Observational design

• structured

  • allow researcher to quantify observations using a pre determined list of behaviours and sampling methods
  • data produced likely to be numerical and quantitative - straight forward analysing and comparing behaviour observed between participants
• unstructured

  • researcher writes down everything they see
  • tends to produce accounts of behaviour that are rich in detail
  • method appropriate when observations are small scale and involve few participants
  • qualitative data - difficult to analyse
  • observer bias risk
• behavioural categories

  • when a target behaviour is broken up into components that are observable and measurable
  • researcher needs to involve all the ways in which the target behaviour may occur within their behavioural categories
  • data collection more objective and structured
  • make sure categories are unambiguous - should not require further interpretation
  • categories should be exclusive and should not overlap
• event sampling

  • counting the number of times a behaviour occurs in a target group or individual
  • useful when the target population or event happens frequently and could be missed if time sampling was used
  • however if the event is too complex the observer may overlook important details
• time sampling

  • recording behaviour within a pre established time frame
  • effective in reducing the number of observations that have to be made
  • however the instances when behaviour is sampled might be unrepresentative of the whole observation