Courses in Qualitative Research Designs

Choosing the right design for your study

Qualitative data analysis is a fascinating stage in qualitative inquiry, yet it can be difficult to see how researchers move from dozens of pages of transcripts to a handful of conclusions. This is because no account is given of what they actually did when analysing their data. This state of affairs undermines the trustworthiness of the analytical journey and impacts negatively on qualitative inquiry as a whole.

What drew me to develop methodological expertise in qualitative analysis was a feeling of frustration that so many well-executed qualitative studies presented a remarkably poor analytical record, despite otherwise carefully reporting the theoretical framework, sampling procedures, and data collection. Qualitative analysis is often reduced to merely “identifying themes” in the data and presenting them in excess as quotes that supposedly epitomise each theme that “emerged” from the data. It goes without saying that themes do not “emerge”! Rather, it is the researcher who, through meaning-making, constructs themes from raw data. This problem of a poor analytical record is often compounded by other methodological problems, such as when the researcher — in disregard of the basic requirements of a given methodology — claims to have applied ‘grounded theory’ or the ‘Miles and Huberman approach’, yet presents no theory or cross-case analysis in the results section. Crucially missing in many qualitative studies is a description of the relationships between themes and of the meaning of these relationships, as only with such a description can we gain a better understanding of a given social phenomenon. But for such a description to be possible, the researcher must genuinely analyse their data, rather than merely sort through large chunks of material. It is only through such an analysis that insightful propositions, explanations or theoretical predictions about the studied phenomenon will be obtained.

The courses in qualitative research designs provide participants with a comprehensive grounding in each design’s historical background and epistemological point of reference, and develop the skills necessary to implement their corresponding coding, analytical, and visualisation procedures in their research. Participants also learn to appraise the quality of published studies that use each design. The courses blend lectures, group work and hands-on exercises. Courses are either half-day (3 hours) or full-day (6 hours) duration. When half a day, the courses take the form of short lectures that only cover the core aspects of each design. When full-day, the courses go deeper into each design’s coding and analytical procedures, which are exemplified in NVivo, MAXQDA or Work / Excel.