In this second part of my research hacks series, I’m sharing some of my favourite advice to make the writing process as efficient as possible.
Academic Consulting Blog
This is the first in a series of blog posts that provide hacks for various aspects of the research process, such as data analysis, writing, and using applications such as NVivo, SPSS and Trello.
Check out our 5 super simple resolutions that will help you reach your research-related goals in 2019.
If you’re an NVivo “newbie” and/or have taught yourself NVivo, read on for some advice that may save you a lot of time and headaches down the track!
Get a quick rundown of the Pomodoro Technique and how it can help you with your research productivity!
I've been busy putting together resources for our new Thesis Boot Camp, and reflecting on my own productivity and things I could improve on – it never hurts to be reminded! If you’d like to take the opportunity to reflect on your own working habits, here’s some videos to get you thinking...
If you have a little time up your sleeve before submitting, we’d recommend engaging the services of a professional proofreader – this post focuses on some tips for making the most of these services.
When I teach qualitative writing, it’s usually predictable as to what questions I’ll get asked as people tend to have the same concerns – this post covers some of the most commonly asked questions.
It's that time of year when many of you are in the thick of analysing qualitative data. If you’re feeling a bit lost as to what’s involved, be assured that you’re likely not the only one!
Mixed methods researchers will have something to be excited about with the latest version of NVivo. A new crosstab feature and support for SPSS data files will really enhance the way qualitative and quantitative data can be integrated within the software...
We’ve all been there – your deadline is looming and you’re desperately trying to proofread your document, but the words are blurry and your attention to detail is long gone...
Here at Academic Consulting, we’re always excited when a new version of one of our favourite research tools is released, but we’re aware that not everyone shares this excitement...
The research is done, you’ve written a fantastic piece of work, your formatting and referencing is on point, and your supervisors have approved your final copy.
It’s the little things that count in life, and this is very much the case with data analysis, where failing to pay attention to small details can result in quite large problems!
Given that confidentiality and anonymity are paramount in the research work we do, pseudonyms in qualitative research are an important consideration, and I’m often asked about these at my NVivo training courses...
I’m often asked if software such as NVivo should be used for qualitative data analysis. For me this is an easy choice, as I’ve used what I’ll refer to as ‘pen and paper’ methods previously, and wouldn’t want to return to them. However, there are some who would disagree with me...
The end of winter feels like it’s dragging on this year, and I’ve been feeling a little uninspired as a result. One of the things I love about research is that it involves building on the experiences and knowledge of others. So when I need a burst of inspiration, it’s probably not surprising that I hunt around the Ted Talks archive for some insight from other researchers. If you’re in need of some inspiration yourself, here’s what I’ve been watching…
Having just finished analysing and writing up some really interesting interview and focus group data, I thought I’d stop and reflect on some of the things I learned (or was reminded of) from this recent project. One of the things I love about research is that it doesn’t matter how experienced you are as a researcher, each project teaches you something new.
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.
If you’ve enrolled in one of Academic Consulting’s upcoming online 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.
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.
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.
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!
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!
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.
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!).
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).
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.
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 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.
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.