Increments of Improvement

"Everything I know is a lie..."  

Up till this points, a lot of the things we were doing in 20.109 lined up with what we learned in 7.05, Biochemistry. I was excited to have hands-on experiments in 20.109 after learning concepts in both 7.05 and 20.109. I was also ready to feel the rush of success after getting beautiful results.

 Little do I know, it was a naive dream. 

I thought I was ready for any results, but apparently "any results" did not include negative specific activities. 

That was when I finally understood that research results don't always go as planned and aren't as easy as we thought they would be, even in a lab class. I think somehow because 20.109 is a lab class, I thought that all the 20.109 instructors had experiments under control and that, besides our own experimental error, nothing can go wrong. 



I think there were multiple things that were hard to do in Module 1. Firstly, learning to properly write/ format scientific writing was definitely a struggle. Captioning and labeling figures took some time to get familiar with, and they are, along with using concise scientific wordings, things I definitely got better at but still need more practice on. Besides formatting, the hardest thing for me was trying to understand the causes of unexpected errors and explaining statistically insignificant data when we expected statistically significant data. As much as I was disappointed at not having good data to back up the hypothesizes we made, I was also grateful that I got the chance to experience unsuccessful results and how to deal with its aftermath. This experience no doubt does not count as a failure, but instead, serves as an experience that prepares us and teaches us how to ask critical questions that will drive research in increments of improvement. 

In Module 2, I will approach this part differently by talking to the 20.109 instructors more. Not that I didn't discuss or talk with the 20.109, but that I believe if we ever were to find ourselves in need of thinking about causes of unexpected error, discussions can lead to more ideas and understandings, and promote a more accurate reasoning of why an experiment didn't go as planned.

To continued experimenting and learning in 20.109!
-- Shin Chang

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