Did I already mention this MOOC watching habit I developed over the summer? I got sucked in to watching lectures online from all sort of classes. It is sort of like being in college again, but when I fall asleep during lecture, I can rewind when I wake up (if I want to).
One of the classes that I devoured video lectures from is , taught by Duke neuroscience prof Dale Purves. It’s got a little bit of that evolutionary-psychologist-explains-everything flavor, and a lot of visual illusions to use-not-abuse in data visualizations.
I remembered it when watching animal videos with my two year old today (his choice). Here is something that 75 million years of primate evolution can do, and it needs quite the visual system to do so: http://www.arkive.org/verreauxs-sifaka/propithecus-verreauxi/video-06a.html
I had a chance to give a lecture on using Python/Pandas in scientific research this week, and it was __________ (fill this in after it happens…). Since I was talking about Python, I decided to make my talk in Python, too. I did this for a few classes in Winter and Summer quarters of 2013, but the technology has come a long way since then. For this time around, I used RISE aka the live_reveal extension, and I found it very promising, although _very_ “bleeding edge” (which is what happens when the cutting edge is too cutting).
To make it really work as a powerpoint killer, I think it needs a little more friendlyness on the slide layout side of things. I don’t need much, but I would like:
* a talk title slide that has title, name, and date;
* a full-screen image slide;
* a way to put slide titles in a consistent place;
Am I totally power-pointed in my desires? I should file some issues on github.
Other wishes, while it’s on my mind: would be helpful to start slideshow from highlighted cell, would be convenient if cell toolbar toggled automatically between slideshow to none when starting and stopping presentation display, make it all easy easy easy to use.
The author of one of the best books on data visualization is giving a massively open online course (MOOC) this fall. I’m going to check it out. You may be interested, too.
It is getting to be the season of new students, and I was inspired to round up a few links on grad school:
Advice for new students from Jennifer Rexford: https://freedom-to-tinker.com/blog/jrex/advice-new-graduate-students/
Managing your advisor by Nick Feamster: http://greatresearch.org/2013/08/14/managing-your-advisor/
A simple test for those thinking of doing a PhD: http://blog.prof.so/2013/06/test.html
It is that time of year again, when the IHME post-bachelors fellows go off for their field placements. Some are keeping nice blogs of their experience:
p.s. The comment spam was getting so bad, I had to turn it off. PBFs, email me if you would like your blog listed here, too.
I’m quite taken with the Software Carpentry approach to teaching scientists computer skills, especially since I saw it in action in UW a few months ago. One aspect that I’ve been trying out for my own course is the “mastery table” approach that the Software Carpentry Instructor Study Groups use. Here is a mastery table for teaching version control. I have made a few of my own, but I don’t think I said enough for any novice to leave competent, according to my ambitions. I will keep trying.
I had a fun time on Monday talking to area high school students at the UW Math Department’s annual Math Day event. My slides and some others are now on the web.
I’m spending yesterday and today helping out with a two day software carpentry workshop at UW.
Software Carpentry helps researchers be more productive by teaching them basic computing skills. We run boot camps at dozens of sites around the world, and also provide open access material online for self-paced instruction. The benefits are more reliable results and higher productivity: a day a week is common, and a ten-fold improvement isn’t rare.
I am impressed by the curriculum and by the attention to evaluation, not an easy task in any educational setting. The 20% productivity increase is an interesting claim. From what I observed yesterday, I would expect huge heterogeneity based on past experience, and I would expect this heterogeneity to be hard to predict.