As I’m wrapping up my PhD, I’ve been reflecting a lot (my alternative is to write my dissertation, so…). How have I gotten where I am? What are the ingredients that have helped me develop a research program on the relationship between metaphor and cognition, to present and publish this work? What wisdom have I absorbed as I’ve woven eleven experiments into a behemoth of a thesis?

I credit much of my own success to many resources that other people have been generous enough to create and share. Here I’ve compiled a list of my favorites — those that provided ideas or skills that I latched onto and others that I wish I had discovered earlier.

General Guides & PhD Advice

Intangibles

Academic “older siblings”: These people don’t need to actually be older than you, they just need to have some wisdom and background in your field that you admire. Ideally, they’re not faculty, but are instead grad students or post docs, since they’ll be much more likely to have time to walk you through that new analysis or might be better at identifying with your grad school troubles. My academic older sibs were not in my lab, but our research areas were similar. It was always a morale boost to be able to learn from and emulate people a few steps ahead of me in their academic careers.

Talks and questions: Go to as many talks as you can in your first couple of years. Pay attention to the way the speaker frames their topic — what kinds of information are they telling the audience? How do they weave theory and experiments together? How do they present their findings? What kinds of questions do people in the audience ask? This will provide implicit learning opportunities. Before you can do great research, you have to truly internalize what great research in your field is. Reading papers is another way to do so, but I found the in-person observation experiences to be irreplaceable.

Contribute to the academic community: It’s important to pull yourself out of your own work and participate in your intellectual community. You can pick up beer for happy hour, cook a dish for the department holiday party, or volunteer more regularly. I spent one year as the grad student rep at faculty meetings, which taught me tons about the dynamics of the department and allowed me to make sure grad student voices were heard when topics of interest to us were discussed. I also spent two years as the larger Cognitive Science Society’s grad student rep, and contributed to the society website and social media, served on a committee to assist scientists who couldn’t come to our annual conference because of the travel ban, and created an event at the conference to offer a professional development opportunity to grad students. It’s important to do things like this because we depend on our departments and societies to support and promote our work, and it sometimes has unexpected personal benefits too, since influential people in your field now know who you are and that you can get stuff done.

Specific Skill Resources

If you’re in a science field, there will probably be technical skills you need to learn or improve for your research. For me, that was mainly programming: I had to figure out efficient ways to implement experiments on the computer, often online, and to analyze the data they generated.

Data Science courses from Johns Hopkins on Coursera. I did a handful of these courses, and they were helpful for learning to use R for statistical analyses. A strength of these courses was that they gave a good sense of context, so I could actually apply the principles they discussed to my own data. Importantly, you do not need to pay for these. You can audit every class in the series.

for these. You can audit every class in the series. R Resources. Dan Mirman’s Cheat Sheet here is extremely helpful. It’s well-organized so that even when you’re not quite sure what function you’re looking for, you have a sense of where on the sheet to look. Once you find the function, the sheet tells you how to use it.

How much statistics do psychological scientists need to know? Also, a reading list by Xenia Schmalz. Her answer to “how much statistics…?” is “As much as possible,” which resonates with my experience. I actually just recently found this guide so haven’t taken advantage of many of the resources suggested, but they look great.

Statistics Tutorials by Bodo Winter. Linear models and mixed models have become extremely popular in my field, because they allow you to model your data and understand how much variance your factors (as main effects and interactions) explain, while also taking individual participants and stimuli into account. Because they’re so powerful, they’re also a bit complicated to learn, but I’ve returned to Bodo Winter’s tutorials many times because they describe what’s really going on when you use these models and include detailed examples.

jsPsych by Josh de Leeuw. jsPsych is a “JavaScript library for creating and running behavioral experiments in a web browser,” which is incredibly useful for making experiments available to a broader audience than the typical participant pool (undergraduates who can participate in person) and for collecting data quickly. There’s thorough documentation, a tutorial for getting started, and a Google group for getting help when you hit snags. I used jsPsych for at least half of the experiments that have made it into my dissertation.

Research Digest: Thinking about Statistics by Christopher Madan. A great reading list covering statistics concepts to actually help you understand what all your numbers and analyses mean.

These lists just scratch the surface of resources that have helped me thrive academically while working on my PhD. Please let me know if you have other favorites I should consider adding.

In my next post, I’ll continue to share resources that have been crucial to my success in grad school, but this time I’ll focus on my top personal resources — things that helped me stay healthy, both physically and mentally, and motivated to do my work.

Edit, 3/14/18. Additional resources from readers’ comments:

“Surviving Your Stupid, Stupid Decision to Go to Grad School” by Adam Ruben

The Professor Is In (2015) – Karen Kelsky, Ph.D

Black Hole Focus (2014) – Isaiah P. Hankel, Ph.D.

Mastery (2012) – Robert Greene

Ph.D. Comics (2006-present) – Jorge Cham, Ph.D.

A Ph.D Is Not Enough (1993) – Peter J. Feibelman, Ph.D.

When I Say No, I Feel Guilty (1975) – Manuel J. Smith, Ph.D.

The Thesis Whisperer blog.