I’m defending my dissertation in a few days, and as a result, I have found myself reflecting on my experiences in graduate school over the last few weeks. Like many grad students, when not attending to my own work, I spent a lot of my time trying help other graduate students with theirs. In most cases, this entailed assisting with analysis syntax writing and interpreting output. This kind of helping was not always strictly prosocial for me. Helping to solve their statistical problems has always been among the most effective methods of self-teaching for me, and I will also admit to having enjoyed the resulting feeling of mastery. And it’s compulsive–I often can’t help myself from doing it.
Students helping students, however, isn’t limited to the domain of statistics. Graduate students help each other in many ways; most programs have students who are some combination of extraordinary theorizers, methodologists, analysts, writers, instructors, and/or networkers (i.e., someone who might not be able to solve your problem themselves, but knows exactly who to ask). And even novice graduate students often have something they could teach others. Indeed, if my five years here have taught me anything, it’s that peer-to-peer learning between graduate students is essential to their success. But there are a number of problems with how this peer-to-peer learning system typically operates in graduate programs:
- The more helpful you are, the more “in-demand” you will become
- Graduate students, like anyone, have a finite amount of time and energy they can spend helping others
- Multiple graduate students often experience the same problems, but at different times
- Graduate students shown a solution to a problem (e.g., by a “maven”) are not necessarily equipped to later teach the solution to others facing the same problem
- New graduate students arrive annually, creating a steady-stream of individuals needing to learn how to do a large assortment of novel tasks
- Experienced graduate students eventually leave their programs, and take their knowledge with them
The problem is essentially one of efficiently increasing the institutional memory of peer-to-peer learning solutions, by cataloguing these solutions, and making them easily searchable and accessible to those needing them. I think the Open Science Framework provides an awesome solution to this problem. So along with the newly minted Dr. Matt Baldwin–another statistical “maven” leaving my program this year–I am going to spend some of my summer setting up a KU Social Psychology Program OSF account.
A number of other students in our program have already expressed enthusiasm about this project. And In a relatively short amount of time, Matt and I have received a lot of great suggestions from them for what sort of content would be useful to include. Need an example analysis script showing you how analyze measurement invariance using the
lavaan package in
R? You got it. Prefer to use
Mplus? That’ll be there too. Need help making a particular type of figure using
ggplot2? We’ll provide as many examples as we can think of. And the OSF account won’t just be for analysis scripts: this account will become a repository of example dissertations, annual evaluation reports, award applications, poster templates, job application materials, reading lists, and virtually any other type of example aid a graduate student in our program might need.
Our program assigns each graduate student a “job” for the year, such as sitting on our admissions committee, or serving as the “Czar” of shared lab space scheduling. Matt and I are hoping to create a job around the continued maintenance of our program’s OSF account, to ensure there is a dedicated person soliciting, adding to, and improving the materials posted on the program’s account. I think this is potentially a very powerful application of the OSF to improving graduate training: students will be able to continue teaching each other, but the same problems won’t need to be continuously re-solved (and those solutions re-taught), as solutions will be shared via the OSF. And as a side-bonus, students using this resource will become increasingly comfortable with the OSF, which might lead to an increase in their adoption of open science practices in their own research.
I encourage others currently in graduate programs to consider setting up a similar resource. And eventually, I think it could be quite interesting for programs to share their resources with one another, so that programs could learn from other programs just as students learn from other students.