Experimental Designs

• Experimental Designs


  Refers to how participants are allocated to conditions within an experiment
• Main types of experimental designs


  • Repeated measures design
  • Independent measures design
  • Matched pairs design
• Independent Measures Design


  Experimental design where different participants are used in each condition of the independent variable
• Independent Measures Design


  • IV= Presence of television while completing homework
  • Condition 1: TV off, Group A 10 students
  • Condition 2: TV on, Group B 10 different students
  • DV: Number of correct answers on homework task
• Repeated Measures Design


  An experimental design where the same participants take part in each condition of the independent variable
• Repeated Measures Design


  • IV= Presence of television while completing homework
  • Condition 1: TV Off, Group A 10 students
  • Condition 2: TV ON, Group A same 10 students
  • DV: Number of correct answers on homework task
• Matched Pairs Design


  An experimental design where pairs of participants are matched in terms of key variables, such as age or socioeconomic status
• Matched Pairs Design


  • IV= Presence of television while completing homework
  • Condition 1: TV off, Group A 10 students
  • Condition 2: TV on, Group B 10 different students matched with Group A
  • DV: Number of correct answers on homework task
• Pros and Cons of Experimental Designs


  • Independent Measures: Participants only need to take part once, reduced participant bias, but different people = different results
  • Repeated Measures: Reduced likelihood of participant variables affecting results, fewer participants required, but order effects may be an issue
  • Matched Pairs: No order effects, can control for participant variables, but impossible to match people exactly, more work to match pairs
• Random Allocation to Conditions

  Randomly allocating participants to independent variable groups to avoid bias and limit the effects of participant variables
• Random allocation does not mean dividing up the group willy-nilly. It means using a mathematical approach to ensure each participant had an equal probability of ending up in each condition
• Order Effects


  When the order in which participants experience conditions has an effect on the results, such as practice effect or fatigue/boredom
• Counterbalancing


  A control for order effects often used in repeated measures designs where participants still do both conditions but in a different order
• Counterbalancing


  • Half participants do condition 1 then 2, and the other half do condition 2 then 1