Welcome to the 20.109 Class Blog!
Our 20.109 Blog is here for MIT's emerging cadre of biological engineers from Course 20. The blog is for your thoughts and work and discoveries in our lab fundamentals class. By capturing your collective experiences in the subject, we hope to learn even more about the work we do -- what's working well and where we need to get better. Please see the first blog post for some important administrative information.
Saturday, October 11, 2014
When "Make it work" didn't work
As I’m guessing is the case with most of my 20.109 comrades,
this is my first real lab class at MIT. While I’ve worked in labs for a while
now, both outside of MIT and through UROPs here, those experiences certainly
did not capture what I’ll call the “thoroughness” of this class. Sure, I’ve had
to produce write-ups on my research, maintain lab notebooks, and more, but I’ve
never really been taught how to efficiently and effectively do these things.
Boy, do I know now.
I feel like my “tagline” on completing assignments so far at
MIT has been, quoting the ever-eloquent Tim Gunn, “Make it work!” (Project
Runway may or may not be a guilty pleasure…). All of my technical classes thus
far have been pset and exam-based, for which “Make it work!” has worked! But
Tim Gunn, sorry to disappoint, “Make it work!” simply won’t work for 20.109.
No more can I start assignments frighteningly close to the
due date, in hopes that bucket-loads of caffeine and blasting motivational
Eminem songs will get me through mountains of assignments and studying at
breakneck speed. Unfortunately, I began the abstract and data summary thinking
that strategy would still get me through.
Woops. I started off creating a hodgepodge of figures, including
both schematics and graphs, only to realize later on that I wouldn’t end up
using many of them anyways. After some fuddling around with those figures and
writing out captions with no clear purpose, I decided to take a step back and
map out my results section. Even at that stage, I struggled to make sense of
all the data I was looking at. What finally helped me shape my thoughts was to take
a break and write a background, solidifying the overall purpose of module one and
directing my results section towards a clear goal. I then actually benefited
from a mistake I had made earlier on during module one – what I’ll call a
blessing in disguise. The initial draft of my module one schematic had been much
more detailed than it needed to be, but eventually I followed this version to
get a grasp on the order of data in my results section. I was definitely appreciative
of having written the methods section already, and plan on doing so with future
reports, as it helped me understand the reasoning behind each experiment we
performed. Next up were the implications, a section that made me appreciate
what we’d been working on, beyond how “cool” I thought each individual method
had been. Writing this section made me wonder whether the therapeutic
applications might actually show up in clinics sometime in the near future!
Finally, I was left with the abstract. While I normally
dread writing abstracts given my experiences with them, I found that everything
just came together as I tried to put my thoughts down. As much as this report made
me suffer, mainly because of my own procrastination, I realized that the whole
process forced me to gain a level of understanding that truly got me excited
about the module and made me appreciate both the steps in experimentation and their
implications, which is probably what made the abstract flow much more easily.
Now that Tim Gunn is dead to me (not really, you can’t not
love the man), I am ready to embark on a new life of zero procrastination, eight
hours of sleep per night, and zero coffee intake. Just kidding! Anyone who manages
to do that at MIT is a wizard in my book. But I will definitely start any
writing for 109 much, much earlier, and also write more efficiently, by mapping
out my thoughts, and probably getting the big picture on paper from the get-go.