7 unique things that make Quirkos awesome

quirkos is awesome


Quirkos is now 3 years old!

To celebrate, we’re taking a break from our regular programming of qualitative method posts to remind everyone why Quirkos is the best qualitative analysis software around...

 

1. All the colours!

Obviously I’m going to start with the most important features first. Some qualitative analysis software restricts you to only 8 colours when customising your themes. Quirkos lets you choose from 16 million colours and that may sound daft, but once you have a large coding framework, giving similar shades of colour to similar themes really makes the coding quicker. Many people find they can identify a colour a lot quicker than they can read a label. You can also easily assign meaning to colours: red things being bad, green things for the environment etc.

 

2. Interactive coding

It’s the moment I’ve come to love most when doing training workshops, the ‘Ahhh!’ of the audience when they see the bubbles grow for the first time when you drop text on them. And so quickly you realise that it is a lot more than a gimmick: having the size of the themes represent the coding lets you see not just that you put the code in the right place, but what topics are emerging most from your coding. It makes me feel a lot closer to my data, and seeing the themes evolve is really engaging.

 

download quirkos

 

3. No Save button

Quirkos is constantly saving after each action, so there is no save button in the interface. I think this initially causes some anxiety in users used to setting up an auto-save or worrying they will loose data. But eventually, it becomes so liberating to just focus on your work. If Quirkos or Windows crashes, or even if you pull out the cord on your computer, when you come back to your project it will be just as you left it.

 

4. Quick and free to learn.

We designed Quirkos to be simple, with the main features you need to do deep analysis and reading of your data, and no distractions from flashy or complex features. A lot of people come to Quirkos after despairing at the amount of time it takes to learn other software packages. Most people who do qualitative analysis aren’t interested in learning technical software. They just want to focus on their research ideas and the data.

All our training materials are freely available online, even our monthly webinars which (unlike others) we don’t charge for or require registration. Some CAQDAS packages can require a lot of extra training, a cost in terms of time and money that institutions sometimes forget to factor in.

 

5. True cross-platform freedom

Quirkos not only has the same features and interface on Windows and Mac, but is fully supported on Linux as well. And project files are completely compatible, so you can pick up and work on any computer using any operating system. If you have Windows at work and a Macbook at home, no problem. We are the only CAQDAS software to support all these platforms, and unlike Nvivo, we let you go from Mac to Windows (and back) without changing your files.

 

6. Free updates

When I was working with other qualitative software for my post-doc research, we had serious problems when new versions of the software came out. It would create new (and terrifying bugs), require us to buy a new licence, and made our data no longer compatible with the old version. Since academic organisations aren’t always the most speedy at installing updates, it meant that we always had issues with a collaborator using an older (or newer) version of the software that wasn’t compatible. This frustrated me so much, I have promised this will not happen in Quirkos.


Over the last 3 years we’ve released 6 updated versions of Quirkos now, and they are all free updates, backward and forward compatible. This means that there is no reason for anyone to be stuck using an old version, and even if they didn’t bother to download the free update, they can still collaborate fully with colleagues using different versions.

 

7. Student licences that don’t expire

In the UK, a typical PhD lasts 4 years, in the US the average is 8.2 years. If you are doing teaching as part of your scholarship or are doing doctoral studies part time, this can get even longer. That’s why our student licences don’t expire. I don’t know why our competitors sell 1 or 2 year licences for students – it always annoyed me when I was studying. Unless you are doing your masters, you’ll probably have to buy another one half way through your research. Sure, you can buy last minute after you’ve done all your data collection, but that is a bad way to do iterative qualitative analysis.

 

Our student licences are the same price (or cheaper) than most other one or two year licences, but are yours for life: for your postdoc career and beyond. I don’t want to see people loose access to their data, and it’s no surprise that we sell so many student licences.

 

So try Quirkos for yourself, and see why researchers from more than 120 universities across the world use it to make their their qualitative analysis go a bit smoother. We’ve got a one month free trial of the full, unrestricted version of Quirkos for you to download right here (that’s also the longest free trial offered for CAQDAS!).

 

Quirkos vs Nvivo: Differences and Similarities

quirkos vs nvivoI’m often asked ‘How does Quirkos compare to Nvivo?’. Nvivo is by far the largest player in the qualitative software field, and is the product most researchers are familiar with. So when looking at the alternatives like Quirkos (but also Dedoose, ATLAS.ti, MAXQDA, Transana and many others) people want to know what’s different!

 

In a nutshell, Quirkos has far fewer features than Nvivo, but wraps them up in an easier to use package. So Quirkos does not have support for integrated multimedia, Twitter analysis, quantitative analysis, memos, or hypothesis mapping and a dozen other features. For large projects with thousands of sources, those using multimedia data or requiring powerful statistical analysis, the Pro and Plus versions of Nvivo will be much more suitable.


Our focus with Quirkos has been on providing simple tools for exploring qualitative data that are flexible and easier to use. This means that people can get up and running quicker in Quirkos, and we hear that a lot of people who are turned off by the intimidating interface in Nvivo find Quirkos easer to understand. But the basics of coding and analysing qualitative data are the same.


In Quirkos, you can create and group themes (called Nodes in Nvivo), and use drag and drop to attach sections of text to them. You can perform code and retrieve functions by double clicking on the theme to see text coded to that node. And you can also generate reports of your coded data, with lots of details about your project.


Like Nvivo, we can also handle all the common text formats, such as PDFs, Word files, plain text files, and the ability to copy and paste from any other source like web pages. Quirkos also has tools to import survey data, which is not something supported in the basic version of Nvivo.


While Quirkos doesn’t have ‘matrix coding’ in the same way as Nvivo, we do have side-by-side comparison views, where you can use any demographic or quantitative data about your sources to do powerful sub-set analysis. A lot of people find this more interactive, and we try and minimise the steps and clicks between you and your data.


Although Quirkos doesn’t really have any dedicated tools for quantitative analysis, our spreadsheet export allows you to bring data into Excel, SPSS or R where you have much more control over the statistical models you can run than Nvivo or other mixed-methods tools allow.

 

However, there are also features in Quirkos that Nvivo doesn’t have at the moment. The most popular of these is the Word export function. This creates a standard Word file of your complete transcripts, with your coding shown as color coded highlights. It’s just like using pen and highlighter, but you can print, edit and share with anyone who can open a Word file.


Quirkos also has a constant save feature, unlike Nvivo which has to be set up to save over a certain time period. This means that even in a crash you don’t loose any work, something I know people have had problems with in Nvivo.


Another important differential for some people is that that Quirkos is the same on Windows and Mac. With Nvivo, the Windows and Mac versions have different interfaces, features and file formats. This makes it very difficult to switch between the versions, or collaborate with people on a different platform. We also never charge for our training sessions, and all our online support materials are free to download on our website


And we didn’t mention the thing people love most about Quirkos – the clear visual interface! With your themes represented as colourful, dynamic bubbles, you are always hooked into your data, and have the flexibility to play, explore and drill down into the data.


Of course, it’s best to get some impartial comparisons as well, so you can get reviews from the University of Surrey CAQDAS network here: https://www.surrey.ac.uk/sociology/research/researchcentres/caqdas/support/choosing/


But the best way to decide is for yourself, since your style of working and learning, and what you want to do with the software will always be different. Quirkos won’t always be the best fit for you, and for a lot of people sticking with Nvivo will provide an easier path. And for new users, learning the basics of qualitative analysis in Quirkos will be a great first step, and make transitioning to a more complex package like Nvivo easier in the future. But download our free trial (ours lasts for a whole month, not just 14 days!) and let us know if you have any questions!

 

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!

 

 

Reflections on qualitative software from KWALON 2016

rotterdam centraal station

Last week saw a wonderful conference held by the the Dutch network for qualitative research KWALON, based at the Erasmus University, Rotterdam. The theme was no less than the future of Qualitative Data Analysis (QDA) software.

 

Chair Jeanine Evers opened the session by outlining 8 important themes the group had identified on qualitative analysis software.

 

The first was the challenge of adding features to software that is requested by users or present in competitors software, without breaking the underlying design of the software. Quirkos really connects to this theme, because we have always tried to have a very simple tool-set, based on a philosophy that the software should be very easy to use. While we obviously take heed of suggestions made by our users, we actually have a comprehensive and limited set of features which we have always planned to introduce, and will continue delivering these over the next few years.

 

However, it is not the intention of Quirkos to become a large software package with lots of features, something Jeanine described as a ‘obese software’ that needs to be put on a diet. It was noted that many software providers have released ‘lite’ versions of their software, and another discussion point was if this fragmented approach can benefit universities and users.

 

User friendliness was another theme of the session, and by keeping Quirkos simple we hope to always have this at the fore of our design philosophy. In my talk (you can now get the slides here) I discussed these themes as mostly being about improving accessibility. To this end, we have tried to make Quirkos not just easier to use, but also to teach and own, with permanent licences and discounts for researchers from  countries that can’t usually afford this type of software. For us, the long-term goal is not just increasing the number of people that use software for qualitative analysis, but the number that are able to take up qualitative research in general.

 

There was also some good discussion at the end of our talk about the risks of making software easy to use: especially that it also makes it easy to use badly. As we’ve discussed many times on this blog, software in general can make it very satisfying to code, and this can appear to be more productive than stepping back and thinking about themes or a undertaking deep readings of the data. These problems can apply to all software packages, so it is important that students and educators work together to learn about the whole analysis procedure, and what part CAQDAS can play.

 

Comments also touched on how memo making is a critical part of a good iterative and reflexive qualitative analysis process: which at the moment Quirkos doesn’t forefront (see for example how F4analyse and a future version of Cassandre will operate). Although it is possible to record memos by typing in a source, which gives you the ability to tag and code your memos, as well as writing notes as source properties, this is currently not highlighted enough and we plan on revamping the memo features in a future update.

 


The final theme of the conference, and a major push, was to promote a standard way to exchange software between qualitative software. At the moment it is very difficult for users to move their coded data from one software package to the other. Although most major packages provide options to export their data to other formats (such as spreadsheet CSV data like Quirkos), there is currently no single standard for how should be formatted, so it is very difficult to bring this data – complete with themes and coding - into another package.

 

There was strong support from the software developers to develop and support such a standard, as well as discussions about existing initiatives such as CATA-XML and QuDEx.


This is very important: but not just for users of different of qualitative analysis software, who want to be able to collaborate with universities and colleagues who use different packages. It’s also important for archival purposes, so that qualitative coded data can be universally shared and stored for secondary analysis, and to make it easier for data to be brought in for analysis from the huge number of digital sources in the digital humanities, such as history, journalism, and social media. Such a standard could also be important for formatting data so that machine learning and natural language processing can automate some of the simpler analysis processes on very large ‘big-data’ datasets.


So there is a lot to be done, but a lot of interest in the area in the next few years, with major and minor players all taking different approaches, and seeking common ground. Quirkos is honoured to be a small part of this, and will do whatever we can to improve the world of qualitative analysis for this and the next generation of researchers.

 

 

Include qualitative analysis software in your qualitative courses this year

teaching qualitative modues

 

A new term is just beginning, so many lecturers, professors and TAs are looking at their teaching schedule for the next year. Some will be creating new courses, or revising existing modules, wondering what to include and what’s new. So why not include qualitative analysis software (also known as CAQDAS or QDA software)?

 

There’s a common misconception that software for qualitative research takes too long to teach, and instructors often aren’t confident themselves in the software (Gibbs 2014), leading to a perception that including it in courses will be too difficult (Rodik and Primorac 2015). It’s also a sad truth that few universities or colleges have support from IT departments or experts when training students on CAQDAS software (Blank 2004).

 

However, we have specifically designed Quirkos to address these challenges, and make teaching qualitative analysis with software simpler. It should be possible to teach the basics of qualitative analysis, as well as provide students with a solid understanding of qualitative software in a one or two hour seminar, workshop or lecture. One of the main aims with Quirkos was to ensure it is easy to teach, as well as learn.

 

With a unique and very visual approach to coding and displaying qualitative data, Quirkos tries to simplify the qualitative analysis process with a reduced set of features and buttons. This means there are fewer steps to go over, a less confusing interface for those starting qualitative analysis for the first time, and fewer places for students to get stuck.

 

To make teaching this as straightforward for educators as possible, we provide free ready-to-use training materials to help educators teach qualitative analysis. We have PowerPoint slides detailing each of the main features and operations. These can be adapted for your class, so you can use some or all of the slides, or even just take the screenshot images and edit the specifics for your own use.

 

Example qualitative data sets are available for use in classes. There are two of these: one very basic set of people talking about breakfast habits and a more detailed one on politics and the Scottish Independence Referendum. With these, you can have complete sources of data and exercises to use in class, or to set a more extensive piece of homework or practical assessed project.

 

We also provide two manuals as PDF files that can be shared as course materials or printed out. There is a full manual, but also a Getting Started guide which includes a step-by-step walkthrough of basic operations, ideal for following in a session. Finally, there are video guides which can be shown as part of classes, or included in links to course materials. These range in length from 5 minute overviews to 1 hour long detailed walkthroughs, depending on the need.

 

There is more information in our blog post on integrating qualitative analysis software into existing curriculums, but it’s also worth remembering that there is a one month free trial for yourself and students. The trial version has all the features with no restrictions, and is identical for students working on Windows, Mac or even Linux.

 

However, if you have any questions about Quirkos and how to teach it, feel free to get in touch. We can tell you about others using Quirkos in their classes, some tips and tricks and any other questions you have on comparing Quirkos to other qualitative analysis software.  You can reach us on Skype (quirkos), email (support@quirkos.com) or by phone during UK office hours (+44 131 555 3736). We’ll always be happy to set up a demo for you: we are all qualitative researchers ourselves, so are happy to share our tips and advice.

 

Good luck for the new semester!

 

Tips for managing mixed method and participant data in Quirkos and CAQDAS software

mixed method data

 

Even if you are working with pure qualitative data, like interview transcripts, focus groups, diaries, research diaries or ethnography, you will probably also have some categorical data about your respondents. This might include demographic data, your own reflexive notes, context about the interview or circumstances around the data collection. This discrete or even quantitative data can be very useful in organising your data sources across a qualitative project, but it can also be used to compare groups of respondents.

 


It’s also common to be working with more extensive mixed data in a mixed method research project. This frequently requires triangulating survey data with in-depth interviews for context and deeper understanding. However, much survey data also includes qualitative text data in the form of open-ended questions, comments and long written answers.

 


This blog has looked before at how to bring in survey data from on-line survey platforms like Surveymonkey, Qualtrics and Limesurvey. It’s really easy to do this, whatever you are using, just export as a CSV file, which Quirkos can read and import directly. You’ll get the option to change whether you want each question to be treated as discrete data, a longer qualitative answer, or even the name/identifier for each source.

 


But even if you haven’t collected your data using an online platform, it is quite easy to format it in a spreadsheet. I would recommend this as an option for many studies, it’s simply good data management to be able to look at all your participant data together. I often have a table of respondent’s data (password protected of course) which contains a column for names, contact details, whether I have consent forms, as well as age, occupation and other relevant information. During data collection and recruitment having this information neatly arranged helps me remember who I have contacted about the research project (and when), who has agreed to take part, as well as suggestions from snowball sampling for other people to contact.

 


Finally, a respondent ‘database’ like this can also be used to record my own notes on the respondents and data collection. If there is someone I have tried to contact many times but seems reluctant to take part, this is important to note. It can remind me when I have agreed to interview people, and keep together my own comments on how well this went. I can record which audio and transcript files contain the interview for this respondent, acting as a ‘master key’ of anonymised recordings. 

 


So once you have your long-form qualitative data, how best to integrate this with the rest of the participant data? Again, I’m going to give examples using Quirkos here, but the similar principals will apply to many other CAQDAS/QDA software packages.

 


First, you could import the spreadsheet data as is, and add the transcripts later. To do this, just save your participant database as a CSV file in Excel, Google Docs, LibreOffice or your spreadsheet software of choice. You can bring in the file into a blank Quirkos project using the ‘Import source from CSV’ on the bottom right of the screen. The wizard in the next page will allow you to choose how you want to treat each column in the spreadsheet, and each row of data will become a new source. When you have brought in the data from the spreadsheet, you can individually bring the qualitative data in as the text source for each participant, copy and pasting from wherever you have the transcript data.

 


However, it’s also possible to just put the text into a column in the spreadsheet. It might look unmanageable in Excel when a single cell has pages of text data, but it will make for an easy one step import into Quirkos. Now when you bring in the data to Quirkos, just select the column with the text data as the ‘Question’ and discrete data as the ‘Properties’ (although they should be auto-detected like this).

 


You can also do direct data entry in Quirkos itself, and there are some features to help make this quick and relatively painless. The Properties and Values editor allows you to create categories and values to define your sources. There are also built in values for True/False, Yes/No, options from 1 -10 or Likert scales from Agree to Disagree. These let you quickly enter common types of data, and select them for each source. It’s also possible to export this data later as a CSV file to bring back into spreadsheet software.

 

mixed method data entry in quirkos

 

Once your data has been coded in Quirkos, you can use tools like the query view and the comparison views to quickly see differences between groups of respondents. You can also create simple graphs and outputs of your quantitative and discrete data. Having not just demographic information, but also your notes and thoughts together is vital context to properly interpreting your qualitative and quantitative data.

 

 

A final good reason to keep a good database of your research data is to make sure that it is properly documented for secondary analysis and future use. Should you want to ever work with the data again, share it with another research team, or the wider community, an anonymised data table like this is important to make sure the research has the right metadata to be used for different lines of enquiry.

 

 

Get an overview of Quirkos and then try for yourself with our free trial, and see how it can help manage pure qualitative or mixed method research projects.

 

 

 

Quirkos version 1.4 is here!

quirkos version 1.4

It’s been a long time coming, but the latest version of Quirkos is now available, and as always it’s a free update for everyone, released simultaneously on Mac, Windows and Linux with all the new goodies!


The focus of this update has been speed. You won’t see a lot of visible differences in the software, but behind the scenes we have rewritten a lot of Quirkos to make sure it copes better with large qualitative sources and projects, and is much more responsive to use. This has been a much requested improvement, and thanks to all our intrepid beta testers for ensuring it all works smoothly.


In the new version, long coded sources now load in around 1/10th of the time! Search results and hierarchy views load much quicker! Large canvas views display quicker! All this adds up to give a much more snappy and responsive experience, especially when working with large projects. This takes Quirkos to a new professional level, while retaining the engaging and addictive data coding interface.


In addition we have made a few small improvements suggested by users, including:


• Search criteria can be refined or expanded with AND/OR operands
• Reports now include a summary section of your Quirks/codes
• Ability to search source names to quickly find sources
• Searches now display the total number of results
• Direct link to the full manual

 

There are also many bug fixes! Including:
• Password protected files can now be opened across Windows, Mac and Linux
• Fix for importing PDFs which created broken Word exports
• Better and faster CSV import
• Faster Quirk merge operations
• Faster keyword search in password protected files

 

However, we have had to change the .qrk file format so that password protected files can open on any operating system. This means that projects opened or created in version 1.4 cannot be opened in older versions of Quirkos (v1.3.2 and earlier).


I know how annoying this is, but there should be no reason for people to keep using older versions: we make the updates free so that everyone is using the same version. Just make sure everyone in your team updates!

 

When you first open a project file from an older version of Quirkos in 1.4, it will automatically convert it to the new file format, and save a backup copy of the old file. Most users will not notice any difference, and you can obviously keep working with your existing project files. But if you want to share your files with other Quirkos users, make sure they also have upgraded to the latest version, or they will get an error message trying to open a file from version 1.4.

 

All you need to do to get the new version is download and install from our website (www.quirkos.com/get.html) and install to the same location as the old Quirkos. Get going, and let us know if you have any suggestions or feedback! You could see your requests appear in version 1.5!

 

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.

 

 

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!