Since the original post came from the perspective of an educator, let me comment in that context. (There are plenty of other important issues raised in this thread, but I don’t have the expertise to say anything useful.)
I’ve taught a few mathematics courses at the college level with a programming component. For these I used Python (though I hope to use Julia in the future).
Based on my own experience, and talking to other instructors, it seems like the primary factor guiding language adoption (in an educational context) is ease for use, both for the students and the instructor. My goal is to teach math, and to the extent I feel that assigning programming problems helps with this, I require programming/simulation/etc. But I’m always doing a cost–benefit analysis in the back of my head, wondering whether the benefits from programming assignments outweigh all the non-mathematical problems that students have to overcome to complete them (learning syntax, debugging packages, debugging language installations, etc.).
If a student feels they spend more time wrestling with the language (or package choice, or poorly supported/broken packages) than doing math, then that’s a bad experience for them. And if I have to answer a ton of incidental language/package questions, which really have nothing to do with the main content I’m trying to teach, that’s a bad experience for me.
So, at the beginning of class, I give a handout on Python with a 30-minute quick start guide to the language and a few package suggestions for basic tasks (e.g. seaborn for plotting). This way they don’t have to Google how to do basic things like plot, or attempt to judge the merits of various libraries; they can just focus on the mathematical content of the course.
I think this is a pretty common approach. For example, in companion site to the book “Fundamentals of Numerical Computation with Julia,” the authors give a few package suggestions for students (along with installation instructions, etc.). See here: GitHub - fncbook/FundamentalsNumericalComputation.jl: Core functions for the Julia (2nd) edition of the text Fundamentals of Numerical Computation, by Driscoll and Braun.. They also standardize on the Plots package in the book.
In light of these considerations, and to respond more directly to the original post: I feel it would be good if people teaching undergraduates could standardize on a few simple packages that are easy to use and bug free, just for the purpose of teaching. They don’t need to be the fastest or most sophisticated, they just need to minimize the number of headaches for the students and instructor.
For more advanced users with more specialized needs, of course other packages may be more useful. But my students and I are not advanced users; we’re just coding up basic simulations/examples to illustrate lecture content.