I'm excited to announce that there will be a summer session for my Dataviz Workshop at NYU (starting June 21). This is a chart-building workshop run like a creative writing workshop. You will work on a personal project throughout the term, receive feedback from classmates, and continually improve the product. I have previously written about the First Workshop here (with syllabus), here, here and here.
Here is the link to register for the course. (Note: the correct class time is 10a - 1p.)
The participants in the First Workshop were very happy with their experience. I can now report on the end-of-course survey. Ten people took the class, and seven responded to the survey. The satisfaction scores are as follows:
It's very gratifying to see that almost everyone thought the class time was well spent. During class, students gave each other feedback on projects. A key to making these sessions work is that students should be both givers and takers. It is really important that they become as comfortable giving critique as taking feedback. I asked the students to self-assess and this is what they said:
I'd also add that the few students who enrolled in the course with less background than the average ended up participating fully and actively in the discussion. As an instructor, I want to get out of the way while keeping the conversation on track. Based on the following rating, I think I did fine:
One of the feedback I received during class--not reflected here--is that some students want to spend more time discussing the reading. I assign three books, which everyone loved but I believe that it is hard for them to finish reading all three books in time for the second class. They would like to spread the discussion of the books over the course of the term. This arrangement would present a challenge. Due to the nature of a workshop, the first two sessions cannot involve project discussion, which is one of the reasons why I give introductory lectures and assign the books. In addition, students spend a lot of time during the term both working on their own projects and reviewing their classmates' projects; and I worry that assigning more reading distracts from the other activities.
Indeed, the course is not a gut course. Several students were surprised by how much work they put in. One or two learned that preparing the data took ten times as much time as they expected. (They selected particularly difficult datasets to work with.)
A specific feedback is to add a session in the computer lab. This creates an opportunity for students to share their knowledge. Those who are good coders can help others who are not with pre-processing tasks. Those who are good with Illustrator can show others how to make the charts pretty. I am not ready for this change in the summer session but in the fall, I'll likely experiment with this.
Finally, the tools used by students are diverse: Excel (5), Illustrator (3), R (2), followed by Powerpoint, Pixelmator (draft stage), Tableau, Stata, Paint and SQL Server (1 each). Three of the students put their work on a Web page, which was the most popular format.
If you are serious about dataviz, please join me this summer for the Second Art of Data Visualization Workshop.
Click on this link to register for the course.