Observational studies
What are observational studies?
Observational studies simply involve watching and recording people’s behaviour
Issues in the design of observations
One of the key influences on the design of any observation is how the researcher intends to
record their data
How do you record people’s behaviour?
o A scoring system (rating a teacher’s level of discipline)
o A check lift of criteria (checking how many certain behaviours an autistic child
displays)
o Keeping a tally (counting the number of times a doll is picked up by a girl or a boy)
This is an example of event sampling
- Making notes
- Video recording
What type of data is produced?
Structured observations
If structured observations are carried out (coding systems, check lists) then quantitative
data can be produced
Strengths
o Quantitative data is numerical, which means that analysing and comparing the
behaviour observed between participants is more straightforward
Unstructured observations
When researchers simply describe what they see this produces more qualitative data
Strengths
o More richness and depth of detail in the data collected
Limitations
o Qualitative data may be much more difficult to record and analyse
o There may be a greater risk of observer bias which unstructured observations
Why is this a limitation?
Objective behavioural categories are not prese t
The researcher may only record those behaviours that “catch their eye” and
these may not be the most important of useful
, Observational design – behavioural categories
In order to produce a more structured record of what a researcher sees or heads, it is first
necessary to break the target behaviour up into a set of behavioural categories
What are behavioural categories?
Before the observation begins the target, behaviour is precisely defined (properly
operationalised) and broken into components within the behavioural checklists (all of the
ways in which the target behaviour may occur) that are observable and measurable
Example?
To target behaviour “affection” may be broken down into observational categories such as:
o Hugging
o Kissing
o Smiling
o Holding hands
Evaluation
Strengths
The use of behaviour categories can make data collection more structured increasing
objectivity
Behavioural categories must be observable, measurable, and self-evident – (not
require further interpretation)
Why is this a strength?
Clear criteria increases reliability and aids recording of observations
Limitations
Researchers should also ensure that all possible forms of the target behaviour are
included in the checklist
There should not be a “dustbin’ category in which many different categories are
deposited.
Categories should be exclusive and not overlap
“smiling vs grinning- hard to discern”
Why is this a limitation?
If categories are not operationalised well, or are overlapping or absent, different
observers have to make their own judgements of what to record where and may
well end up with differing judgements and inconsistent records.
What are observational studies?
Observational studies simply involve watching and recording people’s behaviour
Issues in the design of observations
One of the key influences on the design of any observation is how the researcher intends to
record their data
How do you record people’s behaviour?
o A scoring system (rating a teacher’s level of discipline)
o A check lift of criteria (checking how many certain behaviours an autistic child
displays)
o Keeping a tally (counting the number of times a doll is picked up by a girl or a boy)
This is an example of event sampling
- Making notes
- Video recording
What type of data is produced?
Structured observations
If structured observations are carried out (coding systems, check lists) then quantitative
data can be produced
Strengths
o Quantitative data is numerical, which means that analysing and comparing the
behaviour observed between participants is more straightforward
Unstructured observations
When researchers simply describe what they see this produces more qualitative data
Strengths
o More richness and depth of detail in the data collected
Limitations
o Qualitative data may be much more difficult to record and analyse
o There may be a greater risk of observer bias which unstructured observations
Why is this a limitation?
Objective behavioural categories are not prese t
The researcher may only record those behaviours that “catch their eye” and
these may not be the most important of useful
, Observational design – behavioural categories
In order to produce a more structured record of what a researcher sees or heads, it is first
necessary to break the target behaviour up into a set of behavioural categories
What are behavioural categories?
Before the observation begins the target, behaviour is precisely defined (properly
operationalised) and broken into components within the behavioural checklists (all of the
ways in which the target behaviour may occur) that are observable and measurable
Example?
To target behaviour “affection” may be broken down into observational categories such as:
o Hugging
o Kissing
o Smiling
o Holding hands
Evaluation
Strengths
The use of behaviour categories can make data collection more structured increasing
objectivity
Behavioural categories must be observable, measurable, and self-evident – (not
require further interpretation)
Why is this a strength?
Clear criteria increases reliability and aids recording of observations
Limitations
Researchers should also ensure that all possible forms of the target behaviour are
included in the checklist
There should not be a “dustbin’ category in which many different categories are
deposited.
Categories should be exclusive and not overlap
“smiling vs grinning- hard to discern”
Why is this a limitation?
If categories are not operationalised well, or are overlapping or absent, different
observers have to make their own judgements of what to record where and may
well end up with differing judgements and inconsistent records.
