This information is for undergraduates and Masters students who do projects in Jenny Read’s lab. Many/most of you will be supervised day-to-day not by me but by one of my team: a PhD student or postdoc who has the relevant expertise.
Doing a project in my lab
Most of my projects will involve visual psychophysics in humans or praying mantids. Computational projects are also available, but since I’m in the Faculty of Medical Sciences, most students don’t have the maths/programming expertise to do such a project. But if you do, let me know!
Many students very much enjoy their projects in my lab and get a lot out of their time here. Several of them have even been authors on scientific papers in recognition of the data they have collected. But my work tends to be more computational and probably more abstract than many students will be used to, and will probably be on something completely outside your degree, e.g. insect algorithms for detecting motion. So expect to have to work hard to grapple with unfamiliar concepts!
This can definitely be daunting and you may feel it doesn’t have much relevance to your degree. But in your future career, you are very likely to have to go beyond what you have studied in your degree, so it’s very useful to see how you can apply transferable skills outside your immediate area. If you really work hard and throw yourself into the project, you can learn a lot and gain valuable experience which will be useful in your career.
Here are some quotes from former students:
“Just want to let you know working on the project with everyone in the department has actually been so helpful in gaining experience in psychophysics and the research behind automation. It was really great to do something which maybe isn’t totally specific to Psychology so thank you so much for all the help.”
“I think it’s really important to emphasise how many jobs actually require you to know a lot about different areas of technology. For example [a visiting international PhD student] helped me to use Matlab, I researched into past algorithms that were built for different perceptual systems and how these can potentially be applied to the industry. A lot of the jobs I’m applying for are in digital finance and even they felt that this really stood out on my CV.”
“I really enjoyed working with you and everyone else in the lab and it went from being a very daunting prospect at the beginning (particularly when I didn’t have a clue how to use Matlab!) to being genuinely the best 8 weeks of my education!”
Treat your project as a job not a hobby. Let me know the hours you have available to work on it, around any other university commitments such as lectures. Reply to emails from me or other lab supervisors quickly, certainly either the same or the next working day. Keep appointments and turn up on time. Remember that you will probably want to use your project supervisor as a reference when you are applying for jobs, Masters or PhD placements, and you want us to be able to be enthusiastic about your work ethic, professionalism, reliability, written and oral communication skills, independence, motivation and all-round competence.
I use Microsoft Planner to help manage tasks within the lab. I will assign you tasks to complete on this online system, and I suggest you similarly add tasks there too, adding appropriate start and due dates. This will help you to keep track of what you have to achieve and the time available.
In order to help you manage your project and to avoid pre-submission misery, I suggest the following timeline for a 12 week project:
Weeks 1-3 : read around research question, mug up on relevant background, start writing introduction, start getting familiar with equipment / experiment.
End of week 3: send me the first draft of your introduction. I won’t read it or comment at this stage, but it will concentrate your mind if you have to get something together to send me!
Weeks 3-8 : major data collecting phase.
End of week 5: send me the first draft of your methods section.
End of week 6: produce the first graphs of your data.
End of week 8: have implemented the first statistical analysis. Data will still be coming in, but you will just add that to your worksheet and recompute.
Weeks 9-12: work on writing up your dissertation, redoing the earlier drafts etc.
End of week 10: send me the first draft of your results section.
End of week 11: send me a complete draft of your dissertation. At this point I will give you detailed comments and feedback, which you will then have a week to address.
Allowing time for feedback
I will provide feedback on your drafts, but you need to make sure you allow me enough time to do so. Academics have many time-constrained tasks: submitting grant applications, giving feedback to other students, reviewing papers, writing references for former students and postdocs, resubmitting papers .. all of these have a date they need to be done by and my own time-management involves planning my work to ensure this happens. So my scope for dropping everything to read your project draft is extremely limited. Typically I’ll find space for reading your draft over the course of three or four working days, and then you’ll need to make sure you have enough time to implement the changes I will undoubtedly recommend. So, you need send me your draft at least a week before the deadline, and make sure you’ve got your own time planned out to allow time to work on the feedback.
If for any reason that’s not going to be possible, you need to tell me early so that I can build a slot into my calendar for reading your work. If you’ve already discussed this with me and “booked” me to read your work on Wednesday morning, then sure, you can send it me on Tuesday night and expect a response by Wednesday afternoon. But if you send me your draft, without prior arrangement, saying that you need it back by tomorrow …. yeah, that won’t happen, sorry.
Lab meetings and weekly updates
While you are doing your project, you will be welcomed into the lab team. As part of that, you will attend weekly lab meetings at 10am on Monday morning. You will hear other lab members talk about what they have been doing, and in time, you will start to join in. Initially, lab meetings will be confusing because you won’t know the details of everyone’s projects (we’ll provide a brief background where possible, but to be honest if we went through everyone’s project every week in enough depth for someone new to actually follow, we’d run out of time). But over time you will pick up more and more. Even if you don’t follow the details, it will still provide insight into how science is done; the discussions about what data means or what experiment to do next. You can always follow up with someone afterwards if you are particularly interested in their project, and have them talk you through it. And we definitely encourage you to ask questions – the more involved and switched-on you are, the better!
In advance of each week’s lab meeting, every lab member (including me, and including you) is assigned the Task within Microsoft Planner of completing a “weekly update”. This is a brief description of what you have done that week and your plans for the following week, typically in bullet-point form (“start pilot experiments; read remaining 3 papers”). Then your next week’s report will begin by reviewing what you did and did not achieve out of your plan. I assign this task on Friday morning and need it completed by 9am the following Monday.
Your weekly update should be honest and include any set-backs. Take the opportunity to highlight anything you want to discuss. This might be in the lab meeting if it’s fairly straightforward (“got some good data from the experiments this week – will present graphs in the lab meeting”) or elsewhere if it’s more specialised or will require longer (“tried experiment again but still not working – can we meet next week to discuss this Jenny?”).
When you have results, you will present them at lab meetings. Please spend a little time ensuring that they are in a helpful format and don’t assume that other lab members already know about your project. So for example instead of just showing raw Excel charts with axes labelled “condition 1”, “condition 2”, make a Powerpoint file with a couple of slides on the background, research question etc. Then show the graphs with axes labelled helpfully. The formatting doesn’t have to be perfect, it’s fine if you’ve just pasted on a text box, but your fellow lab members will get more out of your presentation the better they understand what you are doing.
When preparing your results, do think critically about them. It’s easy to mess up plotting, so be self-critical. Do the results look believable? Are the numbers realistic? Are there as many data-points as you were expecting? (e.g. one per participant). Is the condition with the smallest response the one you were expecting to have the smallest response? Pick a couple of data-points and double-check them against the raw numbers. You don’t want to stand up in the lab meeting and present results that a moment’s thought would tell you are just wrong; it will be embarrassing.
Once you are sure you have the results right, think about what they tell you, so that you can explain them for us in the lab meeting i the context of your research question. So don’t just say “here are my results from last week”, say something like “Here are my results from last week. As you can see, [X] is less than [Y], which would imply [Z], but there’s a lot of variability between subjects and N is really too low yet to be sure; I’ll continue collecting data.”
Working with volunteers
Many of you will be running experiments with human volunteers. Obviously, it’s very important you are above reproach in your dealings with these, especially where they are coming from outside the university. All volunteers will need to give informed, written consent to participate. It is important that you keep these secure and give them to Jenny to file at the end of your project.
We generally acknowledge people’s time by giving them a gift voucher for a local shop in recognition of their participation. Obviously, it is essential that you handle this responsibly and keep careful records of the vouchers you have given out. Make a template receipt with your name and the name of your project, ask the volunteer to sign to acknowledge receipt, and again, keep these receipts secure and give them to Jenny or the lab member who is directly supervising you at the end of your project.
When you record a participant’s data, either yourself or via a computer program, do not use their name to identify them. Best practice is to use a code, e.g. P001, P002 etc. Record their gender and year of birth. For children, also include the month of birth, but not the day, so as to reduce the amount of identifying information. If you may want the person to come back for a follow-up experiment, and so need to know who is P001, P002 etc, record that information on paper and lock it in the lab filing cabinet.
Most of my research involves relatively standard office equipment like computers, monitors and projectors. Thus the safety requirements are less stringent than for wet labs, and personally I’m relaxed about you drinking coffee in the psychophysics lab etc. However, please tidy up after yourself. I don’t want to come in and find empty coke cans, crisp packets etc. After you’ve finished work, please shut down computers, turn off monitors etc. This is especially important with projectors.
Look after your data. Keep a lab book (either on paper or electronically) noting what you do each day. Keep any paper record sheets, even after you have transcribed them to computer, and return them at the end of your project. Store computer files on the cloud, e.g. in your university H:\ drive, so that you won’t lose them if your laptop dies or you drop your memory stick down a drain. I would also recommend taking photos of your set-up and videos of stimuli/experiments. These will provide a useful record for you and may even form the basis of figures in your dissertation. At the end of your project, zip up all electronic files that are not already on the university servers, including photos etc, and send them to Jenny.
Writing your dissertation
My major tip for success with your dissertation is: start writing it as early as possible. Students (and occasionally also us academics…) tend to be far too optimistic about how long writing will take them. You will typically start off your project with reading around the research question. So you should aim to start drafting your introduction as you do so. You need to be able to explain to the reader what you are doing and why. Once you are collecting data, you should be able to start writing the methods section. This will probably involve constructing diagrams or taking photos to show the stimuli or apparatus.
You may not be able to write the results section until you have finished collecting data, but you can still start constructing Excel or SPSS worksheets that perform the appropriate analyses and plot the appropriate graphs. Even if you haven’t got any data, for example because you are waiting for ethics approval, you can make up some toy data and start constructing these worksheets. What sort of data do you expect to have? What sort of statistical analysis do you plan to run on it? Make sure you know how to do this in the stats package of your choice.
My second major piece of advice would be: don’t assume the examiner knows anything at all about your research question. They will probably come from some quite different area, and will know as much about stereo vision as I do about retinal development or genetics (which – trust me – is not much). So explain everything very clearly. Run it past your mum, dad or housemates. If they don’t understand your research question, the reader probably won’t either, and, how to put this, it’s possible you don’t understand it very well either.
Do use pictures. Almost everything (and especially stereo geometry) is vastly clearer with a nice picture or diagram. I’m never sure why students are so reluctant to include them. Yes, they are time-consuming to create, but you are allowed to copy one from a published paper or Wikipedia, provided you cite it correctly. It will help your reader understand what you are describing.
Oh and last but not least, use some piece of software such as Mendeley to manage citations, use Word’s reference features to automatically update figure numbers etc for you, and make sure you know how to use Word’s Track Changes and Comment features.