learnr

Barret Schloerke: Lessons Learned Testing 2500+ Shiny Apps Every Day

About the Talk: The Shiny team tests 2500+ different combinations of Shiny Applications, R versions, and operating systems to verify no feature regressions occur within the bleeding edge of the Shiny-verse. Over the past few years, we have learned a few lessons to keep our tests robust and honest. There is a non-zero chance that a test failure is not your fault. When working with CI systems, external influences such as installation failures or slower computing power will prevent tests from executing properly. A picture is worth a thousand tests but visual testing is known to have a non-zero false-positive rate. To address this, we have utilized threshold based image comparisons for flaky tests. We have found that it is best to test the minimal amount of content where possible. Changes in App package dependencies can produce unintended changes in expected outputs. These hard learned lessons have reduced unreliable test results allowing the Shiny team to quickly respond to feature regressions.

Speaker’s bio: Dr. Barret Schloerke is a Software Engineer at Posit. He currently develops and maintains many R packages in the Shiny ecosystem at RStudio including shiny, reactlog, plumber, learnr, leaflet, and shinyloadtest. Dr. Schloerke received his PhD in Statistics from Purdue University under the direction of Dr. Ryan Hafen and Dr. William Cleveland, specializing in Large Data Visualization

Barret Schloerke, Shiny Team

Lucy D’Agostino McGowan | Designing Randomized Studies using Shiny | RStudio

This talk will walk through building a self-contained randomized study using Shiny and learnr modules. We will discuss building informed consent, the randomization process, demographic surveys, and R-based studies into a single online framework to allow users to seamlessly enroll and participate in randomized studies via a single URL. The talk will include both practical recommendations as well as technical code snippets.

About Lucy: Lucy D’Agostino McGowan is an assistant professor of statistics at Wake Forest University, where she leads the WFU Data Science Lab. Her research focuses on causal inference, human-data interaction, and statistical communication

Mine Çetinkaya-Rundel | Feedback at scale | RStudio

As enrollments in statistics and data science courses grow and as these courses become more computational, educators are faced with an interesting challenge – providing timely and meaningful feedback, particularly with online delivery of courses. The simplest solution is using assignments that are easier to auto-grade, e.g. multiple-choice questions, simplistic coding exercises, but it is impossible to assess mastery of the entire data science cycle using only these types of exercises. In this talk I will discuss writing effective learnr exercises, providing useful and motivating feedback with gradethis, distributing them at scale online and as an R package, and collecting student data for formative assessment with learnrhash.

About Mine: Mine Çetinkaya-Rundel is Professional Educator and Data Scientist at RStudio as well as Senior Lecturer in the School of Mathematics at University of Edinburgh (on leave from Department of Statistical Science at Duke University). Mine’s work focuses on innovation in statistics and data science pedagogy, with an emphasis on computing, reproducible research, student-centered learning, and open-source education as well as pedagogical approaches for enhancing retention of women and under-represented minorities in STEM. Mine works on integrating computation into the undergraduate statistics curriculum, using reproducible research methodologies and analysis of real and complex datasets. She also organizes ASA DataFest and works on the OpenIntro project. She is also the creator and maintainer of datasciencebox.org and she teaches the popular Statistics with R MOOC on Coursera

Mine Çetinkaya-Rundel

Yanina Bellini Saibene | On programming, teaching, and building tutorials with learnr | RStudio

Full title: On programming, teaching, and building interactive tutorials with learnr

Teaching R is part of my activities as a community organizer, an RStudio Certified Instructor, a conference chair, and a researcher. Since 2019, I use the learnr package to generate interactive tutorials to teach R synchronously and asynchronously. The addition of the Tutorials panel in RStudio IDE and the need for virtual classes made the use of this package even more interesting. In this talk, I will tell you how to generate interactive tutorials, how to add pedagogical tools to them, what other packages you can use with {learnr} and show multilingual examples.

About Yanina: Yanina Bellini Saibene is a researcher at INTA (National Institute of Agricultural Technology) dedicated to applying data science to the agricultural sector and a professor in several regional specializations about Digital Agriculture and Data Analysis. Yanina is formally trained as a Licenciate in Information System with a Master degree in Data Mining and Knowledge Management. She is an active member of the R Community as an R-Ladies organizer and part of the R-Ladies Global Team. She also is a co-founder and co-chair of LatinR and part of the organizing team of useR!2020 and user!2021 (co-chair). She is also co-founder of MetaDocencia, a open, free, volunteer-lead, not-for-profit educational organization and part of the teams that translate educational and technical material to Spanish

Advanced R Markdown 2-day Workshop - rstudio::conf(2019L)

What is the 2-day Advanced R Markdown Workshop? That’s a great question, I’m glad you asked.

This is a two-day hands-on workshop based on the book “R Markdown: The Definitive Guide”.

This workshop is designed for those who want to take their R Markdown skills to the next level. We’ll talk about many low-level details in the rmarkdown package and the whole R Markdown ecosystem. The two goals of this workshop are: 1) learn how to fully customize R Markdown output (HTML, LaTeX/PDF, Word, and PowerPoint); and 2) learn more about existing R Markdown extensions in the ecosystem, such as flexdashboard, bookdown, blogdown, pkgdown, xaringan, rticles, and learnr. We will also talk about how to use or develop new language engines (languages that are not R), how to develop HTML widgets, and integrate Shiny with R Markdown.

You should take this workshop if you have experience programming in R and want to learn how to take advantage of the amazing breadth and depth of R Markdown. You’ll get the most from it if you enjoy learning how R Markdown works under the hood (which will involve reading some source code), and are seriously interested in hacking (playing) with HTML, JavaScript, CSS, LaTeX, and command-line tools. We will give minimal tutorials on these languages and tools in the workshop, but it may be easier for you to keep pace with the instructor if you already know them before.

This workshop is led by Yihui Xie, Software Engineer and Data Scientist at RStudio. Yihui is the main author of the open-source knitr package for reproducible research and dynamic report generation. He has also created and co-authored several other R packages, including rmarkdown, bookdown, blogdown, xaringan, tinytex, DT, shiny, and leaflet. He has authored and co-authored four books: Dynamic Documents with R and knitr, bookdown: Authoring Books and Technical Documents with R Markdown, blogdown: Creating Websites with R Markdown, and R Markdown: The Definitive Guide.

Speakers: Yihui Xie and Alison Hill with guest lecturers Jiena Gu and Hao Zhu