Literature Review Marathon
Is it just me or does anyone else feel hopelessly behind on literature review? You may have heard of the Dunning-Kruger Effect, "a cognitive bias in which people with low ability at a task overestimate their ability". I'm sure we have all met people like this (*cough cough* Facebook friends who think they understand pandemics better than public health experts and infectious disease researchers). But the figure that explains the Dunning-Kruger Effect is also pretty relatable.
I am about to begin my second year and have started preparing for my preliminary exam, to be taken in the fall. I need to demonstrate "general knowledge". At this point, I don't even know what general knowledge is. Every time I learn something new, 10 things pop up that I need to research! The list of papers I want to read is endless, and lit review can be so time consuming. The brain can be trained much like the rest of the body, so I decided to train my brain to read papers regularly and in better time. The more I read about work in my field, the better I will understand the info (and the less googling I will have to do). The overall goal of this training program is to help me get a decent grasp of the literature and build better reading habits. But what’s grad school without deadlines and a little suffering? So by the end of this program, I will be sitting down and reading for 5 hours straight. This is around the average time taken to run an actual marathon. I’m sharing this program here, to all you gluttons for punishment.
Choose any papers that are relevant to your research, and make sure you read each day for the specified length of time. If you miss a day, just read on a rest day to make up for it. If you know you can’t read for a certain amount of time on a specific day, plan ahead.
Schedule is as follows:
This schedule was inspired by actual training programs for real marathon runners. If it doesn’t work for you, just tweak the schedule to better suit your life and reading goals. I am currently on week 4 of this schedule, and I have read so many papers on my reading list! I've also added about 20 papers to my reading list. It's nice to have some structure and a daily goal. At the end of the 8 weeks, I will choose a day to sit down and read for 5 hours (including snack and bathroom breaks, because I love myself).
1. Make a list of papers you want to read.
Add to this list as you are reading papers and come across citations that are noteworthy.
Make sure to note the title, authors, a single sentence about the paper, and where you learned about this paper. This will help you remember why this paper is important to read.
Example: Scientist, A. Et al. [INSERT TITLE HERE]. A paper about sciencing in science. Paper was cited in [INSERT TITLE HERE] by Experimentalist, A. Et al.
2. Set a timer and hide your phone until you hear it go off.
RESIST LOOKING AT YOUR PHONE UNTIL THE TIMER GOES OFF.
Check out apps like Forest (You plant a tree and set a timer. If you use your phone before the timer goes off, your plant dies! If you make it to the end without using your phone, it goes into your forest and you get points.)
3. Make a google doc with the title and authors of each paper you read.
Once you finish reading a paper, write a short summary about it. This could come in handy for future publications, grants, and dissertations.
4. Keep a list of interesting new words and phrases you’ve read in your papers.
This can be helpful when getting into the habit of using these words or writing a paper that utilizes the jargon.
If a word on this list pops up in another paper, put a check mark next to it. This will highlight important terms in your field.
5. Make ANOTHER list of techniques, concepts, and mechanisms that you are unfamiliar with or would like to learn about, in-depth.
If it comes up again in another paper, put a check mark next to it. This will highlight techniques, concepts, and mechanisms that are really important in your field.
6. Keep a notebook and fill it with notes and thoughts when you are reading.
Good luck and happy reading!