Building an Interactive Tutorial Website for R and Statistics
By Jiena Gu McLellan, Beef Cattle Institute, Kansas State University
Figure 1. Screenshot of a Basic Statistics and Plotting with R Tutorial
Can educators create an interactive tutorial website without knowledge of web programming? Can students learn programming using a tutorial website without downloading or installing any software? The learnr R package (Instruction link: https://rstudio.github.io/learnr/ ) provides answers to these questions and more (Schloerke, Allaire, & Borges, 2018). This article introduces the learnr package from a different perspective.
Traditionally, a beginner learns new programming languages by textbook, tutorial videos and exercises or homework, which has a steep learning curve. A challenge of these traditional educational methods is that students cannot have instant output without installing software and understanding fundamental command lines when practicing coding. This this study mode, students might lose patience or motivation. Therefore, there is a need for an interactive tutorial website that can serve as a virtual tutor and give students instant output or answers. A self-explanatory interactive website for online education provides flexibility and has several additional benefits:
- No download or install: One of big obstacles for a beginner to learn a new programming language is to download and install the software first, which might cause confusion since in general, software in different versions or run in different operating systems might have different requirements. Using an interactive website does not require any preparation before running codes. So simply run the R code and students will get the results. With easy-to-follow instructions and immediate outputs, anyone can easily grasp coding from zero.
- Instant outputs: Students are more comfortable engaging in personalized learning with immediate output or answers. Students with hearing or speech impairments; social anxiety, or those needing more time to organize thoughts would prefer to attend online education and practice what they learned in a timely fashion. An interactive tutorial website might be a great help to practice programming by simply twisting the demo code to view the outputs, which transcends time, geographic, and other barriers of higher education.
- Document a learning progress: As an online tutorial website, it is important to record each student’s learning progress and achievements to heighten motivation. The coding tutorial website using learnr documents each student’s learning progress (exercise input and output, answers to questions, etc.) in their web browser. When students revisit the website they can track their individual progress.
From an educators’ perspective, it is easy to develop a website using learnr even with zero web development skills because learnr makes it easy to turn any R Markdown document into an interactive tutorial (Allaire, Xie, McPherson, Luraschi, Ushey, Atkins, Wickham, Cheng, & Chang, 2018). Tutorials consist of content along with interactive components that will reinforce students’ understanding. Educators can develop narratives, code exercise (R code chunks), multiple choice quizzes, insert videos or interactive Shiny apps for the website.
A demo interactive tutorial website is available from https://appforiarteam.shinyapps.io/PlayR/#section-about. This was built with the learnr package. There are four chapters introducing basic statistics and plotting: static data visualization, interactive data visualization, data manipulation and data modeling. In each chapter, each demo code is followed by a “sandbox” section for students to play with the code and view output. There also are quizzes to reinforce the understanding. The introduction video is available from: https://www.youtube.com/watch?v=62iX1Wh8AC4.
Online education has evolved as a cost effective and convenient alternative to face to face instruction. Building an interactive online tutorial website helps students understand and practice their programming skills in a timely fashion.
Allaire, JJ, Xie, Y., McPherson, J., Luraschi, J., Ushey, K., Atkins, A., Wickham, H., Cheng, J. & Chang, W. (2018). rmarkdown: Dynamic Documents for R. R package version 1.10. https://CRAN.R-project.org/package=rmarkdown
Schloerke, B., Allaire, J.J., & Borges, B. (2018). learnr: Interactive Tutorials for R. R package version 0.9.2.1. https://CRAN.R-project.org/package=learnr
About the Author
Jiena G. McLellan is the Project Coordinator/ Programmer Analyst at the Beef Cattle Institute (K-State Vet Med) and an instructor in the K-State College of Business. Originally from the Guangdong Province in China, she came to K-State with a degree in bioengineering. She received her MS degree in statistics and a Graduate Certificate of Big Data Analytics from Kansas State University after finishing a Graduate Certificate in Public Health. She is interested in storytelling with big data using various tools such as data visualization and applied statistics. Her expertise is in data analytics, applied statistics, and creating interactive applications with automatic reporting systems. At the Beef Cattle Institute (BCI), she works with teams on various topics, including developing dynamic reporting dashboards linked to agriculture research.
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