Quirkos v1.5 is here

Quirkos 1.5 word cloud

 

We are happy to announce the immediate availability of Quirkos version 1.5! As always, this update is a free upgrade for everyone who has ever brought a licence of Quirkos, so download now and enjoy the new features and improvements.

 

Here’s a summary of the main improvements in this release:

 

Project Merge


You can now bring together multiple projects in Quirkos, merge sources, Quirks and coding from many authors at once. This makes team work much easier, and allows you to bring in coding frameworks or sources from other projects.

 

Word Frequency tools including:
 

Word-clouds! You can now generate customisable Word Clouds, (click on the Report button). Change the shape, word size, rotation, and cut-off for minimum words, or choose which sources to include. There is also a default ‘stop list’ (a, the, of, and) of the most frequent 50 words from the British National Corpus, but this can be completely customised. Save the word-clouds to a standard image file, or as an interactive webpage.referednum wordcloud
A complete word frequency list of the words occurring across all the sources in your project is also generated in this view.

  • Improved Tree view – now shows longer titles, descriptions and fits more Quirks on the screen
  • Tree view now has complete duplicate / merge options
  • Query results by source name – ability to see results from single or multiple sources
  • Query results now show number of quotes returned
  • Query view now has ‘Copy All’ option
  • Improved CSV spreadsheet export – now clearly shows Source Title, and Quirk Name
  • Merge functions now more logical – default behaviour changed so that you select the Quirk you want to be absorbed into a second.
  • Can now merge parent and child Quirks to all levels
  • Hovering mouse over Quirks now shows description, and coding summary across sources
  • Reports now generate MUCH faster, no more crashes for projects with hundreds of Quirks. Image generation of hierarchy and overlap views now off by default, turn on in Project Settings if needed
  • Improved overlap view, with rings indicating number of overlaps
  • Neater pop-up password entry for existing projects
  • Copy and pasting quotes to external programmes now shows source title after each quote
  • Individually imported sources now take file name as source name by default

 

Bug fixes

  • Fixed a bug where Quirks would suddenly grow huge!
  • Fixed a rare crash on Windows when rearranging / merging Quirks in tree view
  • Fixed a rare bug where a Quirk was invisible after being re-arranged
  • Fixed an even rarer bug where deleting a source would stop new coding
  • Save As project now opens the new file after saving, and no longer shows blank screen
  • Reports can now overwrite if saved to the same folder as an earlier export
  • Upgrading to new versions on Windows only creates a backup of the last version, not all previous versions, lots of space savings. (It’s safe to delete these old versions once you are happy with the latest one)

 

Watch the new features demonstrated in the video below:

 

 

There are a few other minor tweaks and improvements, so we do recommend you update straight away. Everyone is eligible, and once again there are no changes to project files, so you can keep going with your work without missing a beat. Do let us know if you have any feedback or suggestions (support@quirkos.com)

 

Download quirkos free qualitative analysis software

 

If you've not tried Quirkos before, it's a perfect time to get started. Just download the full version and you'll get a whole month to play with it for free!

 

Quirkos v1.4.1 is now available for Linux

quirkos for linux

 

A little later than our Windows and Mac version, we are happy to announce that we have just released Quirkos 1.4.1 for Linux. There are some major changes to the way we release and package our Linux version, so we want to provide some technical details of these, and installation instructions.


Previously our releases had a binary-based and distro independent installer. However, this was based on 32 bit libraries to provide backwards compatibility, and required a long list of dependencies to work on many systems.


From this release forward, we are releasing Quirkos as an AppImage – a single file which contains a complete image of the software. This should improve compatibility across different distros, and also remove some of the dependency hell involved in the previous installer.


Once you download the .AppImage file, you will need to give the file executable permissions (a standard procedure when downloading binaries). You can do this at the command-line just by typing ‘chmod +x Quirkos-1.4.1-x86_64.AppImage’. This step can also be done with a File Manager GUI like Nautilus (the default in Gnome and Ubuntu) by right clicking on the downloaded file, selecting the Permissions tab, and ticking the ‘Allow executing file as program’ box. Then you can start Quirkos from the command-line, or by double clicking on the file.


Since an AppImage is essentially a ‘live’ filesystem contained in a single file, there is no installation needed, and if you want to create a Desktop shortcut to the software stored in a different location, you will have to create one yourself.
 

Secondly, we have also moved to a 64 bit release for this version of Quirkos. While we initially wanted to provide maximum compatibility with older computers, this actually creates a headache for the vast majority of Linux users with 64 bit installations. They were required to install 32 bit libraries for many common packages (if they did not have them already), creating duplication and huge install requirements. Now Quirkos should run out-of-the-box for a vast majority of users.


Should you prefer the older 32 bit installer package, you can still download the old version from here:
https://www.quirkos.com/quirkos-1.4-linux-installer.run


Supporting Linux is really important to us, and we are proud to be the only major commercial qualitative software company creating a Linux version, let alone one that is fully feature and project compatible with the Windows and Mac builds. While there are great projects like RQDA which are still supported, TAMS Analyzer and Weft QDA have not been updated for Linux in many years, and are pretty much impossible to build these days. Dedoose is an option in Linux since it is browser based, but sometimes requires some tweaking to get Flash running properly. Adobe AIR for Linux is now no longer supported, so the Dedoose desktop App is sadly no longer an option.
 

But Quirkos will keep supporting Linux, and provide a real option for qualitative researchers wanting to use free and open platforms.


We REALLY would love to have your feedback on our new Linux release, positive, negative or neutral! We still have a relatively small number of users on Linux, so your experiences are extra important to us. Is the AppImage more convenient? Have you had any dependency problems? Would you prefer we kept providing 32bit packages? E-mail us at support@quirkos.com and let us know!

 

Comparing qualitative software with spreadsheet and word processor software

word and excel for qualitative analysis

An article was recently posted on the excellent Digital Tools for Qualitative Research blog on how you can use standard spreadsheet software like Excel to do qualitative analysis. There are many other articles describing this kind of approach, for example Susan Eliot or Meyer and Avery (2008). However, it’s also possible to use word processing software as well, see for example this presentation from Jean Scandlyn on the pros and cons of common software for analysing qualitative data.

 

For a lot of researchers, using Word or Excel seems like a good step up from doing qualitative analysis with paper and highlighters. It’s much easier to keep your data together, and you can easily correct, undo and do text searches. You also get the advantage of being able to quickly copy and paste sections from your analysis into research articles or a thesis. It’s also tempting because nearly everyone has access to either Microsoft Office products or free equivalents like OpenOffice (http://www.libreoffice.org) or Google Docs and knows how to use them. In contrast, qualitative analysis software can be difficult to get hold of: not all institutions have licences for them, and they can have a steep learning curve or high upfront cost.

 

However, it is very rare that I recommend people use spreadsheets or word processing software for a qualitative research project. Obviously I have a vested interest here, but I would say the same thing even if I didn’t design qualitative analysis software for a living. I just know too many people who have started out without dedicated software and hit a brick wall.

 

 

Spreadsheet cells are not very good ways to store text.


If you are going to use Excel or an equivalent, you will need to store your qualitative text data in it somehow. The most common method I have seen is to keep quotes or paragraphs as a separate cell in a column for the text. I’ve done this in a large project, and it fiddly to copy and paste the text in the right way. You will also find yourself struggling with formatting (hint – get familiar with the different wrap text and auto column width options). It also becomes a chore to separate out paragraphs into smaller sections to code them differently, or merge them together. Also, if you have data in other formats (like audio or video) it’s not really possible to do anything meaningful with them in Excel.

 


You must master Excel to master your analysis

 

As Excel or other spreadsheets are not really designed for qualitative analysis, you need to use a bit of imagination to sort and categorise themes and sources. With separate columns for source names and your themes, this is possible (although can get a little laborious). However, to be able to find particular quotes, themes and results from sources, you will need to properly understand how to use Pivot Tables and filters. This will allow you some ability to manage and sort your coded data.

 

It’s also a good idea to get to grips with some of the keyboard shortcuts for your spreadsheet software, as these will help take away some of the repetitive data entry you will need to do when coding extracts. There is no quick drag-and-drop way to assign text to a code, so coding will almost always be slower than using dedicated software.

 

For these reasons, although it seems like just using software like Excel you already know will be easier, it can quickly become a false economy in terms of the time required to code and learn advanced sorting techniques.

 


Word makes coding many different themes difficult.

 

I see a lot of people (mostly students) who start out doing line-by-line coding in Word, using highlight colours to show different topics. It’s very easy to fall into this: while reading through a transcript, you highlight with colours bits that are obviously about one topic or another, and before you know it there is a lot of text sorted and coded into themes and you don’t want to loose your structure. Unfortunately, you have already lost it! There is no way in Word or other word processing software to look at all the text highlighted in one colour, so to review everything on one topic you have to look through the text yourself.

 

There is also a hard limit of 15 (garish) colours, which limits the number of themes you can code, and it’s not possible to code a section with more than one colour. Comments and shading (in some word-processors) can get around this, but it is still limited: there is no way to create groups or hierarchies of similar themes.

 

I get a lot of requests from people wanting to bring coded work from a word processor into Quirkos (or other qualitative software) but it is just not possible.

 


No reports, or other outputs


Once you have your coded data – how do you share it, summarise it or print it out to read through away from the glow of the computer? In Word or Excel this is difficult. Spreadsheets can produce summaries of quantitative data, but have very few tools that deal with text. Even getting something as simple as a word count is a pain without a lot of playing around with macros. So getting a summary of your coding framework, or seeing differences between different sources is hard.

 

Also, I have done large coding projects in Excel, and printing off huge sheets and long rows and columns is always a struggle. For meetings and team work, you will almost always need to get something out of a spreadsheet to share, and I have not found a way to do this neatly. Suggestions welcome!

 

 


I’m not trying to say that using Word or Excel is always a bad option, indeed Quirkos lets you export coded data to Word or spreadsheet format to read, print and share with people who don’t have qualitative software, and to do more quantitative analysis. However, be aware that if you start your analysis in Word or Excel it is very hard to bring your codes into anything else to work on further.

 

Quirkos tries to make dedicated qualitative software as easy to learn and use as familiar spreadsheet and word processing tools, but with all the dedicated features that make qualitative analysis simple and more enlightening. It’s also one of the most affordable packages on the market, and there is a free trial so you can see for yourself how much you gain by stepping up to real qualitative analysis software!

 

 

Practice projects and learning qualitative data analysis software

image by zaui/Scott Catron

 

Coding and analysing qualitative data is not only a time consuming, it’s a difficult interpretive exercise which, like learning a musical instrument, gets much better with practice. However, lots of students starting their first major qualitative or mixed method research project will benefit from completing a smaller project first, rather than starting by trying to learn a giant symphony. This will allow them to get used to qualitative analysis software, working with qualitative data, developing a coding framework and getting a realistic expectation of what can be done in a fixed time frame. Often people will try and learn all these aspects for the first time when they start a major project like a masters or PhD dissertation, and then struggle to get going and take the most effective approach.

 

Many scholars, including those advocating the 5 Level QDA approach suggest that learning the capabilities of the software and qualitative data separately, since one can effect the other. And a great way to do this is to actually dig in and get started with a separate smaller project. Reading textbooks and the literature can only prepare you so much (see for example this article on coding your first qualitative data), but a practical project to experiment and make mistakes in is a great preparation for the main event.

 

But what should a practice project look like? Where can I find some example qualitative data to play with? A good guideline is to take just a few sources, even just 3 or 4 from a method that is similar to the data collection you will use for your project. For example, if you are going to have focus groups, try and find some already existing focus group transcripts to transcribe. Although this can be daunting, there are actually lots of ways to quickly find qualitative data that will not only make you more familiar with real qualitative data, but also the analysis process and accompanying software tools. This article gives a couple of suggestions for a mini project to hone your skills!

 


News and media

A quick way to practice your basic coding skills is to do a small project using news articles. Just choose a recent (or historical) event, collect a few articles either from different news websites or over a period of time. Looking at conflicts in how events are described can be revealing, and is good for getting the right analytical eye to examine differences from respondents in your main project. It’s easy to go to different major news websites (like the Telegraph, Daily Mail, BBC News or the NYT) and copy and paste articles into Quirkos or other qualitative analysis software. All these sites have searchable archives, so you can look for a particular topic and find older articles.

 

Set yourself a good research question (or two), and use this project to practice generating a coding framework and exploring connections and differences across sources.

 

 

Qualitative Data Archives

If you want some more involved experience, browse some of the online repositories of qualitative data. These allow you to download the complete data set from research projects large and small. Since much government (or funding board) funded research requires data to be made publicly available, there are increasing numbers of data sets available to download which make a great way to look at real qualitative data, and practice your analysing skills. I’ll share two examples here, the first is the UK Data Archive and the second the Syracuse Qualitative Data Repository.

 

Regardless of where you are based, these resources offer an amazing variety of data types and topics. This can make your practice fun – there are data sets on some fascinating and obscure areas, so choose something interesting to you, or even something completely new and different as a challenge. You also don’t have to use all the sources from a large project – just choose three or four to start with, you can always add more later if you need extra coding experience.

 

 

Literature reviews

Actually, qualitative analysis software is a great way to get to grips with articles, books and policy documents relating to your research project. Since most people will want to do a systematic or literature review before they start a project, bringing your literature into qualitative software is a good way to learn the software while also working towards your project. While reading through your literature, you can create codes/themes to describe key points in theory or previous studies, and compare findings from different research projects.

In Quirkos it is easy to bring in PDF articles from journals or ebooks, and then you will have not only a good reference management system, but somewhere you can keep the full text of relevant articles, tagged and coded so you can find key quotes quickly for writing up. Our article here gives some good advice on using qualitative software for systematic and literature reviews.

 

 


Our own projects

Quirkos also has made two example projects freely available for learning qualitative analysis with any software package. The first is great for beginners, a fictional project about healthy eating options for breakfast. These 6 sources are short, but with rich information, so can be fully coded in less than an hour. Secondly, we conduded a real research project on the Scottish Referendum for Independence, and 12 transcribed semi-structured interviews are made available for your own practice and interpretation.

 

The advantage of these projects is that they both have fully coded project files to use as examples and comparison. It’s rare to find people sharing their coding (especially as an accessible project file) but can be a useful guide or point of comparison to your own framework and coding decisions.

 

download Quirkos qualitative research software

 

Ask around

Talk to faculty in your department and see if they have any example data sets you can use. Some academics will already have these for teaching purposes or taken from other research projects they are able to share.

 

It can also be a good exercise to do a coding project with someone else. Regardless of which option you choose from the example qualitative data sources above, share the data with another student or colleague, and go and do your own coding  separately. Once you are both done, meet up and compare your results – it will be really revealing to see how different people interpreted the data, how their coding framework looked, and how they found working with the software. It’s also good motivation and time management to have to work to a mutually set deadline!

 

 

The great thing about starting a small learning project is that it can be a perfect opportunity to experiment with different qualitative analysis software. It may be that you only have access to one option like Nvivo, MAXQDA, or Atlas.Ti at your institution, but student licences are very cheap and affordable, so make a great option for learning qualitative analysis. All the major packages have a free trial, so you can try several (or them all!) and find out which one works best for you. Doing this with a small example project lets you practice key techniques and qualitative methods, and also think through how best to collect and structure your data for analysis.

 

Quirkos probably has the best deal for qualitative research software, for example our student licences are cheap at just $59 (£49 or €58) and don’t expire. Most of the other packages only give you six months or a year but we let you use Quirkos as long as you need, so you will always be able to access your data – even after you graduate. Even academics and supervisors will find that Quirkos is much more affordable and easier to learn. Of course, there is a no obligation or registration trial, and all our support and training materials are free as well. So make sure you make the most informed decision before you start your research, and we hope that Quirkos becomes your instrument of choice for qualitative analysis!

 

 

Looking back and looking forward to qualitative analysis in 2017

2017 in qualitative analysis software - Janus

 

In the month named for Janus, it’s a good time to look back at the last year for Quirkos and qualitative analysis software and look forward to new developments for 2017.

 

It’s been a good year of growth for Quirkos, we now can boast of users in more than 100 universities across the world. But we can see how many more people are using Quirkos in these institutions as the word grows. There is no greater complement than when researchers recommend Quirkos to their peers, and this has been my favourite thing to see this year.

 

We also we honoured to take part in many international conferences and events, including TQR in January, ICQI in May, KWALON in August and QDR in October. Next year already has many international events on the calendar, and we hope to be in your neck of the woods soon! We have also run training workshops in many universities across the UK, and demand ensures these will continue in 2017.

 

Our decision to offer a 25% discount to researchers in developing countries has opened the door to a lot of interest and we are helping many researchers use qualitative analysis software for the first time.

 

The blog has also become a major resource for qualitative researchers, with more than 110 posts and counting now archived on the site, attracting thousands of visitors a month. In the next year we will be adding some new experimental formats and training resources to complement our methodology articles.

 

In terms of the Quirkos software itself, 2016 saw our most major upgrade to date, v1.4 which brought huge improvements in speed for larger projects. In early 2017 we will release a minor update (v1.4.1) which will provide a few bug fixes. We are already working towards v1.5 which will be released later in the year and add some major new requested features and refinements, but keep the same simple interface and workflow that people love.

 

We also have a couple of major announcements in the next month about the future of qualitative analysis software, Quirkos and the new skills we will be bringing on board. Watch this space!

 

How Quirkos can change the way you look at your qualitative data

Quirkos qualitative software seeing data

We always get a lot of inquiries in December from departments and projects who are thinking of spending some left-over money at the end of the financial year on a few Quirkos licences. A great early Christmas present for yourself the team! It’s also a good long term investment, since our licences don’t expire and can be used year after year. They are transferable to new computers, and we’ve committed to provide free updates for the current version. We don’t want the situation where different teams are using different versions, and so can’t share projects and data. Our licences are often a fraction of the cost of other qualitative software packages, but for the above reasons we think that we offer much more value than just the comparative sticker price.

 

But since Quirkos also has a different ethos (accessibility) and some unique features, it also helps you approach your qualitative research data in a different way to other software. In the two short years that Quirkos has been available, it’s become used by more than 100 universities across the world, as well as market research firms and public sector organisations. That has given me a lot of feedback that helps us improve the software, but also a sense of what things people love the most about it. So following is the list of things I hear most about the software in workshops and e-mails.

 

It’s much more visual and colourful

quirkos qualitative coding bubbles

Experienced researchers who have used other software are immediately struck by how colourful and visual the Quirkos approach is. The interface shows growing bubbles that dynamically show the coding in each theme (or node), and colours all over the screen. For many, the Quirkos design allows people to think in colours, spatially, and in layers, improving the amount of information they can digest and work with. Since the whole screen is a live window into the data, there is less need to generate separate reports, and coding and reviewing is a constant (and addictive) feedback process.


This doesn’t appeal to everyone, so we still have a more traditional ‘tree’ list structure for the themes which users can switch between at any time.

 

 

I can get started with my project quicker


We designed Quirkos so it could be learnt in 20 minutes for use in participatory analysis, so the learning curve is much lower than other qualitative software. Some packages can be intimidating to the first-time user, and often have 2 day training courses. All the training and support materials for Quirkos are available for free on our website, without registration. We increasingly hear that students want self-taught options, which we provide in many different formats. This means that not only can you start using Quirkos quickly, setting up and putting data into a new project is a lot quicker as well, making Quirkos useful for smaller qualitative projects which might just have a few sources.

 

 

I’m kept closer to my data

qualitative software comparison view


It’s not just the live growing bubbles that mean researchers can see themes evolve in their analysis, there are a suite of visualisations that let you quickly explore and play with the data. The cluster views generate instant Venn diagrams of connection and co-occurrences between themes, and the query views show side-by-side comparisons for any groups of your data you want to compare and contrast. Our mantra has been to make sure that no output is more than one click away, and this keeps users close to their data, not hidden away behind long lists and sub-menus.

 

 

It’s easier to share with others

qualitative word export


Quirkos provides some unique options that make showing your coded qualitative data to other people easier and more accessible. The favourite feature is the Word export, which creates a standard Word document of your coded transcripts, with all the coding shown as colour coded comments and highlights. Anyone with a word processor can see the complete annotated data, and print it out to read away from the computer.


If you need a detailed summary, the reports can be created as an interactive webpage, or a PDF which anyone can open. For advanced users you can also export your data as a standard spreadsheet CSV file, or get deep into the standard SQLite database using any tool (such as http://sqlitebrowser.org/) or even a browser extension.

 

 

I couldn’t get to grips with other qualitative software

quirkos spreadsheet comparison


It is very common for researchers to come along to our workshops having been to training for other qualitative analysis software, and saying they just ‘didn’t get it’ before. While very powerful, other tools can be intimidating, and unless you are using them on a regular basis, difficult to remember all the operations. We love how people can just come back to Quirkos after 6 months and get going again.


We also see a lot of people who tried other specialist qualitative software and found it didn’t fit for them. A lot of researchers go back to paper and highlighters, or even use Word or Excel, but get excited by how intuitive Quirkos makes the analysis process.

 

 

Just the basics, but everything you need


I always try and be honest in my workshops and list the limitations of Quirkos. It can’t work with multimedia data, can’t provide quantitative statistical analysis, and has limited memo functionality at the moment. But I am always surprised at how the benefits outweigh the limitations for most people: a huge majority of qualitative researchers only work with text data, and share my belief that if quantiatitve statistics are needed, they should be done in dedicated software. The idea has always been to focus on making the core actions that researchers do all the time (coding, searching, developing frameworks and exploring data) and make them as smooth and quick as possible.

 


If you have comments of your own, good or bad, we love to hear them, it’s what keeps us focused on the diverse needs of qualitative researchers.


Get in touch and we can help explain the different licence options, including ‘seat’ based licences for departments or teams, as well as the static licences which can be purchased immediately through our website. There are also discounts for buying more than 3 licences, for different sectors, and developing countries.


Of course, we can also provide formal quotes, invoices and respond to purchase orders as your institution requires. We know that some departments take time to get things through finances, and so we can always provide extensions to the trial until the orders come through – we never want to see researchers unable to get at their data and continue their research!


So if you are thinking about buying a licence for Quirkos, you can download the full version to try for free for one month, and ask us any questions by email (sales@quirkos.com), Skype ‘quirkos’ or a good old 9-to-5 phone call on (+44) 0131 555 3736. We are here for qualitative researchers of all (coding) stripes and spots (bubbles)!

 

Stepping back from coding software and reading qualitative data

printing and reading qualitative data

There is a lot of concern that qualitative analysis software distances people from their data. Some say that it encourages reductive behaviour, prevents deep reading of the data, and leads to a very quantified type of qualitative analysis (eg Savin-Baden and Major 2013).

 

I generally don’t agree with these statements, and other qualitative bloggers such as Christina Silver and Kristi Jackson have written responses to critics of qualitative analysis software recently. However, I want to counter this a little with a suggestion that it is also possible to be too close to your data, and in fact this is a considerable risk when using any software approach.

 

I know this is starting to sound contradictory, but it is important to strike a happy balance so you can see the wood from the trees. It’s best to have both a close, detailed reading and analysis of your data, as well as a sense of the bigger picture emerging across all your sources and themes. That was the impetus behind the design of Quirkos: that the canvas view of your themes, where the size of each bubble shows the amount of data coded to it, gives you a live birds-eye overview of your data at all times. It’s also why we designed the cluster view, to graphically show you the connections between themes and nodes in your qualitative data analysis.

 

It is very easy to treat analysis as a close reading exercise, taking each source in turn, reading it through and assigning sections to codes or themes as you go. This is a valid first step, but only part of what should be an iterative, cyclical process. There are also lots of ways to challenge your coding strategy to keep you alert to new things coming from the data, and seeing trends in different ways.

 

However, I have a confession. I am a bit of a Luddite in some ways: I still prefer to print out and read transcripts of data from qualitative projects away from the computer. This may sound shocking coming from the director of a qualitative analysis software company, but for me there is something about both the physicality of reading from paper, and the process of stepping away from the analysis process that still endears paper-based reading to me. This is not just at the start of the analysis process either, but during. I force myself to stop reading line-by-line, put myself in an environment where it is difficult to code, and try and read the corpus of data at more of a holistic scale.
I waste a lot of trees this way (even with recycled paper), but always return to the qualitative software with a fresh perspective, finish my coding and analysis there, but having made the best of both worlds. Yes, it is time consuming to have so many readings of the data, but I think good qualitative analysis deserves this time.

 

I know I am not the only researcher who likes to work in this way, and we designed Quirkos to make this easy to do. One of the most unique and ‘wow’ features of Quirkos is how you can create a standard Word document of all the data from your project, with all the coding preserved as colour-coded highlights. This makes it easy to printout, take away and read at your leisure, but still see how you have defined and analysed your data so far.

word export qualitative data

 

There are also some other really useful things you can do with the Word export, like share your coded data with a supervisor, colleague or even some of your participants. Even if you don’t have Microsoft Office, you can use free alternatives like LibreOffice or Google Docs, so pretty much everyone can see your coded data. But my favourite way to read away from the computer is to make a mini booklet, with turn-able pages – I find this much more engaging than just a large stack of A4/Letter pages stapled in the top corner. If you have a duplex printer that can print on both sides of the page, generate a PDF from the Word file (just use Save As…) and even the free version of Adobe Reader has an awesome setting in Print to automatically create and format a little booklet:

word booklet

 

 

I always get a fresh look at the data like this, and although I am trying not to be too micro-analytical and do a lot of coding, I am always able to scribble notes in the margin. Of course, there is nothing to stop you stepping back and doing a reading like this in the software itself, but I don’t like staring at a screen all day, and I am not disciplined enough to work on the computer and not get sucked into a little more coding. Coding can be a very satisfying and addictive process, but at the time I have to define higher-level themes in the coding framework, I need to step back and think about the bigger picture, before I dive into creating something based on the last source or theme I looked at. It’s also important to get the flow and causality of the sources sometimes, especially when doing narrative and temporal analysis. It’s difficult to read the direction of an interview or series of stories just from looking at isolated coded snippets.

 

Of course, you can also print out a report from Quirkos, containing all the coded data, and the list of codes and their relations. This is sometimes handy as a key on the side, especially if there are codes you think you are underusing. Normally at this stage in the blog I point out how you can do this with other software as well, but actually, for such a commonly required step, I find this very hard to do in other software packages. It is very difficult to get all the ‘coding stripes’ to display properly in Nvivo text outputs, and MaxQDA has lots of options to export coded data, but not whole coded sources that I can see. Atlas.ti does better here with the Print with Margin feature, which shows stripes and code names in the margin – however this only generates a PDF file, so is not editable.

 

So download the trial of Quirkos today, and every now and then step back and make sure you don’t get too close to your qualitative data…

 

 

Starting a qualitative research thesis, and choosing a CAQDAS package

qualitative thesis software

 

For those about to embark on a qualitative Masters or PhD thesis, we salute you!

 

More and more post-graduate students are using qualitative methods in their research projects, or adopting mixed-method data collection and using a small amount of qualitative data which needs to be combined with quantitative data. So this year, how can students decide the best approach for the analysis of their data, and can CAQDAS or QDA software help their studies?

 

First, as far as possible, don’t chose the software, choose the method. Think about what you are trying to research, the best way to get deep data to answer your research questions. The type and amount of data you have will be an important factor. Next, how much existing literature and theory there is around your research area? This will affect whether you will adopt a grounded theory approach, or will be testing or challenging existing theory.

 

Indeed, you may decide that that you don’t need software for your research project. For small projects, especially case studies, you may be more comfortable using printouts of your data, and while reading mark important sections with highlighters and post-it notes. Read Séror (2005) for a comparison of computer vs paper methods. You could also look at the 5 Level QDA, an approach to planning and learning the use of qualitative software so that you develop strategies and tactics that help you make the most of the QDA software.

 

Unfortunately, if you decide you want to use a particular software solution it’s not always as simple as it should be. You will have to eventually make a practical choice based on what software your university has, what support they provide, and what your peers and supervisors use.

 

However, while you are a student, it’s also a good time to experiment and see what works best for you. Not only do all the major qualitative software packages offer a free trial, student licences are hugely discounted against the full versions. This gives you the option to buy a copy for yourself (for a relatively small amount of money).

 

There’s a lot of variety in the different qualitative data analysis software available. The most common one is Nvivo, which your university or department may already have a licence for. This is a very powerful package, but can be intimidating for first-time users. Common alternatives like MAXQDA or Atlas.ti are more user friendly, but also adopt similar spreadsheet-like interfaces. There are also lots of more niche alternatives, for example Transana is unmatched for video analysis, and Dedoose works entirely in the cloud so you can access it from any computer. For a more comprehensive list, check out the Wikipedia list, or the profiles on textanalysis.info

 

Quirkos does a couple of things differently though. First, our student licences don’t expire, and are some of the cheapest around. This means that it doesn’t matter if your PhD takes 3 or 13 years, you will still be able to access your work and data without paying again. And yes, you can keep using your licence into your professional career. It also aims to be the easiest software package to use, and puts visualisations of the data first and foremost in the interface.

 

So give Quirkos a try, but don’t forget about all the other alternatives out there: between them all you will find something that works in the way you want it to and makes your research a little less painful!

 

 

Developing and populating a qualitative coding framework in Quirkos

coding blog

 

In previous blog articles I’ve looked at some of the methodological considerations in developing a coding framework. This article looks at top-down or bottom-up approaches, whether you start with large overarching themes (a-priori) and break them down, or begin with smaller more simple themes, and gradually impose meanings and connections in an inductive approach. There’s a need in this series of articles to talk about the various different approaches which are grouped together as grounded theory, but this will come in a future article.

 

For now, I want to leave the methodological and theoretical debates aside, and look purely at the mechanics of creating the coding framework in qualitative analysis software. While I’m going to be describing the process using Quirkos as the example software, the fundamentals will apply even if you are using Nvivo, MaxQDA, AtlasTi, Dedoose, or most of the other CAQDAS packages out there. It might help to follow this guide with the software of your choice, you can download a free trial of Quirkos right here and get going in minutes.

 

First of all, a slightly guilty confession: I personally always plan out my themes on paper first. This might sound a bit hypocritical coming from someone who designs software for a living, but I find myself being a lot more creative on paper, and there’s something about the physicality of scribbling all over a big sheet of paper that helps me think better. I do this a lot less now that Quirkos lets me physically move themes around the screen, group them by colour and topic, but for a big complicated project it’s normally where I start.

 

But the computer obviously allows you to create and manage hundreds of topics, rearrange and rename them (which is difficult to do on paper, even with pencil and eraser!). It will also make it easy to assign parts of your data to one of the topics, and see all of the data associated with it. While paper notes may help conceptually think through some of the likely topics in the study and connect them to your research questions, I would recommend users to move to a QDA software package fairly early on in their project.

 

Obviously, whether you are taking an a-priori or grounded approach will change whether you will creating most of your themes before you start coding, or adding to them as you go along. Either way, you will need to create your topics/categories/nodes/themes/bubbles or whatever you want to call them. In Quirkos the themes are called ‘Quirks’ informally, and are represented by default as coloured bubbles. You can drag and move these anywhere around the screen, change their colours, and their size increases every time you add some text to them. It’s a neat way to get confirmation and feedback on your coding. In other software packages there will just be a number next to the list of themes that shows how many coding events belong to each topic.

 


In Quirkos, there are actually three different ways to create a bubble theme. The most common is the large (+) button at the top left of a canvas area. This creates a new topic bubble in a random place with a random colour, and automatically opens the Properties dialogue for you to edit it. Here you can change the name, for example to ‘Fish’ and put in a longer description: ‘Things that live in water and lay eggs’ so that the definition is clear to yourself and others. You can also choose the colour, from some 16 million options available. There is also the option to set a ‘level’ for this Quirk bubble, which is a way to group intersecting themes so that one topic can belong to multiple groups. For example, you could create a level called ‘Things in the sea’ that includes Fish, Dolphins and Ships, and another category called ‘Living things’ that has Fish, Dolphins and Lions. In Quirkos, you can change any of these properties at any time by right clicking on the appropriate bubble.

 

quirkos qualitative properties editor

 

Secondly, you can right click anywhere on the ‘canvas’ area that stores your topics to create a new theme bubble at that location. This is useful if you have a little cluster of topics on a similar theme, and you want to create a new related bubble near the other ones. Of course, you can move the bubbles around later, but this makes things a bit easier.

 

If you are creating topics on the fly, you can also create a new category by dragging and dropping text directly onto the same add Quirk button. This creates a new bubble that already contains the text you dragged onto the button. This time, the property dialogue doesn’t immediately pop-up, so that you can keep adding more sections of data to the theme. Don’t forget to name it eventually though!

 

drag and drop qualitative topic creation

 

All software packages allow you to group your themes in some way, usually this is in a list or tree view, where sub-categories are indented below their ‘parent’ node. For example, you might have the parent category ‘Fish’ and the sub-categories ‘Pike’, ‘Salmon’ and ‘Trout’. Further, there might be sub-sub categories, so for example ‘Trout’ might have themes for ‘Brown Trout’, ‘Brook Trout’ and ‘Rainbow Trout’. This is a useful way to group and sort your themes, especially as many qualitative projects end up with dozens or even hundreds of themes.

 

In Quirkos, categories work a little differently. To make a theme a sub-category, just drag and drop that bubble onto the bubble that will be its parent, like stacking them. You will see that the sub-category goes behind the parent bubble, and when you move your mouse over the top category, the others will pop out, automatically arranging like petals from a flower. You can also remove categories just by dragging and pulling it out from the parent just like picking petals from a flower! You can also create sub-sub categories (ie up to three levels depth) but no more than this. When a Quirk has subcategories clustered below it, this is indicated by a white ring inside the bubble. This method of operation makes creating clusters (and changing your mind) very easy and visual.

 

Now, to add something to the topic, you just have to select some text, and drag and drop it onto the bubble or theme. This will work in most software packages, although in some you can also right click within the selected text where you will find a list of codes to assign that section to.


Quirkos, like other software, will show coloured highlighted stripes over the text or in the margin that show in the document which sections have been added to which codes. In Quirkos, you can always see what topic the stripe represents by hovering the mouse cursor over the coloured section, and the topic name will appear in the bottom left of the screen. You can also right-click on the stripe and remove that section of text from the code at any time. Once you have done some coding, in most software packages you can double click on the topic and see everything you’ve coded at this point.

 

Hopefully this should give you confidence to let the software do what it does best: keep track of lots of different topics and what goes in them. How you actually choose which topics and methodology to use in your project is still up to you, but using software helps you keep everything together and gives you a lot of tools for exploring the data later. Don’t forget to read more about the specific features of Quirkos here and download the free trial from here.

 

An early spring update on Quirkos for 2016

spring snowdrops

 

About this time last year, I posted an update on Quirkos development for the next year. Even though February continues to be cold and largely snow-drop free in Scotland, why not make it a tradition?!

 

It’s really amazing how much Quirkos has grown over the last 18 months since our first release. We now have hundreds of users in more than 50 universities across the world. The best part of this is that we now get much more feedback and suggestions from qualitative researchers who are using Quirkos for different projects. Although we have always had a ‘road-map’ for developing new features for Quirkos, it’s been an aim to keep that flexible so we adapt to people’s needs.

 

We are planning a new update for Quirkos (free of course) for the end of March 2016. This version (1.4) will be a fairly major upgrade, but as ever will be released at the same time for Windows, Mac and Linux, with identical features and compatibility across all three.

 

The most significant improvement will be speed. Although v1.3 did improve this a little, it was not enough. The underlying ‘engine’ for coding and highlights was laggy and slow with large projects, and required complete rewriting from scratch. It has justifiably been the biggest source of criticism so far about Quirkos, but we hope this will now remove the last thing holding many users back. This has taken months, which is why this release is a little later than our typical quarterly updates. However, the difference so far is amazing: a near 10 fold increase in speed when loading, coding and editing sources. Although the interface will still look the same, everyone will notice the under-the-hood difference in small and large projects alike.

 

There will also be a few minor bug fixes in this release. We had reports that when moving encrypted projects between Windows and Mac, passwords were not accepted. We’ve fixed this issue, and a few others that people have reported. There are also several small improvements suggested by users that should make exploring the data easier. So please always e-mail us with bugs or suggestions, everything reported gets investigated, and we try and fix issues as soon as we can!

 

We will be sending the new version out to an international group of beta-testers at the end of February, so we are confident that everything works as intended before we make it publicly available. The best way to keep abreast of updates is to follow our Twitter feed: twitter.com/quirkossoftware which is usually updated every day.

 

Looking forward, the next release (v1.5) is due for the summer, and will add some exciting new features, probably including the second most frequently requested addition: memos! Proper note taking functionality is top of many people’s request lists, and will make it much easier to record researcher’s ponderings during the analysis process. For the meantime, check out our blog post article on how to record and code your notes in Quirkos. We also hope to add a lot more tools to help look at word-frequency in their qualitative data sets, including the ever popular word clouds!

 

In addition to all this, we will have a major new collaboration to announce in the next few months. This is going to represent a major leap forward in functionality for Quirkos, bringing some top minds into the fray to work on the next generation of qualitative analysis software.

 

So far, we have reinvested all our sales income into development, to make sure that we keep making the software better, and keep current and future users happy. Since all our updates are free, the best way to support further development is to buy a licence, and you will always benefit from work we do in the future to add new capabilities, and be able to suggest the features that will make your qualitative research easier and more fun.

 

 

Starting out in Qualitative Analysis

Qualitative analysis 101

 

When people are doing their first qualitative analysis project using software, it’s difficult to know where to begin. I get a lot of e-mails from people who want some advice in planning out what they will actually DO in the software, and how that will help them. I am happy to help out individually, because everyone’s project is different. However, here are a few pointers which cover the basics and can help demystify the process. These should actually apply to any software, not just Quirkos!

 

First off: what are you going to be able to do? In a nutshell, you will read through the sources, and for each section that is interesting to you and about a certain topic, you will ‘code’ or ‘tag’ that section of text to that topic. By doing this, the software lets you quickly see all the sections of text, the ‘quotes’ about that topic, across all of your sources. So you can see everything everyone said about ‘Politics’ or ‘Negative’ – or both.

 

You can then look for trends or outliers in the project, by looking at just responses with a particular characteristic like gender. You’ll also be able to search for a keyword, and generate a report with all your coded sections brought together. When you come to write up your qualitative project, the software can help you find quotes on a particular topic, visualise the data or show sub-section analysis.  

 

So here are the basic steps:

 

1.       Bring in your sources.
I’m assuming at this stage that you have the qualitative data you want to work with already. This could be any source of text on your computer. If you can copy and paste it, you can bring it into Quirkos. For this example let’s assume that you have transcripts from interviews: this means that you have already done a series of interviews, transcribed them, and have them in a file (say a Word document or raw text file). I’d suggest that before you bring them in, just have a quick look through and correct them in a Word Processor for typos and misheard words. While you can edit the text in Quirkos later, while using a Word or equivalent you have the advantage of spell checkers and grammar checkers.

 

Now, create a new, unstructured project in Quirkos, and save it somewhere locally on your computer. We don’t recommend you save directly to a network location, or USB stick, as if either of these go down, you will have a problem! Next, bring in the sources using the (+) Add Source button on the bottom right. You can bring in each file one at a time, or a whole folder of files in one go, in which case the file name will become the default source name. Don’t forget, you can always add more sources later, there is no need to bring in everything before you start coding. Now your project file (a little .qrk file you named) will contain all the text sources in one place. With Quirkos files, just backing up and copying this file saves the whole project.

 


2.       Describe your sources
It’s usually a good idea to describe some characteristics of your qualitative sources that you might use later to look for differences or similarities in the data. Often these are basic demographic characteristics like age or gender, but can also be things about the interview, such as the location, or your own notes.

 

To do this in Quirkos, click on the little grid button on the top right of the screen, and use the source properties. The first thing you can do here is change the name of the sources from the default (either a sequential number like ‘Source 7’ or the file name. You can create a property with the square [+] ‘Quickly add a new property’ button. The property (eg Gender) and a single value (eg Male) can be added here. The drop down arrow next to that property can be used later to add extra values.

 

The reason for doing this is that you can later run ‘queries’ which show results from just certain sources that have properties you defined. So you can do a side-by-side comparison of coded responses from men next to women. Don’t forget, you can add properties at any time, so you can even create a variable for ‘these people don’t fit the theory’ after you’ve coded, and try and see what they are saying that makes them different.

 

 

3.       Create your themes
Whatever you call them: themes, nodes, bubbles, topics or Quirks, these are the categories of interest you want to collect quotes about from the text. There are two approaches here, you can try and create all the categories you will use before you start reading and coding the text (this is sometimes called a framework approach), or you can add themes as you go (grounded theory). (For much much more on these approaches, look here and here.)

 

In Quirkos, you create themes as coloured bubbles, which grow in size the more text is added. Just click on the grey (+) button on the top right of the canvas view to add a new theme. You can also change the name, colour, level in this dialogue, or right click on the bubble and select ‘Quirk Properties’ at any time. To group, just drag and drop bubbles on top of each other.

 

 

4.       Do your coding
Essentially, the coding process involves finding every time someone said something about ‘Dieting’ and adding that sentence or paragraph to the ‘Dieting’ bubble or node. This is what is going to take the most time in your analysis (days or weeks) and is still a manual process. It’s best to read through each source in turn, and code it as you go.

 

However, you can also use the keyword search to look for words like ‘Diet’ or ‘eating’ and code from the results. This makes it quicker, but there is the risk of missing segments that use a keyword you didn’t think to search for like ‘cut-down’. The keywords search can help when you (inevitably) decide to add a new topic halfway through, and the first few interviews haven’t been coded for the new themes. You can use the search to look for related terms and find those new segments without having to go over the whole text again.

 

 

5.       Be iterative
Even if you are not using a grounded theory approach, going back over the data a second time, and rethinking codes and how you have categorised things can be really useful. Trust me: even if you know the data pretty well, after reading it all again, you will see some topics in a slightly different light, or will find interesting things you never thought would be there.

 

You may also want to rearrange your codes, especially if you have grouped them. Maybe the name you gave a theme isn’t quite right now: it’s grown or got more specific. Some vague codes like ‘Angry’ might need to be split out into ‘Irate’ and ‘Annoyed’. Depending on your approach, you  will probably constantly tweak and adjust the themes and coding so they best represent the intersection of your research questions and data.

 

 

6.       Explore the data.
Once your qualitative data is all coded, the big advantages of using CAQDAS software come into play. Using the database of your tagged text, you can choose to look at it in anyway: using any of the source properties, who did the coding or when, or whether a result comes from any particular group of codes. This is done using the 'Query' views in Quirkos.

 

In Quirkos there are also a lot of visualisation options that can show you the overall shape and structure of the project, the amount of coding, and connections that are emerging between the sources. You can then use these to help write your outputs, be they journal articles, evaluations or a thesis. Software will generate reports that let you share summaries of the coded data, and include key statistics and overviews of the project.


While it does seem like a lot of work to get to this stage, it can save so much time at the final stages of writing up your project, when you can call up a useful quote quickly. It also can help in the future to have this structured repository of qualitative data, so that secondary analysis or adding to the dataset does not involve re-inventing the wheel!

 

Finally, there is no one-size-fits-all approach, and it's important to find a strategy that fits with your way of working. Before you set out, talk to peers and supervisors, read guides and textbooks, and even go on training courses. While the software can help, it's not a replacement for considered thinking, and you should always have a good idea about what you want to do with the data in the end.

 

 

Teaching qualitative analysis software with Quirkos

students learning quirkos on a laptop

 

When people first see Quirkos, we often hear them say “My students would love this!” The easy learning curve, the visual feedback and the ability to work on Windows or Mac appeal to students starting out in qualitative analysis. We have an increasing number of universities across the world using Quirkos to teach CAQDAS at both undergraduate and post graduate levels. I just wanted to give a quick overview of why this can be such a good solution for students and educators:

 

1. Fits into tight curriculums
Because Quirkos can be taught from start to finish in an interactive 2 hour lab session, it fits neatly into a full module on Qualitative Methods. In one session students can have the skills to do qualitative analysis using a basic CAQDAS package, where other software would require multiple sessions, or a dedicated workshop as a full day event. Thus other sessions can focus on methods, methodology and coding approaches, with students able to quickly apply software skills to their theoretical knowledge.

 

2. Suitable for both post-grads and undergraduates
Quirkos offers enough features and flexibility to be included in research-based masters or PhD training. RTP modules can easily link to a session delivered by university based instructors, without needing external experts to come in and deliver specialist software training. However, Quirkos is simple enough to teach that undergraduate courses in social science can include it in a module on qualitative approaches, and include lab sessions on the basics of software. This is a great basis for later doing research based projects, as well as a useful transferable skill for many industries, including public sector and market research. Since the basic operation of the software is the same, departments have the option to integrate undergraduate and post-graduate training, and use the same materials and course guides.

 

3. Approach agnostic
Quirkos does not encourage a specific analytical approach, and is just as suitable for emergent analysis as grounded theory. Students can be tasked with example projects to analyse with either approach, and choose a middle ground that works best for their own research project. The software gets out of the way, and lets teachers focus on the theory without worrying about how it fits with available tools.

 

4. A visual approach that underscores learning
Visual-based learning can help both understanding and retention and the way that Quirkos makes the coding process live and interactive helps students see their coding, and how it affects the analysis of a project. A very visual approach not only lets students see their findings emerge, but also understand visually what happens during qualitative analysis. By moving their themes and grouping them by drag-and-drop, students can also group topics in their framework, and use colours to represent different groupings. This provides a way of working that is inherently creative, experimental, and satisfying. Quirkos is the only software package based around a graphical user interface, and offers a unique way for students to understand the functionality behind CAQDAS.

 

5. Self-support and learning options
Students increasingly prefer online course materials they can consume in their own time. Quirkos helps educators by providing all our online support guides for free, giving students great flexibility in how they can learn. They can choose either written materials, or video guides of varying length and specificity, and access them without registration or any intervention from the department. Signposting to the materials is easy, and requires no special software or platform to access. We are always around to directly answer technical issues or queries from students.

 

6. Example projects
We provide several example datasets for students to use either in independent learning or guided workshops, at basic and advanced levels. These materials are free for course leaders to include in their materials, or students can download them as they wish. These can be very useful when undergraduates are practicing different qualitative approaches, or if postgraduate researchers wish to experiment with example data before working on their own projects. Since many RTP programmes are requirements in the first few years of a PhD or research masters (before data collection) this high-quality and challenging real data is a great practice resource to put training in practice.


7. A gateway to more advanced techniques
Quirkos aims to provide all the basic features of CAQDAS software, but without any of the bloat that confuses first time users who should be more focused on the data and methodological considerations. However, should students need to later move on to more advanced packages such as Atlas TI, MAXQDA or Nvivo, learning Quirkos is an easy access point, and encourages familiarity with the basics of coding. We also offer export options that help people get their data from Quirkos into other packages for further statistical exploration. Since the basics between all these packages are the same, Quirkos is the perfect first step in the door, and students with advanced needs can quickly learn other packages.

 

8. Flexible licensing for departments and individuals
While everyone can download and use Quirkos with the free trial, we also make sure that we can provide institutions with affordable and accessible permanent access to Quirkos and updates. We offer a site-wide ‘floating’ licence, ideal for teams or lab work that allows a set number of users at any one time, with the ability to add more users at any time. Smaller evaluations and research groups can also buy individual based licenses immediately with a credit or debit card. We are always here to help with purchase orders, IT and other logistical requirements. With significant group discounts, we are confident that we will always be the cheapest option for qualitative analysis software, and the best place for students to start out into the word of qualitative research.

 

 

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...

 

 

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!

 

 

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.

Announcing Pricing for Quirkos

At the moment, (touch wood!) everything is in place for a launch next week, which is a really exciting place to be after many years of effort. From that day, anyone can download Quirkos, try it free for a month, and then buy a licence if it helps them in their work. We've set up the infrastructure so that people can either place purchase orders through their finance department, or make a direct sale through the website by credit or debit card. We can then provide a licence code immediately, and users can unlock Quirkos and use it without any time limit. We don’t want to tie people into contracts or recurring payments; the licence will not expire, and will entitle you to any future updates for that version.

 

The interest we’ve had from users over the past few months has been overwhelming, and we want to have a flexible price structure that is appropriate for lots of different groups. One of my key aims has been to systematically remove the barriers to doing qualitative research – and price is a big hurdle at the moment. I’ve had conversations with so many people who have taken one look at the licence costs of the major qualitative analysis packages, and walked away. To really open up qualitative research for everyone, that needs to change. Our licence will cost roughly half that of our competitors', and we will offer a range of discounts for teams from different backgrounds.

 

First of all, we think Quirkos will be great for students, not just at a PhD level, but also at Masters or Undergraduate level, when there isn’t always the time to spend learning other qualitative research software. So, we are starting the student licence at £35 (roughly €45, US$60), so that people at all stages of learning can get started with qualitative research.

 

For professional academics and people working in the charity sectors, we will heavily discount the licence cost to £180 (€230 / $290). Already we have had beta-testers in the NHS and local government, and users in government institutions or NGOs, can get a licence for just £320 (€400 / $516).

 

Finally, the full licence for commercial use will be £390 (€490 / $620) and comes with our highest level of customer support. Everyone will be able to access regularly updated discussion forums and on-line learning materials, and professional users will also have access to personal e-mail support with a rapid response rate.

 

We really want to encourage a new generation of qualitative researchers and we think we’ve set a fair price that makes access easy, while allowing us to continue to add new features, and provide a strong level of support. Then you can focus on your data and findings, and not just the tools that help you get results.

 

(These are initial indicative prices, subject to change, and currency rates, local sales tax or VAT may lead to some variation in these numbers)

 

 

Paper vs. computer assisted qualitative analysis

I recently read a great paper by Rettie et al. (2008) which, although based on a small sample size, found that only 9% of UK market research organisations doing qualitative research were using software to help with qualitative analysis.

 

At first this sounds very low, but it holds true with my own limited experiences with market research firms, and also with academic researchers. The first formal training courses I attended on Qualitative Analysis were conducted by the excellent Health Experiences Research Group at Oxford University, a team I would actually work with later in my career. As an aforementioned computer geek, it was surprising for me to hear Professor Sue Ziebland convincingly argue for a method they defined as the One Sheet of Paper technique, immortalised as OSOP. This is essentially a way to develop a grounded theory or analytical approach by reducing the key themes to a diagram that can be physically summarised on a single piece of paper, a method that is still widely cited to this day.

 

However, the day also contained a series of what felt like ‘confessions’ about how much of people’s Qualitative analysis was paper based: printing out whole transcripts of interviews, highlighting sections, physically cutting and gluing text into flipcharts, and dozens and dozens of multi-coloured Post-it notes! Personally, I think this is a fine method of analysis, as it keeps researchers close to the data and, assuming you have a large enough workspace, it lets you keep dozens of interviews and themes to hand. It’s also very good for team work, as the physicality gets everyone involved in reviewing codes and extracts.

 

In the last project I worked on, looking at evidence use for health decision making we did most of the analysis in Excel, which was actually easier for the whole team to work with than any of the dedicated qualitative analysis software packages. However, we still relied heavily on paper: printing out the interviews and Excel spreadsheets, and using flip-chart paper, post-its and marker pens in group analysis sessions. Believe me, I felt a pang of guilt for all the paper we used in each of these sessions, rainforests be damned! But it kept us inspired, engaged, close to the data and let us work together.

 

So I can quite understand why so many academics and market research organisations choose not to use software packages: at the moment they don’t have the visual connection to the data that paper annotations allow, it’s often difficult to see the different stages of the coding process, and it’s hard to produce reports and outputs that communicate properly.

 

The problem with this approach is the literal paper-trail – how you turn all these iterations of coding schemes and analysis sessions into something you can write up to share with others in order to justify how you made the decisions that led to your conclusions. So I had to file all these flip-charts and annotated sheets, often taking photos of them so they could be shared with colleagues at other universities. It was a slow and time consuming process, but it kept us close to the data.

 

When designing Quirkos, I have tried in some ways to replicate the paper-based analysis process. There’s a touch interface, reports that show all the highlighting in a Word document, and views that keep you close to the data. But I also want to combine this with all the advantages you get from a software package, not least the ability to search, shuffle dozens of documents, have more colours than a whole rainbow of Post-it notes, and the invaluable Undo button!

 

Software can also help keep track of many more topics and sources than most people (especially myself) can remember, and if there are a lot of different themes you want to explore from the data, software is really good at keeping them all in one place and making them easy to find. Working as part of a team, especially if some researchers work remotely or in a different organisation can be much easier with software. E-mailing a file is much easier than sending a huge folder of annotated paper, and combining and comparing analysis can be done at any stage of the project.

 

Qualitative analysis software also lets you take different slices through the data, so you can compare responses grouped by any caracteristics for the sources you have. So it's easy to look at all the comments from people in one location, or between a certain age range. Certainly this is possible to do with qualitative data on paper as well, but the software can remove the need of a lot of paper shuffling, especially when you have a large number of respondents.

 

But most importantly, I think software can allow more experimentation - you can try different themes, easily combine or break them apart, or even start from scratch again, knowing that the old analysis approach you tried is just a few clicks away. I think that the magic undo button also gives researchers more confidence in trying something out, and makes it easier for people to change their mind.

 

Many people I’ve spoken to have asked what the ‘competition’ for Quirkos is like, meaning, what do the other software packages do. But for me the real competitor is the tangible approach and the challenge is to try and have something that is the best of both worlds: a tool that not only apes the paper realm in a virtual space, but acknowledges the need to print out and connect with physical workflows. I often want to review a coded project on paper, printing off and reading in the cafe, and Quirkos makes sure that all your coding can be visually displayed and shared in this way.

 

Everyone has a workflow for qualitative analysis that works for them, their team, and the needs of their project. I think the key is flexibility, and to think about a set of tools that can include paper and software solutions, rather than one approach that is a jack of all trades, and master of none.

 

Analysing text using qualitative software

I'm really happy to see that the talks from the University of Surrey CAQDAS 2014 are now up online (that's 'Computer Assisted Qualitative Data Analysis Software' to you and me). It was a great conference about the current state of software for qualitative analysis, but for me the most interesting talks were from experienced software trainers, about how people actually were using packages in practice.

There were many important findings being shared, but for me one of the most striking was that people spend most of their time coding, and most of what they are coding is text.

In a small survey of CAQDAS users from a qualitative research network in Poland, Haratyk and Kordasiewicz found that 97% of users were coding text, while only 28% were coding images, and 23% directly coding audio. In many ways, the low numbers of people using images and audio are not surprising, but it is a shame. Text is a lot quicker to skip though to find passages compared to audio, and most people (especially researchers) and read a lot faster than people speak. At the moment, most of the software available for qualitative analysis struggles to match audio with meaning, either by syncing up transcripts, or through automatic transcription to help people understand what someone is saying.

Most qualitative researchers use audio as an intermediary stage, to create a recording of a research event, such as in interview or focus group, and have the text typed up word-for-word to analyse. But with this approach you risk losing all of the nuance that we are attuned to hear in the spoken word, emphasis, emotion, sarcasm – and these can subtly or completely transform the meaning of the text. However, since audio is usually much more laborious to work with, I can understand why 97% of people code with text. Still, I always try to keep the audio of an interview close to hand when coding, so that I can listen to any interesting or ambiguous sections, and make sure I am interpreting them fairly.

Since coding text is what most people spend most of their time doing, we spent a lot of time making the text coding process in Quirkos was as good as it could be. We certainly plan to add audio capabilities in the future, but this needs to be carefully done to make sure it connects closely with the text, but can be coded and retrieved as easily as possible.

 

But the main focus of the talk was the gaps in users' theoretical knowledge, that the survey revealed. For example, when asked which analytical framework the researchers used, only 23% described their approach as Grounded Theory. However, when the Grounded Theory approach was described in more detail, 61% of respondents recognised this method as being how they worked. You may recall from the previous top-up, bottom-down blog article that Grounded Theory is essentially finding themes from the text as they appear, rather than having a pre-defined list of what a researcher is looking for. An excellent and detailed overview can be found here.

Did a third of people in this sample really not know what analytical approach they were using? Of course it could be simply that they know it by another name, Emergent Coding for example, or as Dey (1999) laments, there may be “as many versions of grounded theory as there were grounded theorists”.

 

Finally, the study noted users comments on advantages and disadvantages with current software packages. People found that CAQDAS software helped them analyse text faster, and manage lots of different sources. But they also mentioned a difficult learning curve, and licence costs that were more than the monthly salary of a PhD student in Poland. Hopefully Quirkos will be able to help on both of these points...

 

Quirkos is coming...

key

 

Quirkos is intended to be a big step forward for qualitative research. The central idea is to make text analysis so easy, that anyone can do it.

That includes people who don't know what qualitative analysis is, or that it could help them to better understand their world. This could be a council or hospital trust wanting to better understand the needs of people that use their services, or a team developing a new product, wanting feedback from users and consumers.

And for experienced researchers too, the goal was to create software that helps people engage with their data, rather than being a barrier to it. Over the last decade I've used a variety of approaches to analysing qualitative research, and many collegues and I felt that there had to be a better way.

Quirkos aims to make software to easily manage large projects, search them quickly, and keep them secure. To visualise data on the fly, so findings come alive and are sharable with a team of people. And finally to make powerful tools to sort and understand the connections in the data.

After years of planning, these pieces are finally coming together, and the prototype is already something that I prefer using to any of the other qualitative software packages out there. In the next few weeks, the first version of Quirkos will be sent to intreped researchers around the globe to test in their work. A few months later, we'll be ready to share a polished version with the world, and we're really excited that it will work for everyone: with any level of experience, and on pretty much any computer too.

There are a lot of big firsts in Quirkos, and it's going to be exciting sharing them here over the next few weeks!