Research Methods

• Types of experimental methods

  • field
  • laboratory
  • quasi
  • natural
• Aims

  General statement made by the researcher which tells us what they plan on investigating, the purpose of their study. Developed from theories/similar research.
• Hypotheses

  A precise statement which clearly states the relationship between the variables being investigated. Either non-directional or directional.
• Independent variable

  The aspect of the experiment which has been manipulated by the researcher or changes naturally to have an effect on the DV.
• Dependent variable

  The aspect of the study which is measured by the researcher and has been caused by a change of IV. All other variables that could affect the DV should be carefully controlled so that the researcher is able to confidently conclude that the effect on the DV was caused by only the IV.
• Operationalisation of variables

  Refers to the act of a researcher clearly defining the variables in terms of how they are being measured. The hypotheses should also show this operationalisation.
• Control of variables

  In an experiment, the only aspect that should affect the DV is the IV. Any other variable should be removed from the experiment or well controlled.
• Extraneous variables

  Any other variable that is not the IV which affects the DV. Examples are the age of participants.
• Confounding variable

  Confounding variables do change systematically with the IV. These make it difficult for the researcher to be sure of the origin of the impact of the DV as the confounding variable could have been the cause. An example would be the time of day the experimental task is done.
• Demand characteristics

  Refers to any cue that the researcher or the situation may give which makes the participant feel like they can guess the aim of the investigation. This can cause the participant to act differently within the research situation. Decreases the validity.
• Investigator effects

  Any unwanted influence from the researcher's behaviour, either conscious or unconscious, on the DV. This includes the design of the study, the selection of participants and the interaction with each participant during the research investigation.
• Randomisation

  The use of chance to reduce the effects of bias from investigator effects. This can be done for the design of materials, deciding the order of conditions, the selection of participants.
• Standardisation

  The exact same formalised procedures and instructions for every single participant involved in the research process. This allows for elimination of non-standardised instructions as being possible extraneous variables.
• Laboratory experiment

  • Takes place in a special environment whereby different variables can be controlled.
  • high degree of control, easy to replicate
  • experimenter's bias, low ecological validity
• Field experiment

  • An experiment conducted in a more natural environment, not in a lab but with variables still being well controlled
  • Naturalistic, more natural behaviours occur, controlled IV
  • Ethical considerations, invasion of privacy, loss of control over extraneous variables hence precise replication not possible
• Quasi experiment

  An experiment whereby the IV has not been determined by the researcher, instead it naturally exists.

  • controlled conditions, high internal validity
  • cannot randomly allocate participants to conditions, may be confounding variables present
• Natural experiment

  An experiment in which the IV is not brought about by the researcher hence would have happened if the researcher was not there. For example, studying reactions to earthquakes.

  • high external validity, dealing with real life issues
  • naturally occurring events, may be rare so unlikely to replicate, very difficult to randomise
• Sampling

  The population is a group of people from whom the sample is drawn.
• Opportunity sampling

  Participants happen to be available at the time which the study is being carried out so are recruited conveniently.

  • time saving and less costly
  • not representative of the whole population, lacks generalisability
  • researcher bias, control who they want to select
• Random sampling

  All the members of the population have the same equal chance of being selected. Uses a random number table or number generator.

  • no researcher bias
  • time consuming
  • volunteer bias - participants can refuse to take part so can end up with unrepresentative sample
• Systematic sampling

  A predetermined system is used whereby every nth member is selected from the sampling frame.

  • Avoids researcher bias and usually fairly representative
  • not truly unbiased unless you use a random number generator and then start the systematic sample
• Stratified sampling

  The composition of the sample reflects the varying proportions of people in particular subgroups (strata) within the wider population. Firstly you identify strat. Then you calculate the required proportion needed for each stratum based on the target population. Then select at random from each stratum using a random selection method.
• Stratified sampling

  • no researcher bias - selection is done randomly
  • produces representative data due to the proportional strata, generalisation possible
  • time consuming to identify strata and contact people from each
  • identified strata cannot reflect all the differences between the people of the wider population
• Volunteer sampling

  Involves self selection whereby the participant offers to take part either in response to an advert or when asked to.

  • Quick access to willing participants, makes it easy and not time consuming
  • Participants are more likely to cooperate in the study
  • Volunteer bias, the study may attract a particular profile of a person
  • Motivations like money may cause participants to not take the study seriously
• Experimental design

  • independent groups
  • repeated measures
  • matched pairs
• Independent groups

  The participants only perform in one condition of the IV.

  • no order effects, reduced risk of demand characteristics
  • no control over participant variables
  • more participants needed
  • random allocation may solve participant variables
• Repeated measures

  The same participants take part in all conditions of the IV.

  • eliminates participants variables
  • fewer participants needed
  • order effects presented eg boredom
  • counterbalancing may solve
• Matched pairs

  Pairs of participants are first matched on some variable that has been found to affect the DV. One member of each pair does one condition, the other does another.

  • no order effects
  • reduced risk of demand characteristics
  • time consuming
  • large pool of potential participants needed
• Pilot studies

  Small scale version of an investigation which is done before the real investigation is undertaken. They are carried out to allow potential problems of the study to be identified and the procedure is to be modified to deal with these.
• Single-blind procedure

  A research method in which the researchers do not tell the participants if they are being given a test treatment or control treatment. Avoids demand characteristics.
• Double-blind procedure

  Neither the participants nor the experimenter knows who is receiving a particular treatment. Used to prevent bias is research results due to demand characteristics or placebo effects. Reduces investigator effects as the investigator is unable to unconsciously give clues to what condition they're in.
• Observational techniques

  • naturalistic
  • controlled
  • overt
  • covert
  • participant
  • non-participant
• Naturalistic observation

  Watching and recording behaviour in the setting where it would normally take place.

  • high ecological validity, high external validity
  • low ecological validity IF participants become aware that they're being watched
  • difficult to replicate
  • uncontrolled confounding and extraneous variables are present
• Controlled observation

  Watching and recording behaviour in a structured environment eg lab.

  • more control over extraneous variables
  • easy replication
  • more likely to be observing unnatural behaviour
  • low mundane realism so low ecological validity
  • demand characteristics presented
• Overt observation

  Participants know that their behaviour is recorded and watched.

  • ethically acceptable as informed consent is given
  • more likely to be recording unnatural behaviour
  • demand characteristics present
• Covert observation

  The participants are unaware that their behaviour is being watched and recorded.

  • Natural behaviour, high internal validity
  • Reduced demand characteristics
  • Ethical issues, no informed consent and invasion of privacy
• Participant observation

  The researcher who is observing is part of the group that is being observed.

  • More insightful, increased validity
  • Researcher may lose objectivity as may start to identify too strongly with the participants
• Non-participant observation

  The researcher observes from a distance so is not part of the group being observed.

  • Researcher can be more objective as less likely to identify with participants
  • Open to observer bias
  • May lose valuable insight
• Observational designs

  • Unstructured
  • Structured
• Unstructured observational design

  Consists of continuous recording where the researcher writes everything they see during the observation.

  • more richness and depth of detail
  • qualitative data, more difficult to record/analyse
  • greater risk of observer bias