UXjam

#ixd11 rejection is bittersweet (but mostly sweet)

All afternoon yesterday Twitter was abuzz with #ixd11 lightning talk rejection notices, and I sat wondering where mine was. I dug through my spam folder to no avail, wondering if by some ridiculous fluke I’d actually been accepted—and subsequently being fairly terrified. After accepting a 6-month position as Editor in Chief of The Triangle on top of my already crazy senior year schedule, there’s no way I would have time to develop the talk to the extent that I’d hoped when writing the proposal.

Finally I found the fateful email hiding along with most other emails with “IxDA” in the subject line, properly labeled and auto-archived thanks to Gmail. D’oh.

Now that I finally know I’m not presenting, I’m applying to be a student volunteer. w00t. Have to milk it while I’m still eligible :)

Anywho, this was my proposal. It’s a little long and at times academicky, but the actual talk would not sound quite as pretentious. I definitely want to either develop a talk or write something more extensive in the future, so any comments/questions/suggestions would be greatly appreciated. I’d also really love to hear about other people’s research analysis and synthesis processes.

Thanks so much to @zakiwarfel, @judyphilip, @stellargirl, @martytdx and most especially @dantemurphy for feedback and encouragement. And to @jehring for being my final proofreader. And to @jkolko and @mjbroadbent for weeding through over 300 submissions. Wow.

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Watch your language: Mindful tagging as qualitative analysis

In their Interaction10 keynotes, Jon Kolko and Nathan Shedroff mentioned that qualitative data is at the heart of our practice. Whether conducting contextual interviews or observing remote usability tests, we record a lot of data, which often leaves us asking: “How do we extract significant insights?”

Typically, tags and controlled vocabularies are used to classify resources— books, articles, images, blog posts, etc—for the purpose of retrieval. When used to describe discrete chunks of qualitative data, controlled index terms make it quick and easy to filter for comprehensive analysis.

But before data can be sliced and diced, researchers must tackle the tedious task of tagging. This process immerses them in meaning and is essential to effective analysis—as each piece of the puzzle is examined and put in its place, the bigger picture reveals itself. The researchers intimately familiarize themselves with the data and develop a lexicon with which to think about, discuss, and later access various facets. Vetting terms for inclusion in a controlled list, researchers are forced to consider what they are actually saying about each piece of data—and, in turn, why it matters. Collaborative curation of the term list allows multiple researchers to engage in analysis simultaneously, and the process of reconciling synonyms and other personal variations in vocabulary richens the method.

Using examples from exploratory and evaluative research studies, we will discuss the process of sifting through qualitative observations, the different types of analytical tags, what makes a good descriptor, how to examine data once it’s indexed, digital vs. analog sorting, and playing well with others.

Novice researchers will learn a systematic approach to analyzing qualitative data. The more experienced will gain a renewed appreciation for this tried-and-true method.