Now that the showcase is done and our papers are handed in, my reflections on the Freedom of Speech* project are taking a different form. The intensely action-oriented thoughts and feelings of the last six weeks were marked by a combination of stress and optimism: there was so much work to be done, but I always found my self talk leaning towards “it’s going to happen” (until the last day, when it switched to a tired but satisfied-enough “it’s going to be what it is”).

Now, without the deadline of a presentation and audience looming, I’m much less stressed about the project. But without the motivation of that deadline, I’m less optimistic about its future. As a recovering perfectionist, I am now okay with the idea that a project can be useful and valid without functioning 100% seamlessly. But I want the tool to work as well as possible so that people can use it without encountering faulty information or frustrating glitches, and that’s definitely not the case yet. But it’s hard to imagine going back to it without my whole group there to share in the process.

It’s lead me to wonder if the site is a beta version or a rough draft. To me, calling it a beta version implies that the same site will be reworked and updated, and the final product would look and function similarly, but at a higher level. Calling it a rough draft (which is increasingly how I feel about the Explore page) opens the door to many more revisions, not just functionality upgrades. For one thing, I’m not nearly as excited about the topic model results now as I was when I first ran the model, and I wonder if they really add much value to the Explore page. The topic model proved a fun exploratory analysis tool, but I think its merits are more limited than I first imagined, especially in the face of the manual data grouping that Martin and Joanne did to make the eras on the timeline.

Thinking about that now brings me back to my first semester in this program — I took a GIS course at Hunter College (Intro to Cartography and Geovisualization), and my major takeaway was that good maps are 10% GIS and 90% context and design. The actual “truth” of the coordinates and GIS layers is obviously important to get right, but the vast majority of communicating the argument or point of a map comes from everything else: colors, labels, statistical breaks, symbology, and maybe most importantly, context. That’s how I’m feeling about the topic model: however cool or interesting the results are, they’re probably only about 10% of the way towards making a good end product. I didn’t leave enough time to build out that context or consider how I would lead a user through the topic model, and in the end, I find Martin’s context-rich descriptions of the eras of free speech to be a much more compelling part of the site.

I think the topic model has potential, but implementing it in a way that really helps users to gain new knowledge about freedom of speech cases would require, at the least:

• including the full 10-word topic somewhere, not just a representative title, so that users can see the words that make up a topic
• including a quick definition of what topic modeling is
• omitting the topic model data point for cases where it adds little to no value, as in cases where the top topic is a mix of unspecific words (this is true of a lot of cases) or cases that don’t have a strong one or two topics

Those are my thoughts for the future of the Explore page topic model, which in truth probably isn’t even top of my list to fix up (looking at you, wrong case showing up in the case modal). As far as deadlines go… I’m definitely taking the coming week off. Five fully online courses later, I maybe feel more beat than I ever have at the end of a school year and am 100% ready for the semester to be over: for some summer, some days outside without opening my computer, and some sleep.

After that, maybe I’ll hit up our group’s Discord server to run my tech edits by them, set a one week deadline, and see if I can squeeze a few more days of “it’s going to happen” energy into the project.

I’m fairly sure I’ve missed a post or two, so consider this a combination make-up-farewell post. I want to start by saying that it was a pleasure to work alongside everyone in this course, not just my group. I think being in a classroom environment where everyone is in a similar boat to you with regards to working on a group project made me more comfortable working on my own. To clarify, even in other courses where I’m working on a project, not everyone in that class is working in a group – some work alone, some work in pairs, some work with more. I suppose it’s a matter of feeling secure, if anything.

Something that has come up across all of my classes at least tangentially this semester is the idea of memory and how it interacts with other more immaterial concepts, such as narrative and archiving. It’s made me think about how the memories of not simply this class, but how each of our projects will affect their their respective “environments” (“environment” as in “environment scan”) over time. This may seem needlessly existential, but, how will these projects look after they go dormant? That is, for the projects that are going to receive constant updates, I wonder how they will look at their culmination-before-stagnation, how they look before they go otherwise untouched for an indefinite period of time.

On a brighter note, I’ve also been wondering what will happen when (and if, I suppose) one of us will be reading some scholarly article or academic paper and see one of our projects cited in it. In fact, one of us could even encounter it in a more casual, mainstream context.

I’d also like to put an idea I’ve been toying with forward – during this semester, I looking at heraldry as a form of rebus, which posed a number of intrinsic and distinct challenges. For instance, the fact that when one “solves” a coat of arms, one will generally end up with a far more abstract and less defined result than when one solves a rebus. Indeed, “solving” a coat of arms is more like a fusion of mapping an area and analyzing a painting, while solving a rebus is more like a combination of solving a math problem and analyzing a poem: in the case of the former, it’s less straight-forward, and there are theoretically multiple, possibly radically different yet still correct methods and answers. So, I pose this question: while heraldry has connections to conventional rebuses that aren’t too obscure, what items, further removed from heraldry, could be interpreted as one would interpret a rebus?

Whatever the case may be, I wish you all the best of luck in your endeavors, and I look forward to potentially working with any or all of you next semester. Farewell, and have a lovely summer.

The Careers at the Intersection of Education and Technology panel took place on May 11th, and it included professionals working in this new and in-demand field.  The event highlighted the diverse and unique positions that merge digital humanities, digital pedagogy, open education, library studies, and coding. The panelist included Barbara Hubert from Brainpop,  digital humanities fellow Erin Rose Glass, and Museum Educator Maria Janelli. These Graduate Center Alumni gave insight into working with a Ph.D. title, how much technical or educational experience one needs to work in this field, and how one might land a job that blends these two ever-changing fields.

Like lessons I’ve learned in my Digital Pedagogical courses, the alumni reiterated that one of the main rewards of this intersection between education and technology is giving students more agency and access to educational material and digital skills like coding. While at the panel, I couldn’t help but be reminded of my team’s project, Corona Chronicles. This living, breathing, student-centered archive thoughtfully curated, is a tool of access and agency for middle and high school age learners to tell their story their way.

The panel gave me comfort and confidence in all of the tools I’m learning in the digital humanities program and what the career world looks like for people with our unique and versatile set of skills and interests. Along with host Joseph Paul Hill, the panelists spoke about the demand in both the educational world and the technology/digital production world for digital humanities and digital pedagogy skills. They gave tips on how to best present our learning and praxis experiences on resumes and CVs, highlighting the nature of our projects, project management skills, design and implementation, and how we work with data.

The most important lessons from this panel were to 1. you don’t need to be an expert in both education and technology to acquire a position that merges these two fields; you have to be open to learning new capabilities and collaborating with others in your team (who are also diverse when it comes to skills). 2. When learning one software or programing language, one must also be open to teaching these to others. 3. Most importantly, one must network and maintain connections with fellow alumni, educators, and other professionals one meets along the one way. This last point is not unique to technological nor educational opportunities. Still, it is special to this intersection since you will always be learning new pedagogical and digital skills and constantly collaborate with people from a completely different background and maybe more or less experience in either education or technology.

I think I have 5 personal blogs left to write, which pretty much coincides with having built an almost-fully functional website in the last… 3 weeks. I honestly haven’t had much to write since my topic modeling posts — the update each week is that I am neck-deep in coding, which is a state that I alternately love and hate.

I hate it because it involves hours and hours of sitting, often so engaged in a problem that I forget to move or drink water for an unreasonable amount of time. I hate it because it leaves my body restless and my brain knackered. I hate it because the emotional landscape sometimes involves great swathes of frustration with just pinpricks of triumph before I turn to the next tangled problem.

I love it, though, because it really is like learning a new language. It’s a language of functionality and precision, and of breaking the problem I want to solve down into a set of tasks that a computer can accomplish. I’ve enjoyed learning over the course of my degree that there’s rarely just one way to do that. There may be one way that’s the most performant, one that’s the most mobile-friendly, one the most visually pleasing, or one the easiest. Beyond that, there may be one way that accomplishes what you really intend and one that seems logically sound but ultimately fails (for example, select all the women in this dataset and select all the not men in this dataset are equally easy tasks for a computer but certainly not equal questions for a researcher — intention is key, as is a data structure that allows you to ask exactly the question you want).

Sometimes these different  “best ways to break down a task” overlap, sometimes they don’t. Sometimes I have the knowledge and bandwidth to make an informed decision or improve on an old way of doing things, other times I’m so relieved to hack out a way that just WORKS, I don’t even think about the others. That’s definitely a plus one for collaboration, since looking at other peoples’ code often teaches me about the ways I haven’t chosen.

I love coding because I get to not only think about all of that, but actually do it. I hope it never gets old for me to write out text commands and see them bring dynamic shapes and colors and movement and information to life online.