Nicholas Woolf and Christina Silver

Nick and Christina have been working together since the first ATLAS.ti User Conference in Berlin in 2013, where Nick gave the keynote introducing Five-Level QDA. We discovered that that we had independently reached similar conclusions about how to better help students and researchers gain CAQDAS expertise, and since then we have been developing, refining and implementing the Five-Level QDA method.

Below you can read about us and the on-going training and consulting we offer researchers, Christina in the UK and Nick in the US.

You can find a list of our publications here

Nicholas Woolf, Ph.D.

Nicholas Woolf
Nicholas Woolf

Nick has been training qualitative researchers and teaching CAQDAS workshops in the US and Canada since 1998. He specializes in working with researchers to think through their research questions, turn the questions into a coherent analytic plan, and design the process for implementing the plan on a CAQDAS package. Once the plan is designed, Nick provides project-based training in ATLAS.ti, meaning that time is spent on learning just the ATLAS.ti skills needed for each phase of the project, rather than in comprehensive training in the entire program, much of which may not be required for a particular study. The focus is on efficiently completing the project, in terms of both time and cost.

For individual researchers and dissertations students Nick guides the data analysis phase of a project from inception of the plan to completion of the project using the Five-Level QDA  method. About half the needed consulting time is generally spent at the beginning planning stage, and the remainder on an as-needed basis as the project progresses.

For team and funded research projects Nick’s role varies greatly according to need. For some projects he serves only as an outside consultant, providing guidance and advice at turning points of a data analysis on an as-needed basis. For other projects he is more involved as a team member, participating in or leading the data analysis, and training and coaching the researchers in whatever features of ATLAS.ti  they need to use. With some projects Nick undertakes the entire data analysis himself, and participates in the writing of the resulting papers. Nick has been involved in a range of projects, from evaluations to grounded theory studies, including studies in  family medicine, public health, education, and leadership and management studies.

After observing the learning process of thousands of his students in ATLAS.ti workshops, Nick developed a perspective for helping researchers more quickly gain the expertise that long-term users of CAQDAS develop through trail-and-error. He called this Five-Level QDA and presented this method as the keynote address at the 2013 ATLAS.ti User’s Conference in Berlin. Since then he has been working with Christina Silver in further developing and offering the method as a CAQDAS pedagogy. Their textbook Five-Level QDA: A method for harnessing powerfully will be published in 2017.

View further details about Nick's services

View Nick's publications

Contact Nick 

Christina Silver, Ph.D.

Christina Silver
Christina Silver

Christina has been using and teaching CAQDAS packages since 1997. She has conducted many different research projects, big and small, with and without the use of qualitative software – including her own studies and many other academic and applied research projects. She has experience in using most of the leading CAQDAS packages and has taught almost 10,000 researchers in their methodologically-informed use.

Christina’s passion is working out creative and efficient ways to analyze different types of data using customized software applications. She really doesn’t mind the topic, she just wants to get her hands on data and harness software tools! She enjoys the dynamic nature of intensive workshop-based training, coaching and project consultancy, where she can help design strategies that are best suited to the needs at hand. This way, she learns from those she works with – and everyone is happy!

Christina’s particular interests relate to the relationship between technology and methodology and the teaching of computer-assisted analysis. Joining forces with Nick to refine Five-Level QDA has given her the ability to support researchers to harness CAQDAS powerfully in a more structured and effective way.

Some examples of consultation projects in harnessing CAQDAS packages powerfully, using Five-Level QDA, that Christina specializes in are:

  • Project planning and research design – working with groups and individuals to determine how to structure their work in the context of CAQDAS use.
  • Mixing methods – working with groups to plan how to integrate qualitative and quantitative materials, as well as how to transform qualitative information into quantitative information, with a view to applying statistical analyses in other software (e.g. SPSS).
  • Planning for your PhD – working with doctoral students to highlight how CAQDAS can help them project manage their PhD.
  • Planning for team work – working with research teams to highlight the considerations applicable when working together on a single research project using software.
  • Train the Trainer – working with university faculty to design curricula for integrating CAQDAS learning into methods courses.

Christina has designed and carried out analysis for a number of independent organizations. She has taught under- and post-graduate qualitative methods courses in UK and European universities and currently contributes to doctoral programs at several institutions, using Five-Level QDA in workshops of varying lengths.

Christina Co-founded Qualitative Data Analysis Services (QDAS) through which she and colleagues, including Nicholas Woolf, provide consultancy, analysis and training. Additionally, she is the Manager of the CAQDAS Networking Project and Co-Director of Day Courses in Social Research, both in the Department of Sociology at the University of Surrey, UK. Christina is based in the UK but travels around Europe (and beyond).

View more information about Christina

View Christina's publications 

View Christina's LinkedIn profile

View Christina's Twitter account

Contact Christina 


The advanced NVivo workshop was so useful. I now have the skills to enable me to use NVivo much more powerfully. Christina is a brilliant trainer and she adapted the course to suit the requirements of those that attended. Christina also gave everyone individual help with their projects. I could not recommend Christina's course highly enough, or emphasise more the value of this course for researchers working with qualitative data.
Caroline Andow, Postgraduate Researcher
University of Southampton


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.


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.


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.


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.


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.