10 reasons to try qualitative analysis with Quirkos

10 quirkos qualitative bubbles

Quirkos is the newest qualitative research software product on the market, but what makes it different, and worth giving the one-month free trial a go? Here’s a guide to the top 10 benefits to switching to Quirkos:

 

1. Ease of Use
When we ask people what they like most about Quirkos, we hear one word: ‘intuitive’. We find that most people can get going after just watching a 5 minute video, since the interface is so graphical.


2. Everything is Visual
Bubbles grow as data is added. Colours help your group your themes, and clusters move bubbles together as connections emerge. Graphs show you key stats from your sources. This is not like working with a spreadsheet, Quirkos turns exploring text into an immersive process.


3. Speed of coding
Researchers spend most of their time coding sections of text, so we try and make it as quick as possible. Adding text to a theme is a simple drag and drop operation, but there are also keyboard shortcuts that can make adding text to multiple themes a breeze (or a whirlwind!).


4. Visual exploration
Of course Quirkos has great tools to explore your data once it is coded. But they are all based around visual feedback, giving you an instinctive feel for emerging findings. For example, side-by-side comparisons let you see how different groups of participants are responding.


5. Custom reports
Your work is not useful unless you can share the results. Our reports are very customisable, letting you choose which sections and detail to show, and naturally are full of graphical ways to represent your text data.


6. Connect with other applications
Researchers need to be flexible in how they work, which is why Quirkos supports bringing text in from all kinds of software like Word, PDFs and on-line survey platforms. But it also lets you get data out as well, to explore further in Excel, SPSS or even back to Word.


7. Free training and support
All our support options are available on-line with no subscription or fee. This includes detailed manuals, one-minute video guides, and interactive tutorials, as well as example projects to experiment with. Save time and money in training with software you can teach yourself. If you get stuck, e-mail or Skype the developers directly: qualitative researchers who are there to make your research go smoothly.


8. Cross-platform with no bumps
Work on Windows, Mac or Linux with an identical interface and features everywhere. You can save work on one system and keep going on another with no issues.


9. Cheap as chips
We think we are the cheapest qualitative software around, especially for our student licence. Also, our licences don’t expire, so you can keep working on your data for year after year.


10. Try for free
Our free trial is exactly the same as the full version, and gives you a month to try before you buy. If you like working with Quirkos, you can just buy and enter the licence code, and away you go.


We are proud of our software, which is why we always like people to try before they buy, and see the benefits for themselves. Download the free trial from here, and make your qualitative analysis a less stressful process!

 

Fracturing and choice in qualitative analysis software

broken glass CC by Jef Poskanzer

 

Fundamental to the belief behind starting Quirkos was a feeling that qualitative research has great value to society, but should be made accessible to more people. One of the problems that we frequently saw with this was the difficulty that qualitative researchers had in choosing and using qualitative analysis software. Choice is great, but social scientists have to choose between many different software packages, and IT departments have to provide installations and technical support for the systems that different users want.


This month the market leader QSR International will release a new version of their Nvivo software for Windows, with a very different model – it will be split into three different versions, ‘Starter’, ‘Pro’ and ‘Plus’. Each version has a different features enabled or disabled, and will be offered at a different price point. This seems potentially laudable, for example introducing a new basic version that is (hopefully) cheaper, should allow more people access to this well-known qualitative software.


However, it also seems to greatly complicate the position for users, systems administrators and educators, who now have to deal with no less than five different versions of Nvivo! In addition to the Starter, Pro and Plus for Windows, there is a separate version for Mac (with different capabilities, interface and file format), as well as the server based Nvivo for Teams. It raises many difficult questions: Where should new users start? What versions should institutions and IT departments purchase and support? How can those offering training provide sessions that will be useful to all these disparate users?


At the same time, I understand that the new Windows versions have had all the icons redesigned, breaking continuity for existing users, and instantly making textbooks and teaching materials obsolete (yet again: I remember the complaints about the new layout when the last-but-one version of Nvivo came out). Of course guides always need to be updated to take account of new features, but changing the icons means that materials covering even basic functions will need to be reworked, or will become confusing.


Obviously I am discussing a competitor’s project here, but one that I find useful, and have personally used many times in different research projects. I can’t help the feeling that the additional fracturing of the Nvivo user-base will further complicate the situation for end users, especially those in large organisations. These may or may not upgrade to the latest version, and I know there is always a few years of grief trying to work with other teams who have a different and incompatible version, as well as finding training for the version you are working with.  But in addition, it may not always be clear for students what version their department has access to (or that they can take home), and so which features will be available to them.


Yet it doesn’t have to be this way, MAXQDA for example manages to provide the same software for Windows and Mac, with the same interface and compatible files. Yes, they also have options for a ‘pro’ and ‘free’ read-only version, but I feel the differentials are much clearer, and from a IT and support point of view, rollout is much simpler.


Quirkos continues to have just one version of the software, offering all the same features to everyone. It also has exactly the same capabilities and interface on all platforms, Windows, Mac and Linux, and uses files that are an open standard, and immediately compatible across all operating systems. We also make our updates free, to help everyone to work on the same version of the software, and don’t break compatibility with older versions! We think that this is the best way to develop and release software, and will continue to do so – none of our users will be seen as poor-cousins.

 

Levels: 3-dimensional node and topic grouping in Quirkos

levels and groups in Quirkos

 

One of the biggest features enabled in the latest release of Quirkos are 'levels', a new way to group and sort your Quirks thematically. While this was always an option in previous versions, they are now fully integrated into the search and query views, making them much more useful. However, this is a tricky thing to describe conceptually, so this post will give a few use-case scenarios.

 

In Quirkos, the topics or themes that you code to (called nodes in Nvivo) are represented as bubbles. These can be moved around the canvas to be grouped by location, given similar colours, or arranged alphabetically or by size. However, they can also be grouped into topics with sub categories, by dragging a bubble onto another one. This creates a parent-child relationship where the parent category, say 'Drinks' can have any number of sub-categories, such as Juice, Tea, Water etc. It is also possible to have sub-sub categories (grandchildren), so in this example, you might have types of Juice such as Orange, Apple and Cranberry.

 

So far so good – this allows you to quickly see the quotes you assigned to all types of Drinks, or just the Juices using the Hierarchy view. However, this parent-child grouping has a limitation, in that a sub category, say Orange Juice, cannot belong to more than one parent. So we can't describe Orange Juice as being a type of Drink, as well as a form of Fruit.

 

This is where the 'level' function comes in. A Quirk can belong to any number of levels, which can contain any number of Quirks. So if you created a level called Fruit, by right clicking on any Quirk, selecting the Quirk Properties, you will see all the levels defined in the project, and the Quirk can belong to any number of them. So Orange Juice can belong to a level called 'Fruit', along with Apples, and Oranges, while also being defined as a sub-category of Drink. Alternatively, you could have a level for Drink, and describe some Quirks as being a Drink as well as a Fruit.

 

The other way that the levels can be helpful is when working on a large project that might have multiple outputs. If you are working on a PhD thesis, or a long report, you might have chapters that only cover certain themes. With the levels function, you can define Quirks that will be relevant to a particular chapter or topic, and see results or reports for just that level. This way, if you are writing about nutrition, the Orange Juice theme can belong to the chapter for Drink and for Fruit, and you will see relevant quotes for each chapter.

 

To work with levels, just right or long click on any Quirk, and select the Quirk properties. In this box you will see a button for 'Levels Editor', this can be used to define, change or remove levels in the project. Click Save once you are done. Once some levels have been created, you can use the slide toggles shown above in the Quirk Properties dialogue to assign that Quirk to any number of levels. You will obviously need to go though and do this for all the Quirks in the project you want to put into a level.

 

the levels assignment in quirk properties

 

Once you have done this, you can choose the corresponding level as a filter option in the Query view (LV) or in the search results, to generate reports or see text search results from text coded in one or more levels.

 

Everyone likes to work with their themes or nodes differently, and now we have many more ways to group and sort them. You can arrange them physically around the canvas, give them meaningful colours, create a grouped stack with sub-category relationships, and also group them by 'level' like an overlapping Venn diagram.

 

We are going to improve the ways you can work with levels in the future, including visualisations of levels on the canvas, but we want your feedback for the best way you would like to see this! Should Quirks belonging to a level get a certain colour halo, or be shown in a literal 3D level view like levels in a building? Should the canvas rearrange on command to group all Quirks belonging to certain levels together? Is the term 'levels' the right one to use in this situation? The more people are using Quirkos, the more different ways people are working with it, and we want to choose the best and most flexible ideas, so let us know!

 

 

Quirkos for Linux!

quirkos loves linux

 

We are excited to announce official Quirkos support for Linux! This is something we have been working on for some time, and have been really encouraged by user demand to support this Free and Open Source (FOSS) platform. Quirkos on Linux is identical to the Windows and Mac versions, with the same graphical interface, feature set and file format, so there are no issues working across platforms.


Currently we are only offering a script based installer, which can be downloaded from the main download page. In the future we may try and offer some packaged based deb or rpm downloads, but for the moment there are two practical reasons this is not feasible. First, it is much easier for us to provide one installer that should work on all distributions, regardless of what package manager is utilised. Secondly, Quirkos is build using the latest version of Qt (5.5) which is not yet supported in most stable distributions yet. This would either lead to dependency hell, or users having to install Qt5.5 libraries manually (which actually take up a lot of space, and are themselves based around a script based installer). However, we will revisit this in the future if there is sufficient demand.

 

Most dependencies can be solved by installing qt5 from your repository, although most KDE desktops will already have many of the required packages.

 

Once downloaded, you must make the installer file executable. There are two ways to do this, either by running “chmod +x  quirkos-1.3-linux-installer.run” from the shell in the directory containing the installer, or an alternative GUI based method in Gnome is to right click on the file in the Nautilus file browser, select the properties tab, and then tick the 'Allow executing file as program' box.


Once you've done this, either double click on the file, or run in the bash terminal with “./quirkos-1.3-linux-installer.run”. Of course, if you want to install to a system wide folder (such as /opt/bin) you should run the installer with root permissions. By default Quirkos will install in the user's home folder, although this can be changed during the install process. An uninstaller is also created, but all files are contained in the root Quirkos folder, so deleting the folder will remove everything from your system. After installing, a shortcut will be created on the desktop (on Ubuntu systems) which can be used to run Quirkos, or dragging the icon to the Unity side-bar will keep the launcher in an accessible place. Otherwise, run the Quirkos.sh file in the Quirkos folder to start the application.


If you are looking for FOSS software for qualitative research, try RQDA, an extension for the versatile R statistical package, an open source alternative to SPSS. There is also Weft QDA, although this doesn't seem to have been updated since 2006. It's worth noting that both have fairly obtuse interfaces, and are not well suited for beginners!


We have tested Quirkos on numerous different systems, but obviously we can't check all iterations. So if you have any problems or issues, PLEASE let us know, this is new ground for us, and indeed is the first 'mainstream' qualitative analysis software to be offered for Linux. In fact, tell us if it all works fine as well – the more we hear people are using Quirkos on Linux, the better!

 

 

Quirkos 1.3 is released!

Quirkos version 1.3 on Linux

We are proud to announce a significant update for Quirkos, that adds significant new features, improves performance, and provides a fresh new look. Major changes include:

  • PDF import
  • Greater ability to work with Levels to group and explore themes
  • Improved performance when working with large projects
  • New report generation and styling
  • Ability to copy and paste quotes directly from search and hierarchy views
  • Improved CSV export
  • New tree-hierarchy view for Quirks
  • Numerous bug fixes
  • Cleaner visual look

 

We’ve made a few tweaks to the way Quirkos looks, tidying up dialogue boxes and improving the general style and visibility, but maintaining the same layout, so there is nothing out of place for experienced users.

 


There is once again no change to Quirkos project files, so all versions of Quirkos can talk to each other with no issues, and there is no need to do anything to your files – just keep working with your qualitative data. The update is free for all paid users, and a simple process to install. Just download the latest version, install to the same directory as the last release, and the new version will replace the old. There is no need to update the licence code, and we would recommend all users to move to the new version as soon as they can to take advantage of the improvements!

 


Lots of people have requested PDF support, so that users can add journal articles and PDF reports into Quirkos, and we are happy to say this is now enabled. Please note that at the moment PDF support is limited to text only – some PDF files, especially from older journals that have been scanned in are not actually stored as text, but as a scanned image of text. Quirkos can’t read the text from these PDFs, and you will usually need to use OCR (optical character recognition) software to convert these (included in some professional editions of Acrobat Reader for example).

 


We have always supported ‘Levels’ in Quirkos, a way to group Quirks that can work across hierarchical groupings and parent-child relationships. Many people desired to work with categories in this way, so we have improved the ways you can work with levels. They are now a refinable category in search results and queries, allowing you to generate a report containing data refined by level, and a whole extra dimension to group your qualitative themes.

 


Reports have been completely revamped to improve how you share qualitative data, with better images, and a simpler layout. There are now many more options for showing the properties belonging to each quote, streamlined and grouped section headings, better display of hierarchial groupings, and a much more polished, professional look. As always, our reports can be shared as PDF, interactive HTML, or customised using basic CSS and Javascript.

 


Although the canvas view with distinctive topic bubbles is a distinguishing feature in Quirkos, we know some people prefer to work with a more traditional tree hierarchy view. We’ve taken on board a lot of feedback, and reworked the ‘luggage label’ view to a tree structure, so that it works better with large numbers of nodes. The hierarchy of grouped codes in this view has also been made clearer.

 


There are also numerous bug fixes and performance improvements, fixing some issues with activation, improving the speed when working with large sources, and some dialogue improvements to the properties editor on OS X.

 

We are also excited to launch our first release for Linux! Just like all the other platforms, the functionality, interface and project files are identical, so you can work across platforms with ease. There will be a separate blog post article about Quirkos on Linux tomorrow.

 


We are really excited about the improvements in the new version, so download it today, and let us know if you have any other suggestions or feedback. Nearly all of the features we have added have come from suggestions made by users, so keep giving us your feedback, and we will try and add your dream features to the next version...

 

 

Bing Pulse and data collection for market research

bing pulse example

 

Judging by the buzz and article sharing going on last week, there was a lot of interest and worry about Microsoft launching their own market research platform. Branded as part of ‘Bing’, their offering, called ‘Pulse’ has actually been around for a while, and is still geared around collecting feedback from live events, especially political discussions.


I can see why this move might have a lot of companies worried, it seems to me that the market research arena is crowded with start-ups and established firms offering platforms, or ‘communities’ for collecting participant data. There’s LiveMinds, Aha!, VisionLive, a quick search will bring up dozens of competitors. So an entry into the market from an organisation with deep pockets and brand awareness like Microsoft may well have many looking to see how this develops. However, with my own limited time with Pulse, I don’t think there is much to worry about yet.


First of all, Pulse is currently entirely focused on one niche, feedback on live events. There are no tools to do anything like advert or creatives validation, no proper survey tools or interactive online focus groups. The MO is very much quantitatively focused, with very little option to capture qualitative feedback at this time. Secondly, it seems to have a lot of limitations, and in this beta state, almost no documentation.


I quickly got stuck trying to create a real-time voting question, with a mandatory box for ‘response theme’ that was greyed out, but wouldn’t continue without being completed. The ‘help’ tools just link to a generic Bing help website, which don’t contain any content about Pulse. The layout is a little confusing, getting you stuck in a strange loop between the ‘Live Dashboard’ and ‘Pulse Options’, and it’s also slow: get used to seeing the little flapping loading logo after every action.

 

As for integration, the only option at the moment seems to be the API, which only has four available calls. There doesn’t seem to be any way to get results (especially those not covered by those API calls) out from the platform: I can’t see any CSV export or the like. Also, considering the powerful analytic options available through the Azure platform, it’s disappointing not to see any easy integration there. In short, far from being a quick DIY solution, you will need someone to programme yet another API into your platform to do anything more than look at a few graphs on the Pulse platform.

 

I want to stress that this was hardly a detailed review and test of the capabilities of the platform, my opinions are based just on playing with it for an hour or so. However, it is nice to be able to try it out with just a registration, personally I don’t like products where the demo is locked away and difficult to try out. It’s a competitive market, and I feel more inclined to trust software that the developers aren’t shy of showing off!

 

Now, I understand that most market research providers are not so much worried about the current feature set of Pulse, but what this entry into the field means in the future, especially for a product that Microsoft is content to offer for free at this time. But I would echo some of the comments made in the Greenbook article by Leonard Murphy, that it usually doesn’t make sense for market research firms to do their own their own quantitative data collection. The future, he says, is integrating with data collection tools and adding value in terms of insight, custom development and consultation.


And that is the crux with all these market research platforms: they are primarily data collection tools, with limited analytics. Pulse doesn’t seem to have anything on this front at the moment, but with too many of these solutions, the insight stops with a couple of graphs or statistics. I feel there is still the need to integrate with another tool, or draw from extensive market research analytic experience to make anything from the data once it has been collected. It maybe that most clients don’t expect or require any kind of rigour in the breakdown of project results, especially when it comes to qualitative data. I am still yet to see anything that looks to me like a true end-to-end platform for market research, but am willing to be proved wrong!

 

At the moment, there are some great and flexible tools for collecting customer data online, be it quantitative or qualitative. But these are ubiquitous, and very cheap to run – we host an online survey platform for our customers for free, just as a convenience. Yet getting to answers and insight from that data usually requires an additional analytical step, especially for qualitative research. As I’ve said before,  the most difficult step is understanding the data and how you integrate analytics into your workflow. Increasingly the data collection platform you choose, and how much you pay for it will not be an issue.

 

 

What can CAQDAS do for you? The Five-Level QDA

five level qda

 

I briefly mentioned in my last blog post an interesting new article by Silver and Woolf (2015) on teaching QDA (Qualitative Data Analysis) and CAQDAS (Computer Assisted Qualitative Data AnalysiS). It’s a great article, not only because it draws from more than 20 years combined pedagogical experience, but suggests a new way to guide students through using software for qualitative analysis.

 

The basis of the strategy is the ‘Five-Level QDA’ approach, which essentially aims to get students to stop and think about how they want to do their qualitative analysis before they dive head-first into learning a particular CAQDAS package. Users are guided through a five-step tool that I would paraphrase as:

 

  1. Stating the analysis/research objectives
  2. Devising an analytic plan
  3. Identifying matches between the plan and available tools
  4. Selecting which operations to do in which tools
  5. Creating a workflow of tools and software to meet all the aims above


For more detail, it’s worth checking out the full article which includes example worksheets, and there is also a textbook due out covering the approach in more depth. It’s also interesting to see how they describe the development of their pedagogical approach in the last decade or so.

 

The Five-Level method is designed to be delivered remotely, as well as in workshops, but to start out with being a software agnostic approach, drawing from the experience of the trainers to choose the best approach for each researcher and research project. Based around Analytic Planning Worksheets, it feels like the main aim is to get people to step back and think about their needs before learning the software.

 

This is often badly needed, mostly due to the practical limitations. Firstly, many people (especially new researchers) don’t do a detailed analytical plan when designing their project or research questions. In qualitative research, this is not always a disaster, often one source of investigation ends up being much richer than anticipated, and the variety of methods used mean that data doesn’t always look as we thought it would when we started (for better or worse).

 

However, there are also some very practical limitations which lead to people learning a CAQDAS package before they start their research journey. Often training courses are only offered once a semester (or year), so you need to take advantage of that when you can. While ideally there would be an interactive process between learning the capabilities and refining the analytical strategy, in the timescale of one project this is not always feasible. Often people have learnt so much after their first qualitative project, that the next time their analytical approach is extremely different.

 

The other issue is what CAQDAS is actually available: often a department or school will have a licence for just one (or maybe two) packages, and understandably, the training offered will often focus on those. There are also practical limitations when working as part of a team (especially people in a different institution) who might not have access to the same software. This affects the approach a lot, because it’s important to choose a workflow that everyone can participate in. I’ve been involved in projects where we end up using Excel for analysis, because everyone had access and familiarity with spreadsheet software.

 

I think that this is the kind of consideration that the Silver and Woolf worksheets are trying to tease out, and their examples illustrate how by point 5 people have chosen a number of tools that they can use together to answer their research questions.

 

As a final point, I think that RTP (Research Training Programmes) courses offered for post-grad students sometimes leave a lot to be desired on this front. Even those that are specifically on qualitative methodologies (where available) tend in my experience to have little more than a slide on the whole analysis process, and sometimes just a bullet point on software! I spend a lot of time talking to people about CAQDAS, and I am always surprised at how few people have heard even of NVivo, let alone a dozen alternative packages that I could name off the top of my head. Yet each has its own strengths and weaknesses: Transana is great for video, the Provalis products for stats geeks, MaxQDA a friendly all-rounder, Dedoose for working remotely, and Quirkos obviously for beginners.

 

But it’s a chicken and egg problem – to know what which software is best, you need to know what you can do with it. Which is why it can help so much to draw on the experience of CAQDAS trainers, but not just to go on a course and learn one package, but to go with an open mind and a research question, and let them suggest the best combination for each approach. In short, ask not what your CAQDAS can do for you, ask what you want to do with your CAQDAS!

 

Update (14/8/15):

 

Christain Schmieder has written a response to this blog post and the 5-level QDA, and how it links into his curriculum for qualitative question generation using CAQDAS.

 

 

The CAQDAS jigsaw: integrating with workflows

 

I’m increasingly seeing qualitative research software as being the middle piece of a jigsaw puzzle that has three stages: collection, coding/exploring, and communication. These steps are not always clear cut, and generally there should be a fluid link between them. But the process, and enacting of these steps is often quite distinct, and the more I think about the ‘typical’ workflow for qualitative analysis, the more I see these stages, and most critically, a need to be flexible, and allow people different ways of working.

 

At any stage it’s important to choose the best tools (and approach) for the job. For qualitative analysis, people have so many different approaches and needs, that it’s impossible to impose a ‘one-size-fits-all’ approach. Some people might be working with multimedia sources, have anything from 3 to 300 sources, and be using various different methodological and conceptual approaches. On top of all this are the more mundane, but important practical limitations, such as time, familiarity with computers, and what software packages their institution makes available to them.

 

But my contention is that the best way to go about facilitating a workflow is not to be a jack-of-all trades, but a master of one. For CAQDAS (Computer Assisted Qualitative Data AnalysiS) software, it should focus on what it does best: aiding the analysis process, and realise that it has to co-exist with many other software packages.

 

For the first stage, collection and transcription of data, I would generally not recommend people use any CAQDAS package. If you are recording transcripts, these are best done on a Dictaphone, and transcribing them is best done in proper word-processing software. While it’s technically possible to type directly into nearly all CAQDAS software tools (including Quirkos), why would you? Nearly everyone has access to Word or LibreOffice, which gives excellent spell-checking tools for typos, and much more control over saving and formatting each source. Even if you are working with multimedia data, you are probably going to trim audio transcripts in Audacity (or Pro-Tools), and resize and colour correct pictures in Photoshop.

 

So I think that qualitative analysis software needs to recognise this, and take in data from as many different sources as possible, and not try and tie people to one format or platform. It’s great to have tight integration with something like Evernote or SurveyMonkey, but both of those cost extra, and aren’t always the right approach for people, so it’s better to be input-agnostic.

 

But once you’ve got data in, it’s stage 2 where qualitative software shines. CAQDAS software is dedicated to the coding and sorting of qualitative data, and has tools and interfaces specifically designed to make this part of the process easier and quicker. However, that’s not how everyone wants to work. Some people are working in teams where not everyone has access to CAQDAS, and others prefer to use Word and Excel to sort and code data. That should be OK too, because for most people the comfortable and familiar way is the easiest path, and what it’s easy to forget as a software developer is that people want to focus on the data and findings, not the tools and process.

 

So CAQDAS should ideally be able to bring in data coded in other ways, for people that prefer to just do the visualisation and exploration in qualitative software. But CAQDAS should also be able to export coded data at this stage, so that people can play with the data in other ways. Some people want to do statistical analysis, so it should connect with SPSS or R. And it should also be able to work with spreadsheet software, because so many people are familiar with it, and it can be used to make very specific graphs.

 

Again, it’s possible to do all of this in most CAQDAS software, but I’ve yet to see any package that gives the statistical possibilities and rigour that R does, and while graphs seem to get prettier with every new version, I still prefer the greater customisation and export options you get in Excel.

 

The final stage is sharing and communicating, and once again this should be flexible too. Some people will have to get across their findings in a presentation, so generate images for this. Many will be writing up longer reports, so export options for getting quotes into word-processing software is essential again. At this stage you will (hopefully) be engaging with an ever widening audience, so outputs need to be completely software agnostic so everyone can read them.

 

When you start seeing all the different tools that people use in the course of their research project, this concept of CAQDAS being a middle piece of the puzzle becomes really clear, and allowing people flexibility is really important. Developing CAQDAS software is a challenge, because everyone has slightly different needs. But the solution usually seems to be more ways in, and more ways out. That way people can rely on the software as little or as much as they like, and always find an easy way to integrate with all the tools in their workflow.

 

I was inspired to write this by reading a recent article on the Five-level QDA approach, written by Christine Silver and Nick Woolf. They outline a really strong ‘Analytic Planning Worksheet’ that is designed to get people to stop and break down their analytical tasks before they start coding, so that they can identify the best tools and process for each stage. This helps researchers create a customisable workflow for their projects, which they can use with trainers to identify which software is best for each step.

 

Next week, I’m going to write a blog post more specifically about the Five-level QDA, and pedagogical issues that the article raises about learning qualitative research software. Watch this space!

 

 

Using Quirkos for fun and (extremely nerdy) projects

This week, something completely different! A guest blog from our own Kristin Schroeder!

 

Most of our blog is a serious and (hopefully) useful exploration of current topics in qualitative research and how to use Quirkos to help you with your research. However we thought it might be fun to share something a little different.


I first encountered qualitative research in a serious manner when I joined Quirkos in January this year, and to help me get up to speed I tried to code a few things to help me understand the software.
One of the texts I used was a chapter from The Lord of the Rings, because, I thought, with something I already know like the back of my hand I could concentrate on the mechanics of coding without being distracted too much by the content.


I chose ‘The Council of Elrond’ – one of the longest chapters in the book and one often derided for being little more than an extended information dump. Essentially lots and lots of characters (some of whom only appear in this one scene in the whole book) sit around and tell each other about stuff that happened much earlier. It’s probably not Tolkien’s finest writing, and I suppose, most modern editors would demand that all that verbal exposition should either be cut or converted into actual action chapters.


I have always loved the Council chapter, however, as to me it’s part of the fascinating backdrop of the Lord of the Rings. As Tolkien himself puts it in one of his Letters:


“Part of the attraction of the L.R. is, I think, due to the glimpses of a large history in the background: an attraction like that of viewing far off an unvisited island, or seeing the towers of a distant city gleaming in a sunlit mist.”


Of course, if you are a Tolkien fan(atic) you can go off and explore these unvisited islands and distant cities in the Silmarillion and the Histories of Middle Earth, and then bore your friends by smugly explaining all the fascinating First and Second Age references, and just why Elrond won’t accept an Oath from the Fellowship. (Yes, I am guilty of that…)


Looking at the chapter using Quirkos I expected to see bubbles growing around the exchange of news, around power and wisdom, and maybe to get some interesting overlap views on Frodo or Aragorn. However, the topic that surprised me most in this chapter in particular was Friendship.


I coded the topic ‘Friendship’ 29 times – as often as ‘Relaying News’ and ‘History’, and more often even than collective mentions of Elves (27), Humans (19) or the Black Riders (24).


The overlap view of ‘Friendship’ was especially unexpected:

 

The topics ‘Gandalf’ and ‘Friendship’ overlap 22 times, which is not totally surprising since Gandalf does most of the talking throughout the chapter, and he is the only character who knows everyone else in the Council already. But the second most frequent overlap is with Elrond: he intersects with Friendship eight times, which is more often than Frodo who only gets five overlaps with Friendship!


Like most of the Elves in Lord of the Rings, Elrond is rather aloof and even in his own council acts as a remote facilitator for the other characters. Yet, the cluster view on Friendship led me to reconsider his relationship not only with Gandalf (when Gandalf recites the Ring inscription in the Black Speech, he strongly presumes on Elrond’s friendship, and Elrond forgives him because of that friendship) but also with Bilbo.


Re-reading Elrond’s exchanges with Bilbo during the Council, I was struck by the gentle teasing apparent in the hobbit’s reminders of his need for lunch and Elrond’s requests that Bilbo should tell his story without too many embellishments and it need not be in verse. The friendship between Bilbo and Elrond also rather explains how Bilbo had the guts to compose and perform a song about Elrond’s father Eärendil in the previous chapter, something even Aragorn, Elrond’s foster son, described as a daring act.


Perhaps none of this is terribly surprising. Within the unfolding story of the Lord of the Rings, Bilbo has been living in Elrond’s house for 17 years - time enough even for busy Elflords to get to know their house guests. And for readers who grew up with the tale of The Hobbit, Bilbo’s centrality may also not be much of a surprise. For me, however, looking at the chapter using Quirkos opened up a rather pleasing new dimension and led me to reconsider a couple of beloved characters in a new light.

 

 

Participatory Qualitative Analysis

laptops for qualitative analysis

 

Engaging participants in the research process can be a valuable and insightful endeavour, leading to researchers addressing the right issues, and asking the right questions. Many funding boards in the UK (especially in health) make engaging with members of the public, or targets of the research a requirement in publicly funded research.

 

While there are similar obligations to provide dissemination and research outputs that are targeted at ‘lay’ members of the public, the engagement process usually ends in the planning stage. It is rare for researchers to have participants, or even major organisational stakeholders, become part of the analysis process, and use their interpretations to translate the data into meaningful findings.

 

With surprisingly little training, I believe that anyone can do qualitative analysis, and get engaged in actions like coding and topic discovery in qualitative data sets.

 

I’ve written about this before but earlier this year we actually had a chance to try this out with Quirkos. It was one of the main reasons we wanted to design new qualitative analysis software; existing solutions were too difficult to learn for non-expert researchers (and quite a lot of experienced experts too).

 

So when we did our research project on the Scottish Referendum, we invited all of the participants to come along to a series of workshops and try analysing the data themselves. Out of 12, only 3 actually came along, but none of these people had any experience of doing qualitative research before.

 

And they were great at it!

 

In a two hour session, respondents were given a quick overview of how to do coding in Quirkos (in just 15 minutes), and a basic framework of codes they could use to analyse the text. They were free to use these topics, or create their own as they wished – all 3 participants chose to add codes to the existing framework.

 

They were each given transcripts from someone else’s anonymised interview: as these were group sessions, we didn’t want people to be identified while coding their own transcript. Each were 30 minute interviews, around 5000 words in length. In the two hour session, all participants had coded one interview completely, and done most (or all) of the second. One participant was so engrossed in the process, he had to be sent home before he missed his dinner, but took a copy of Quirkos and the data home to keep working on his own computer.

 

The graph below shows how quickly the participants learnt how to code. The y axis shows the number of seconds between each ‘coding event’: every time someone coded a new piece of text (and numbered sequentially along the x axis). The time taken to code starts off high, with questions and missteps meaning each event takes a minute or more. However, the time between events quickly decreases, and in fact the average time for the respondents was to add a code every 20 seconds. This is after any gaps longer than 3 minutes have been removed – these are assumed to be breaks for tea or debate! Each user made at least 140 tags, assigning text to one or more categories.

 

 

So participants can be used as cheap labour to speed up or triangulate the coding process? Well, it can be more than this. The topics they chose to add to the framework (‘love of Scotland’, ‘anti-English feelings’, ‘Scottish Difference’) highlighted their own interpretations of the data, showing their own opinions and variations. It also prompted discussion with other coders, about what they thought about the views of people in the dataset, how they had interpreted the data:


“Suspicion, oh yeah, that’s negative trust. Love of Scotland, oh! I put anti-English feelings which is the opposite! Ours are like inverse pictures of each other’s!”

 

Yes: obviously we recorded and transcribed the discussions and reflections, and analysed them in Quirkos! And these revealed that people expressed familiar issues with reflexivity, reliability and process that could have come from experienced qualitative researchers:


“My view on what the categories mean or what the person is saying might change before the end, so I could have actually read the whole thing through before doing the comments”


“I started adding in categories, and then thinking, ooh, if I’d added that in earlier I could actually have tied it up to such-and-such comment”


“I thought that bit revealed a lot about her political beliefs, and I could feel my emotions entering into my judgement”


“I also didn’t want to leave any comment unclassified, but we could do, couldn’t we? That to me is about the mechanics of using the computer, ticky box thing.”

 

This is probably the most useful part of the project to a researcher: the input of participants can be used as stimulus for additional discussion and data collection, or to challenge the way researchers do their own coding. I found myself being challenged about how I had assigned codes to controversial topics, and researchers could use a more formal triangulation process to compare coding between researchers and participants, thus verifying themes, or identifying and challenging significant differences.

 

Obviously, this is a tiny experimental project, and the experience of 3 well educated, middle-class Scots should not be interpreted as meaning that anyone can (or would want to) do this kind of analysis. But I believe we should do try this kind of approach whenever it is appropriate. For most social research, the experts are the people who are always in the field – the participants who are living these lives every day.

 

You can download the full report, as well as the transcripts and coded data as a Quirkos file from http://www.quirkos.com/workshops/referendum/