Lyn’s favourite things: Time management strategies
By Lyn Lavery
Following on from my last ‘Favourite Things’ post on keeping organised, this month I’m covering tips for maximising my time. I’m a big fan of making the most of the time I have as it means I have more time to spend on the things I enjoy. Here are my three favourite strategies for doing just that.
Eat a frog
If you’ve ever had the experience of sitting down to check your emails first thing in the morning, only to realise three hours later that the most productive time of your day has disappeared, then I highly recommend frog eating. The idea comes from Mark Twain – he suggested that if you eat a live frog first thing in the morning, you’ll know that’s the worst thing that will happen to you all day. The popular time management book Eat That Frog by Brian Tracey suggests that your “frog” is your biggest and most important task. For many of us, this is the task that we are most likely to procrastinate over. It’s also potentially the task that could make the biggest difference to productivity or progress towards a larger goal.
Tracey’s book has some excellent tips for frog eating (e.g. if you have to eat a live frog, it doesn’t pay to sit and look at it for very long). For researchers, I have a couple of my own tips:
Don’t eat a frog that’s too large – tasks (and frogs) are easier to achieve when they’re bite-sized. ‘Work on my PhD’ is too large, and not specific enough, but reading that journal article on your desk is do-able in one sitting.
Reward yourself for eating your frog – here at Academic Consulting we keep Freddos (a.k.a. chocolate frogs) on hand for when we finish a particularly difficult task.
The Pomodoro Technique is based on those tomato shaped oven timers that you’ve probably seen before – Pomodoro is Italian for tomato. The idea is that you set a timer for 25 minutes, and you work uninterrupted for that time – turn your phone, email etc. off and just focus. After 25 minutes, take a 5 minute break and do something different – stretch, get a cup of tea or walk around the office. You then start another 25 minute block. The people that developed the technique suggest that for every four Pomodoro’s you complete, you should take a longer break. I find for me personally, I need to take a longer break after three.
There are a number of things that I particularly like about the Pomodoro Technique – one is that you start to learn how long things take you – most of us are terrible at estimating how long a task will take, but you start to get better at this once you chunk things into 25 minute blocks. Also, research consistently shows that regular breaks improve performance, but we can be quite bad at actually doing this, so the Pomodoro Technique is a good reminder.
Fit the big rocks in first
A standard technique for teaching time management is to give a group a pile of rocks and a carton of sand and ask them to put both into a jar. The idea is that the rocks represent the high priority tasks and the sand is the low priority tasks. Obviously the order you put them into the jar is important. If you put the sand in first, the rocks just aren’t going to fit. If you put the rocks in first, the sand can filter into the jar around it. Moral of the story, if you don’t complete the important tasks first, they’re not going to get done.
A nice technique for helping you fit those big rocks in is to make a meeting with yourself – literally. If you were meeting another person, you’d arrive on time with your phone switched off and you’d dedicate your concentration for the time you have set aside. So why not treat your own time with as much respect? The really nice thing about this technique is when a colleague or family member asks you to do something else, you can honestly say, “I’m sorry but I have a meeting at that time”.
My last tip also relates to the jar of rocks – there’s always smaller blocks of time that you can make the most of. The jar looks full with rocks, but there are in fact small gaps. I like to keep a list of tasks that will only take me 5–10 minutes (I call these my ‘quick wins’). That way when I find myself with a few minutes to spare I can get a task achieved and cross it off my list.
Pick one of the above techniques to try out over the next week – remember though that not all strategies work equally well for everyone so it’s important to find what works for you personally!
Tips for online training
By Lyn Lavery
If you’ve enrolled in one of Academic Consulting’s upcoming online training courses, we recommend you take the time to plan ahead to ensure you get the most out of the session. We’ve compiled some tips to help you do just that.
Check in advance whether you can successfully connect
We use GoToWebinar to deliver our online training – this doesn’t require any special equipment to participate but there are some minimum system requirements. GoToWebinar have a Get Ready page that you can visit to check whether you meet these. This webpage does all the work for you, checking your OS, browser version, and even the strength of your internet connection.
Also on the above ‘Get Ready’ page is a link to connect to a test session. We strongly recommend that you try this well in advance of the session – if you experience issues connecting you’ll need to troubleshoot, and it’s possible that you may need to seek support from your local IT staff. You don’t want to be doing this two minutes before the session is due to start!
Ensure you have a stable internet connection
Online training can use considerable bandwidth, so plan to attend the training at a location with a stable internet connection (using the guest WiFi at your local café is probably not the best idea, much as the coffee is probably excellent). If you find the audio or video skipping during the session, try closing down other applications that may be using bandwidth such as your email or Skype.
Things to think about for software training
If you’re attending a software-related training course such as NVivo or SPSS, check beforehand that your license is up-to-date and that the version you’re using matches the one we’ll be presenting with (the version number is always detailed in the course description). If you’re using a different OS or version, don’t panic – the course may still be relevant to you, but check with us beforehand to make sure.
For our software training courses, you’ll receive a copy of the practical exercise files beforehand in case you’d like to follow along as we present. Ensure you download these locally before the course so that you have easy access to them.
Following along live with the presentation works best if you have a dual screen set-up (it’s a little tricky juggling both GoToWebinar and the software you need on a single screen). If you’re not lucky enough to have two monitors, you could consider having a second device set-up. For example, you could play the webinar on a mobile device while you’re working through the exercises on your computer. If that all sounds a bit too tricky, don’t feel like you need to follow along live – you’ll receive a copy of the recording after the session and you will be able to use this to practise at a later stage.
Maximise your learning opportunities
For any of our training courses that are two hours or longer in length, we send you a copy of the course materials (handouts and slides) ahead of time. It might be helpful to review these beforehand and also print them off in case you wish to take additional notes.
You’ll receive a link to a recording of the session and will have access to this for a two-week period. Try and make some time to review the material as soon as possible after the course – this is a great strategy to solidify new learning.
To get the most out of your online training, and to minimise distractions, pop a do not disturb sign on your office door and turn your email and phone off.
Do ask questions throughout and make the most of opportunities for interaction – this is an excellent way to learn the material and you’ll likely enjoy the session more by participating.
Lyn’s favourite things: Keeping organised
By Lyn Lavery
In case anyone missed our recent research webinar series, I thought I’d do a rundown of my favourite tips, starting out with what I use to stay on top of the huge pile of information, ideas, literature, and data that comes my way. I think I sometimes give the impression that I’m a seriously organised and efficient person, but my colleagues will attest to the fact that being organised isn't something that comes naturally to me – I definitely have to work at it, and these are the things in my research toolkit that assist with this.
I use Trello to organise the projects and tasks I need to complete. It’s like having a giant wall with different coloured post-it notes that you can constantly re-arrange depending on their priority. Tasks can have due dates and other information assigned to them and you can organise these tasks to suit. Trello becomes particularly useful when you’re working in a team, as everyone has a central place to see what needs to be done, and as it’s online, everyone in your team can access it. Trello is free or you can subscribe for additional functionality and storage.
Evernote is my “go to” application for storing information such as meeting notes, snapshots of webpages, and reminders of project-critical information that I might need while I’m out of the office. The thing I love the most about Evernote is that I’ve never not been able to locate a piece of information I needed. You can tag information with keywords and store within customised notebooks, and the powerful search function recognises even the messiest handwriting. There is a free version of Evernote, but once you start using it you’ll likely be hooked and want to splash out for one of the paid subscriptions.
XMind is a mind mapping application that I use for notetaking and tracking the light bulb moments I have as a researcher. I use it for a range of purposes, for example, to help me take notes at a research team meeting, plan a chapter I’m going to write, or even just brainstorm for an upcoming project. There is a free version with reasonable functionality, or you can pay to upgrade to XMind Pro.
Zotero helps me keep my literature organised – importing information into my account is a breeze and once it’s there I can easily organise it within custom collections or with tags (keywords). My PDFs are neatly linked to the citation they relate to and I can take notes on each article that are attached to the item itself. Zotero is open source so you don't need to pay for it, but there are costs involved if you exceed the basic storage capacity.
Lastly, NVivo is my software of choice when it comes to managing my qualitative data. Not only does it keep my coding nicely organised, but I can use memos to keep track of my own reflections, I can ask it to track every action I make in a project, and its search capacity helps me track down that great quote that I just can’t seem to lay my hands on. I might have conducted my qualitative analysis with highlighter pens and scissors in the past, but now that I’ve used NVivo there’s no going back – it makes my life as a researcher significantly easier. There is a price tag attached, but check with your organisation as to whether they have an existing license you can tap into.
There’s a growing trend towards training courses being offered in online formats. Here at Academic Consulting, we prefer face-to-face training (we like to see your smiling faces!), but the reality is that busy researchers often don’t have the time to attend face-to-face courses.
When I mention that most of our training is now online, I’m usually greeted with horrified expressions. Being a curious researcher, I’ve been interested to understand why, and as a result I’m increasingly aware of the different views people have about online learning. So, I decided to dispel a few of the myths for you...
Myth #1: I won’t be able to ask questions
Online training often refers to pre-recorded content that can be watched at your own pace, but this isn’t always this case. For example, some online training provides the capacity for you to ask questions in an asynchronous format. Sure, you don’t get an answer right away, but you can still ask! In an Academic Consulting training course, you can do both – our sessions are presented live and the facilitator answers submitted questions as they come in. Sometimes the best questions don’t occur to you until after the training though – you’re welcome to email these through to us when they come to mind.
Myth #2 & #3: My technical skills aren’t good enough/I can’t attend as I don’t know what to do
The system we use is incredibly user-friendly. If you’re new to the format, check out the YouTube video we’ve created for newbies – this shows you how to connect, what the platform looks like etc.
Not sure you’ve got the right equipment to take part? All you need is an internet connected device and speakers (headphones might be useful if you share an office). You can be using a desktop, laptop, or mobile device – it doesn’t matter. Not sure your machine has what it takes? GoToWebinar will automatically check whether you meet the system requirements if you visit: https://care.citrixonline.com/gotowebinar/get-ready.
If you’re unsure about the technical side of things – you can “try before you buy”. We have a number of free, one-hour webinars that you can attend to see how you find the experience. Details of upcoming webinars can be viewed on our training schedule
Myth #4: I won’t be able to keep up
No worries – we record all our sessions, and you’ll have access to the recording for two weeks after the training. If you need the content later on, just email us to ask and we’ll grant you access again. For our software workshops, having a recording to practise with makes for an ideal learning experience – if you can’t keep up in the live session you can watch again, and press pause whenever you need to.
Myth #5: I won’t get training notes
As part of your registration fee for our online sessions, you’ll receive training notes and/or copies of Powerpoint slides. We send these beforehand so that you can print them off to take notes during the session if you want to - just like being in a face-to-face class. Speaking of which...
Myth #6: I won’t feel part of a ‘class’
It certainly won’t be exactly the same experience, but you’ll get to hear other attendees’ questions, and take part in quizzes and other interactive exercises. We put a lot of effort into ensuring our online courses are as similar to face-to-face classes as possible, so while you won’t be able to “see” fellow attendees, you’ll get a feel for who else is online with you.
If you still have concerns or are not sure which course is right for you, then don’t hesitate to contact me to discuss. I look forward to “seeing” you online!
NVivo coding tips and tricks
By Lyn Lavery
We’ve used NVivo extensively for coding over the years and have discovered a number of tips and tricks that we’d like to share. We’re not suggesting that these are the “right” way to code (we don’t believe there is such a thing), but we’ve certainly found that we’ve saved ourselves some time, not to mention headaches, by following the suggestions below!
Create descriptions for all your nodes
Take the time to enter descriptions when you create nodes. This can be beneficial both to the coding process, as well as your overall data analysis. Nodes often represent abstract or complex concepts, so it’s easy to forget what you intended, and meanings can evolve over time as your analysis progresses. For those of you working in teams, descriptions are particularly important to ensure that everyone has a shared understanding of the nodes. Descriptions can be entered as you create a node within the ‘New Node’ dialog box, or you can insert and amend them at a later stage.
Keep an eye on the number of nodes in your project
One of the problems with NVivo (admittedly a positive one) is that it is very easy to create nodes and perform coding. The downside of this is that it is very easy to get carried away! Having a large number of very specific nodes can slow you down and negatively impact on the overall quality of your data analysis.
One of the most common questions we’re asked is “How many nodes should I have in my NVivo project?” Our usual response is that there is no magic number – this will be driven by your methodology and research questions, the type of analysis you are looking to perform, as well as the nature of your data. Keep in mind though that ‘less is more’!
Be selective about how much data you code
Another area where the ‘less is more’ principle applies is in relation to the amount of text to select when coding. Many researchers intuitively want to include surrounding contextual data. Unfortunately, this can create problems later on as you end up with lots of extra reading around the primary content. It also makes it difficult to discern patterns in the data. We recommend that you code only the data that specifically relates to the node that you are coding to. And, remember that NVivo allows you to easily view contextual information if needed. Simply right-click over coded text and select either Open Referenced Source, Coding Context, or Spread Coding.
Keep track of your coding
I know that I like to keep track of my coding as I go, just to make sure the information has been coded to the right node. There are a few ways to do this - my preference is to use the ‘Coding Density Bar’ (from the ribbon choose View > Coding Stripes > Coding Density Only). This appears as a stripe down the right-hand side of your document, and if you ‘hover’ your mouse over the stripe it will list all the nodes that relate to that section of data. As this is updated as you code, you’re able to keep an eye on which node(s) the data has been coded to.
Allow sufficient time for coding
Lastly, don’t under-estimate how long the coding process will take. Even with the benefit of a tool such as NVivo, qualitative data analysis can be a complex process and you need sufficient time to do it justice. When planning your research, we recommend that you leave yourself more time than you think you will need for this stage of the process. It’s also important that you avoid coding for too long in one sitting, and we always like to take a break between coding each source. These simple steps will help maintain a high standard of coding for your research project.
There’s only room to share some of our coding advice in this blog, so if you’d like to extend your learning in this area, consider attending our online course Become an NVivo Coding Ninja. We’ve got a lot more tips to share! Alternatively, our NVivo Core Skills course is suitable for those new to the software who are looking for an introduction to the coding process, and is offered both face-to-face and online. Hope to see you there!
What's a masterclass?
By Lyn Lavery
I’ve been pondering the meaning of the term ‘masterclass’. I began thinking about this last November when I caught up with some of my fellow NVivo trainers in Melbourne. One of them had enrolled in a survey masterclass and was rather annoyed to find that it was introductory level. At the time I had just scheduled some masterclasses for our own training programme, so I was left wondering whether I had appropriately described these!
Fast forward six months and I found myself enrolling in a masterclass at my local yoga studio. Sitting in the studio that morning, a moment of horror dawned – what on earth was I doing in a masterclass? I’d only been practising yoga for a year – remembering the names of the poses was hard enough, never mind the correct placement of my feet (the fact that I’m terribly clumsy and hopeless at remembering left from right doesn’t help either, but that’s a story for another blog post!).
Once I got past the fact that I was completely out my depth, I got an enormous amount out of that particular class. I not only learned lots from the teacher, but also from the more advanced students attending. There were some really interesting discussions (which I could mostly understand thanks to having been taught the basics well), there were a lot of laughs, and most importantly I left feeling inspired about what was possible with my yoga practice.
A quick check on Google for the term masterclass reveals various definitions, all of which focus on the class being taught by an expert. I particularly liked a definition that suggested a masterclass is taught by someone who is “charismatic”, but that’s probably because I’m teaching our sessions! In terms of who attends a masterclass, some definitions state that the attendees would be “exceptional” or “good students”, while others suggest that masterclasses are suitable for beginners through to experts.
So having thought at length about this, I’ve decided that a masterclass is a one-off, special event, taught by someone who is expert in the subject matter, and hopefully charismatic! Attendees may include anyone with a genuine interest in the subject, regardless of their level of experience, but ideally they'll know the basics.
So – if you like the sound of our two upcoming masterclasses on Qualitative Data Analysis and NVivo – but are worried you’re not “expert” enough, then you might like to rethink this! For the Qualitative Data Analysis Masterclass, all you need to know is a little about the process of coding, and ideally you’ll have had a go at analysing some qualitative data yourself. The NVivo Masterclass requires that you know how to set up a project and perform coding, and you’ll also need a basic understanding of classifications and queries. My hope is that like my own recent experience at a masterclass, you’ll learn lots, we’ll have some laughs and interesting discussions, and most importantly you’ll leave feeling inspired for your next qualitative project. Can’t wait to see you there!
Writing up qualitative research
By Rachael Butler
While preparing for one of our Writing up Qualitative Research workshops recently, I began to reminisce about my early research career and the process of writing reports back in the early 90s (yep, that long ago!). These were the days when I had to share a computer with the other junior researcher in the organisation – we mainly hand wrote our reports and passed them over to production staff who would type them up for us. Our manager would then make significant edits via red pen slashes across the page, the material would be sent back to the production team, and so the process would go. Thankfully, technology and work practices have moved on, but it did remind me of the sweat and tears I used to go through to draft a report. I also remember that, while I struggled with writing for a number of years, all of a sudden something just seemed to ‘click’ and it has actually now become one of my favourite stages of the research process.
So, I thought I’d share a few things I’ve learnt along the way to streamline the writing process: both in terms of saving time, and in relation to reducing stress levels!
Start with the easy stuff. If I’m having an off day and struggling to write, instead of torturing myself trying to finish the section I had earmarked for completion, I switch my focus to the ‘easy stuff’. Material that falls into this category generally includes descriptive sections such as methods or sample composition. More often than not, this gets me into a writing flow and I can then switch back to the earlier material, which somehow no longer seems as difficult.
Don’t labour too long over a sentence or phrase (or even a word). Again, this can result in increased stress and delays to your writing. If I’m struggling to find the right word or phrase I either insert something temporary and highlight it, or just put in a series of ???? to hold the place. Usually when I come back to it later, it is much easier to identify the right words or phrases.
Make use of existing material. There’s nothing more satisfying than copying and pasting material from earlier documents (e.g. a research proposal) into your report or thesis. Boom - instant word count! You will probably need to tweak it a bit, but I generally find it easier to edit earlier writing rather than starting from scratch. Existing material can also include field notes or memos you’ve kept during your research journey that can be transformed into findings within your document.
Make sure your analysis is complete before you start writing. If I try and start writing a chapter or section before I have fully analysed the data, I generally find it difficult to get my ideas down on the page. Or, at the very least, they come out jumbled and unclear. Although it may feel a bit like you are going backwards in the process, if this happens to you, I would suggest that you go back to your data, revisit your analysis, and start writing again once it’s clearer in your mind. This almost always resolves the problem for me.
Pick your time of day to write. I don’t know about you, but come 3 o’clock in the afternoon my brain tends not to be at its peak performance (my colleagues will attest to this!). I am most definitely a morning person, and boy is this evident when it comes to writing. The paragraph I struggle over at 6pm, I can whip up in five minutes at 6am the next morning. My preferred writing time is between about 6am and 11am. This may be different for you – I have friends who get on a roll with writing at 2am. Whenever your productive time is, make sure you schedule your writing around this.
Edit from paper-based copies. I can touch type and am pretty fast on the old keyboard – but when it comes to serious editing, I find that I do it more effectively from print-outs of my writing. There’s something about moving away from my computer and reading through a paper copy that allows me to get a better sense of the text, how it flows, and whether or not the structure is working. I usually do this well into my writing, when I’ve got a reasonable chunk of text to review. I know it’s not great for the environment to be printing out reams of paper every day, but you can minimise the impact by being selective about when you do it, making sure you print double-sided, two pages per sheet, etc.
I hope the above tips are helpful for those of you who find the writing process difficult. Let us know if you have any other tips from your own experiences – we’d love to hear them! And, if you are interested in learning more, consider signing up for our Writing Up Qualitative Research online training course.
Why I love Zotero
By Lyn Lavery
I was an early adopter of EndNote – I hate to show my age, but I started using it when Endnote 2 was around. I was a pretty big fan for years – I think I must have facilitated several hundred EndNote training courses when I worked at The University of Auckland, and I certainly used it for both my master's and PhD theses. Somewhere around EndNote 9 I started to lose enthusiasm due to the combination of technical glitches and seeing so many students use it badly (not a reflection on the students involved, it just wasn’t particularly intuitive). On the hunt for a possible replacement I stumbled across Zotero – I still remember how excited I was the day I discovered it (which makes me wonder if I need to get out more!).
So why do I love Zotero so much? What initially grabbed me was the ease of importing reference information. This was also easy in EndNote, but not to the same extent. With Zotero I can visit a webpage that contains a reference (or references) and click a button in the address bar – hey presto, the information is saved in my Zotero library. Got a folder of PDF files? Simply drag and drop into your library and ask Zotero to retrieve the metadata – this finds all the citation information for your PDFs, creates entries for them, and then handily attaches the PDFs. Perhaps a colleague has just handed you a hardcopy of a book they recommend – scan the barcode with a mobile device and bring the bibliographic details across to Zotero from there. These are just some of the incredibly quick ways of bringing your reference information into Zotero.
Another thing that appealed to me about Zotero was that it’s open source. Unless you’re covered by an institutional site license, you’ll need to purchase a license for EndNote – Zotero is free, which means you can take your references wherever you go. It’s also easy to use across multiple computers – you can sync your library to the cloud, which also serves as a handy back-up. Entering information in manually (should you ever need to, which is unlikely) is extremely intuitive, and the Zotero interface is uncluttered and easy to navigate.
But what if I’m using EndNote/Mendeley/RefWorks I hear you ask? No problem – your treasured references can all be brought across into a Zotero library.
Zotero works across multiple operating systems, and can operate as a standalone application or as a plugin for Firefox, Chrome or Safari. You can download both Zotero and the word-processor plugins you need from https://www.zotero.org.
If you’d like to learn more, or you’re interested in the nuts and bolts of using Zotero, register your interest for our Introduction to Zotero online training.
Developing a coding framework with NVivo maps
By Lyn Lavery
I’ve been busy coding survey data in NVivo recently – if you follow me on Twitter you might have noticed me tweeting some #nvivotips as I code. The data relates to students’ experience in an online learning environment. When I started developing the coding framework for it, I started out with what Pat Bazeley refers to the ‘scribble and doodle’ method – I like this approach when it’s a small dataset that I’m working with. If you haven’t come across the technique – it’s nothing fancy – it’s literally making notes and scribbles on a hard copy of the data. I’ve included a photo, just to prove it’s not complicated (in case you think your vision has gone blurry, the actual data is blanked out for confidentiality).
From there I started to list out what I thought my nodes might be. My first iterations all ended up in the bin – I kept needing to redo the connections between the ideas. Thankfully I then remembered the new mind mapping function in NVivo 11 – perfect for mapping out my nodes and enabling me to move my ideas around as my thinking changed. Before I knew it, I had my nodes sorted and I probably saved a few trees in the process given the way I was screwing up pieces of paper when I started!
The NVivo help files define mind maps as a “brainstorming tool that starts with a central topic”. So, if you’re developing a coding framework, your central topic might be your research question or main topic of interest with your subtopics or possible themes/nodes branching out from there. Below is the mind map I generated for the online learning data I was working with.
NVivo mind maps allow you to go one better than just brainstorming. On the ribbon you’ll find a handy ‘Create as Nodes’ button – this takes the ideas in your mind map and creates your nodes automatically from them.
You’ll still need to add descriptions for each of your nodes (always an important part of the coding process), but at least the mind map function has helped you along the way with your coding framework. You can learn more about the mind maps feature of NVivo, in this short video.
If you’re a visual person like I am, you might be interested in some of the other visualisation tools NVivo has to offer. We run our Painting the Picture in NVivo online course which covers a number of the new visualisation tools in NVivo 11, throughout the year. Or, if you’re looking for further tips for developing a coding framework, check out our Analysing Qualitative Data course.
So I’ve done my coding in NVivo … Now what?
By Lyn Lavery
A common problem researchers face when they’ve completed their initial coding in NVivo is knowing what to do next. They know they eventually need to start writing, but they’re not sure how to get there from their coded nodes. If this applies to you, read on for some tips on moving forward at this stage of the analysis process – some of these are NVivo specific but others require a bit of old-fashioned brain work! For those of you that learn better by seeing things in action and being able to ask questions, we’ve also included links to some of our related upcoming online training courses.
Review your coding
Once you’ve “finished” coding in NVivo, it pays to review your coding and node framework. The first thing we usually do is read through the content of each node to check if it’s correct. In some cases, we might adjust the level of coding (is there too much or too little material coded for example). Alternatively, some of the data may have been coded incorrectly to the wrong node, and it pays to find this out sooner rather than later so that it can be corrected.
At this stage you may also want to check whether any categories can be combined to create broader themes. Sometimes the opposite applies and you need to “code on” from a larger node to create more specific categories. Viewing your standalone nodes can sometimes reveal that they can be grouped together in a hierarchy. All of these tasks can be quickly and easily completed in NVivo – if you need some tips for how to go about this, our Become an NVivo Coding Ninja session outlines the “how to” of these steps.
Moving beyond description
Depending on how you have developed your nodes in NVivo, you might find at this stage that your nodes are quite “low-level” or descriptive. Don’t despair if this is the case – sometimes this type of coding can be a useful springboard for developing more analytic level themes, although this will require some thinking on your part! A good starting point for this is revisiting your research question(s) – it’s easy to have forgotten these by the time you’ve finished your initial coding. If you need further ideas, we recommend Bazeley (2009) and Braun and Clarke (2006) – full citations are below. If you’d like some concrete examples of how to move to a more analytic level of analysis, we cover this in our Analysing Qualitative Data session.
Query your data and coding
The query tool in NVivo can be particularly useful at this stage of the process, as it can help you identify patterns in your data that you may have otherwise missed. Scanning the results of a word frequency query, for example, may help to identify additional themes or categories. You might also like to run text searches for specific concepts that have already been coded – this can be checked against manual coding to ensure that nothing has been left out.
Two of our favourite features of the software are coding and matrix coding queries. These allow you to search for patterns across themes, and will also break down nodes according to different demographic or descriptive categories (e.g. what did different age groups say about aspects of the natural environment). Both of these techniques may introduce new ideas and relationships that allow you to develop your analysis further or help to structure your write-up.
The saying that “a picture paints a thousand words” definitely applies to qualitative data! NVivo has a range of visualisation tools that can help you think through patterns and relationships, and NVivo 11 has introduced some new maps that we’re really liking here at Academic Consulting. Try using Project or Concept Maps, as well as Explore and Comparison Diagrams. In addition to assisting with your thinking, they can also be exported and included in your write-up or PowerPoint presentation. Don’t feel like you have to use NVivo visualisations only – remember that applications such as Inspiration and XMind are also great, as is good old pen and paper.
Plan for your write-up
Unfortunately, there’s no magic button in NVivo that will complete your write-up for you. When you’re at this stage, there are a number of ways you can work with your NVivo projects. We often print or export node content so that we can refer to it as we write. As qualitative researchers, we also like to include verbatim extracts in our writing, so find it useful to copy content from an NVivo node and paste it directly into a Word document (if you are lucky to have a dual screen set up you can even drag it directly across). Our Writing Up Qualitative Research course covers practical advice on writing up from NVivo.
Our last piece of advice? Don’t rush the steps above – once you’ve completed your initial coding it’s easy to rush headlong into trying to write up. Taking the time to review and reflect on your coding is where some of the real insights can occur, and that’s one of the many pleasures of completing a qualitative project!
Bazeley, P. (2009). Analysing qualitative data: More than ‘identifying themes’. Malaysian Journal of Qualitative Research, 2, 6–22.
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101.
Confessions of a thesis writer: Formatting faux pas
By Lyn Lavery
I have a confession to make – I didn’t use styles and templates in Microsoft Word when I wrote my Master’s thesis. Those of you who know me will be surprised to hear this as I’m an ardent promoter of them now. It wasn’t that I didn’t think they would be helpful – I simply just wasn’t aware that they were a possibility.
As a result of not making the most of these features in Word, the days prior to me submitting weren’t much fun, and there certainly wasn’t much sleep to be had. I had written my thesis chapters in separate documents and when I went to combine them, the formatting of the overall document went seriously awry. Every time I thought I had fixed an issue, the formatting would slide on me again. I’d mention the issues I had incorporating my appendices into the document, but I believe I may have blanked the trauma permanently from memory. Creating the table of contents involved me sitting in the middle of the lounge floor surrounded by hundreds of pages of printouts, with my Mum and brother frantically trying to assist by calling out the page numbers for each section.
Rest assured, I certainly didn’t format my PhD this way. By this stage I’d learned a bit about thesis formatting having spent several years teaching this to postgraduate students at the University of Auckland. I still wrote my thesis in separate chapters, but they each had the same template applied with built-in and consistent styles. These styles enabled me to automatically create a table of contents, and thanks to using captions on my tables and figures, I could quickly create lists for these also. Once my document had all been successfully collated, I also knew tricks for quickly navigating around it when I needed to make final edits. All up – a much less stressful experience which certainly didn’t cost me any sleep.
What did I learn from this? In addition to learning an awful lot about managing a long document, I also learned that sometimes as a postgraduate student, you “don’t know what you don’t know”. It pays to take the time to find out how technology can assist you – talk to other students to find out what they learned the hard way, and learn what software your institution supports.
What else did I learn? I learned that it pays to have a helping hand with thesis formatting, and that’s why Academic Consulting has training and individual assistance covering this. If you’d like to learn how to format your own document like a pro, check out our Managing Long Documents in Word training course. Alternatively, if you’re just wanting a few tips, try – Ten Time-Saving Features in Microsoft Word.
If you’re short on time, we’re happy to do the formatting for you (we can also assist with proofreading and reference checking if this is required). Details of these services can be found on our website. Handing these last minute nitty gritty tasks over to someone else can be pretty helpful when you’re in the final sleep deprived stages!
Just a final note – if you’ve stumbled across this blog post because you’re a thesis writer yourself, then I’d like to wish you all the best. It certainly takes a lot of hard work but that means that the finished product is even more of an achievement. Make sure you have a celebration planned for afterwards!
Transcription tips and tricks
By Rachael Butler
As researchers, we know that transcribing can be an arduous and challenging task! While some of you may be contracting this work out to professional transcribers, many researchers and students will undertake their own transcription. This may be due to a lack of budget, or because of the benefits it can provide in terms of increased familiarity with your data. Indeed, listening and re-listening to audio recordings can mean that you discern additional insights from what your participants say, and how they say it. If you’re in a position where you’re transcribing your own data, don’t view it as a negative – it can be incredibly valuable. To help you out, here’s some lessons we’ve learned over the years – we hope you find them useful.
Make sure you have clear recordings to work with
As part of planning for transcription, it is vital to gain a clear audio recording. There is nothing worse than that sinking feeling when you realise that you have an unclear (or even worse, unusable) audio file – this will impact on both the length of time required for your transcription, as well as the quality of the final document. Ensure that your recording device is of a high standard, and try to minimise background noise where possible.
Get the right equipment
There are a number of tools available to assist transcription – these can save time and reduce pain and frustration along the way!
As a starting point, we strongly recommend you purchase a foot pedal. This will allow you to play back your recordings, and control the speed, volume, and rewind/forward functions with your foot – keeping your hands free for typing. Depending on the digital dictaphone you have purchased, you may have been provided with a 'transcription kit' that contains software for playing back your recordings. Alternatively, we recommend the use of Express Scribe which is transcription software, and can be operated by using keyboard shortcuts or a foot pedal. Amongst other useful features, such software contains an automatic backstep, which means that whenever you stop it playing, the recording rewinds slightly. This is an invaluable function, and can save significant amounts of time.
Allow sufficient time
Transcribing is likely to take longer than what you think. Depending on the quality of your recording and your typing speed, you could be looking at between 4–6 hours for one 60-minute interview. Note also that focus groups, or interviews with more than 2–3 speakers are likely to take longer.
The other thing to factor in is break times. You’re most likely already aware of the value in taking regular breaks and its positive impact on productivity. This is particularly important during transcription, as it also prevents possible injury from extended computer use.
Think about your transcribing conventions
It’s important to think about the conventions you employ in your transcripts. This includes the level of verbatim required. For example, do you need to transcribe the ‘ums’ and ‘ers’, and indicate all pauses? The conventions you utilise will be determined by your qualitative methodology, and we recommend that you review relevant literature in your area to see what is appropriate. If you cannot find anything specific to your discipline, Powers, W. R. (2005). Transcription techniques for the spoken word. Lanham, MA: Altamira Press may be a useful text. A key thing to keep in mind with conventions is that they should be consistent across all your transcripts.
Other considerations include formatting conventions. For example, if you’re using software such as NVivo, investigate how your transcripts can be prepared to facilitate certain data analysis tasks. You might want to also develop a template for your transcripts rather than setting up a new document each time. Getting these aspects organised at the beginning will save potential re-formatting further down the track.
Once you’ve completed your transcription and are looking towards the analysis stage of the research process, we have some courses that could help. Our Analysing Qualitative Data online course gives practical advice on identifying themes and conducting coding on your transcripts. If you’d like to learn how software can assist with this process, check out our NVivo Core Skills training courses, offered both face-to-face and online.
Using NVivo for literature reviews
By Lyn Lavery
Those of you who have attended any of my recent NVivo training will be aware that I’m a huge fan of using NVivo for literature reviews. I also love the fact that as soon as I mention it to other researchers, I can see their eyes light up with the possibilities that the software has to offer. It’s easy to understand why researchers are making the connection between NVivo and literature reviews. The processes involved are very similar to those involved in qualitative data analysis. In both, we read and reflect on text, make comments, identify key themes, look for great quotes, identify contradictions, and so on.
Using NVivo for literature reviews has several potential advantages. One key benefit is the ability to store everything related to your review in one place. I’m the type of researcher that if I let myself get away with it, I’d have information everywhere - my desk would be a mess of journal articles printouts, handwritten notes and post-its, while my computer would have electronic files in various random locations. With NVivo, I can have the PDFs of my journal articles, notes I’ve taken from books, and reflections on my readings, all stored in one place. Even better, these can all be coded at nodes in NVivo that represent the various topics of interest for my review. I can also store various attributes about my references such as year of publication, methodology used, and country of origin.
These attributes bring me to the second advantage of using NVivo for a literature review. NVivo has a powerful query tool which allows you to examine your coding across attributes. Let’s say you have a review on the literature relating to transcription, and you’re interested in the way authors discuss the importance of software and technology across different disciplines. If you code at a node for ‘Software and technology’ and include an attribute for author discipline, you can run a Matrix Coding Query in NVivo to examine this. Likewise, you may be interested in how authors discuss a particular topic over time – Matrix Coding Queries are an easy way to assess this.
The query tool also allows you to query the text itself. Text Search Queries allow you to look for particular words or phrases in the literature, and the results of these can be easily converted to nodes. Hence, it’s a very fast way to locate key topics and have the associated text organised in one place for later reference. Likewise, the Word Frequency Query allows you to examine the most frequently occurring words across the literature, which is an excellent way to identify key topics in the beginning stages of a review. Both Text Search and Word Frequency Queries can also be displayed visually, which is an excellent technique for exploring patterns in the literature.
When you get to the write up stage, that’s when it starts to get really exciting. Using our transcription example above, let’s say you are interested in the impact of difficult recordings on the person transcribing. If you have coded your literature at a node for this, all you need to do it open the node and you have all the related text in one place to assist with your write-up. The Matrix Coding Queries mentioned above can also be very useful at this point.
Some of my other favourite NVivo literature review tips include:
Have a node where you code any ‘Great Quotes’ that you want to include in your write-up.
Use Annotations for brief reflections and See Also Links for making connections between authors.
Information from reference management software (EndNote, Zotero, Mendeley, and RefWorks) or online note taking software (Evernote and OneNote) can be imported into your literature review project.
Framework Matrices are an excellent way to compare across authors or summarise findings from key articles.