observation techniques

• P observation (s = strength)

  observer is a P in the behaviour being observed

  s - provides special insights into behaviour, from 'inside' - P has a greater familiarity w what's likely to happen and see greater detail

  s - observer closer os can see + hear more

  w - objectivity decreased (observer bias) as familiarity w situation

  w - difficult to monitor behaviour unobtrusively
• Non-P observation

  Observer is not a P

  s - objectivity increased due to psychological + social distance

  s - observe unobtrusively so P's not self conscious and act naturally

  w - may misinterpret communication within group - reduce validity

  w - observer nay see less
• Structured observation

  some variables manipulated by researcher (eg in a lab)

  s - controlled environment so can focus on particular aspects of behaviour and draw conclusions

  s - possible to draw some tentative casual conclusions

  w - environment may feel unnatural and P doesn't behave normally so less ecological validity

  w - P may know they're being observed (eg in a lab) so she demand characteristics
• Naturalistic obsevation

  everything left as usual, unstructured environment

  s - realistic + natural behaviour

  s - useful method for new area o research - gives ideas of further investigations to be planned

  w - more likely to be covert - ethical issues

  w - if focus is too wide, difficult to draw conclusions
• Overt observation

  P aware of being observed

  s - avoids lack of informed consent because P's decide to participate

  s - observer doesn't have to hide - easier to see what's going on

  w - demand characteristics - alter behaviour when observed
• Covert observation

  P unaware of being observed

  s - P's behave more naturally

  w - ethical issues due to consent (but can give informed consent after or withdraw data - difficult)

  w - invasion of privacy - unethical to record people, even in public
• Event & time sampling

  e - draw up a lis of behavioural categories then tally every time each behaviour occurs in a specific time period

  t - count behaviours at regular intervals or take samples at diff times of day/month
• Event & time sampling eval

  s - Both make it more manageable

  s - event is useful when behaviour only happens occasionally (missing even reduces validity)

  s- time allows for tracking of time related changes to behaviour

  w - may not be representative if list of events isn't comprehensive

  w - time may reduce validity as some behaviours missed if occurs out of time interval
• Behavioural categories

  objective methods to separate continuous stream of action into components - counted

  s - enables systemic observation so important info not overlooked - increases validity

  s - categories can be tallied and conclusions drawn

  w - categories may not cover all possibilities - some behaviours not recorded, decreasing validity

  w - poor design of categories reduces reliability
• CONTENT analysis

  Changes to quantitative from qualitative eg tally everytime a theme occurs in a book
• Quantitative eval strengths

  As data comes from secondary sources such as articles or TV - doesn’t change. So other researchers can check if conclusions are correct (inter-rather relatability)

  Quantitative tallying of themes allows data to be statistically analysed (objective results)

  Unlikely to be ethical issues, usually involves analysing existing sources (eg content can be assumed to be gained by og researcher)
• Quantitative weakness

  Secondary data can be out of date or not relevant for the specific research which lowers validity