Blog Posts

Codes are the example par excellence for our constant banging on about strategies and tactics. Reminder: strategies are what you plan to do, and tactics are how you plan to do it. When using a CAQDAS program, the tactics are very different in nature from the analytic strategies. A strategy might be to compare the men and women respondents in a study by separately conceptualizing the male responses from the female responses. The tactic to fulfil it will depend on the CAQDAS pa

There is no answer to this perennial question – not even any guidelines. You need as many codes as you need – in other words, however many are needed to capture what’s going on in the data in relation to your analytic focus and research objectives. How many depends on what you’re using the codes to represent, how you derive them, and how you intend to use them in the analysis. I’ve done substantial projects with as few as 22 codes, and others that required several hundred. Co

What lies behind the red flag question: “I’ve done all my coding – now what?” In my last blogpost I considered the first likely culprit: starting to code before thinking through its purpose. But thinking about the purpose isn’t enough. A second issue is the need to think about coding as an on-going process – not as a single event that gets “done” before moving on to the next event. Coding is the opportunity to repeatedly connect with our data. Moments of contact There are

Yet again this week I was asked the red flag question in a CAQDAS workshop: “Coding’s done. Now what?” This flags the inappropriate use of CAQDAS: no analytic planning done before plunging into helter-skelter coding. In this post and the next I’ll deal with the two underlying problems: starting to code without thinking about its purpose, and thinking of coding as an event rather than a process. Taken together these can result in a mass of codes that don’t lead to a thoughtful

Kath McNiff’'s post on the NVivo Blog about classifying data in NVivo has prompted me to get writing about how I deal with this teaching challenge. For me, teaching students to choose between the available tools for classifying data and how to harness them appropriately revolves around units. Classification confusions For years I've experimented with different ways of teaching how to harness the NVivo tools for classifying factual characteristics of data and respondents - fo