Workshop exercises for participatory qualitative analysis

participatory workshop

I am really interested in engaging research participants in the research process. While there is an increasing expectation to get ‘lay’ researchers to set research questions, sit on review boards and even ask questions in qualitative studies, it can be more difficult to engage them with the analysis of the research data and this is much rarer in the literature (see Nind 2011).

However, Quirkos was specifically designed to make qualitative text analysis engaging and easy enough that participants could learn to do it with just a little training, and in this blog post article from last year I describe how a small group were able to learn the software and code qualitative data in a two hour session. I am revisiting and expanding on this work for a talk in the Digital Tools thread of the 2016 ICQI conference in Champagne Illinois this month, so wanted to revisit this a little.

When I had attempted to engage participants in qualitative analysis before, it had been fairly limited in scope. The easiest way was essentially to present an already complete draft ‘report’ or overview of the analysis and findings, and use that for comment and discussion. While this allows respondents some ability to influence the final outputs and conclusions, the analysis process is still entirely led by the researcher, and they don’t really get a chance to change how data is interpreted. The power dynamics between researcher and participant are not significantly altered.

My feeling is that respondents are often the experts in what is being studied (i.e. their own experiences), and I worry that if presented with all the data, they might rightly conclude “You’ve interpreted this as being about x when it is really about y”.

Yet there are obvious problems that occur when you want respondents to engage with this level of detail. First of all, there is the matter of time: qualitative analysis is extremely time consuming, and in most projects asking someone to analyse all the data is asking for days or even months of commitment. This is not feasible for most respondents, especially if asked to do this work voluntarily parallel to the full time, paid job of the researcher! 

Most approaches in the literature choose to engage a small number of participants in the analysis of some of the data. For example Jackson (2008) uses group exercises successfully with people from different educational backgrounds. The DEPICT model breaks down the work so that the whole dataset is covered, but each team member only has a few transcripts to code (Flicker and Nixon 2015).

However, when it came to run participatory analysis workshops for the research project we did on the Scottish Referendum Project, we had an additional secret weapon: Quirkos! One of the main design briefs for Quirkos was to ensure that it was simple enough to learn that it could be used by research participants with little or no formal training in research or qualitative analysis. The workshops we ran with research-naïve respondents showed that such a software package could be used in such a way.

I was initially really worried about how the process would work practically, and how to create a small realistic task that would be a meaningful part of the analysis process. Before I started, I considered a series of tasks and scenarios that could be used in a participatory analysis workshop to get respondent input into the analysis process. I’ve included some brief details of these below, just in case they are helpful to anyone else considering participatory analysis.



Blank Sheet

The most basic, and most scary scenario: the coding team is provided with just the raw transcript(s), with no existing topic framework or coded data. They start from scratch, creating their own coding framework, and coding data. This is probably the most time consuming, and conceptually challenging approach, but the most neutral in terms of influence from the researchers. Participants are not provided with any preconceptions of what they should be exploring in the data (although they could be provided with the research questions), and are free to make their own interpretations.



Framework Creation

Here, I envisage a series of possible exercises where the focus is on not the coding of the data explicitly, but consideration of the coding framework and possible topics of interest. Participants choose topics of significance to them, or that they feel are appearing in the data. Here the process is like grounded theory, participants are given one (or several) transcripts to read, and asked what topics are significant. This works well on large sheets of paper with Post-it notes, but by creating the coding framework directly in the software, participants and researchers can easily utilise the developed framework for coding later. Could exist in several variants:

Emergent Coding
As above: creating a coding framework (probably from scratch, or with some example topics already provided by the researcher)

Grouping Exercise
A simpler task would be to present a pre-prepared list of many possible topics of interest created by the researcher, and ask participants to group them either thematically, or by order of importance. This gives respondents an easier start on the coding framework, allowing them to familiarise themselves with the process and topics. It is more restrictive, and plants directions of interest for the participants, but they would remain able to challenge, add to, or exclude topics for examination.

Category Prompts
Here the researcher has created a few very broad categories (for example Health, Housing, Family) and the participants are encouraged to populate the framework with more specific sub categories. This approach is a good middle ground, where the researcher can set some broad areas of interest, but participants have say in what direction topics should be explored in detail (say Expensive food, Lack of open space).

After one or more of these exercises, the participants could go on to use the coding framework to code the data themselves, or the researcher can use the contributed topic guide to focus their own coding.



Coding exercises

In these three exercises, I envisage a scenario where some coding has already been completed, the focus of the session is to look either at coded transcripts (on screen or printout) and discuss how the data has been interpreted. This could take the form of:

Researcher Challenge: Where the researcher asks the participants to justify or explain how they have coded the data
Participant Challenge: Participants examine data coded by researchers, question their rationale and suggest changes
Group Challenge: Participants and researchers code the same transcript separately, and get together to compare, contrast and discuss their results.

With all these approaches, one can apply several overall philosophies:
Individual: Where each respondent or researcher works on their own, adding separately to the total coding of the project
Collaborative: Analysis is done as part of a team, working together
Comparative: Where analysts work separately, but come together to discuss and contrast their work, creating a final dialogue from the input of the whole group.


Finally, the team should consider whether the aim of the project is to actually create a direct analysis outcome from these sessions, or if they are exercises which are themselves part of the qualitative data generated from the project. For our sessions, we also recorded, transcribed and analysed the discussion which took place around the coding, which itself also contributed nuanced and valuable insight into the thought processes of the participants. Of course, this leaves the problem of creating an infinite Ouroboros loop of data generation, if respondents were then invited to analyse the transcripts of their own analysis sessions!


Which approach, and how far the participatory process is taken will obviously depend on the research project and desires of the researcher. However, my main aim here is to just get people thinking about the possibilities, and if engaging participants in the research process in some way will challenge the assumptions of the research team, or lead to better results, and more relevant and impactful outputs.


Here are the slides of my ICQI 2016 talk, and the complete data (raw and coded) and summary report on the Scottish Referendum Project is here. I would welcome more discussion on this, in the forum, by e-mail ( or in the literature!


Don't forget, the new version of Quirkos is now available, for researchers and participants alike to bring their qualitative analysis to life. Download a free trial today!



Free materials for qualitative workshops

qualitative workshop on laptops with quirkos


We are running more and more workshops helping people learn qualitative analysis and Quirkos. I always feel that the best way to learn is by doing, and the best way to remember is through play. To this end, we have created two sources of qualitative data that anyone can download and use (with any package) to learn how to use software for qualitative data analysis.


These can be found at the workshops folder. There are two different example data sets, which are free for any training use. The first is a basic example project, which is comprised of a set of fictional interviews with people talking about what they generally have for breakfast. This is not really a gripping exposé of a critical social issue, but is short and easy to engage with, and already provides some suprises when it comes to exploring the data. The materials provided include individual transcribed sources of text, in a variety of formats that can be brought into Quirkos. The idea is that users can learn how to bring sources into Quirkos, create a basic coding framework, and get going on coding data.

For the impatient, there is also a 'here's one we created earlier' file, in which all the sources have been added to the project, described age and gender and occupation as source properties, a completed framing codework, and a good amount of coding. This is a good starting point if someone wants to use the various tools to explore coded data and generate outputs. There is also a sample report, demonstrating what a default output looks like when generated by Quirkos, including the 'data' folder, which includes all the pictures for embedding in a report or PowerPoint presentation.


This is the example project we most frequently use in workshops. It allows us to quickly cover all the major steps in qualitative analysis with software, with a fun and easy to understand dataset. It also lets us see some connections in the data, for example how people don't describe coffee as a healthy option, and that women for some reason talk about toast much more than men.


However, the breakfast example is not real qualitative data - it is short, and fictitious, so for people who come along to our more advanced analysis workshops, we are happy to now make available a much more detailed and lively dataset. We have recently completed a project on the impact on voter opinions in Scotland after the 2014 Referendum for independence. This comprises of 12 semi-structured interviews with voters based in Edinburgh, on their views on the referendum process, and how it has changed their outlook on politics and voting in the run-up to the 2015 General Election in the UK.


When we conducted these interviews, we explicitly got consent for them to be made publicly available and used for workshops after they had been transcribed and anonymised. This gives us a much deeper source of data to analyse in workshops, but also allows for anyone to download a rich set of data to use in their own time (again with any qualitative software package) to practice their analytical skills in qualitative research. You can download these interviews and further materials at this link.


We hope you will find these resources useful, please acknowledge their origin (ie Quirkos), let us know if you use them in your training and learning process, and if you have any feedback or suggestions.