Training, consulting and analysis services
We provide a range of services in association with Qualitative Data Analysis Services (QDAS). All our work is based on the principles of Five-Level QDA. This has proven effective in ensuring projects are successful from start to finish, and that after our work together you are well-positioned to continue harnessing a CAQDAS package to produce high-quality QDA.
We offer three areas of service
Online QDA Training
Nick focuses on online training & coaching, project consulting, and data analysis services, using ATLAS.ti. Contact Nick by email.
Face-to-face Training Workshops
Christina focuses on face-to-face training workshops, as well as online training & coaching, project consulting, and data analysis services using all major CAQDAS packages. Contact Christina by email.
Our colleagues at QDAS may also be more suited to a particular project, or may join one of us in assisting you. All our services are customized to your needs, and we will begin by working with you to decide the best way to serve you. Visit QDAS for further information about our services and colleagues.
Thanks again for a great session! I really can't imagine how we could have proceeded without this kind of in depth training. Now on to the real work...Jennifer Sweeney, MSLS, PhD
School of Education, University of California, Davis
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.