Experimental methods

• aims = what the researcher intends to investigate
• hypothesis = a statement of what the researcher believes to be true
• operationalised = clearly defined and measurable
• Directional hypothesis:

  • states whether the changes are greater/less, positive or negative etc (states the kind of difference you are expecting)
• Non-directional hypothesis:

  • doesn't state direction/kind of difference expected
  • simply states that there is a difference
  • used when there is no theory/previous research or it is contradictory
• Independent variable = what is manipulated by the experimenter in order to impact the dependent variable
• Dependent variable = what the experimenter measures
• Extraneous variables:

  • any variable, other than the IV that may have an effect on the DV if it is not controlled
• Confounding variables:

  • change systematically with the IV so we cannot be sure if any observed change in the DV is due to the CV or the IV
  • e.g. previous knowledge in an experiment of effects of revision on grades
• Minimising the influence of EVs through:

  • randomisation
  • standardisation
• Demand characteristics refer to any cues given from the researcher or situation which may reveal the aim of the study and cause the participants to change their behaviour.
• Investigator effects: any effects of the investigator's behaviour on the outcome of the research (the DV) and also on design decisions.
• Randomisation: the use of chance when designing investigations to control the effects of bias
• Standardisation: using exactly the same formalised procedures for all participants in a research study, otherwise differences become EVs
• Pilot studies = small-scale trial runs of investigations which test the research before the real study to give the opportunity to modify the design
• Control groups (independent groups design) and control conditions (repeated measures design) are used to enable comparison. Both help to establish causation.
• Single blind trials - a participant doesn't know the aims of the study so that demand characteristics are reduced
• Double blind - both the participant and the researcher don't know the aims of the study so that demand characteristics and investigator effects are reduced
• Independent groups: each participant is tested in only one condition. Participants are randomly allocated to conditions. This removes participant bias as each participant has the same chance of being in either condition.
• Independent groups: advantage

  • NO order effects
  • reduced chance of demand characteristics so increases chance of more 'natural' behaviour - higher realism

  This is because all participants are only taking part in one condition
• Independent groups: disadvantage

  • no control of participant variables - differences between conditions may be caused by using different people rather than the IV. This acts as an EV/CV.
  • less economical as the study will need twice as many participants as needed in a repeated measures design in order to achieve the same data. More time spent recruiting = more expensive
• Repeated measures: same participants used in all conditions. In order to avoid order effects, the order of conditions should be counterbalanced.
• Repeated measures: advantage

  • participant variables are eliminated as each participant in both conditions has the same characteristics. This controls an important CV.
  • Fewer participants are needed than in independent groups and therefore less time is spent recruiting participants, also less costly
• Repeated measures: disadvantage

  • Order effects occur due to factors such as practice and fatigue. This reduces the validity of the results
  • Increased chance of demand characteristics as ppts may guess the aims and change their behaviour. This may reduce validity of results
• In repeated measures, counterbalancing means that the participant sample is divided in half, with one half completing the two conditions in one order and the other half completing the conditions in the reverse order

  Order effects can also be controlled through randomisation (e.g. material for experiments is presented in a random order)
• Matched pairs: participants are matched as closely as possible with another participant (paired on participant variables that are relevant to the experiment). One member of each pair is randomly allocated to one or other condition.
• Matched pairs: advantage

  • no order effects as participants are only tested once - enhances validity of results
  • able to control participant variables as participants are matched on a variable that is relevant to the experiment - enhances validity of results
• Matched pairs: disadvantage:

  • time consuming to match participants exactly and need twice as many ppts as repeated measures. more time= more expensive
• Laboratory experiments: controlled experiments where extraneous and confounding variables can be controlled. Independent variable is manipulated by researcher, DV is measured.
• Lab experiment: strengths

  • Precise control of EVs and CVs means that their effect on the DV can be minimised. This means researchers can be confident that the IV has caused the change in the DV, high internal validity
  • Easier to replicate as greater control means less chance of new EVs. This means findings can be confirmed, supporting their validity.
• Lab experiment: limitation

  • may lack generalisability as the controlled lab environment may be artificial, making ppts aware that they're being studied. Therefore, behaviour may not be natural, meaning it cannot be generalised to everyday life (low external validity)
  • increased chance of demand characteristics as there are cues in the experimental situation that may encourage ppts to behave differently. This means that the findings may be explained by these cues rather than the effect of the IV - low internal validity
• Field experiment: conducted in a natural setting, researcher finds participants, IV is manipulated, effect on DV is recorded.
• Field experiment: strengths

  1. More natural environment means that participants are more comfortable which makes their behaviour more authentic. This means that results may be more generalisable to everyday life
  2. Participants are unaware that they're being studied. This means they're more likely to behave normally so findings can be generalised. This gives the study greater external validity
• Field experiments: limitations

  1. More difficult to control CVs/EVs. This means that observed changes in the DV may not be due to the IV, but do the the CVs/EVs. This makes it more difficult to establish cause and effect than in the lab.
  2. Ethical issues, particularly informed consent as participants in a field experiment cannot give informed consent. This is an invasion of people's privacy, which raises ethical issues.
• Natural experiment: experimenter does not manipulate the IV, the IV would have varied even without the experimenter present. DV may be naturally occurring (e.g. exam results)
• Natural experiments: strengths

  • may be the only practical/ethical option as it may be unethical to manipulate the IV. A natural experiment may be the only way to remain ethical when researching certain topics.
  • Greater external validity as natural experiments involve real-world issues . This means the findings are more relevant to real experiences.
• Natural experiments: limitation

  1. The natural event may only occur rarely as many natural events are 'one-offs'. This reduces the opportunity for research. This may limit the generalisations of the findings that can be made for other situations
  2. Participants aren't randomly allocated. This means the experimenter has no control over which participants are placed in which condition as the IV is pre-existing. This may result in CVs that aren't controlled.
• Quasi-experiments: based on a pre-existing difference between people e.g. age. No one has manipulated this variable. DV may be naturally occuring or may be devised by the experimenter.
• Quasi-experiments: strengths

  • high control - often carried out under controlled conditions and therefore shares some of the strengths of lab studies. This means replication is possible
  • Comparisons can be made between people as the IV is a difference between people. This means comparisons between different types of people can be made.
• Quasi-experiments: limitations

  • participants aren't randomly allocated. The experimenter has no control over which ppts are placed in which condition as the IV is pre-existing. Therefore, participant variables may have caused the change in the DV, acting as a CV.
  • casual relationships aren't demonstrated as the researcher does not manipulate/control the IV. This means we cannot say for certain that any change in the DV was due to the IV