While I read around the topic of digital education governance and data mining, I took it quite literally for this weeks’ data collection. With time on my hands and our school still on Spring break, I turned to my favourite video game ever since we got introduced to it during the IDEL course: Minecraft!
I usually play every few weeks, always in creative mode, and there is almost nothing else that helps me to unwind; in short, it’s the best form of escapism for me. For this week, I decided to set up a new world in survival mode because I wanted to track the interactions with objects and mobs.
I played every afternoon for the past 4 days and kept a record with ‘statistics’, a game feature to track certain tasks in the form of numerical data.
I tried to make the underlying “information infrastructure “(Anagnostopoulos, 2013, p. 3) that you’re often not aware of while playing visible. I used Minecraft Education and selected some data to visualise my first four days in a new Minecraft world. On the one hand, it was so much fun because Minecraft offers you unlimited possibilities to be creative. On the other hand, I had to be conscious and keep in mind that it had to fit in a screenshot.
Here you can see the kilometres I walked each day:
I have taken the screenshots so that you can read the signs. It would certainly be a more enjoyable experience to walk through this Minecraft data world, which would then be like a history tour through my world ;-).
This is a visualisation of the interactions with the crafting table.
For the third data viz, you can see the mobs killed each day. You can’t see the precise number (each mob is a carpet block), yet you can compare between the days.
What is interesting to me is how little information each data visualisation conveys, yet if you merge each day’s data, they can tell a story. For example, on Day 3, you would conclude I haven’t spent much time in the game if you just look at the kilometres. However, the information of the second (72 interactions with the crafting table) and third visualisation (36 mobs killed) tell you that I probably spent more time in my house, where my crafting table is based and that I built weapons to fight mobs. If you transfer this idea to data sets, you must constantly question what a certain data means in context and what other information has to be taken into account before interpreting data!
References:
Anagnostopoulos, D., Rutledge, S.A. & Jacobsen, R. 2013. Introduction: Mapping the Information Infrastructure of Accountability. In, Anagnostopoulos, D., Rutledge, S.A. & Jacobsen, R. (Eds.) The Infrastructure of Accountability: Data use and the transformation of American education.
Very cool use of Minecraft as a dataviz tool! I suppose you could say something about the ‘blocks’ as graphical constraints on the user’s interpretation too, much as all dataviz shape user perception. Perhaps you could consider this a little further this week, as you hopefully find some time to explore the HESA and OECD data we’ve suggested. These are supposed to be relatively simple, ‘user-friendly’ interfaces that mediate interaction with vast infrastructures of data collection and analysis. But in making the data user-friendly, do they put limits on what you can do or what interpretations are available?