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.

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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.

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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.