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Qualitative Research Methods & Data Analysis

Instructor

Level

B = Basic
M = Intermediate
A = Advanced

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Location

Further and more detailed information, including the schedule, can be found in the current course tables in the syllabus of the respective course, if the course is offered in the next sessions. The following text serves as information on what can be expected in terms of content in the course.

Qualitative Research Methods and Data Analysis presents strategies for analyzing and making sense of qualitative data. Both descriptive and interpretive qualitative studies will be discussed, as will more defined qualitative approaches such as grounded theory, narrative analysis, and case studies. The course will briefly cover research design and data collection strategies but will largely focus on analysis. In particular, we will consider how researchers develop codes and integrate memo writing into a larger analytic process. The purpose of coding is to provide a focus to qualitative analysis; it is critical to have a handle on coding practices as you move deeper into analysis. The course will present coding and memo writing as concurrent tasks that occur during an active review of interviews, documents, focus groups, and/or multi‑media data. We will discuss deductive and inductive coding and how a codebook evolves, that is, how codes might “emerge” and shift during analysis. Managing codes includes developing code hierarchies, identifying code “constellations,” and building multidimensional themes. The class will present memo writing as a strategy for capturing analytical thinking, inscribed meaning, and cumulative evidence for condensed meanings. Memos can also resemble early writing for reports, articles, chapters, and other forms of presentation. Researchers can also mine memos for codes and use memos to build evocative themes and theory. Coding and memo writing are discussed in the context of data-driven qualitative research beginning with design and moving toward presentation of findings. The course will also discuss using visual tools in analysis, such as diagramming core quotations from data to holistically present the participant’s key narratives. Visual tools can also assist in looking horizontally across many transcripts to identify connective themes and link the parts to the whole.