Research Methods in Practice 2
Clare Walsh, Michael Verde, Julien Besle
Overview
In this course, you’ll get a guided introduction to doing research as a team. Across weekly two-hour workshops, you’ll go through the whole research cycle. You’ll pick a topic (from a list), plan a study, build an experiment, collect data, analyze that data, and give a group presentation on your findings. You’ll then write up the whole thing in journal article format. The focus is on learning a few techniques well, and getting lots of practice in those techniques. You’ll learn how to do good, open, reproducible science, and you’ll be well prepared for the research methods components of your final year.
More information is given on the module outline page.
Before the course begins
One week before this course begins, you must:
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Check you can log into RStudio online, and resolve this issue with the Tech Office if you cannot.
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Complete the R revision worksheet, as this course assumes this particular information will be fresh in your mind. It should take approximately 30-45 minutes to complete.
If you ever want to look back at earlier materials on R, you can find them all on the main RMINR site. On that site, Part 1 and 2 are the Stage 1 materials, Part 3 is a a briefer version of Stage 1 for revision purposes, and Parts 4 and 5 are the Stage 2 materials.
Week-by-week plan, with resources
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Week 1: Select topic and learn about statistical power
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Week 2: Define question, outline design and learn about data preprocessing
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Data preprocessing worksheet.
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One-page summary form, with example.
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Week 3: Finalise experimental design
- Full protocol form, with example.
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Week 4: Build experiment
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Building an OpenSesame Experiment worksheet.
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Video about using JATOS: Uploading an OpenSesame Experiment
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Week 5: Upload experiment and begin to learn about ANOVA
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Within-subject differences worksheet.
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Week 6: Collect data and finish learning about ANOVA
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Understanding interactions worksheet.
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Factorial differences worksheet.
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Week 7: Finish data collection
- Video about using JATOS: Exporting results
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Week 8: Analyse data
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Week 9: Write a presentation
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EASTER BREAK
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Week 10: Give presentation
- Presentation feedback form with example feedback.
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Week 11: Planning a report
- Bullet point plan: There is no form for this, but there is a example answer.
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Week 12: Critique and support
- Main report template with example answer and mark scheme. Also, see this really bad answer for comparison.
- Report writing FAQ
Some explanations
Why no stats lectures?
There are no lectures in this module, deliberately. You will come across statistical techniques and other research methods at the time you need them to solve a problem, and you will apply that learning immediately to a task you have to complete (the project). This is how people learn and become truly competent in any complex skill. Not by listening in the abstract, but doing concrete tasks.
Why RStudio?
The statistical techniques we introduce will be demonstrated through RStudio. Other software could have been used, but RStudio is both free (so you can be sure of being able to use it after graduation if you wish), and by far the most popular choice of software for people who make a living out of analyzing data (over 80% of data scientists surveryed by the Rexler Analytics used R; SPSS came second with 29%).
Why fixed topics?
The reason that we get you to pick a topic from a pre-approved list, rather than give you a free choice, is that (a) this maximises the chance of your topic working (i.e. producing clear interpretable results with the sample size available), and (b) ensures your topic is suitable as an illustration of the key statistical and research methods concepts covered in this module. In next year’s dissertation, when you have largely completed your basic research methods training, the choice of topic will be less restricted.
Why group work?
Group work can sometimes be challenging, including dealing with issues surrounding everyone pulling their weight. Learning to deal with these issues effectively is part of the intended learning outcomes of the module, and it is also an unavoidable part of working life, post-graduation. Also, in each of the previous years in which we’ve run this module, those students who did not engage with group work were also the ones who scored mostly poorly on the individual main report, presumably due to a lack of understanding of the group project. So, console yourself in the knowledge that freeloading doesn’t really work in this module for the freeloader, and it’s much more of a problem for them than it is for you.
Why weekly PsyLab activities?
The weekly pass/fail PsyLab activities are there to help you keep on track throughout the module - you cannot pass this module by ‘cramming’ at the end, only by doing the work set at around the time set. If you are more than a week behind on a PsyLab activity, you will find that it has closed, and you will have to ask your personal tutor to re-open it for you. This is a deliberate decision we’ve taken to provide you with an indication that you are falling behind in your studies, something you should discuss with your personal tutor anyway.
Many of the weekly PsyLab activities build towards writing your report - in particular the one-page summary, protocol, and Abstract, PsyLabs.
Why a presentation AND a report?
Giving a presentation is an important transferrable skill (arguably more so than the main report, depending on your career choice). It also provides an opportuinity for you to get feedback on your project in a component worth 20%, which should help you score better on your main report on that same project, which is worth 80%.
Licence
This material is distributed under a Creative Commons licence. CC-BY-SA 4.0.