Remember when we would get all up in arms about whether or not you needed to code in order to participate in DH? Here’s my take: No.* No because all of our interactions with computing machine are mediated - you are not closer to the “truth” by being able to work in a programming language. That said, 1. you do need to engage with the computational processes (I’m over the “I’ve had an idea for a website / database / tool; who will build it for me?”) and 2. eventually the easy-to-use tools will fail you or won’t do what you want, and then you’ll be learning code. So participate with the easy-to-use tools because eventually, if you stick with it, the fun questions will require you to learn more.
But I didn’t start there. It has always been important to me to learn the code. This has been driven in part by necessity (there were few tools in 2011 were not either prohibitively expensive or overly simplistic) and by a desire to understand as far as I could the underlying process. Code has been my route into computational thinking, into learning how to split large programs into discrete, tractable, iterable chunks. Has it taken a long time to gain momentum this way? Yes. Do I regret it? Not for a minute. And I want others to have the opportunity for the experience of learning how to think through their ideas and their research practices computationally.
But, two years into the role of being the DH person in a department is shifting my perspective on the issue of tools or low-barrier-to-entry solutions for people who are interested in working with digital sources and in computational processing but are not yet ready to dive into the world of R or NumPy/Pandas/SciKit-Learn/Jupyter ecosystem in Python. This is especially true for students who expect there to be an app for that, but for whom the inner workings of their computers (let alone the web) is largely obscure.
(Here is my obligatory aside about the advantages of being an elder millennial, where computers have always been around, but I have grown up along side many of these technologies - looking at you, Web. I had a telling moment in class in the Fall when we were talking about major shifts at the current moment that have destabilized social norms and technology did not come to mind for the students - to them, the internet has always been; the world has always included “the digital.”)
Shifting back into looking at tools is proving a hard transition after spending 10 years working hard to get behind them. And I am not sure yet how to balance the need to get students up and running with something to convince them that it is worth looking behind the curtain with the need for it to be hard enough to help them to think differently. Also the world of research software for digital humanities is wildly different from when I started (you all have done amazing work!) There are so many new resources out there, and these have the potential to structure the ways students learn to approach computational questions, teaching good research practices from the start.
So one of my projects for the summer is to identify tools that I want to weave into my teaching that do the work of making the computational work easy enough to get students started but that nudge them to think about the computational processes taking place behind the scenes in a way that hopefully inspires some to ask more questions (and eventually learn some Python). Because turns out not everyone is keen to learn BeautifulSoup right off the bat ….