Experimental Design

Cards (15)

  • Experimental design refers to the way in which participants are arranged within different experimental conditions.
  • Independent groups - participants are split into two groups and each only experience one level of IV.
  • Independent Groups Evaluation
    • No order effects - Participants are less likely to get bored, tired or guess the aim as they have only experienced one condition.
    • Participants can confound the results - random allocation is used to deal with this.
    • Less economical - 2 times as many participants are needed to achieved this compared to repeated measures.
  • Repeated measures - all participants experience all levels of IV and then the 2 mean scores from both conditions would be compared.
  • Repeated Measures Evaluation
    • Participant variables are being controlled because the same participants are in both conditions.
    • More economical then independent groups or matched pairs as half the amount of participants are needed.
    • Order effects can impact the results - task completed in one condition, could have an impact on the task completed in another.
    • Demand characteristics can also be an issue
  • Matched pairs - participants would be paired up based on a trait relevant to the study.
  • Matched Pairs Evaluation
    • Order effects and demand characteristics are less of an issue cause participants only take part in one condition.
    • Impact of participant variables are reduced, but can never be eliminated completely.
    • Less economical than other designs, especially if a pre-test is required.
  • Lab experiments are conducted in a highly controlled environment (not always a laboratory).
  • Lab Experiments Evaluation
    • High control of EVs and CVs - allows use to determine cause and effect.
    • Increase replicability.
    • Lack of realism can increase demand characteristics.
    • Low external validity/Lacks generalisability.
  • Field experiments - IV is still manipulated by the researcher, but in a natural, everyday setting.
  • Field Experiment Evaluation
    • Higher mundane realism
    • Higher external validity
    • Less control of EV and CV - cause and effect are harder established.
    • Ethical Issues - consent and privacy - if they don't know they are in an experiment how can they consent.
  • Quasi Experiment - IV is based on existing difference between. No one has manipulated this - it simply exists and cannot be changed. Eg; Age, Gender, Sex, Smokers ect.
  • Quasi Experiment Evaluation
    • Often carried out in controlled conditions
    • Confounding variables can occur as use random allocation to conditions is not possible.
  • Natural experiment - researcher has no control of IV and cannot change it. Would have occurred even if the experimenter was not studying it. IV is natural, not necessarily the setting. Eg; Natural disasters, system changes, technological development.
  • Natural Experiment Evaluation
    • Opportunities for research that may not be conducted otherwise - for practical or ethical reasons.
    • High external validity.
    • Research worthy events many only happen very rarely.
    • It may not be possible to randomly allocate participants to different conditions.