Qualitative Research Basics: A Guide for Engineering Educators

It is a good habit to review one's data daily during collection to make sure raw notes are
edited into a form that will be usable even after time has dimmed the memory of the
actual experiences of the day. Expanded notes that add the detail that there was not time
enough to note while collecting data are written frequently by researchers in the pauses
between data collection activities during a study.
A second activity that needs to take place right from the start of data collection is data
storage and organization. Given the large volume of text that normally accrues from a
qualitative study, even the most casual researcher has to adopt structured habits for
labeling data in standard fashion (who, when, where, pagination, file name, and the like)
and keeping it safe (according to Human Subjects confidentiality agreements) and with
like pieces (such as in binders, electronic file folders or drives, or in labeled paper folders
in a locked file cabinet).
Reviewing and Selecting Data
As data accumulate, the more the researcher reviews them, the easier subsequent work
becomes. Some of the data collected in a qualitative study, especially the data collected in
the early period of a study before the focus was narrowed, will be peripheral to the main
research questions. Interview transcripts will contain whole pages that document times
when the interviewee strayed from the subject or digressed into an amusing but not
relevant memory. Field notes will often contain laborious descriptions of the actions of a
participant who later dropped out of the study. These data segments are candidates for
what some researchers call “data reduction.”
Deciding what data are most pertinent to the study, however, is not always
straightforward and requires the judgment of the researcher. Like all other analysis
activities, selecting useful data from the total data collected is an activity that depends on
the care and sensitivity that the researcher brings to it. Researchers vary in their selection
decisions, some finding that they can reduce the amount of data they analyze at an early
stage without damaging its integrity, and others feeling that they must work with a larger
amount of data through the whole process. While data not considered relevant at the start
of analysis can be set aside as other data become the main focus, they should not be
destroyed in the event that their importance only becomes clear as the analysis proceeds.
Sorting the Data into Categories
As data are selected for further analysis, the researcher develops a sense for the ways in
which they can be fitted together. Often, a preliminary sort can be made on the topics that
were explored through the observations or interviews. These may correspond to interview
questions when structured interview formats are used. For example, all comments in the
interviews on first-year students who abandoned engineering as a field of major study
might be placed in such preliminary categories as “perception of lack of fit,” “academic
issues,” “time management,” “financial,” or the like. Selecting a comment is called
“chunking,” and deciding how much or little of a given text should be selected for
classification is a decision made on the basis of the type of study. For standard studies (as
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