Dataviz MOOC Review: Brace yourself, enjoy the ride

That's it, the MOOC on infographics and data visualization by Alberto Cairo is done, over, finished, completed. Phew. It was more work than I expected. It says four to six hours per week, but for me it was more around ten to twelve; less at the beginning and more towards the end. It was not easy to manage having a job and a family, like many other students and the teacher himself. Several students posted their work mentioning their difficulties in meeting deadlines and class requirements. That's why six weeks were really enough and, after going to bed at 4 am to finish my final assignment (the good old days), I am still recuperating. Still, I was stimulated and motivated enough to make it to the finish line. I hope we'll know how many of the 2000 made it.

Several people have already provided their review (here, here, Knight Center, and Cairo himself). Here's mine.

The good

The engagement of the teacher. It was impressive to see him everywhere making comments on a majority of discussions and projects, at least in the first few weeks. It was also motivating because it gave credence to the discussion forums. I was impressed by his engagement on Twitter and his generosity in shining a light on the students' blogs and entries. In fact, it motivated me to start this blog.

The Functional Art is a great book that will complement those of Stephen Few and Edward Tufte. I especially like the interviews at the end to give a perspective on the industry.

The journalistic angle. I had never seen this in my other readings, all of which were focused on more technical aspects of data visualization. The insistence on finding and showing a narrative has changed the way I do data visualization for the best.

The exercises. I'm glad we were pushed to produce something within relatively short deadlines. It is one thing to criticize, but quite another to deliver. I leave the class with something to show and that's something.

The network of students. It was one of my objectives when joining this class to find fellow data visualizers and this goal has been achieved in large part thanks to the forums and the regular interactions. I hope to stay in touch and continue to follow a few of the students.

The duration. Six weeks was good - long enough to get immersed, but short enough that it didn't become too much of a burden.

The price. It's amazing that we can get such quality education for free. Where's the catch?

The bad

The limited feedback by participants. It had greatly improved in the last week, but earlier I've seen a lot of feedback limited to some "good job, I like your colors". It sometimes looked like someone's just trying to tick a box for class participation. The initial 500 words request that was waived might have been to high, but there should be a threshold. We can benefit a lot from the feedback of our fellow students, but also from a careful consideration of their work. In fact, this experience convinced me further than team work can improve this kind of output.

The ugly

The platform. A few years ago, it would have been good enough, but nowadays, we are used to much more response and intuitive user interfaces and it is hard to adjust one's expectation to a rather antiquated one. I could barely find my way around in the first week and it never got comfortable. There were features so deep that they might as well be hidden. For instance, who else realized that we could establish "contacts" with other students, à la Facebook? Even I had a hard time remembering where my list was (it's under Messages). The inbox format is most bizarre, with messages taking a sixth of the screen width. I also wish that the images could be seen in line, even if hosted elsewhere. I am not sure it is worth trying to fix this platform and suspect it would be better moving to an entirely new one.

I have much more high than low points. My experience was very positive, both for a MOOC and for the knowledge. I would do it again in a heartbeat and in fact, I'll now be on the lookout for MOOCs and other data visualization training.

tl;dr: take it, brace yourself.