RStudio Cloud for teaching students

Hi! Could you please describe if and how RStudio Cloud can be used for teaching R programming in RStudio to students in the university? What are the benefits of doing so?

Many thanks in advance,

RStudio Cloud can definitely be used for teaching R programming to university students. We've had a number of professors working with it since last fall, and they tell us it's gone very well. Some of the benefits are that there's no need for the professors to spend time setting up and managing servers, and for the students there's no software to install. There are also a number of features that make distributing, and reviewing, class assignments easy. The best way to learn more would be to look at the Cloud Guide ( - and be sure to review the section titled "Using Private Spaces in Courses and Workshops".

Hope this helps - and let us know if you have more questions.


Who should university instructors contact about increasing the number of students we can host in the private space? RStudio notes:

"Each account is allocated one private space, with up to 3 members and 5 projects. You can submit a request to the RStudio Cloud team for more capacity if you hit one of these space limits, and we will do our best accomodate you."

I expect to have scores of students in class the first day and, on that first day, I hope to have them playing with data, similar to the description here:

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Sounds great - and good question. When you encounter a limit (either by trying to add > 3 members or > 5 projects), you'll get prompted to request additional capacity. Just fill out the requested information - if you enter the course name, topic and at what university, how many students you expect to have, a rough idea of the total number of projects you expect to create with your students, and when the course will run, we'll receive your request and set you up so you have what you need.

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Is there any issue with asking students each to create their own account? I don't need the assignment features for my class (I don't think). There will be about 175 students.

There's no requirement to use a space for teaching - and whether you do or don't use a space, each student will still need to create an account.

As an FYI, here are a few of the advantages of using a space for a course:

  • It allows you to access the students' work (projects) without them having to make their work public.
  • It allows you to easily distribute example or assignment projects to all the class members.
  • It allows you to define a base set of packages & files (using the Base Project Template feature in Space Settings) that will get included any time a student creates a new project via the New Project button in the space.

But if none of the above matter to you, it's totally fine to just have each student do work in their own personal workspace (called "Your Workspace").

thanks for laying those out. My understanding is now better.

What I am thinking about is how I might get students to hand in assignments. We have Quercus/Canvas here. My thinking is to get the students to use a Notebook and then Preview it and hand in either the HTML itself (via downloading/uploading or some other way).

I'm thinking this way because then the recording of grades would be in a central place that the students can see. (I'm also thinking that I want the students' experience to be as similar as possible to what they would encounter outside of my course, eg. in the workplace later, so I don't want to make things "too easy".

Last year, I had the students download and install R Studio on their own machines, and that was OK; I'm currently exploring this mechanism that might be easier to manage.

Any thoughts? (I realize that this is rather vague, but I'm currently exploring how well the mechanism might work.)

Yep, that approach for handing in assignments should work fine if you're not interested in seeing the source code behind the work. At some point, we expect to look at integrations with course management systems like Canvas, but that's still a ways off for us.

One of the motivations for Cloud is that we want to make the initial experience of doing data science gratifying, rather than a struggle to figure out how to get the right software installed and working on your machine (which we also try to make as painless as possible, but even if it's a problem for only a few kids in your course, can be a real initial roadblock - and local install can always be covered later in a course if you think that's important to cover) - so your thought that you might use Cloud rather than start with the download / local setup bit is definitely in line with our thinking / mission as well.

thanks for sharing your thoughts. That's very helpful.

Later in the course, my students will also be learning SAS, which is also done (most easily) online, so there will be a certain consistency there. I am definitely doing R first, though (your word "gratifying" definitely comes to mind!).

I am thinking that I will recommend Cloud, but also mention the local install idea (with instructions that students can read later if they want to explore it themselves).

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