[acbart]

As someone who uses "Data Science" to teach "Computational Thinking", I think this blog post hits on a lot of really valuable pedagogoical notes. Getting motivated, learning things through doing, and having a strong context for your learning.

For those wondering why I put my buzzwords in quotes, it's because I don't want to sound like I'm a huge proponent of either of them. CT is the term I use to describe how I teach my students about abstractions, algorithms, and some programming. DS is the term I use to describe how students learn all of that in the context of working with data related to their own majors. I'm not trying to claim some crazy paradigm shift, just that it's a great way to convince students that CS is useful to them.