Article

Qualitative Data Analysis Techniques

Anthony J. Onwuegbuzie and Magdalena Denham

in Education

ISBN: 9780199756810
Published online June 2014 | | DOI: https://dx.doi.org/10.1093/obo/9780199756810-0078
Qualitative Data Analysis Techniques

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Qualitative research can be traced back to ancient times; however, the use of qualitative methods began to be formalized in certain disciplines (e.g., sociology, anthropology) only in the 19th century. Broadly speaking, qualitative research involves an in-depth examination of human experiences and human behavior, with the goal of obtaining insights into everyday experiences and meaning attached to these experiences of individuals (via qualitative methodologies such as biography, autobiography, life history, oral history, autoethnography, case study) and groups (via qualitative methodologies such as phenomenology, ethnography, grounded theory), which, optimally, can lead to understanding the meaning of behaviors from the study participant’s/group’s perspective. Qualitative researchers tend to investigate not just what, where, and when, but more importantly the why and how of events, experiences, and behaviors. Thus, qualitative researchers are much more likely to study smaller but focused samples than large samples. In general, qualitative research studies primarily involve the collection, analysis, and interpretation of data (i.e., information) that naturally occur. Of these steps, the analysis of data arguably represents one of the most difficult steps—if not the most difficult step—of the qualitative research process because it involves a systematic exploration of meaning and the achievement of verstehen (i.e., understanding). More specifically, qualitative data analysis is a process that comprises multiple phases, and from which findings are extracted or emerge. These phases include examining, cleaning, organizing, reducing, exploring, describing, explaining, displaying, interrogating, categorizing, pattern finding, transforming, correlating, consolidating, comparing, integrating, synthesizing, and interpreting data, in ways that allow researchers to see patterns, to identify categories and themes, to develop typologies, to discover relationships, to cultivate explanations, to extract interpretations, to develop critiques, to generate or to advance theories, and/or the like, with the goal of meaning making. A criticism of qualitative data analysis is that because it typically involves examination of data extracted from small, nonrandom samples, findings stemming from any qualitative analysis usually are not generalizable beyond the local research participants. However, what is a limitation for one purpose (i.e., generalization of findings to the population the sample was drawn from), is a strength for another purpose. Specifically, the examination of relatively small samples allows qualitative researchers to collect (maximally) rich data (e.g., via in-depth interviews, focus groups, observations, images, nonverbal communication). This, in turn, makes it more likely that as a result of the qualitative data analysis, verstehen will be achieved.

Article.  27797 words. 

Subjects: Education ; Organization and Management of Education ; Philosophy and Theory of Education ; Schools Studies ; Teaching Skills and Techniques

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