Cornell College Senior Profile
Hey there!
Cornell College just published my senior profile – check it out here. It features some interview questions about my time at Cornell as well as a couple snazzy photos.
academic
Interactive Data Analysis and Visualizations
Data Visualization Tools for the Web
One of the major advantages of the digital humanities is the ability to work with and analyze lots of data. Naturally, one wants to visualize that data and analysis results. There are a lot of options out there when it comes tools that aid in data visualization, and some are more intuitive to use than others. While it is wonderful that there are so many tools, it can be difficult to know which ones are best for the job. Their usefulness depends on the type of data being worked with, the overall scope of the project, and how much technical expertise there is on the team.
Chart Making
If you already have the data you want to show and know what kind of visualization you are after, there are several simple chart options available, especially for web display.
Google Charts
Google Charts is a common tool used to make interactive charts on webpages using HTML, CSS, and JavaScript. This may sound a little daunting, but it was designed so that non-coders would still be able to pick it up relatively easily. There is a decent range of available chart types, and all of them are interactive, making them great for integrating into a digital report or webpage. One can either make the data table in the code themselves, or they can link to an online spreadsheet (such as Google Sheets). This is a little limiting in that this is the only way to import data sets, and if one is looking for a more complicated display, it would take a lot more fiddling with code than what might be comfortable. However, it makes great aesthetically pleasing interactive charts for simple needs.
Variance
Variance Charts also plots simple charts via HTML and CSS, but attempts to smoothen out the learning curve even further by dropping the need for JavaScript knowledge altogether. It also is a step up from google charts in that you can import csv files, instead of having to link to a google sheet. However, it does not inherently make the charts interactive. It is a good fit for quick charts with little coding knowledge, and still allows for some stylizing. As they state on their own home page, Variance is not the best choice for more complicated visualizations or data sets greater than ~20k rows.
JS Libraries
If there are project members who are knowledgeable about JavaScript and the HTML DOM/Canvas, then there are many JavaScript libraries that make custom interactive charts easier and more appealing, such as D3js, Plotlyjs, Highcharts, and ChartJS. D3js in particular can be used for complicated data analysis and mining as well. (Many of the higher-level chart makers are built on D3js). These libraries are a good option when there is a programmer on the team, when showing the data is essential, and when the visual needs a certain level of customization that can’t be reached with simpler tools. There are a huge number of these, so the best way to determine which one will be best is to take a quick glance at each and pick the one that works best for the needs or the project.
Data Visualization
For more in-depth analysis or complicated data manipulation, charting tools alone are not going to be the easiest to use. If the project is still in the analysis stage, there are a few good pieces of data analysis software.
Plot.ly
Plot.ly is an online graph maker that lets you import data from multiple sources and requires no coding knowledge to use. It does, however, require an account, and does not have the most intuitive interface. But for those looking for something simpler than Tableau or Orange and do not need their more complex analysis capabilities (or is unable to download them), Plot.ly is a great option, especially as coding knowledge is not really needed. If there is a programmer on the project, then Plot.ly also has a JavaScript library to make more customized visualizations. There is a free and paid version.
Tableau
Tableau is a desktop data visualization software. It lets you either manually define or import data sets from several different filetypes. It allows for many ways to display data, and was specifically created to help with data analysis and visualization. There is a free version (Tableau Public) and a paid version, meaning that the free version students would likely use is a little more limited. It requires no programming experience, but the graphs on Tableau public are all shared to the web publicly, and has limited visual control. However, the interactive visuals can be embedded into other web pages or downloaded as still images.
Orange
At first glance, Orange works much in the same way as Tableau, but is free and open source. It also allows for a lot more involved data mining and analysis. However, its user interface is not as easy to pick up, and to do the more involved data analysis requires more expertise. Its visuals are also not quite as sophisticated, but it is a much more robust tool for an aspiring data scientist. It does not require programming to use, but there is the option to do some scripting if one desires.
Play favorites
These are all decent programs, and in most cases there is not going to be a “best tool” for any given task. Yet one should still keep in mind the skillset and end goals when picking tools. In the end, it comes down to what needs to be accomplished, and what one likes to use and is comfortable with.
DHSI – 3D Modeling and Games for Digital Humanists
These past two weeks, I have been at the DHSI (Digital Humanities Summer Institute) conference. It’s not the easiest experience to describe. There are classes, colloquiums, guest speakers, talks called “unconferences”, presentations, and hangouts. The participants by a vast majority are grad students and above. In each of my classes, I’ve had a nice mix of grad students, phd students, full on professors, and a few others. I think it’s safe to say it’s a mostly academic-minded conference, though there is definitely value for non-academics with an interest in digital humanities as well. Something that I found absolutely fantastic is that there was a significant lack of barriers or separation by academic group (ie. if I wished, as an undergrad, I could go to dinner with a professor, a phd student, and a masters student with no weird separation or awkwardness in discussion that one tends to experience otherwise). All in all, a fantastic experience – I learned quite a lot, and gained a ton of inspiration for the future.
The first class I took was 3D modeling, which was essentially intro to SketchUp. We made a nice replica of a building in downtown Victoria:
Here’s the front:
I worked mostly on the back:
I think it all turned out pretty well, for a small group of people who had never used SketchUp before.
The people in this course, by the way, were awesome – Among getting encouraged to become a medievalist, I was able to get a lot of advice and interest about my project, and my impostor syndrome melted away the more I spoke with people.
This second course, Games for Digital Humanists, I decided to take because it’s super relevant to my project, and also, vidja gams are cool. The first day of the course inspired me with many ideas for awesome blog posts, which of course I will obviously write as soon as I have time and my brain isn’t melting (which, by the way, is why I haven’t been keeping up with the weekly updates).
The first few days were spent working on some fascinating theory (I sense a lot of reading in my future), and then the class split into groups. The instructors of this course invented a game to create games, and so we played this game to come up with a game design. It’s really neat – the last time they taught this course one of the groups took their idea to a kickstarter! (It got fully funded, too). The idea we prototyped was a storytelling game along the same lines as dix-it (fantastic game, by the way, especially with the right people). A group of players draw one protagonist card and one setting card. Then a timer is set and one player draws a “bad” card and has to say a line or two of a story (using the setting and protag) while trying to put a good spin on the bad card. The next player then draws a bad card and does the same thing, trying to build off the previous player’s story bit. The end goal is to make the story end on a happy note.
Messy design process (complete with fish)!
We made paper cards and playtested a few rounds – not bad! Something I’d try with the right group of people. I don’t think we’ll be making any kickstarters, though we learned a lot. It was essentially a super short project process, complete with bumps and hurdles. Not a bad ending for just a few days. I also was able to ask some advice about my project from the instructors, and I have a much clearer idea of a timeline and the project’s overall future than I did before.
I feel like I have grown a lot from this trip. Here’s hoping the return trip to the US goes well!
Reflection: Learning with Digital Games (2010)
I’ve already spoken my thoughts about a couple chapters of this book in a previous blog post, but as of last week I have finished the rest of the book. This has probably been my favorite pedagogy and gaming book so far: it’s well-written, a quick read, and the author clearly knows their stuff about both teaching and gaming. Even though it’s 6 years old now, I would say teachers interested in incorporating games into their lessons would get a lot of value from reading this.
On to what I’ve pulled from the rest of the book:
Part I: Theory
There are several different lists related to learning, the most useful of which is Prensky’s 5 levels of learning from games (which actually can function more as an assistant for game design, i.e. figuring out what each of these IS in your game).
- How to do something, i.e interaction with the system (for my first game: point-and-click)
- What to do in the game, i.e. game progression/goals
- Why you do things in the game i.e. long-term affects
- Context and value systems in the game
- The ability to make decisions based on the value system in the game
The other lists were related to game pedagogy in areas other than literature, as much (especially early) gaming pedagogy is centered around primary and secondary education for teaching math and sciences.
Part II: Practice
This section was fantastic – it inspired a lot of design spreadsheets on my part. It has a lot of fantastic advice for the early stages:
When you begin to think about games for learning, start with the learning objectives you want the students to achieve during the session [in my case, individual game], which can then form part of a design specification for the game you want to use.
Then, think about the types of activity that you would normally undertake with students in order to meet those outcomes. How might these activities be [effectively] embedded into a game?
And for overall lesson incorporation: A game is part of the overall learning package. If the game itself cannot fully meet all learning objectives, there can be additional outside activities surrounding the game. While I am not doing a lesson plan, we have talked about how information (esp. cultural) reinforcement could happen through this method – having quizzes or exercises that relate to the information learned from playing a game.
They also had a list of things to include for Effective Game design for Learning:
- Support active learning: encourage exploration, problem-solving + inquiry
- Environment should engender engagement [immersion]: explicit + achievable goals, high level of interactivity, large world, multiple pathways to success
This point, I’m going to argue about a little. Not that these are bad things for an immersive game, but there are many types of games out there, and one game doesn’t need ALL of these to be immersive. A huge world, multiple endings, or even high interactivity can help, but there is a huge amount of wonderful little games that don’t have those things that are completely immersive. I’m gonna throw interactive fiction as a genre out there. While there are IF games that have big worlds and high interactivity (however one quantifies that), many have limited options and a small environment that are just amazing. The goals aren’t always clear either, and a game that encourages exploration might actually benefit from not having a clear goal with an explicitly defined path from the beginning. The player’s ability to completely ignore the main questline in Skyrim, for example, is what makes the exploring aspect of it so fun. Games with a sense of urgency to their goals and quests hinder the player’s comfort in exploration. That is not to say that having a clear goal means having a sense of urgency, but that is a pretty common theme. - The game world should be appropriate for the learning context: ie fits with the curriculum or assessment , personally relevant to students (motivation)
- The game should provide ongoing support: initial ease into gradual difficulty
Whether a game is useful or appropriate will depend also on the type of students and their backgrounds, experiences, and preferences. I’ve talked a little bit about this before, but I run into the extra challenge of having an audience that I know nothing about save that they have access to internet and presumably are high-intermediate to advanced FL learners.
There is a chapter in this book about skills required for game creation, which reminded my once again why I wish I had a whole team of people. According to this, skills needed are: a subject expert, educationalist, game designer, programmer, interaction designer, graphic designer, and writer. While among the three people working on this we have all of these skills covered (mostly) it’s a ton to focus on at once.
That’s the bulk of stuff for the rest of this book. The next several posts will likely be more about the game design process/progress.
Book: Digital Games and Language Learning (2011)
The second book I’ve completed for my research is Digital Games and Language Learning by Freitas and Maharg. 2011 isn’t too long ago generally speaking, but 5 years is on the older side for video games. A couple of the educational games it referenced were even older – dating back to the early 2000s.
This book spent a lot of time talking about “Serious Games” with the Capitals And Everything. I had never heard of Serious Games, and the authors did not define it anywhere in their book at all. I later found out that is just refers to games whose primary purpose is something other than entertainment, but no one besides educators uses this term as far as I’m aware. They also talked a lot about Feedback, sometimes with and sometimes without capitals, which they also failed to define. I initially thought the chapter about feedback would be on student response to a game, IE game testing, but instead it seems that by “feedback” the authors are referring instead to the brain’s response to input.
The first several chapters were spent on not-quite-relevant pedagogy theory and more ambiguous uses of terminology. Later on, however, they made several useful cases for what should be part of an educational game:
- Students should have the freedom to fail, experiment, and exert effort
- games are not about memorization
- build scaffolding for future learning: ideally, people who have played my games would be better off in their next language course than another student in the same course who hadn’t had the extra practice
- offer clear incentives for more success
- partial rewards for partial success
- avoid brick walls – ie not letting players into a certain area until they’re at a high enough level (there are ways around this that don’t frustrate players)
The rest of it talked about stealth learning – that is definitely something I hope to accomplish, particularly with cultural and literary learning.
