I'm in nuclear engineering now, I'm seeing a similar process. It used to be Matlab for everything but once the Anaconda Python distro came out and made installing python and the science libraries a simple process many undergrads are now using Python instead. The Spyder editor with the documentation window makes it really easy for undergrads to lookup functions, similar to the Matlab editor.
My SO is teaching physics in small university. Used to use Excel, Matlab, some other statistics packages. Now it is Anaconda all the way down.
As for Jupyter (which I love), there's nteract , which Netflix seems to be supporting .
Also for the original poster (whose psycholinguistics work I am familiar with), it's easy to move data between R and Python using the rpy packages (which works in notebooks!)
Since then Python is my go-to language, but that didn't stopped me from exploring other languages like Julia, for large numerical analysis or Go.
I see that Pythonification he talks about around me, and it's true that is becoming ubiquitous and the defacto langugae on sciences, specially on life sciences.