I just performed a very unscientific study of thesis bibliographies. Of the last 5 doctoral theses published to ProQuest, there were an average of 333 entries per bibliography.* That’s an average of 333 books, journal articles, theses, reports, or other sources that those doctoral students read well enough to cite. That’s a lot of reading.
And that number only captures the reading that ends up in the thesis. How many more sources are read but never cited? The total reading list for doctoral students can end up in the hundreds or even thousands of sources.
That’s a lot of information to take in – so how do you process it all?
Here at Thesislink we’ve posted before about taking notes to maximise your information recall. We wrote about the “Forgetting Curve,” which suggests that you can limit how much you forget by reviewing your notes with diminishing frequency. That’s a great strategy for remembering what you read – go back over it after a day, then a week, then a month, then a year. It’ll stick in your brain like a certain Hanson song in the late 90s.
But what if you don’t just want to remember? What if you want to digest what you read, and make it easy to find and write about it later?
There’s no one best way to approach the task of reading for a thesis. Everyone has different preferences, and different sources for that matter. Coming up with a good system for remembering and processing what you read is a matter of personal trial-and-error, more than anything else. But there are a few tricks you can borrow.
I use an old-school colour coding system to mark up my readings. I have four standard themes that I look for when I read, corresponding to four chapters of my thesis. Each theme has a colour, and when I spot content relating to that theme, I add a neon post-it flag. Now I know that, when I pick up a book or paper that I’ve read, any orange post-it flags will point me to content on the commercialisation of genetic technologies. When I wrote my chapter on commercialisation, I just hunted down all my orange post-its, and went to work.
The 3M stationery division has done very well out of me.
That system works for me because I tend to use the same dozen books a lot, and I own copies of each. It doesn’t work so well with library books or online resources, though.
Another trick is to create an indexed “quote bank” as you read. When you spot something you think you may want to cite, type up the quote in a document or database (make sure you record the source, including page numbers) and keep your quotes organised with headings or keywords. Then, when you’re writing up, you’ve got a bank of material you can draw on. Just make sure you always check back to the original source before citing to make sure you don’t accidentally take the material out of context!
Some people swear by marginalia. That’s a fancy term for the notes you write in the margins capturing your thoughts and responses to the material. Marginalia can be great for difficult readings, particularly philosophical or theoretical papers. They can help you to record and work through the meanings you extract from the text, and just as importantly, they can also help you to develop your opinions or angle on the writing.
For those who like to read digitally, many e-readers now allow you to highlight, take notes, and perform keyword searches. The latter is incredibly handy if you’re working with a book or document that doesn’t have an index. You can also digitally highlight and take notes within PDFs if you have Acrobat Pro, or if you are tech-savvy enough to work with some of the free software packages that offer PDF editing functions (see here for instructions). This can be great for people who work primarily with electronic articles.
These are just a few ways to approach reading for a thesis. If you’ve got a brilliant system for working with your readings, let us know in the comments! If not, take heart and Google pictures of Einstein’s desk. It’ll make you feel a whole lot better.
*Danger, Will Robinson: don’t take this number as a requirement! It’s just a very rough ballpark estimate using a very small sample size. The expected number of entries in a bibliography is highly variable by discipline anyway, so don’t feel you have to have 333 entries in yours – you may have more or less.
