research design

• Lab Condition/Experiment


  A research method in which there is an IV, a DV and strict controls. It looks for a causal relationship and is conducted in a setting that is not in the usual environment for that behaviour.
• Experimental Design


  The way in which participants are allocated to levels of the IV
• Independent Measures Design


  An experimental design in which a different group of participants is used for each levels of the IV
• Repeated Measures Design


  Each participant performs in every level of the IV (reduces individual differences)
• Participant Variables


  Individual differences between participants (age, sex etc.) that could affect their behaviour in a study
• Demand Characteristics


  Features of the experiment that might give away the aim. This can cause participants to change their behaviours (to match what they think they should do). Reduces validity.
• Random Allocation


  Reduces the effect of confounding factors (e.g. individual differences). Participants are put in each level of the IV such that each person has an equal chance of being in any condition.
• Order effect


  Consequences of participating in the same experiment more than once:
• Practice Effect


  Performance improves because they experience the task more than once (familiarity/learning)
• Fatigue Effect


  Performance declines because they experience the task more than once (boredom/tiredness)
• Counterbalancing


  Overcomes order effect in repeated measures design. Each possible order of levels of the IV is performed by a different sub-group. Also described as ABBA design (as one group does A&B, other group does B&A)
• Matched Pairs Design


  Participants arranged into pairs, similar in ways that are important to the study. 1 member of each pair performs different levels of the IV.
• Standardisation


  Keeping the procedure exactly the same for each participant - ensures any difference in DV is due to IV, not conditions.
• Reliability


  The extent to which a procedure, task or measure is consistent, for example that it would produce the same results with the same people on every occasion.
• Experimental Designs


  • Independent Measures Design
  • Repeated Measures Design
  • Matched Pairs Design
• Repeated Measures Design


  1. Same group of people participate in every level of the IV

  2. Counterbalancing to reduce order effect

  3. Fewer participants needed
• Advantages of Repeated Measures Design

  Participant variables less likely to distort results
• Disadvantages of Repeated Measures Design

  • Order effect (practice/fatigue) could affect results
  • Participants more likely to spot demand characteristics as seeing both IVs
• Independent Measures Design


  1. A separate group of participants is used for each experiment condition

  2. Random allocation could reduce effects of individual differences
• Advantages of Independent Measures Design

  • Different participants used so no order effects
  • Participants only do experiment once, so no effect of demand characteristics
• Disadvantages of Independent Measures Design

  • Important individual differences could distort results
  • More participants needed - less effective as difficult to find
• Matched Pairs Design


  1. Participants matched into pairs who are similar (e.g. age, gender, intelligence)

  2. Each of the pair then participates in each level of the IV
• Advantages of Matched Pairs Design

  • Participants only see 1 level - reduces effect of demand characteristics
  • Individual differences are matched (as much as possible) so participant variables less likely
  • No order effects
• Disadvantages of Matched Pairs Design

  • Similarity is limited - participants must be carefully screened
  • Small sample size as matching is difficult