Observational design

• Structured observations are when researchers use a pre-determined list of behaviours and sampling methods to record behaviour systematically.

  • They are used for large samples and reliability.
• A strength of structured observations is that the data is easier to analyse and compare the behaviour between participants.

  • This is because it produces quantitative (numerical) data.
• Another strength of structured observations is that it has higher reliability.

  • Standardised behavioural categories mean multiple observers are more likely to agree (high inter-observer reliability).
• A weakness of structured observations is that they may reduce the richness and depth of data.

  • Some unexpected behaviours might be missed because they aren’t in the coding frame.
• Another weakness of structured observations is that behaviours may be over-simplified.

  • Categories may not capture the context or meaning behind behaviours.
• An unstructured observation is one where the researcher records all relevant behaviour with no pre-determined categories.

  • This is more appropriate to use when observations are small in scale and involve few participants.
• Strengths of unstructured observations:

  • Rich, qualitative data → Captures the full complexity and context of behaviour.
  • Allows for unexpected behaviours to be recorded.
• A weakness of unstructured observations is that they are difficult to analyse.

  • This is because they produce qualitative data which is harder to analyse and compare.
• Another weakness of unstructured observations is that they lower reliability.

  • Observers may only record behaviour that 'catch their eye' and these may not be the most important or useful - leads to observer bias.
  • Observers may focus on different behaviours, leading to inconsistency.
• Behavioural categories (behavioural checklists) are created before an observation to produce a structured record of what is observed.

  • It is when a target behaviour is broken down into specific, observable and measurable categories.
  • Ensures consistency and reduces subjectivity in recording data.
• Strengths of behavioural categories:

  • Increases objectivity and reliability → Ensures different observers record behaviours consistently.
  • Easier to analyse → Can quantify observations.
• Weaknesses of behavioural categories:

  • Categories may be too broad → Some behaviours may overlap
  • Some behaviours may be missed → If not included in the coding system, lowering the validity
• Continuous recording of behaviour is a key feature of unstructured observation in which all instances of a target behaviour are recorded.
• In structured observations, a systematic way of sampling observations is used. The two sampling techniques include event sampling and time sampling.
• Event sampling is when the observer records a specific behaviour every time it occurs in a target individual or group.
• A strength of event sampling is that it is useful when behaviours or events happen infrequently.

  • This ensures no important behaviours are missed.
• A weakness of event sampling is that if the behaviour happens too often or if it is too complex, it may be difficult to record accurately.

  • This means that important details may be missed, lowering the accuracy of the data.
• Time sampling is when observations are made at regular, pre-established time intervals.
• A strength of time sampling is that it is effective at reducing the amount of data recorded.

  • This makes it more manageable for the researcher.
• A weakness of time sampling is that it may miss important behaviours if they happen between observation intervals.

  • This makes the observation less representative and then less valid.