🔨 Tools for Integrating Data Science in the Introductory and Intermediate Statistics Classroom

# 🔨 Tools for Integrating Data Science in the Introductory and Intermediate Statistics Classroom
## <br> 🔗 <a href="http://bit.ly/tools4ds">http://bit.ly/tools4ds</a>
### <br> 🌈 Dr. Allison Theobold <br> 🎲 Dr. Kelly Bodwin
### February 19, 2021

---

layout: true
  
<div class="my-footer">
<span>
<a href="http://bit.ly/tools4ds" target="_blank"><b>http://bit.ly/tools4ds</b></a> - Dr. Allison Theobold & Dr. Kelly Bodwin
</span>
</div> 
---

.large[
- know R
- are familiar with R Markdown
- are interested in integrating R into your course(s)
]

---

.pull-left[
  .huge-text[Tools]
]
.pull-right[
.large[
1. At-home Install
2. RStudio Cloud
3. Shiny Apps
4. learnr Tutorials]
]

---

class:center, inverse

---

* Most of what you want to teach will work with older versions of R...

* ... but earlier than **R 3.4** is a problem.

* **Solution**:  Have students on old machines use RS Cloud.

---

---

<center> 
![](images/binaries.png)

---

Do you want to install from sources the package which needs compilation?

Do you want to install from **developer version** sources **as opposed to CRAN version** the package which needs compilation?

![](https://media1.giphy.com/media/8vUEXZA2me7vnuUvrs/200.gif)

---

```r
Error in loadNamespace(name) : there is no package called 'here'
```

```r
Error in library(here) : there is no package called 'here'
```
--

* This means that a dependency didn't auto-install like it should have.

* Why?

* No idea.  Just install the package directly

```r
install.packages("here")
```

---

```r
Error: package or namespace load failed for 'tidyverse' in loadNamespace(j <-
i[[1L]], c(lib.loc, .libPaths()), versionCheck = vI[[j]]): namespace 'tibble' 
2.1.3 is already loaded, but >= 3.0.0 is required
```

This means you're trying to update a package that's in use!

Clear out the **environment**, including "hidden objects"

Close other R/RStudio windows.

Try to install again.

---

Things I have seen students do...

* Download a dataset to a random folder, expect it to be read into R automatically.

* Never **save** or **knit** their R Markdown file.  Lose everything when something crashes.

* Re-download the lab every time they want to work on it, open it from their downloads folder, copy paste code from a Google Doc.

* Re-download R or RStudio every time they want to open it.

---

* Using a Studio computer means students taking exams out of their comfort zone...

* ... but troubleshooting individual laptops during an exam is impossible!

* Not all students can afford the most powerful computer.

* Not all students have a laptop computer they can bring to class.

---

class:center, inverse

---

- Install R
- Install RStudio
- Install the following packages:
  - rmarkdown
  - tidyverse 
  - ...
- Load these packages
- Install git
- Install MiKteX
]

- Go to rstudio.cloud
- Log in

```r
>hello R!
```
]

.footnote[
.small[
__*__ Çetinkaya-Rundel, Mine. "Teaching R online with RStudio Cloud." [RStudio Webinar](https://rstudio.com/resources/webinars/teaching-r-online-with-rstudio-cloud/). 
]
]

---

## What is RStudio Cloud?

.pull-right-wide[
.large[We created [**RStudio Cloud**](https://rstudio.cloud/) to make it easy for professionals, hobbyists, trainers, teachers, and students to do, share, teach, and learn data science using R.]
]

---

background-image: url(images/rstudio-annotated.jpg)
background-position: center
background-repeat: no-repeat
background-size: 800px
class: middle

---

background-image: url(images/cloud-annotated.jpg)
background-position: center
background-repeat: no-repeat
background-size: 800px
class: middle

---

## Workspaces

---

## Projects

.pull-left[
</br>
A new project in RStudio Cloud
<img src="images/cloud-project.jpg" width="120%" style="display: block; margin: auto;" />
]

.pull-right[
</br>
is a new project in RStudio IDE
<img src="images/rstudio-project.jpg" width="90%" style="display: block; margin: auto;" />
]

---

## Sharing Options

</br>

- Option 1: Share a single project
--

- Option 2: Invite users to a workspace (presumably with many projects)

---

</center>

</br>

- Students land directly in a project upon login
- Works well for workshops where all work will be completed in a single project
- Also great for sharing code in general, e.g. collaboration, reprexes, etc.
]

.pull-right[
### Not so good...
<img src="images/cloud-copy.png" width="60%" style="display: block; margin: auto;" />
- Students need to remember to make a copy of the project (which means you need to remember to remind them!)
- You can't keep track which students started their assignment
- You can't easily peek into student projects
]

---

</center>

</br>

### Good!

- Base projects with desired packages installed
- Assignments -- no more "make a copy of the project before starting work"
- Peek into students’ projects
]

- Students land in the workspace, may need to provide instructions for the next steps
- Git config for each project can get tedious and doesn't reflect realistic practice
]

---

.pull-left[
<img src="images/pricing-free.png" width="836" height="150%" style="display: block; margin: auto;" />

</br>

<img src="images/pricing-organization.png" width="150%" style="display: block; margin: auto;" />
]

</br>
</br>

<img src="images/pricing-instructor.png" width="150%" style="display: block; margin: auto;" />
]

---

class:center, inverse

---

---

* Students get experience with code without typing code

* Gives them an easy "copy-paste" resource

* No need to install or interact with R/RStudio

]

* Apps need to be hosted somewhere

* Many students using app at once = high computing demand

* Hard to create (for now)

]

---

</br>
</br>

---

* R package to create your own exercises

*  Distribute exercises to students in package form

*  More info: https://rstudio.github.io/learnr/publishing.html

---

```r
penguins %>%
  filter(bill_length_mm > 5) %>%
  ggplot(aes(x  = {quant_var}, fill = {cat_var})) +
  geom_histogram()
```

```r
textInput("quant_var", 
          "What quantitative variable?")

textInput("cat_var", 
          "What categorical variable?")
```

```r
decorate_shiny("plot1") %>%
  shindig("renderPlot")
```

```r
plotOutput("plot1") 
```

---

class:center, inverse

---

## 📦 learnr

- **learnr** is an R package that makes it easy to create interactive tutorials from R Markdown documents.

- Tutorials can include:
  - Narrative, figures, illustrations, and equations
  - Code exercises (R code chunks that users can edit and execute directly)
  - Multiple choice questions
  - Videos (YouTube, Vimeo)
  - Interactive Shiny components

- learnr is on CRAN

```r
install.packages("learnr")
```

---

background-image: url(images/learnr.png)
background-position: center
background-repeat: no-repeat
background-size: 1000px
class: middle

---

[**`[code]`**](https://github.com/rstudio/learnr/blob/master/inst/tutorials/ex-data-filter/ex-data-filter.Rmd)
]

---

class:center

</br>

---

## YAML

Start with a YAML, just like in R Markdown:

```r
---
title: "Starting with Data"
output: 
  learnr::tutorial:
    progressive: true
    allow_skip: true
runtime: shiny_prerendered
---
```

1. Create a new RMarkdown file
2. Select from Template
3. Choose the Interactive Tutorial template from `learnr`
4. Start editing!

---

## Narrative

- R Markdown style section and subsection headings with `##`, `###`, etc.
- Text, figures, illustrations, and equations.
- Videos: supported services include YouTube and Vimeo

---

## Multiple choice questions

```r
quiz(
  question("What position is the letter A in the english alphabet?",
    answer("8"),
    answer("14"),
    answer("1", correct = TRUE),
    answer("23"),
    incorrect = "See [here](https://en.wikipedia.org/wiki/English_alphabet) and try again.",
    allow_retry = TRUE
  ),

question("Where are you right now? (select ALL that apply)",
    answer("Planet Earth", correct = TRUE),
    answer("Pluto"),
    answer("At a computing device", correct = TRUE),
    answer("In the Milky Way", correct = TRUE),
    incorrect = paste0("Incorrect. You're on Earth, ",
                       "in the Milky Way, at a computer.")
  )
)
```

---

## Code exercises - rendered

</br>
</br>

---

## Code exercises - code

---

## Code exercises - solution

---

- Deploy on
  - shinyapps.io (variety of pricing plans available)
  - RStudio Connect (free for academic use, requires setup)

- Essential reading:

- [Publishing learnr Tutorials on shinyapps.io](https://cran.r-project.org/web/packages/learnr/vignettes/shinyapps-publishing.html) by Angela Li
  - [Teach R with learnr: a powerful tool for remote teaching](https://education.rstudio.com/blog/2020/05/learnr-for-remote/) by Allison Horst
  - See the [publishing instructions](https://rstudio.github.io/learnr/publishing.html) on the learnr website for step-by-step instructions

---

---

# What are my resources?

* Does your university have server time for hosting `learnr`/`shindig` tutorials?

* If not, does your university have funding sources to host these things elsewhere?  (e.g. shinyapps.io)

* Can you acquire funding for RStudio Cloud?  Can you charge students to use it?

* How much do **you** enjoy creating/teaching with R resources?

---

# What are my learning objectives?

* If **learning R** is one of them...

...students should probably have a native install!

* If **understanding how statisticians use code** is one of them ...

... consider `shindig` tutorials, `learnr` tutorials with pre-supplied code, or RS Cloud.

* If **software is not a learning objective**...

... consider using R as a back-end only, to make your own life easier.

---

]

]