It looks slightly different from a local RStudio session, and Your web browser with full functionality, including built-in integration of R RStudio Cloud is a cloud computing service hosted by RStudio. If your course requires large computational resources and you have these available locally or through a paid cloud service, RStudio Server may be another viable option.Are technical issues with your computer preventing you from completing the pre-course tasks or doing the course sessions?Ī last-ditch solution may be to use the RStudio Cloud platform to do the course.
Each project copy is given 1 GB of memory and 1 CPU, so large data possibilities are limited. The initial member limit for workspaces is 10 members, but all requests for more space are honored (anecdotally, classroom sizes > 100 students are possible). Feedback is generally positive, and most recommendations are to save often in case the session crashes, which is rare. It is in beta, so there may be some instabilities. There are a few notable limitations to RStudio Cloud. The working environment for a user looks like a typical RStudio window:Īnd that’s it! There is plenty more detailed discussion of RStudio Cloud’s capabilities and options here. All users have the ability to download files to their personal computer if they choose. They can then edit their own copy, interacting with the R script exactly like they would on their personal computer. Assignments make it easy for students to obtain their own copy of the project (this includes files, packages, and code), which they do by clicking on the assignments link. When you are ready to distribute the project, you then change the permissions to allow everyone in the space access and select the option to make this project an assignment. You first create a project within this space and populate it with files, packages, and code that you want students to access. Note- administrators and moderators can edit other users’ projects, but they can only do this when the user has closed the project. If you are fortunate to have a teaching assistant, you can change their permission to moderator, giving them permission to view, manage, and edit all projects in the space. When you add users to the space, their default position is a contributor- they can create, manage, and edit their own projects. As an administrator, you can manage membership and can view, edit, and manage all projects in the space. You first set up a private space and determine who can access the space.
You can find a detailed and readable guide here! If you are not quite sure this is for you, below is a typical use case, containing only the essential details. Inviting and organizing to your private space is simple. This is critical for teaching! You decide who can access this workspace. Only you can access your project, but you can adjust permissions to let them be viewed and copied by other users. You store code, packages, and files here. The structure of RStudio Cloud is as follows:
If a student has a problem, you can check on their project and even make fixes from your computer (with some restrictions)! This means that you can load all necessary files and packages into a central location and distribute RStudio sessions to each of your students without worrying about differences in operating system, versioning differences, etc. The “central location” is a remote server hosted by RStudio that removes much of the headache from admin duties (and having to contact IT). It is a way for team members (students, teachers, etc.) to collaborate, using the same set of software managed from a central location that the administrator, i.e. the teacher, has control over. RStudio Cloud allows teams to manage R projects in a common space.
Luckily RStudio, the company behind the popular interactive development environment, has a strong, free(!) solution. The less setup and maintenance, the better. This is especially true in the current remote learning environment. For example, the time to set up programming exercises, troubleshoot technical issues, and follow progress can quickly eat away at time you as an instructor would probably like to spend covering course material. Efficiently integrating the language into a course can be difficult. The R programming language is a powerful analytical tool that is commonly taught alongside applied fields like statistics, ecology, finance, and more.
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