As the first unit of our technical writing course comes to a close, I’d like to take a moment to reflect on the writing assignments, the peer-reviewing and editing process, and what I learned from them. I usually don’t have many opportunities to write structured texts, and I possibly wrote more over the past month than the four before that. I’m grateful for this opportunity to practice, and I’m confident that I will solidify my skills by the end of the semester.
For the definition assignment, I took quite a bit of time to decide on a word to define– it had to be a bit more technical, so that it would require a definition, but not too obscure that I could not explain it without having to define other words. Eventually I landed on “machine learning.” As a data scientist by profession, I have thoroughly researched this field and I keep up with the latest advancements within it. Nevertheless this assignment posed a challenge, specifically how to summarize it effectively and briefly to a nontechnical reader. For this my sources came in handy, especially two books that are popular in the machine learning field. I decided to include a visual to better-illustrate reinforcement learning, one of the sub-fields I included in my definition. For this I was able to use an animation from a personal project. Although I created it, it still posed a challenge to explain what exactly was happening in it. Overall, I think the definition was a success, and my peer-review partner praised it in her review.
Priyanka Patel was my peer-review partner for the assignment, and we reviewed each-others’ definitions. I think this is an extremely helpful process for improving writing skills, as it highlights the weaknesses that the writer may have missed, and grants a second perspective to the writing. In Priyanka and I’s case, I think this was particularly helpful, because I have no experience in the dental field (her definition was related to the dental field), and as far as I know she had no experience with machine learning. Both her and I were able to identify some words and phrases that may have been confusing to a non-technical readers outside our respective professions. As English may not be Priyanka’s first language, there were a few recurring grammatical mistakes. Fixing these mistakes was the easiest suggestion I gave, because it was the first thing I noticed when reading her definition. I had more difficulty providing suggestions about the phrasing of the sentences, because although they did not quite sound right to me, I could not pinpoint what she had to change in order to fix them. After a bit of thinking, I wrote a few examples to her about how rearranging the order of the words and limiting the sentences to one subject could improve the readability of her sentences. Since I learned English at a young age, I never had to address my own grammar, but this process definitely helped me turn abstract ideas into concrete ways to improve writing (including my own).
In return, Priyanka wrote me an excellent review of my definition. Although she gave it a lot of praise, she highlighted important things that I had missed. After reading her perspective and looking back at my writing, I definitely agreed with most of her suggestions. For example, the description of the image I provided was too vague, and I had done the caption incorrectly (not following MLA format). As well, despite thoroughly checking my own writing, she was able to spot a grammatical mistake I had made. However, I decided not to add another paragraph to the expanded definition as she had suggested, because she commented on the number of paragraphs but not which content was missing in her opinion. I found the editing process very interesting and helpful, because of the added perspective and useful advice that I can improve my writing with.
If possible, in the future I will always try to have a friend or colleague proof-read my writing before I post or send it, because the editing process may reveal crucial mistakes or simply provide good suggestions! After receiving the peer review from Priyanka, I’m very satisfied with the updated version of my definition of Machine Learning. Below are links to both the definition and Priyanka’s review.