Then open a new R Markdown file by selecting “File” / “New File” / “R Markdown” / “From Template”, then “Interactive Tutorial (learnr)”. Want to explore on your own? Install the learnr package. Learnr to teach mosaic at the JMM minicourse The tutorials were part of a pair of JMM 2019 minicourses. Importantly, Randy has also provided open access to the R source code used to create the learnr tutorial for mosaic. Randy Pruim set up a learnr tutorial Less Volume, More Creativity (screen shot below) that can get a student up and running quickly with the fundamentals of working with mosaic before the student moves to the RStudio environment. Your learnr lesson is experienced like an interactive section of a textbook that was custom-build by YOU. They can now be directed to a single webpage hosting your learnr lesson. Suddenly there are even fewer software applications to jump between for students.Īn R code file to run piece-wise in order to answer questions in a separate file, orĪ pre-built R Markdown file to work through by reading and adding code to answer questions (which might then be knit at the end), orĪ shiny app to play around with in order to answer questions within a separate document With learnr, instead of a single shiny application that you may have created for a particular activity, imagine building an entire lesson out as a series of sections/pages which inform students of new ideas and ask that they play around with R code, submit code, and answer questions… all using a single R Markdown document. The example above is the tip of the iceberg. In the example above you can see the section headings on the left, and the selected section’s content in the center which includes information and an area for code to be entered, run, and submitted. Alternatively, hosts shiny apps and learnr apps for free (with certain size and use limits). We’ll see how to combine code and text into a single R Markdown file, the perfect document format for automated reporting and reproducible research. If you have an RStudio server (see our recent blog on RStudio in the cloud), an RS Connect server can be set up in parallel. Using R Markdown you’ll be able to generate reports straight from your R code, documenting your work and its results as an HTML, pdf, slideshow, or Microsoft Word document. Note that as with any shiny app, the learnr activity needs a home in the cloud if it is to be shared across users. Each learnr tutorial is a shiny interactive document. With our two-part introduction to shiny last week ( part 1 and part 2), your excitement for learnr should be multiplicative. Videos (supported services include YouTube and Vimeo). Narrative, figures, illustrations, and equations.Ĭode exercises (R code chunks that users can edit and execute directly). Straight from Garrett Grolemund’s fantastic introduction to the package, tutorials can include any or all of the following: With this vehicle instructors can offer interactive tools to their students to allow them to explore datasets in use from the class, a textbook, or even collected themselves. Install.The learnr package makes it easy to turn any R Markdown document into an interactive tutorial. R Markdown is an easy-to-write plain text format for creating dynamic documents and reports. # Sets the local working directory location where you downloaded and saved the Ohio poverty dataset. Although you can do this in the Files and Packages tab in the lower right-hand corner of the Studio environment, you can hard-code these items in a chunk as follows: # Set the Working Directory and Install Needed Packages You learned in Lesson 2 that you should set your working directory and install the needed packages in the first chunk of the RMarkdown file. The symbols to denote a code chunk are ``` and ```. For a general tutorial by the R-studio team, see here: įor this lab, you can choose to use either an R-script or an R-Markdown document to complete this exercise, in whichever environment you are more comfortable.To get started, see Lesson 2 - markdown.When you run each of these, then the code runs below each chunk, so you can intersperse your analysis within your report itself. R-Markdown is another way to run code, where you essentially make an interactive report which includes "mini consoles" called code chunks. Most of you have likely been working in R-scripts where the code and results run in the console. As we discussed in Lab 2, there are two ways to enter code in R. You should already have installed R and RStudio from earlier lessons.
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