Qualitative Research in a World of Big Data: Debunking the isms of Qualitative Research

Image via WikipediaOK--I am going to take a flying leap into space.  Qualitative research had its beginnings in the late 1800's with the first steps of anthropology, sociology, and related areas in which non-numerical studies were being conducted.  As often happens in the early stages of a field, many of the conversations about methods and terms occurred in silos--disciplinary and otherwise.  Thus, ethnography was seen as separate from phenomenology.

As time went by and the field of qualitative research matured, more connections were made across fields, and yet methodological discussions were still emerging as separate 'isms'.  So now we have case study, grounded theory, ethnomethodology, discourse analysis, narrative analysis--you name it!

Today researchers, graduate students, reviewers of articles and proposals--try to sort out these various isms.  I have graduate students who spend hours trying to differentiate case study from ethnography in hopes of answering the questions of an ardent dissertation committee member.  I get email from fellow faculty members who want help answering a reviewer who thinks their piece should be described as grounded theory.  I know of proposals rejected on similar grounds--lack of specificity about the qualitative research method being used.

Over time, exposure to these various conversations, and most important long experience with qualitative research software--I am coming to realize that all these isms are bogus.  Yes, you heard it right here--they don't really amount to a hill of beans.  Rather they are artifacts of our colonial and post-modern past.  They were needed to flesh out the field of qualitative research, but we are at the point of a major paradigm shift which will allow us to consolidate these ideas and reorient ourselves in a more productive way.

The impetus of this change is big data, computers, globalization, and everything that is going along with this data revolution.  I am coming to believe as Tim Berners-Lee, the so-called founder of the Internet, has suggested--that it's all about data.

What I've learned from qualitative data analysis software (QDAS) is that these various isms are critical background, they give us the pieces that we can now ask about from a more synthesized perspective.  The question is not whether the work is ethnographic, case study, grounded theory, or phenomenology...those were the old questions--the new questions are more generic:

• What is the unit of analysis?  A cultural group, a geographic location, a case (meaning an event, a particular issue, an instance, a specific problem), a role group (teachers, nurses, etc.)...Does the analysis incorporate several connected units?  
• What kinds of data will I collect?  
• How fine or gross will my analysis be?  
• What kinds of sorting mechanisms will be involved--do I need cases and attributes?  Or will simple thematic codes be appropriate?  
• What kinds of numerical data will I be integrating with the non-numerical data, if at all, and how do I need to strategize my use of tools?  

Quite frankly--the isms of qualitative research--are, at this point, antiquated relics.  They are artifacts of the build up to where we are now.

I am often told that these isms are essential because they determine how I will analyze and what I will find--prove it!!  What the isms often mean is that my jargon will be different.  I will couch my presentations in different styles of the professional genre.  After having overseen many studies, I don't find that the studies turn out so differently because of the ism that is assumed, rather they turn out differently because they have a different unit of analysis, they collect different kinds of data, they rely on different forms of sorting, and they work at a gross/medium of fine level of analysis.  Seeking and creating patterns is informed by reading about various isms...but in the end it all kind of comes down to the same thing.

What we need now is to collapse the isms into a system that will place us within the conversations that are occuring about data of all sizes, all units, all forms.  The discussion is about data.  The discussion is global.  The discussion is jumping around in and out and making hash of the isms.

I've reached the end of my patience with these isms--individually I love them in their own way--but I (and others around me) are being strangled by the isms of qualitative research.  Let's take a stand against ism madness in qualitative research, and join the bigger conversation that we have been avoiding through our technophobia.  Come on qualitative researchers!!