experimental design

• Experimental design - the different ways in which the testing of pps can be organised in relation to the experimental conditions
• Independent groups - Participants are allocated to different groups where they take part in only one condition of the independent variable
• Strengths of independent groups:

  • order effects are not a problem and so participants are less likely to guess the aim
  • You can also use the same materials across conditions because the pps are different
• Limitations of independent groups:

  • if a researcher finds a mean difference between the groups on the DV, this may be more to do with individual differences (participant variables) than the effects of the IV
  • it is less economical than repeated measures because you need twice as many participants to produce equivalent data
• Random allocation - an attempt to control for participant variables in independent groups design which ensures that each participant has the same chance of being in one condition as any other
• Repeated measures - All participants take part in all conditions of the independent variable
• Strengths of repeated measures:

  • no effect of participant variables as the pps are the same across all conditions
  • Fewer pps are needed
• Limitations of repeated measures:

  • order effects
• order effects -  each participant has to do at least two tasks and the order of these tasks may be significant. Being exposed to all conditions, pps can see what is changed between conditions and may guess the aim of the experiment and so order acts as a confounding variable (leads to demand characteristics). The order in which pps experience the conditions may affect their performance due to practice or fatigue
• Counterbalancing - an attempt to control for the effects of order in a repeated measures design. Half the pps experience the conditions in one order and the other half in the opposite order
• Matched pairs - All participants are paired on specific key variables relevant to the DV and then one person from each pair is put in each condition of the IV
• Strengths of matched pairs:

  •  minimises risk of order effects and demand characteristics
• Limitations of matched pairs:

  • although there is some attempt to reduce participant variables, matched pairs design can only match on variables known to be relevant to the experiment, there could be unknown variables of relevance which would remain unaccounted for as participants can never be matched exactly
  • Matching is also less economical as it can be time-consuming and expensive, especially if a pre-test is required