I teach a linear-algebra course with about 200 students. This is not a programming course, nor are students expected to learn to program. However, we want to incorporate computation into the course — both in the lectures and in the assignments, even if the latter are merely using Julia as a glorified calculator to start with. For this to work it is essential that doing computation has a low barrier to entry.
In such a large course, it a huge headache to deal with everyone’s installation problems, especially on the ancient underpowered Windows laptops that some students have. And you will have a mess with students (including students who joined the class a few days late, as many students do) struggling to do the first assignment (or two or three) because of software problems that they didn’t sign up for in a math course. Before juliabox, I went through this for small classes (< 40 students) and I recall weeks of pain at the beginning of each semester.
On top of that, because Julia is a young language, you can expect that most of the TAs and other help resources are newcomers to Julia (if they are familiar at all, which is doubtful), and will be helpless in the face of installation problems.
This is the kind of thing where juliabox has been indispensable — without something similar, I don’t think it would have been possible to incorporate Julia for computation into large classes here.
Because we’ve used Julia in several classes for several semesters now, that gives me some leverage to press our university to allocate funds (either for a juliabox contract or for a local jupyterhub installation), although I don’t know yet whether I will be successful or how long it will take. For people introducing Julia for the first time at a school, I think getting these kinds of funds will be much more difficult.
The best hope for many schools, in my mind, is to piggyback off of Python and/or R — convince the university to set up JupyterHub or similar for use in established courses that employ Python or R. Once that is done, adding Julia to the mix should be relatively easy. For the same reason, juliabox as a turnkey service may be more successful if they can offer Python and R as well as Julia.