Author: Dr Lyn Lavery, Director, Academic Consulting (www.academic-consulting.co.nz)
Research questions (RQs) are a central part of the research process. They should be clear, researchable, and connect with theory/research (Bryman & Bell, 2011). The development of a good RQ is a crucial step of the research process that can take some time—it’s well worth spending this time at the outset of your project, ideally in conjunction with your supervisor.
While the development of a RQ is important, this blog post is about not losing sight of it during your thesis journey. Your RQ isn’t just something to get you started on the research process—it should underpin all stages of your research, particularly data collection and writing. If you’re in the early stages of your research, you may be wondering how on earth someone could forget their RQ. Every week I see students who are so engrossed in collecting/analysing data, they’ve actually forgotten what they set out to achieve in the first place. One
of my favourite pieces of advice for postgraduate students is that they print out a copy of their RQ and place it in an obvious position in their working environment (e.g., right above their computer). That way they’ll be constantly reminded of the question they are trying to answer. This blog post highlights some of the main research/writing stages that your RQ plays a role in.
Provides a focus for your literature review
Your literature review should have an “upside-down triangle” structure. It starts out discussing the broader context of your topic, and then starts to become more and more specifically focused on your RQ. Typically, your RQ will be presented at the end of your literature review—by the time your reader reaches this point, they shouldn’t be at all surprised as to what your RQ is. The idea is that in the lead-up to presenting it you will have done an excellent job of discussing and critiquing the existing research, so that the gap in the literature (and therefore your RQ) should be obvious.
As part of my work with postgraduate students I see a lot of literature reviews that fail to meet the above structure. They tend to discuss the topic generally, are far too long, and unfocused on their RQ. If I’m honest, I fell into the same trap myself as a Master’s student. My topic was on the friendships of children with ADHD. I recall being very confident about my draft literature review when I sent it off to my supervisor for comment—I felt I had done an excellent job of summarising the literature on ADHD and had a second section summarising the research on children’s friendships. My supervisor proceeded to put a red pen through the majority of it, and rightly so. Why was he right? My RQ was about the friendships of children with ADHD—not about ADHD in general or friendships in general. My re-write was much more focused on my RQ, but I greatly regretted the time I had wasted on unnecessary writing!
Provides a framework for your data collection
All data collection methods and instruments need to be a good match for your RQ. This is something you should discuss with your supervisor—there’s nothing worse than rushing out to collect a large amount of data, only to find that you’ve chosen the wrong data collection method to answer your RQ!
Your RQ also helps you decide what’s important to ask and what isn’t. One of my pet peeves is research projects that ask “nice to know” questions. Never ask questions for the sake of it—
they need to answer your RQ in some way. If they don’t, then there’s no point analysing them, so why ask them in the first place? Not only is this bad research practice, but it’s also disrespectful to the participants that have given up time to participate in your study.
Provides a framework for your data analysis and write-up
Most of my one-to-one work with postgraduate students concerns how to progress their data analysis. Their data is collected, entered into the appropriate software package, and they’re ready to begin their analysis. This is usually the point where they feel overwhelmed and don’t know where to start. It’s easy to have lost sight of your RQ by this point—data collection can be time consuming, and it may have been months (even years) prior to when the RQ was developed. The first thing you should always do before starting your data analysis is revisit your RQ—this will help enormously with your analysis, regardless of whether it’s qualitative or quantitative.
When it comes to writing up, qualitative researchers (and sometimes quantitative) are often faced with the prospect of having far too many results for the word limit. A simple strategy for reducing these is to focus on the results that best answer your RQ. This isn’t to say that you should pick and choose the findings you like the best, simply that your thesis is a piece of work that should be focused on your RQ.
Hopefully the above points have illustrated some of the stages of your thesis that the RQ needs to play a part. Why not dig out that long forgotten RQ today and make sure it has its rightful place in your research!
Reference:
Bryman, A. & Bell, E. (2011). Business research methods (3rd ed.). Oxford: Oxford University Press.
