Overview

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

QDA Consulting  QDA Training Courses  QDA Data Analysis
                          

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.  

Testimonials

I highly recommend Nick Woolf's workshops. I learned more in two days than in months of tinkering on my own. Nick does a masterful job of blending didactic instruction with one-on-one coaching.
Kimberly Jinnett, Ph.D.
Senior Evaluation Officer, Wallace-Readers Digest Funds, The University of British Columbia

Blog

No 'basic' or 'advanced' CAQDAS features

No 'basic' or 'advanced' CAQDAS features
By Christina Silver on May 13, 2017 at 09:25 AM in CAQDAS commentary

This blog post is a response to Steve Wright’s reaction to a post I made on Twitter: “There are no basic or advanced #CAQDAS features, but straightforward or more sophisticated uses of tools appropriate for different tasks”

Thanks Steve for starting this conversation – it’s really important to debate these issues, and fun too! The sentiment behind the Twitter post underlie the Five-Level QDA® method that Nick Woolf and I have developed. Our forthcoming series of books explain our position, so here I briefly respond to Steve’s comments.

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The Five-Level QDA method books are in production

The Five-Level QDA method books are in production
By Christina Silver on Mar 05, 2017 at 08:04 PM

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.

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Don't blame the tools: researchers de-contextualise data, not CAQDAS

Don't blame the tools: researchers de-contextualise data, not CAQDAS
By Christina Silver on Jan 07, 2017 at 06:26 PM in CAQDAS commentary

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.

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An illustration of how CAQDAS tools can bring us closer to data

An illustration of how CAQDAS tools can bring us closer to data
By Christina Silver on Nov 14, 2016 at 10:49 AM in CAQDAS commentary

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.

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Does CAQDAS distance us or bring us closer to our data?

Does CAQDAS distance us or bring us closer to our data?
By Christina Silver on Oct 01, 2016 at 09:29 AM in CAQDAS commentary

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.

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