Let's learn about the method of qualitative observations and the types of observations, then look at some helpful examples.
While data from an experiment is structured and assumes a form that provides for easy data analysis, observation data can adopt as many forms as can be perceived by the researcher.
There are qualitative and quantitative observations. A quantitative observation can involve measurements of the numerical value of observed phenomena (e.g., the size of a crowd or the weight of an object). The quantitative data collected from such an observation might be helpful for a statistical research study in contexts where the theory is already established and needs confirmation or critique.
On the other hand, a qualitative observation adopts a naturalistic inquiry to understand a phenomenon whose attributes may not be quantified. Qualitative researchers might be more interested in capturing data about the physical appearance of certain people, the sounds of a particular event, or the feel of a specific texture in building materials.
To understand qualitative observation, let's list some contexts where qualitative researchers conduct observational research.
This method deals with many different topics, including:
Direct observation is ideal for these sorts of inquiries, as experimental or quantitative research cannot capture the sort of rich data found in a natural environment.
This means that qualitative observation often requires more than textual description. For example, when a researcher wants to compare how supporters of a particular sports team might interact with other fans, they may want to document different styles of clothing or the sounds and images associated with each sports team.
In such cases, the researcher will want to employ a data collection method that documents video, audio, and images for later discussion. An especially illustrative picture collected for this study can provide a helpful example to research audiences of the culture being discussed.
Here are several examples to consider:
Often, a textual description of each example may only give you basic insights about each experience.
However, imagine what sensory information you might need to fully understand the experiences in each example in this list.
Consider the following sentence:
"The people in the train station walked to the track leading to their destination."
This provides some surface details, but is it deep enough for readers to feel the experience?
The researcher's role in this case is to observe these contexts and, later on, immerse the research audience with the sensory data from those situations:
In contrast with typical experimental research, observing has several important traits to consider.
There is no one qualitative observation definition as it can take on many forms. Generally, there are no right or wrong answers regarding how to observe.
While the different types of qualitative observation may differ in how the researcher engages participants, the process in which they gather data for sensory information is largely the same.
A researcher can observe from afar and take notes about the sensory information they receive.
This is the simplest method that a researcher can employ. People may also see this method as the most objective as it removes the researcher from the environment altogether.
This kind of qualitative observation relies on the researchers gathering information through participation and reporting on their personal experiences within a given context.
Unlike naturalistic observation, where the researcher can be a complete observer, active participation can collect information about a cultural process or ritual whose essence can only be understood firsthand.
In a complete participant observation, researchers can also ask direct questions to those they observe to gather their perspectives about the process in which they participate. This allows observers to view a culture's characteristics from different angles, rather than rely on one subjective view alone.
In a structured qualitative observation, the researcher isolates their research participants to elicit and observe a certain set of behavioral responses.
For example, a researcher may provide children with some toys in a room to see how they will respond.
Structured observation may also be useful for quantitative observation, especially if the research inquiry relies on observing quantifiable phenomena that might be easier to capture in a controlled setting. Either way, observing people in this manner may not capture the natural part of interactions and behaviors that might exist in a natural environment.
All qualitative observation can be time-consuming, but longitudinal observation can involve the researcher in several weeks or months of study. Examples of qualitative observation that are necessarily longitudinal include studies of academic performance over time, quality of life in palliative care, and impacts of climate change on communities.
These inquiries not only identify examples of phenomena in discrete moments but also across long periods. Researchers conducting qualitative observation over a longitudinal scale should be prepared to observe changes in participants that are otherwise invisible at any particular moment in a study.
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While this may not necessarily sound scientific, qualitative observation can provide many an example of the characteristics of sensory phenomena that may not be available in a basic, textual description of research.
ATLAS.ti is especially useful for analysis of qualitative observation data. Qualitative data can take on many different formats from plain text to video files to PDF documents. This is especially important when the qualitative observation method relies on the five senses for qualitative data collection.
In Document Manager, researchers can create projects in ATLAS.ti to store all of their various project-related files for easy and efficient analysis later.
One of the most common critiques of qualitative observation is that it generates subjective data, given that subjective methods are employed to gather data and can be limited by personal bias. When discussing qualitative observations, the researcher should take care to acknowledge and express their own biases to their research audiences to establish transparency in the research study and data they present.
Readers of observation research benefit from understanding how the researcher views the context they observe, the attributes of the phenomenon they see, and the thought process they adopt to describe the findings in their study. This requires providing the audience with a clear definition of the phenomenon they want to describe as well as a detailed accounting of what the researcher assumes about the phenomenon.
Typically, data analysis of qualitative observation is based on inductive reasoning aimed at developing theories for completely unknown or largely unknown phenomena. This is different from quantitative observation or experimental research that seeks to confirm existing theory and whose methods seek to identify trends or provide the right or wrong answer to a research inquiry.
Theoretical development places equal importance to both qualitative research and quantitative research. However, the theory generated from qualitative observation can be strengthened through quantitative or experimental research by conducting further qualitative observation in another context to mitigate the subjective nature or any individual study.