group completes the conditions in this order: condition B followed by condition A
• Counterbalancing is used to control for order effects (practice, fatigue, boredom)

Evaluation of repeated measures design

Strengths

• Individual differences/participant variables are not an issue with this type of design
• Fewer participants are required with this design 

Weaknesses

• As the participants take part in all conditions there is no possibility that order effects could affect their performance in the task
• Participants are more likely to succumb to demand characteristics as they take part in all conditions i.e. their go of a trial or task could give them a clue as to what is being tested/the study’s aim

• Participants (usually) achieve just one score as they (usually) only take part in one condition
• Participants are assessed and matched on the characteristic(s) that are important for the particular research they are taking part in, e.g. age, ethnicity, gender etc. 
• Often MZ (Monozygotic/ identical) twins are used for this design as they create the perfect matched pair (one twin can be assigned the experimental condition and the other twin the control condition)
• The matched participants are then randomly allocated to one condition each 
• As each participant is related to their pair this design produces related data, e.g:
  • In an experiment on the social learning of aggression, participants would be matched on a scale according to how aggressive they already are
    • Participant A who ranked 10 for aggression would be matched with Participant B who also ranked 10 for aggression 
    • Participant A takes part in condition 1 of the experiment; Participant B takes part in condition 2 of the experiment
  • This matching helps to factor out aggression as a possible confounding variable in the experiment i.e. any difference in scores should be due to the effect of the IV and not on natural aggression levels

Evaluation of matched pairs design

Strengths

• As participants take part in only one condition of the IV order effects are not an issue
• Matched pairs design is the only way of factoring out individual differences without using repeated measures (some experiments cannot use repeated measures due to the nature of the task) 

Weaknesses

• It is impossible to match participants absolutely 100% so that each is a mirror image of the other (even MZ twins have differences in personality, abilities etc.)
• This is the most problematic and time-consuming design (which is why it is rarely used by researchers)