Blog Post

The Only D I Ever got in College

The only D I ever got in college was in Introduction to Computer Science, a freshman level course I took at Rutgers nearly ten years ago. I hated that class. I remember walking to the recitation dragging my feet wishing I was going anywhere else. Thinking back on the class now, I cannot specifically pinpoint what I hated about it so much that caused me to minimally apply myself. Maybe it was early in the morning? Or cut into my time spent watching Jersey Shore? (I went to a New Jersey state school, of course I watched Jersey shore) Whatever the reason was, I accepted my D and immediately forgot everything I had learned in the class.

Or so I thought. Our recent workshop on TEI and XML, led by Marcus Bingenheimer, reminded me of a lot of the concepts I had learned in that freshman level class. Yet this time around I found myself much more interested; my brain thinking of all the ways XML might be useful to me in analyzing texts. I think Peter said it best when he mentioned something along the lines of using these digital techniques in order to have more power over the texts we use! While I am not sure if I will end up using these technologies in my own project, I think the mere fact that I could made me much more interested in them.

I think the most interesting element about all of this is how my attitude changed about the same knowledge and information. What once seemed pointless to me, now feels like an important skill I would like to have in my scholar Swiss army knife.    

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2 comments

XML still surprises me with it's complexity and potential, so I'm glad you are also discovering the power in xml and tei. But isn't that how it always is--something is more meaningful when it's related to your own project? Who knows, you might even end up wanting to learn a programming language yet. 

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I've been having similar feelings about statistics lately. For so many years I went out of my way to avoid anything that even sounded like numbers might be involved and now my dissertation is focused on a model based in statistics. I'm not sure I've fully come around to loving stats, but I certainly am beginning to appreciate the applications more. 

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