research methods

• Demand characteristics


  A cue that makes participants unconsciously or consciously aware of the aims of the study or helps participants work out what the researcher expects to find
• Investigator effect


  Any effect of the investigators behaviour - conscious or unconscious - on the researcher outcome - the DV
• Standardisation


  Having the exact same procedure and instructions for each of the participants
• Randomisation


  Use of chance in order to control for the effects of bias when designing materials and deciding order of conditions
• Extraneous variables


  'Nuisance' variables that can affect the DV but does not vary systematically with the IV - make it more difficult to detect cause and effect
• Types of extraneous variables


  • Participant variables - something that varies among participants - fatigue
  • Situational variables - something that varies in the setting/situation — time given
• Confounding variables


  Variable that is NOT the IV but varies systematically with the IV and could be causing change in the DV - reduces validity
• Control


  The extent at which any variable is held constant or is regulated by a researcher
• Validity


  Refers to whether the observed effect is a genuine one
• Types of validity


  • Internal - the degree to which an observed effect was due to the experimental manipulation of the IV rather than other factors eg confounding variables
  • External - the degree to which a research finding can be generalised to other settings, groups of people or other time periods
• Bias


  Limits extent of generalisation - certain groups are over or under represented
• Generalisation


  Extent at which findings can be broadly applied to the population
• Reliability


  Consistency - finds the same results every time and its not a one-off
• Types of hypothesis


  • Directional - predicts the outcome of the experiment
  • Non-directional - simply states there will be a difference but doesn't state the outcome
  • Null - states that there will be no difference
• Research process


  1. Review previous research

  2. Decide on an aim and make hypothesis

  3. Design a study

  4. Conduct research

  5. Analyse and report findings

  6. Add to and revise theories
• Matched pairs design


  • Matching up participants based on a factor that may affect the DV such as age or IQ - then the pairs are put into different conditions
  • Attempts to control for confounding variable of participant variables

  Pros

  • some control
  • Demand characteristics not likely
  • No order effects - one condition

  Cons

  • participants can never be matched exactly
  • Time consuming to match everyone
  • If one participant drops out, the other has to as well
• Independent design


  • Participants only do one condition and are randomly allocated to one of them
  • Attempts to evenly distribute participant variables

  Pros

  • order effects are unlikely
  • demand characteristics are unlikely
  • Takes less time to conduct study

  Cons

  • poor control of participant variables
  • More people but less data
  • Participant variables may affect results
• Repeated measures design


  • All participants do all conditions
  • Uses counterbalancing to balance order effects - AB, BA - ensures internal validity

  Pros

  • participant variables are controlled because they do one condition
  • Fewer participants are needed

  Cons

  • order effects arise - boredom or fatigue on 2nd condition
  • Demand characteristics are more likely - guess aim
  • Experiment takes twice as long
• Types of experiment


  • Lab - performed in a controlled environment and the IV IS manipulated
  • Natural - the IV varies naturally, the experiment takes advantage of a pre-existing variable
  • Field - occurs in real world settings and the IV IS manipulated
  • Quasi - IV is based on an existing / naturally occurring difference or trait
• Types of sampling


  • Random
  • Opportunity
  • Stratified
  • Volunteer
  • Systematic
• Pilot study


  Small scale version of an investigation that takes place before the real thing
• Labexperiment


  Performed in a controlled environment and the IV IS manipulated

  Pros

  • replication is easier
  • High control over extraneous variables

  Cons

  • may lack generalisability because the environment may be artificial
  • Low external validity
  • Demand characteristics may arise
• Naturalexperiment


  The IV varies naturally, the experiment takes advantage of a pre-existing variable - usually an event that has occurred. - can be in a lab or natural environment

  Pros

  • allows research to take place that may be unethical otherwise

  Cons

  • event may happen rarely
  • May not be randomly allocated
• Fieldexperiment


  Occurs in real world settings and the IV IS manipulated

  Pros

  • higher mundane realism
  • More natural, valid and authentic

  Cons

  • ethical issues - do not know they are being observed - no consent is given
  • Less control over extraneous variables
• Quasiexperiment


  IV is based on an existing / naturally occurring difference or trait eg eye colour -no manipulation of the IV

  Pros

  • high external validity
  • Carried out under controlled conditions

  Cons

  • cannot randomly allocate participants - meaning extraneous variables may occur
• Randomsampling


  Obtain a list of everyone and give them a number and use a number generator or a hat to pick participants

  Pros

  • potentially unbiased
  • Confounding or extraneous variables should be equally divided
  • Good internal and external validity

  Cons

  • time consuming
  • Full list may be hard to obtain
  • Could still be unrepresentative
• Opportunitysampling


  Selecting people who are willing and available

  Pros

  • less costly in time and money

  Cons

  • unrepresentative - cannot be generalised
  • Researcher bias - has control over selection of participants
• Stratifiedsampling


  Identify categories eg age that make up a population and work out proportions needed for sample to be representative and participants are selected from strata using lottery technique

  Pros

  • representative sample - generalisation is possible

  Cons

  • cannot reflect all ways that people are different - complete representation is possible
• Volunteersampling


  Selecting themselves to be apart of a sample from an advert etc

  Pros

  • Easy
  • Less time consuming
  • More engaged participants

  Cons

  • volunteer bias is a problem
  • May attract a certain ‘profile’
• Systematicsampling


  Every nth member of target population - that is in alphabetical order

  Pros

  • objective - researcher has no influence

  Cons

  • time consuming
  • Participants may refuse to take part which makes it a volunteer sample
• Ethical issues


  Arise when a conflict between the rights of the participant in studies and the goal of the research to produce authentic, valid data
• Right to withdraw


  • Participants can stop participating if they feel uncomfortable
  • Participants have the right to refuse permission for the researcher to use their data
• Confidentiality


  Concerns the communication of personal information from one person to another, the trust that the info will be protected
• Informed consent


  Participants must be given comprehensive info concerning the nature and purpose of the research and their role in it - so they can make an informed decision on whether they want to participate
• How researchers deal with informed consent

  1. Participants should be given full details of the study - the aim of it and how the data will be used - only once they have this info they should be asked to formally indicate their agreement

  2. Presumptive consent - gained from a similar group, if they agree, consent of other group will be presumed

  3. Prior general - agreeing to be deceived, without knowing how
• problems with dealing with informed consent?

  Knowing the aim of the study can lead to participants not acting naturally so little value is learnt
• another problem with informed consent?

  There is no guarantee participants do actually understand what they are agreeing to
• Deception


  When the participant is not told the true aims of the experiment
• How researchers can deal with deception


  1. Avoid it if at all possible - especially when it is likely participants will object later

  2. Debrief participants after the study and give them a chance to withdraw their data

  3. Gain approval of ethics committee
• WHat problems can occur from deception?

  Debriefing doesn't stop participants feeling embarrassed or uncomfortable