I have written many papers before, and writing about something outside of my area of interest (like that one 10 page report I had to write on experimental Balinese music) has been pretty rough. But I was ready for 20.109! How hard could writing about your own field be? You just describe the experiments and report your results, right?
Well it turned out to be slightly more complicated than that. As our instructors mentioned, good scientific papers told a story; they used the IMRAD (introduction, methods, results and discussion) format in a cohesive manner, making transitions between sections smooth, avoiding repetition, and keeping things interesting until the ending (discussion) section. It was capturing that flow that was most difficult for me as I wrote our result summary for Module 1.
The great thing about 20.109 is how prepared I felt by the time I sat down to write my summary. The first draft assignment was great exercise, and the feedback I received on it gave me a good idea of things I had to watch out for in general. But when I decided to use my draft as a starting point, I made the mistake of starting the story from the middle.
I wrote out the rest of our experimental results, and prepared (and numbered) all my figures, and finished the results section. What I didn't take into account was why anybody would care about these results. So I started writing my "background and motivations" section, coming up with a useful application for the assay we developed in class. But when I reread my results section again, I noticed that the results I had presented didn't have anything to do with the motivation I suggested. In fact, they didn't seem to really point towards any kind of general conclusion at all!
And so, around 1AM Friday morning, I decided that I needed to reinterpret my data and rewrite a large portion of my results section. I somehow managed to do all of this in time, but I definitely learned the importance of developing a general flow -or story- for a scientific paper before starting any of the subsections. The data analysis we make had to be meaningful within the context of our proposed purpose.
I never thought I'd learn the ways of good storytelling from a lab class, but 20.109 has been full of great surprises so far.