Saturday, June 28, 2014

Teaching visualization podcast: The best parts

I guess that it's hardly a surprise that I found the latest datastori.es podcast fascinating. Enrico Bertini, Moritz Stefaner, Scott Murray, and Andy Kirk did a great job at describing many of the tensions, struggles, and trade-offs visualization educators face, and at offering useful suggestions. Quick notes:

Enrico: “When people think about professors they believe that once the semester ends you’re done with your job. Which is actually the opposite: Now you can finally do your job!”

Andy: “(One of the main challenges is) to find a way to bridge the gap between the top people (…) the ‘Illuminati’ of the field, (those who are) pushing the boundaries of what we should do, what we could do creatively and theoretically, and the everyday person who is working with data (…) How to make the translation to the lower end of the pyramid.”

Andy: “I bang the drum incessantly on ‘it depends‘. You need to embrace all these principles, but I try to be not very dogmatic and avoid some sort of cookie-cutter approach.”

Enrico: “We all know that the principles that we teach are not necessarily black and white (…) But it’s a struggle because on the one hand, if you make everything relative you run the risk that the students will walk away with nothing. I wonder if it’s better to give some clear-cut rules and principles and then let them discover that there are cases in which this doesn’t work.”

Scott: “One of my main ongoing challenges is the tension between tools, process, principles, and history on one side, and then the technology on the other side, because the technology can just eat up so much time!”

Scott: “You cannot really separate the tools from the process.”

Enrico: “It doesn’t matter how much theory or how much principles you teach. You need to have your students practicing those principles. Otherwise, they won’t absorb them.”

Enrico: “The last time I taught my course I introduced d3.js. I didn’t let students use any other tools or frameworks and this worked just perfectly, much better than I expected. I think that one of the reasons is that students managed to help each other a lot, they mastered the language in a few weeks. I had an assistant teaching them a d3 seminar, and the feedback from the students was great.”

Enrico: “One thing that frustrates me is that many of my students come to my class with this mindset that data analysis is just aggregation, aggregating everything and coming up with four numbers. And it’s not. It’s about disaggregation, about showing as many details as you can without overwhelming people. Then it starts working really well.”

Scott: “I think that it’s a great idea to begin by seeing tons of examples. The first assignment in my course is a short one: Go out into the world and find a handful of infographics, statistical charts, whatever. Choose the ones that you believe are successful or unsuccessful and then write about them, critique them, and tell us about them. To me the first step is to build this library in your head of what the possibilities are.”

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