Who We Serve
We serve students, researchers, and faculty in one key area of the qualitative research process: harnessing tools to fulfill analytic strategies, when dedicated CAQDAS packages have been chosen for this task.
A major purpose of Five-Level QDA is to lay out the entire picture, the full range of activities that have to be addressed in a qualitative project, of which choosing and harnessing the tools to use is but one.
In these pages we describe how Five-Level QDA is relevant to:
Nick Woolf is the best instructor I have had for learning a software application....Nick's highly interactive teaching style significantly increased my success...I returned to work with renewed insight and ideas about where my research was leading. Nick presented a remarkably effective class for both new and experienced researchers.Mary F. Annese, MPA, Research Specialist
The Casey Family Program
We're really excited to have submitted to Routledge our manuscripts for three books on the Five-Level QDA method - one each for ATLAS.ti, MAXQDA and NVivo. Nick developed the theory and when we met in 2013 we realized that we had both come to very similar conclusions about the issues involved in teaching and learning to harness CAQDAS packages powerfully. We've since been working together to refine, test and write-up the method.
In an earlier post on CAQDAS critics and advocates I promised to provide evidence for my position that CAQDAS packages are not distancing, de-contextualising, and homogenising, as is sometimes claimed. I have already argued that CAQDAS packages actually bring us closer to our data, and given an illustration of how this can happen, so here I consider the de-contextualizing issue.
In my previous post I argued that using dedicated CAQDAS packages for analysis could bring us closer to our data, rather than distance us from it, as some critics suggest. Here I illustrate this by outlining how different CAQDAS tools can be used in to fulfil a specific analytic task, thus bringing us closer to data.
Let's imagine we are doing a project in which we need to generate an interpretation that is data-driven rather than theory-driven. It could involve one of a number of analytic methods, for example, inductive thematic analysis, narrative analysis, grounded theory analysis, interpretive phenomenological analysis'. Whatever the strategy, an early analytic task may be to familiarize with the transcripts in order identify potential concepts. There are several different ways we could go about fulfilling this analytic task using dedicated CAQDAS packages. Here I discuss three.
In an earlier post on CAQDAS critics and advocates I promised to provide evidence for my position that CAQDAS packages are not distancing, de-contextualising, and homogenising, as is sometimes claimed. So I'm starting a series of posts. First I'm taking the suggestion that the use of CAQDAS distances us from our qualitative data and illustrate why I believe the converse to be true. Here I outline my position, and I'll illustrate my argument with examples in subsequent posts.
As well as our own Five-Level QDA blog Nick and Christina have contributed to other blogs, newsletters and magazines on aspects to do with the use of CAQDAS packages. In addition, there are posts and resources written by others which are related to our work that we think researchers using different CAQDAS packages may find useful. Here we collate these resources for easy access. We will update this post as additional resources come to our attention relate to Five-Level QDA. If you know of something that should be listed here, please let us know.