How Much I Read Every Month During My PhD
When I first started my PhD at UC Irvine, I thought it would be interesting to keep track of how much I was reading over time. That way, my future self (me now!) could visualize and analyze this data. Every time I took notes on an article or book that I read, I included the date at the top of my note file in Zotero. This week, I finally got the time to export those notes and create this graph of my reading volume over time.
First, a note on what I mean by “read.” Mostly, this means reading the abstract, introduction, and conclusion to determine the main points, and efficiently skimming the rest, as described in this useful guide that I read before coming to grad school. I am almost never as efficient as I’d like to be, and often do end up reading things completely. Obviously, I read some things much more fully than others. By “things” and “items,” I mean articles, papers, and books. Some things were much longer than others. Some things I read multiple times (this is not reflected in the graph), and most things I only read once.
My hope in sharing this is that it will be helpful for PhD students who are just starting out, or for potential PhD students, to get a sense of what the process will be like over time. Everyone hears that PhD students read A LOT, but I’m not sure if anyone has quantified this. Of course, this is n = 1, and I have no idea where I fall along the spectrum of other students. Who knows if I’m even average among Informatics or HCI students. Across other disciplines, there are vastly different norms about how much people read, and how long the things are that people read.
In total, I read 975 items during my PhD. At first glance, this seems like a lot, and it kind of seemed like a lot while I was doing it. But really, a large chunk of this reading occurred during two big literature review periods: reading for my advancement to candidacy (which in my program at that time was basically me presenting on a self-defined reading list), and writing my dissertation’s related work chapter. The other spikes on the graph are around things like paper deadlines, course work, and internship literature reviews.
On average over time, I only read about 17 items per month. That’s less than one item per working day! Considering that much of the reading was concentrated in particular periods, I actually usually read considerably fewer than one item per working day — which means, a few things per week. This seems like good news for potential PhD students, because it sounds manageable! During your PhD, you’ll have many other things you’ll be working on, and finding time to read will be difficult. You still need to do it, but if you read a few things every week, you’ll at least be on par with me (the guy who thought to quantify his PhD reading over time).
At some point during my third year, I started actually adding reading to my daily to-do list, to make it a daily habit (which is reflected in the graph becoming somewhat more steady in 2016, particularly after my internship). In hindsight, this was a great practice that I would have started much sooner. There are always things on my “to read” list, whether or not I am working toward a particular degree milestone or paper deadline. Structured reading habits allow you to stay current with the literature in your area, catch up on formative work you haven’t read yet, and explore new areas and methods. Daily reading might not be manageable for everyone, but I recommend deciding how much you want to be reading, and specifically adding it to your list of things to do.
I hope that this is in some way useful to people, or at least interesting! I hope it doesn’t give everyone the reaction it gave to my labmate Mark Baldwin, whose “stress levels skyrocketed just looking at that chart.”
Regarding the content of my reading notes over the past five years, here’s a word cloud:
Thanks for reading!
Notes:
There are some minor errors in my data collection and analysis because I did not keep perfect records.
This analysis does not include reading work that was not published yet — reading my colleagues’ papers to give them feedback, reviewing papers, etc. That’s something that I spend a lot of time doing, but did not keep track of as diligently.
