What is Observational Research?
Observational research (or field research) is a type of correlational (i.e., non-experimental) research in which a researcher observes ongoing behavior.
There are a variety of types of observational research, each of which has both strengths and weaknesses. These types are organized below by the extent to which an experimenter intrudes upon or controls the environment.
Observational research is particularly prevalent in the social sciences and in marketing.
Observational research is a social research technique that involves the direct observation of phenomena in their natural setting. This differentiates it from experimental research in which a quasi-artificial environment is created to control for spurious factors, and where at least one of the variables is manipulated as part of the experiment.
Observational research is typically divided into naturalistic (or “nonparticipant”) observation, and participant observation.
Case studies and archival research are special types of observational research.
Naturalistic (or nonparticipant) observation has no intervention by a researcher. It is simply studying behaviors that occur naturally in natural contexts, unlike the artificial environment of a controlled laboratory setting. Importantly, in naturalistic observation, there is no attempt to manipulate variables. It permits measuring what behavior is really like. However, its typical limitations consist in its incapability exploring the actual causes of behaviors, and the impossibility to determine if a given observation is truly representative of what normally occurs.
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In participant observation, the researcher intervenes in the environment. Most commonly, this refers to inserting himself/herself as a member of a group, aimed at observing behavior that otherwise would not be accessible. Also, behaviors remain relatively natural, thereby giving the measurements high external validity.
Case Studies are a type of observational research that involve a thorough descriptive analysis of a single individual, group, or event.
They can be designed along the lines of both nonparticipant and participant observation. Both approaches create new data, while archival research involves the analysis of data that already exist. A hypothesis is generated and then tested by analyzing data that have already been collected.
This is a useful approach when one has access to large amounts of information collected over long periods of time. Such databases are available, for example, in longitudinal research that collects information from the same individuals over many years.
Special qualitative analysis software tools like ATLAS.ti help the researcher to catalog, penetrate and analyze the data generated (or, in archival research found) in a given research project.
All forms of observational or field research benefit extensively from the special capabilities of a dedicated data anlaysis tool like ATLAS.ti.