Celebrating our 100th R exercise set

[This article was first published on R-exercises, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Yesterday we published our 100th set of exercises on R-exercises. Kudos and many thanks to Avi, Maria Elisa, Euthymios, Francisco, Imtiaz, John, Karolis, Mary Anne, Matteo, Miodrag, Paritosh, Sammy, Siva, Vasileios, and Walter for contributing so much great material to practice R programming! Even more thanks to Onno, who is working (largely) behind the scenes to get everything working smoothly.

I thought perhaps this would be a good time to share some thoughts on the ideas behind the site, and how to proceed from this point onward. The main idea is pretty simple: it helps to practice if you want to learn R programming.

The two problems we’re trying to solve

Although the idea itself is simple, for many people, and perhaps you as well, following up on this idea is a challenge. For example, practicing R programming requires a certain task that has to be completed, a solution to an analytical problem that has to be found, or broader goal definition. Without this, we would just be typing random R syntax, or copy-paste code we found somewhere on the web, which will contribute little to improving our R skills. The main problem R-exercises is trying to solve is how to specify these tasks, problems and goals in a useful, creative and structured way. The exercise sets are our (current) solution to this problem.

But there’s a second challenge for those who want to practice: Staying focused. Live throws many distractions at us and while you perhaps found some interesting problems to practice your R skills, sooner or later practicing fades away when more urgent matters pop up. So, the second problem R-exercises is trying to solve is how to practice in a focused, persistent way. Offering new exercises on a daily basis, rather than one-time communication (e.g. a book or course) is our solution to this second problem.

Filling a gap in existing solutions

Is there a need for a site filled with exercises? There is an enormous amount of educational material on R available already. Our Course Finder directory includes 140 R courses, offered on 17 different platforms. Many universities teach R as part of their methods/statistics course programs. There are plenty of books on R. A search for “tutorial” on blog aggregator R-bloggers, reveals 1783 articles. And then there’s Youtube. It seems, with so much material, gaps are unlikely. But are they?

Going back to the two challenges we just described, we think what we’re offering is complementary to courses, books, classes and tutorials. Because the focus of most courses, books, classes and tutorials is on explaining/demonstrating things instead of practicing (the first challenge). And their focus is temporary, not necessarily persistent (the second challenge). It’s gone after you completed the course, read the book or watched the video tutorial.

In their excellent book “Make it stick”, Roediger and McDaniel explain that many of our intuitive approaches to learning (e.g. rereading a text) are unproductive. Instead they advise: “One of the best habits a learner can instill in herself is regular self-quizzing to recalibrate her understanding of what she does and does not know.” From this perspective, R-exercises can help you to recalibrate your understanding of what you know and don’t know about R.

The next 100 sets

We’re committed to keep expanding R-exercises, and adding more exercise sets. A while ago we started to differentiate sets in terms of difficulty (beginner, intermediate and advanced), an idea that many readers seemed to like when we proposed it. Recently we started to include information about online courses directly related to the exercises in a set, so for those who want to learn more, it’s easy to find a relevant course quickly.

Another idea we have is to offer premium (paid) memberships, with access to more extensive learning materials related to each exercise set. We’d actually love to hear your suggestions on how we can improve and expand R-exercises. What would you like to see on the site in 2017?

To leave a comment for the author, please follow the link and comment on their blog: R-exercises.

R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.