Starting your final year at university is an exciting time – you’re coming to the end of this chapter of your life, and this year will hopefully equip you with the skills and confidence you need to begin any new adventures.
However, your final year can also be fraught with anxiety. Many psychology degrees in the UK require you to take on a research project of your own and write an empirical dissertation. This can be a particularly daunting prospect if this is your first time undertaking your own original research.
I’ve been through this process myself and since I’ve (almost) finished a PhD in cognitive psychology. This required me to support final-year students as a tutor and supervisor, from developing a research question, to designing and setting up the experiment, doing the data collection and analysis, as well as the actual writing of the dissertation.
Here are my top 10 tips for acing your research project work:
1. Don’t panic – create a plan!
Working on your dissertation will involve some serious project management skills, so get your calendar out and start planning early.
- A top tip for planning work on any project is to plan backwards. Instead of focusing on what you need to do right now, start by putting your deadline in your calendar, and work your way back. Think about what needs to be done by what date before the final deadline, e.g. when do you need to send a draft to your supervisor to give them enough time to give you feedback and to give yourself enough time to make those changes to your draft?
- Define your major milestones: what are the big tasks you need to get done? This could be for example handing in a draft, finishing the analysis, or finishing data collection. You can then break down those big tasks into smaller tasks and subtasks, e.g. writing the methods section, creating a figure, running a certain statistical test for one of your hypotheses, etc. This way, the massive tasks will seem a lot less daunting.
- Most tasks take twice as long as you think, so make sure you plan early and generously.
- Gantt charts are a great way to visualise the time you need for each task. You can draw Gantt charts with a project management software, using MS Excel, or even by hand. Start by marking out the time you have available, working your way from your deadline backwards – this can be in months or in weeks. Then think about your milestones and your subtasks and mark out how long you estimate each of your tasks to take, starting with the most important tasks. This way you will be able to easily see when you’ll have time to spend on smaller tasks (e.g. formatting the document with appropriate margins, making your tables look aesthetically pleasing, etc).
- Your Gantt chart will also help you set monthly or weekly goals so that you can prioritise the most urgent and important tasks.
- To-do lists are great – but you need to actually check them, so use tools that work for you. If you like to physically write down and cross out items on your to-do list, remember that lists on individual pieces of paper can easily get lost. A more permanent option is to fix a list to your workstation, using a pinboard or whiteboard in a fixed location, or to use a notebook that you can carry around with you. Alternatively, there is a host of great options to keep track of your to-do lists digitally. There are dedicated apps for list writing and task management that allow you to sort your lists into different categories and set reminders. Wunderlist, Todoist, or Trello, are just some of the apps available.
- Structure your to-do list if you can: what is urgent and important and needs to be done NOW? What is less urgent and should be done NEXT?
- To make your weekly goals less daunting and give yourself some structure for working, you can use a technique called calendar blocking. Sit yourself down before the start of each week with a nice cup of tea, and structure your working week: block out specific chunks of time in your day for a task. The key here is to be as specific as possible so that when the time comes, you’ll know exactly what you must do and have no excuse to procrastinate. Avoid blocking out 8 hours at a time for big and vague tasks such as “write the introduction section”. Instead, try to schedule blocks of 1-2 hours at a time with very specific tasks like “write paragraph about topic X for the introduction section”, or “run statistical test Y”.
- Use procrastination to your advantage. It’s often hard to keep focus on any one thing for too long. When you’re struggling to get into the “zone” for writing, for example, you can get other, less daunting and cognitively demanding tasks done in that time, e.g. double-checking your reference list or making a figure look nice. This way you won’t be wasting your time. It’s a good idea to keep a list of tasks that you can do whenever you’re not quite in “thinking mode”, so that you always have something to do that will move your project forward.
2. Get support
Working on your research project can be an isolating experience. As you’ll likely be spending a lot of time working on your project during your final year, it’s important to build up a good support network.
- Choose your supervisor wisely. The kind of relationship you have with the academic who will be guiding you through your research project will affect how much you enjoy your project, and, ultimately, the quality of your work. If you have to choose between someone with a reputation for brilliance in the field, or someone who you know to be a kind person, go for the kind one. Do your research on your supervisor – find out from previous students what they’re like. Are they supportive? Will they respond to student questions in a timely manner and without being condescending?
- Establish a professional working relationship with your supervisor, making sure that you both know what you expect from each other throughout the project. For example, ThinkWell offer free downloads of forms you can use to clarify your expectations in your first supervisory meeting.
- Your university might expect you to be very proactive in your supervisory relationship, e.g. it may be up to you to schedule regular meetings with your supervisor. Don’t be afraid to take the lead a little bit, so you can ensure you stick with your project plan. Having regular meetings – and a clear agenda for each meeting – is important especially in the first stage of your project, where you will be finalising your experimental design. Always take notes of what you’ve discussed in your meeting!
- Remember that there are no “stupid questions”; when you don’t know something, ask!
- If your supervisor has a lab or a reading group that meets regularly to discuss their ongoing research or current literature, do join! Don’t be afraid to contribute to discussions and ask questions. You will benefit from the expertise of the other students and researchers in the group, and they will benefit from yours.
- It is equally important to get support from your friends and fellow students while you’re working on your research project. You could schedule regular meetups or writing clubs where you do some work together and talk to each other about what you’ve learned from working on your projects so far. Exchange ideas and experiences, or just vent about any difficulties you’ve encountered.
3. Take a step back and ask yourself “Why?”
It’s easy to get lost in the details of designing your experiment, coding participant responses, and analysing data. Every now and then, find a quiet moment to sit down armed with just a piece of paper and a pen, and try to answer one or more of the following questions about your project:
- If you had to, how would you summarise your research question and method in a single tweet?
- In one sentence only, how would you convince someone that your research is important?
- What do you expect the results of your experiment to be, and what will they mean?
- What is the main message you want people to take away from your research?
- How would you explain your dissertation to someone with no scientific knowledge?
Doing this repeatedly and at different points during your project work will help you write a dissertation with a clear main message and well-defined research question.
4. Don’t be too ambitious
It’s easy to get overly excited about doing your first research project by yourself, and you might find yourself wanting to answer ALL the questions and test ALL the people. Remind yourself that you have limited time. Your final mark won’t depend on finding a particular result, on the complexity of your design or the number of participants you tested – so be tactical and keep it as simple as possible. If you are struggling with this, try some of the following steps:
- Simplify your research question or reduce the scope of your research to make it manageable. For example, rather than asking “What are the factors that determine children’s development of Theory of Mind?”, ask a more contained research question like, “Does a child’s family structure affect their Theory of Mind development?”.
- Remember that everything is likely to take twice as long as you think – that’s especially the case for data collection!
- Ask your supervisor early on whether you will have any help (e.g. from research assistants, other students, or your supervisor) with data collection, or whether you will you have to do it all by yourself. Plan accordingly.
- Set a realistic recruitment target for your participant sample. If possible, run a power analysis once you have finalised your design, or ask your supervisor to help with this. A power analysis will help you figure out the minimum number of participants you will need to recruit to make sure your statistical tests have enough statistical power to detect the effect that you’re after. A basic tutorial for doing power analyses can be found here. Remember that you won’t be marked down if you don’t recruit a certain number of participants, so set yourself a reasonable minimum target.
- Reduce the time that data collection takes by testing participants online rather than in the lab. Wherever possible, online experiments are a viable alternative to lab-based experiments. Classic effects found in psychology studies have been replicated with online participants, and recent research suggests that the quality of the data you can get from online samples isn’t any different from the data quality from lab-tested student populations (Peer, Brandimarte, Samat, and Acquisti, 2017; Barnhoorn, Haasnoot, Bocanegra, & van Steenbergen, 2015; de Leeuw & Motz, 2016; Reimers & Stewart, 2015). There are excellent tools available to help you set up your experiment online. For example, you can use Gorilla to set up your experiment, send a direct link to potential participants or post it on social media to get people to do the experiment on their own device online. You can also use participant recruitment platforms like your university’s participant pool (e.g. Sona system), or Prolific Academic (www.prolific.ac). These tools are particularly helpful if you need to recruit participant populations that are notoriously hard to find, e.g. people with impairments, speakers of a specific language, or a particular age range.
- If it’s not possible to run your experiment online, you could check whether your lab set up and experimental design allow you to test more than one participant at the same time. You could also see if there are other students in your lab group or your cohort who are also recruiting from the same population as you. Could you combine efforts, and test the same people on two experiments at the same time?
- Maximise the quality of the data you’re collecting. It’s frustrating to test lots of participants and end up with data that is unusable because some people didn’t take the task seriously. To avoid this, keep your experiment as short as possible, and make sure it’s interesting and – if possible – fun for your participants. By doing this, you will increase the likelihood of people actually completing your task and putting appropriate effort into their performance.
- Ask research questions that you are confident you can answer with the statistical techniques that you are familiar with. There will be not much time to learn any new fancy statistical methods, so it’s best to design your experiment with a particular analysis method in mind that you are comfortable with.
5. Organise your reading – reference managers are your friends!
When you start out reading papers for your project, you may find that you manage quite well just with a folder full of pdf documents called “64747ghdl.pdf” or “memory.pdf”. But as you download more and more articles, you will soon find that this technique won’t cut it.
Reference managers may sound scary at first, but they will be super useful when it comes to organising your reading list and making a bibliography for your dissertation. Your university may have subscriptions to EndNote or Mendeley. A free, open-source alternative is Zotero.
As a first step, use your usual routes of finding relevant literature. This could be:
- Google Scholar
- Subject-specific databases
- Your university library
- From bibliographies of highly relevant papers, e.g. review papers
Take the time to quickly scan the abstracts of the papers you find to make sure they are relevant to your topic before you download the pdf files. It’s a good idea to have a system for naming your article pdfs; you can try out your own system, but one that might work for you is Author_etal_Year_JournalAbbreviation_AbbreviatedTitle.
You can then load the relevant papers into your reference manager. If the pdf document is machine readable, the programme will automatically also upload any citation data from the document (i.e. authors, year, publication, page numbers etc). Within your reference manager, you can organise journal articles into folders (e.g. by whether they are urgent or less urgent for you to read, or by topic), and use tags (e.g. for different topics, methods or participant groups). This allows you a very systematic overview of the relevant literature for your project. You can also mark papers that you have read, and those that still need reading.
You may also find that just reading a paper is not enough for you to remember its content. Note-taking is an important part of the reading process. There are different approaches to note-taking; trial and error is usually a good way of finding one that works for you.
- Reference managers allow you to take notes directly within the software. These notes will then be saved with the journal article.
- You can keep a separate word document, where you write short narrative summaries of the papers you have read.
- You may find it useful to keep an Excel sheet with basic information about each paper (e.g. you can make columns for the main research question asked by the paper, the number of participants, the type of task, the analysis method used, the main result, etc.). Excel is great for this because it allows you to easily sort and organise the papers you’ve read by this information.
- An analogue alternative to all of this is keeping a notebook for your reading. As handwritten notebooks aren’t easily searchable like a word document, you may find it useful to number the pages, and include a table of contents, so you can easily find your notes on a particular study again.
When it comes to writing up your dissertation, reference managers are an absolute godsend! Download the MS Word plugin for your reference manager, and you’ll be able to automatically insert APA-formatted references in your text and create a bibliography in a mouse click. (Of course, technology doesn’t always get it right, so make sure to double-check your reference list and in-text citations when you edit your draft!). All in all, using a reference manager will save you a lot of time and frustration.
6. Prepare with clear hypotheses and a detailed plan for analysis
Your interpretation of your experimental results and your write-up will be much easier if you start out with clear hypotheses and a plan for your analysis. It’s important for scientists to be transparent in their work, for example by pre-registering their predictions and analysis plans [https://how-to-open.science/plan/preregistration/how/]. A pre-registration is a detailed plan that is usually submitted to a web platform BEFORE a researcher embarks on data collection. This way, other researchers can check that they haven’t run any funky analyses on the data that weren’t originally planned or that you haven’t have changed their hypotheses after they found out the results of the studies.
You can do your own pre-registration on a smaller scale. This will force you to think about your predictions early on and to clarify your research question. It will also make the analysis stage a lot easier. Importantly, a “pre-registration” document or a “research plan” will help you identify any flaws in your method BEFORE you’ve gone through all the trouble of collecting and analysing your data.
To create a “pre-registration” or a “research plan”, you can do the following:
- Specify your research question.
- Write a detailed description of your method, e.g.
- How many participants are you planning to recruit?
- What characteristics will your participants have, e.g. are you recruiting a particular population? Are there any exclusion criteria, i.e. will you only allow people with particular characteristics to take part?
- What is your experimental design? Is it within- or between-subjects? What are your independent and your dependent variables?
- What stimuli will you be using? Are you doing any counterbalancing or randomisation? What is the task your participants will be doing?
- Write down what your hypotheses are and what you expect your data to look like if those hypotheses turn out to be correct. You could even draw a graph to show what your expected results would look like.
- Think about how you will treat your data: Will you exclude any trials e.g. because participants have taken too little or too much time to press a button? How will you be able to tell whether your data is of good quality, or unusable (e.g. because a participant hasn’t understood the instructions)?
- Make a detailed plan about the kinds of statistical tests you will need to use to answer your research question.
7. Use Gorilla to set up professional-looking experiments in no time
Setting up your experiment to work the way you want it to will be a major part of your project work. Researchers can programme their own experiments or use specialised software. If you have no experience coding, don’t overcomplicate things by trying to learn a programming language and programming your own experiment from scratch.
There are tools available that make setting up psychology experiments a breeze. For example, Gorilla is a great tool even for beginners.
With Gorilla’s intuitive user interface, you can learn to set up a simple experiment in half an hour. The Task Builder allows you to create experiments with word, picture, or video stimuli, and record participant responses and reaction times. You can also easily set up Questionnaires and collect e.g. demographic data or rating responses. The undergraduates I’ve taught have found Gorilla easy and intuitive to use, and generally required little help from me to set up their own experiments.
With Gorilla, you’ll be able to visualise your experimental design, and understand the logic behind important design features like counterbalancing and randomisation. This is a very important skill if you’re thinking about doing postgraduate study in psychology.
The great thing about Gorilla is that it can be used for both lab-based experiments and for online experiments, so you will have a lot of flexibility. Plus, your experiment will look neat and professional without you having to put a lot of effort in. You can make the experiment more appealing to participants by including features like a progress bar that lets them know how much more time they’ve got left on a task, or personalisable response buttons that you can make to look like Smiley faces or pictures of cats if you fancy. The possibilities are (almost) endless!
Gorilla’s collaboration functionality also means that you can work on your experiment set up together with your supervisor or other students, so you won’t need to do everything by yourself and get help when you need it.
You can also find simple how-to guides and videos on the support pages, and adapt example experiments to your own needs. If you ever run into any problems with your experiment, you can always contact the support desk, and if your experiment is very complicated, they also offer a consultancy service that will help you set it up according to your specifications.
8. Always double- and triple-check your experiments!
It can be very tempting to quickly set up an experiment (especially if you’ve set it up with Gorilla!), and then jump straight into data collection. However, it’s important to make sure that your method is sound, that the experiment runs without errors, and that it gives you the kind of data that you want.
It’s therefore a good idea to test out (or “pilot”) your experiment before you embark on collecting data from real participants.
- Firstly, test the experiment on yourself. Run through all the different versions of your task to make sure that stimuli are displayed properly, and any randomisation you’ve set up works.
- If you’ve set up your experiment with Gorilla, you can send a link with the experiment to a few friends or collaborators and get them to run through your experiment as well. For example, you could try out the experiment on 3-5 lab mates or other students in your cohort, and pilot on 5-7 friends who don’t do psychology to make sure the task instructions you’ve written are clear.
- Ask your guinea pigs for feedback after the experiment, e.g. whether the instructions were easy to follow, whether they guessed what your hypothesis was, and whether the task ran smoothly, and they could see or hear the stimuli. With Gorilla, you can include all these questions in a Questionnaire tacked to the end of your experiment, and then delete that Questionnaire once your pilot stage is completed.
- Check the feedback, and act on it. For example, you might have to make changes to any instructions that were difficult to understand or adapt the difficulty level of your task if necessary. Make sure you discuss those changes with your supervisor!
- Check that the output files from your pilot participants give you the information you need: Are you measuring what you want to measure? Do you need any additional data that you maybe hadn’t thought about?
- It’s a good idea to run your data analysis plan on your pilot data to make sure you have all the data, and metadata you need. The spreadsheets you need to set up your Gorilla experiment can easily be populated with such metadata, and you may find it useful to include as much information as you can in there, e.g. information about which condition each trial was in, which answer was correct, etc.
9. Get to know a good statistics software – but also learn to love Excel
Researchers often frown at Microsoft Excel but it’s going to be super useful for your data wrangling (this is when you “wrangle” your data into the format you need for your analysis). Unless you’re already familiar with R and other programming languages that allow you to get your data in the right format easily, it’s worth spending some time getting familiar with Excel’s functions.
- Always keep an unchanged raw data file and make changes only to copies of that original. This is particularly important when working with Excel, where you don’t have a record of what changes you have made to the file. This way, you can always revert to the raw data in case something went wrong (in particular with the sort function!).
- Use Excel’s filter function to display only the rows you’re interested in. This will give you an overview of what your data looks like.
- You can also use the sort function to sort your data by particular variables – just be careful to select ALL the columns you want to sort, so you don’t end up messing with whose data is whose.
- You can use colour-coding to help you understand your spreadsheet in a visually more intuitive way.
- Use arithmetic functions to calculate simple things like means, or standard deviations from your data. This will help you get a quick overview.
- Get familiar with Excel’s more advanced functions. For example, Pivot Tables are a great tool to summarise data quickly. You can use these to calculate means or standard deviations grouped by different conditions. There are lots of tutorials on YouTube on how to use Pivot Tables, so just have a browse and find one that appeals to you.
- You can also use Excel to create figures of your data (e.g. bar plots or scatter plots) in a relatively pain-free way.
For data analysis, you should stick with what you know. Don’t attempt to learn how to use an entirely new statistics software unless you have someone to help you.
Most psychology degrees use SPSS; make sure you know your way around it. Unfortunately, SPSS is not the most intuitive software.
10. Do your writing in chunks – and give yourself enough time to edit
It’s tempting to leave your writing to the last minute, or to attempt to write your whole dissertation in one go. This is definitely not an approach I would recommend.
Instead, remember that although the dissertation is a big piece of writing, it consists of different subsections. Writing a draft is a milestone task, but you can break it down into subtasks by thinking about the dissertation structure.
My main tips for your writing are:
- Use Dropbox or some other cloud storage system to save your Word documents. All your files will be backed up, so there will be no danger of losing your work. Otherwise make sure you’ve got back-ups, e.g. store your drafts on an external hard drive as well as your laptop.
- Try planning your Introduction section early on. This is where you set up the background of your topic, and define your research question, so can make a broad outline from the start. Remember that reading the literature also counts towards your writing efforts, so schedule enough time for reading in your project plan.
- Use mind maps or other visual schematics to plan your writing top-down from the start.
- If you’re a very haptic person, you may find it helpful to use post-it notes to play around with different structures. On each post-it note, write down a main argument or a brief summary of a paper you’ve read. Then group the post-its thematically; can you identify individual sections or paragraphs? You can then organise your post-it groups into a logical, linear structure.
- Think about your sections and subsections (e.g. the thematic groups of post-it notes) and give them a heading each. Write those headings into a Word document to help you organise your sections.
- See if you can estimate a word count for each section. How about each paragraph? When you have broken down your writing plan into sections of only 200-500 words each, you will find that writing those individual sections is a lot less daunting than having to think about a whole Introduction section.
- Outline in a little bit more detail what each of your sections or paragraphs will say: What’s the key message of the section? What papers will you need to cite here to support your argument? How is the section linked to the previous and to the next section?
- It’s a good idea to focus on different sections at different points throughout the year. For example, it will be easier to write the Method section as you are setting up your experiment because you then won’t forget important details. You may want to do this as you’re writing your “pre-registration” or “research plan”. Similarly, writing the Results section may be easiest to do alongside your data analysis.
- Write the final versions of your Introduction and the Discussion sections in parallel. This way you will avoid the common mistake of talking about some important concept in your Discussion that you haven’t introduced in the beginning. Make clear how you’ve addressed the research question that you’ve set up in the Introduction, and what the answer to that question is in your Discussion.
- Use the tools that are available in MS Word to your advantage. For example, the Styles feature allows you to specify different levels of headings and set default formats for particular sections of text. When you go to the View tab and enable the Navigation pane, you can then easily navigate your document to move between different sections and subsections. You can even select a whole section and move it to a different point in your document.
- When it comes to actually sitting down and crafting your dissertation, I recommend you use the Pomodoro technique. Giving yourself an unspecified amount of time to do your writing is often counterproductive as you eventually get bored or hungry, and will end up procrastinating. Instead, try to focus on writing for a specified chunk of time (e.g. 20 minutes, or an hour), and set an alarm. At the alarm, take a break. This can be 5 minutes only, or an hour for lunch. Don’t try to cram your writing into long chunks of more than an hour at a time – this is exhausting and will not be very productive.
Getting a first draft on paper is a great feeling. However, when you make your project plan, you will also need to consider that you’ll need enough time to go through your dissertation draft again and edit your writing. Good editing is usually rewarded by a substantial increase in marks, so don’t skip this step!
It’s best to finish your draft, and then take a break of at least a couple of days. Do your editing only after you’ve taken that break so that you can look at your writing with fresh eyes and a clear mind. If you’re having a hard time spotting typos and concentrating during editing, try changing the font style in your Word document. This makes it much easier to catch typos, and it will hopefully give you a fresh perspective on your writing. Try to reverse-outline your own writing. This means going through each paragraph and marking its key message. You can use this reverse-outline to check whether your structure makes sense, e.g. do the paragraphs follow each other logically?
Finally, if your university requires you to submit a hard copy of your dissertation, set your printing and binding deadline a few days before your hand-in deadline. You never know what can happen!