A common theme on this blog is an attempt to provide guidance on the things that, as academics, we are meant to know how to do, but on which we rarely receive any explicit training. For today’s June Blog I thought I’d write one of these posts, about designing a small research project.
As people become more independent as academics, there’s a lot of small project supervision required. By small, I’m talking about a project carried out as part of a taught Masters degree, or smaller. The former mostly takes place over about a 4 month period – though initial planning might happen much earlier – with relatively full-time focus available for the last 2.5 months. Smaller projects might include summer placements for visiting students (anything from 4-10 weeks) and undergraduate mini-projects. For example, at my University, medical students do “student selected components” in their 5th year, which last about 16 weeks but involve about 6 full weeks’ worth of dedicated project time. One thing to note is that some small project designs will need to be created for student groups – I’m not going to tackle the specific elements that apply to group work today, that’ll have to wait for another blog.
So let’s assume you have a single student joining you for something like 6-12 weeks of full-time work. How do you help them design a project and achieve their goals?
Check the course requirements
I’ve supervised students on degree courses in departments of Psychology, Clinical Psychology, Linguistics, Education, Medicine – and if this has taught me anything, it’s to check the course handbook right at the start! Some programmes have specific rules about the kinds of data you need to work with – for example, whether students are expected to compile their own, new data set or not. You’ll also want to think about the perspective of the second marker. If they are from a different disciplinary background to you, you want to make sure your student is deploying the kind of questions and methods they will expect to see. So, for example, when supervising medical students I will try to make sure we are examining a question with clear clinical relevance, even though I’m not a medic myself.
Another key factor is to make sure you are informed about the deadlines – not just for the final project report but any interim milestones. Some departments will have students present a poster about their project plan, or ask supervisors to confirm that they are satisfied with student progress at the project midpoint. Another rule might concern what you are allowed to comment on in terms of the final report. Some courses only allow supervisors to comment on one full draft (I personally prefer to see a methods section + detailed outline for other report sections, and then a full draft) or to comment on everything except the discussion. So make sure you are on the right side of all of this info from the outset.
Keep it small
The single biggest threat to a small student project is over-ambition. Students will often approach the work – understandably, and rightly so – as a chance to discover something important in their field. But the honest truth is that masters projects rarely lead to important discoveries. The purpose of a masters degree is to learn how to do science, which may be slightly different from actually doing science. Yes, students are learning “on the job” and of course there are plenty of important scientific insights to be gained. But both of these aims – student learning and scientific insight – will be most effectively achieved if the project design is modest in scale. A petite project delivered to a high standard will be a much better investment of your time and your student’s time than a large project full of compromises, delays and anxiety.
What does “reasonable” actually mean?
Well, here’s a few rules of thumb to help, noting that I and my students have broken these rules multiple times…
1. stick to a single methodology. Mixed methods studies automatically entail more decision-making and are harder to write up. Also, you’re unlikely to have time to carry out each type of data collection sequentially, and so the end results may just contradict, rather than informing each other.
2. if you want to collect new data face-to-face, collect it from undergrads. Collecting data face to face – running experiments and doing IQ tests – takes a lot of time and effort to organise. If you are also trying to reach a specific population when you do this – neurodivergent children, adolescents with depression, carers of people with dementia – you will have many more hurdles to overcome in recruitment, study design and responsible management of data collection.
3. If you want to work with a particular population, keep it low impact for them. If you want to recruit people from a particular group, you are placing a burden on individuals who probably already have a lot going on in their lives, to also engage with your research. In an ideal world, this kind of work is developed gradually and carefully in partnership with stakeholders, and has a plan for implementation of the findings. These steps are virtually impossible to squeeze in to a small project and so in-person working with any kind of atypical population needs to be as low impact as possible. Think about phone / video interviews, a (short) online survey or maybe an online focus group.
4. The topic matters too. Yes, you might be interested in the intersection of homophobia and ableism, but do consider whether this small student project is the right forum for addressing such a potentially difficult topic. It might be – a lot depends on the life experiences of the student of course – but as a supervisor, don’t shy away from directing your student down a path carries less risks for participants.
5. Ask a question you can actually answer. I’ve had students come to me before wanting to do a project about something like emotion perception and autism. This is a literature that is absolutely rife with contradictory small studies, none of which do much to enlighten, let alone improve the lives of autistic people. Another small study is unlilkely to resolve the complex debates in the field. So instead try to find an area where even a very small amount of new information might add value.
All this is not meant to limit you to a “boring” project. Instead, try to be creative. Can your student identify an important and under-studied intersection and gain some insights into something barely understood? Could interviews with autistic teachers, doctors, nurses or psychologists yield useful insights for practice? What are the experiences of parents of autistic children with visits to the dentist? Another fruitful angle is to explore some routine outputs from your field, and extract insights about dominant theory or language. For example, would a systematic analysis of the last ten years of conference proceedings tell you about shifts in the discourse? What about a content analysis of policy documents relating to your field? This can be a really accessible project to do – with no ethics required, the data freely available and straightforward to code – that also delivers important new knowledge. It might be a great option for a student who is also working part-time or has a health condition that impacts their work, who needs to be able to work flexibly.
Getting ethical approval is one of the major barriers for a small project because it can take a long time and cause significant delays. For shorter projects then, I would try to stick to analysis of existing data (where permission is already in place), literature review, or analysis of data in the public domain. That said, the process of seeking ethical approval is very useful – it helps you articulate exactly what you propose to do – and so if you don’t decide to collect your own new data, you might still want to think about writing a protocol for what you will do. Remmeber as well that “analysis of existing data” isn’t always as simple as it sounds. Getting hold of the data, understanding the data, checking quality, dealing with missing data – all of these things can take time and should not be underestimated. Make sure you scope out the data availability at a very early stage.
Another practical dimension to consider is cost. Lots of students will be unaware that many assessments – questionnaires etc – cost money. Even if your department can loan them an assessment kit, they may need to pay for record forms for each participant. Make sure you and the student know what budget is available – if any – and make a plan that fits with what you can afford.
Once you have your plan in place, work with your student to break it down into manageable pieces, and plan for supervisions at the key turning points in the work. In other words, map your supervision onto the project – as far as you can – rather than sticking to a supervision schedule that is the same for everyone. Hopefully this will mean you step in at the right moment to help them make decisions.
If you can keep your student projects modest in scale, hopefully the end result will be a high quality piece of work that they can be proud of. It’s quality, not quantity, that counts.