observational design

what are the different types of observational design

behavioural categories, event sampling, time sampling

what are behavioural categories?

list of specific predefined behaviours that an observer looks for and records during an observation

strength of behavioural categories- objectivity

promote objectivity and consistency in observational research- predefined list of what to look for, observers less likely to be influenced by bias/subjective interpretations so data more reliable and replicable

strength of behavioural categories- checklist

checklist allows for quantitative data collection- useful in structured observations- help to stay focused and organised

weakness of observational categories- rigid

too rigid- miss unanticipated yet important behaviours resulting in a loss of rich qualitative data

weakness of observational categories- simplification

process of defining behaviours in advance may cause oversimplification, may struggle to accurately identify and record behaviours in real time

what is event sampling?

researcher records specific behaviours every time they occur in the observation period

strengths of event sampling

- focus on specific relevant behaviours so data collection process more efficient and manageable

- high inter-observer reliability as behaviours clearly defined in advance

weakness of event sampling- context

may miss important contextual info/behaviours which happen outside the predefined categories, reducing richness and depth of data, may be observer overload leading to missed data, compromising validity of findings

weakness of event sampling- no data

may end up with little/no data if target behaviour doesn't occur during observation period

what is time sampling?

researcher records behaviours at specific time intervals

strengths of time sampling

- less time consuming and more manageable than continuous observation so observer focuses more effectively, improving accuracy and reliability of data

- observe over longer periods so easier to identify patterns/changes in behaviour over time, good if behaviour is frequent/ongoing

weakness of time sampling- missing behaviours

may miss important behaviours that occur between observation intervals- if a significant event happens after a time point it wont be recorded reducing validity of data- bad if studying infrequent/brief behaviours

weakness of time sampling- context

hard to understand full picture as may not capture context/sequence of behaviours so must carefully choose interval length to balance practicality with data richness