The Basics of Qualitative Research
By Juliet Corbin & Anselm Strauss
This is our first guest blog post from Shahtab Wahid. He is an Interaction Designer on the User Experience (UX) Team at Bloomberg LP working on researching and designing collaboration tools for the financial markets. He is a hokie (Virginia Tech) lifer. You can reach him at @shahtabwahid.
When people talk about UX they usually talk about something that mimics the software lifecycle: do a set of contextual interviews to get a high level understanding of user needs, develop those needs into workflows, develop wireframes for those workflows, then test test test as the wireframes are being developed and implemented. However, when people talk about testing their assumptions they usually talk about usability testing or some other form of quantitative evaluation.
Here is an inside look on what goes through my mind every time someone talks to me about quantitative UX research:
Them: Hey Shatab! I’m going to design a fancy new product for this cool user base.
Me: (Cool!)
Them: Of course, I need to know more about the users so I’m gonna do some research.
Me: (Hooray research!)
Them: I think I’m gonna do a survey….
Me: (Ugh.)
Them: Maybe some task-based usability study too. Oh, and EYE-TRACKING!
Me: (Bah! God help me.)
It’s not that quantitative methods are bad. Quantitative measures can tell you the usage facts behind existing software tools. Which is fine, I guess. The problem is that I want more than that. I want to know why and how things happen; I want to understand the deeper level issues that the product is trying to solve. That’s why I’m much more excited about qualitative methods, like interviews and contextual inquiries. Qualitative methods enable you to uncover users’ mental models and motivations which quantitative methods cannot do.
Here is what people grapple with: qualitative methods can be confusing and distinctly non-formulaic. It can even be hard to to talk about qualitative research at times, since the outcomes of a qualitative study are impossible to predict. To help mitigate these problems I’ve found the book The Basics of Qualitative Research to be an excellent reference in answering all the questions I have had about qualitative research.
What I enjoy about the book is that it starts off by getting into the mind of a qualitative researcher. Corbin and Strauss (Strauss being one of the leading figures in qualitative research) explain that a committed qualitative researcher is “drawn to the fluid, evolving, and dynamic nature of [the qualitative] approach in contrast to the more rigid and structured format of quantitative method.” Here they draw the distinction between qualitative and quantitative researchers as a difference in personality, rather than just choice of methods. This is because good qualitative researchers are curious, creative, and take pleasure in ambiguity.
One of the major drawbacks of qualitative research is how it is perceived. Many people try to “bash” qualitative research for its fluffiness. However, what this book does is provide a UXer the ability to stop for a moment and see the amount of work you have to do to analyze data. From establishing a firm protocol, to creating different kinds of coding methods, the ability to get reliable and informative data is a science rather than an art.
In particular, the later chapters in the book explain how to make sense of data — which is anything but “fluffy”. The reader learns what it means to code all the data using axial and/or open coding. And, when in practice, the research has to come up with categories and eventually link them together. That not only takes time, but a rigorous sense of the data and how the pieces fit together.
Overall, the book is a very detailed guide to figuring out the why and the how. The authors do a great job of explaining by often taking a step back to do ‘methodological notes’ to explain what is going on from a methods standpoint. Additionally, all the steps of the qualitative methods are described through the lense of long-running examples that help show how to interpret meaty qualitative data.
The best part of the book is that the last chapter is dedicated to answering questions students asked over the years. There are extended answers about using software tools for analysis, the lack of ‘numbers’, and how much data is actually needed. I think it’s a nice way of addressing some of the challenges of doing qualitative research when you get down and dirty with everything.
The last thing to say about this book is that I once recommended it to a colleague of mine and she said she learned a lot from this. It’s true. This book can really teach so much, but I’ve got to say it’s a bit of a tough read. This isn’t the type of book you’re going to immediately go through from start to finish in one shot. There’s a lot of absorb. For me, it really serves well as reference when I have a lot of data to work with. My concern with the book is that it probably works well for researchers who already have an interest in qualitative research. I’m just not sure if anyone can use it to convert a quantitative researcher or other skeptics.
Book club questions
Given your work context, how do you think you would go about convincing your stakeholders that you need to be able to do this type of research before jumping into design?
