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When and When Not to use Phenomenology


In our work of mentoring students at several different online universities, we see many dissertation proposals that use phenomenology as a research design.  Yet the reasons for choosing phenomenology are often unclear, and sometimes do not fit the nature of the problem and purpose.  Research designs come in and out of fashion, and at this point in time phenomenology seems to be all the rage.  But is it really the right design for your problem and your study?

Phenomenology is a design that best fits research problems that are unstructured, and for which there is little or no research or evidence in the literature.  Given the explosive growth in doctoral level scholarship in the last decade, encountering problems like this is less common than one might think.  Most major social or organizational problems have already attracted considerable empirical investigation, and even minor problems have probably been investigated at some level.  Yet we still see proposals for phenomenology even for well-studied problems or issues that have been investigated in both quantitative and qualitative research.  This is an indicator that doctoral learners are focusing erroneously on methodology, and not on the problem.

Phenomenology involves gathering the lived experiences of individuals, and if these experiences are unique and largely unstudied, then a phenomenological study can generate thick descriptions of great value for understanding a problem that has not been well studied.  However, the results of phenomenological studies are, largely not generalizable beyond the sample.  These results can be very useful for scoping the dimensions of an unstructured problem, and gaining sufficient knowledge to then structure theory and an understanding of variables pertaining to the problem.  This knowledge can to develop subsequent surveys or quantitative studies, which may then generalize to broader populations.  But if an issue has already been well studied, then yet another phenomenological study of the same problem will generate little additional insight.

Unfortunately, there is a mistaken belief among some doctoral learners that a phenomenological study is easier than other qualitative or quantitative designs, and therefore a faster path to degree completion.  Think again. In reality, well-executed phenomenological studies can be very challenging, may involve use of more difficult analytical tools, and require considerable effort.  Learners who are avoiding other designs such as quantitative surveys, perhaps because they are afraid of statistics or out of a mistaken belief that quantitative studies are much more difficult, should reconsider their assumptions.

Finally, it is important to keep in mind that the nature of the problem that should lead to selection of method and design, and not the reverse. When should you use phenomenology?  Use it when it makes sense, and not just because it’s popular.

For additional information on phenomenology, and when and where to use it, see these links on

What is Phenomenological Research

Paradigm Assumptions

Validity and Reliability in Qualitative Studies

Choosing Your Research Project






Take your passion and make it happen


When conducting scholarly research, it is important to understand the role passion plays. Passion can help us stay motivated and focused, but it can also blind us to the truth. If we pick a topic to convince the world of the one true answer to a question we pose, we are probably asking the wrong question and writing a position paper rather than conducting scholarly research. To help you harness the passion in a scholarly way, come check out:

Transcribing Interview Data


By Marilyn Simon and Jim Goes

Many researchers and students who choose qualitative methodology end up gathering and transcribing interview data, whether they are conducting a phenomenological study of participant “lived experiences”, gathering data for case studies or ethnographies, or using other designs.  A successful study using interviews inevitably involves transcription of interview data, yet many new researchers are not sure about how to do it.  Moreover, we sometimes see presentations of interview results that demonstrate weak analysis, short discussions, and limited development and integration of categories and themes.  These problems are often an indicator and result of poor transcription and analysis of interview data.

Our latest resource addresses this problem, and provides guidance for transcribing interview data as an important step towards a substantive, credible qualitative study.

Transcribing interview data


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