R Shiny in the Classroom

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Three years ago, while I was teaching elementary statistics at a community college in California, finally fed up with the cost and deficiencies of the technology foisted on students by proprietary textbook sites and math homework websites, I decided to create a suite of R Shiny applications which would provide the students with a free computing resource to accomplish three things. It would:

(1) give students the means to perform all basic statistical computations associated with an elementary statistics course. In particular, it would allow students to perform tests and compute confidence interval constructions beginning either raw data or, as is often the case in textbook problems, working from summary statistics,

(2) provide data simulations and interactive demonstrations to illustrate fundamental statistical concepts, and

(3) assist students in deciding what sort of statistical tool/computation is appropriate to use in a given situation through the use of an ‘expert system’ front end.

As matters eventuated, I ended up quitting my teaching and going on a very long bike ride across Western Europe before I could implement my idea (a different and perhaps more interesting tale). But I finally did do so when I returned to the US, deploying my apps using an R Shiny server deployed on an NGINX webserver on a cloud instance of Ubuntu 16.04 which I initiated specifically for the purpose. The result is here:

http://104.236.178.75:3838/sort/sorta/ Many of the apps could certainly be refined and stabilized. I am completely self-educated in all things computing, in particular as regards R programming and R Shiny app development. These apps were written as learning projects for me as much as they were intended to address the three goals enumerated above. But as an outgrowth of writing the statistics apps, it became clear to me that Shiny apps are widely adaptable to a host of pedagogical purposes, really across disciplines, although, because of the nature of R, applications for use in the teaching of math, statistics, and the sciences come first to mind.

I went on to create a few dozen Shiny apps for non-statistical but mostly pedagogical applications. Those of vaguely mathematical theme are here


https://www.apclam.com/shinymath.html


whereas an over-arching point of access to all such apps is here

https://www.apclam.com/shinydir.html .

My point here is not so much to draw attention to the apps which I have developed and deployed which, as I freely admit are rudimentary in many respects, as rather to call the attention of deans, department chairwomen and chairmen, and faculty members at high schools, colleges and univesities to the opportunity to use R Shiny to liberate curricula, and budgets, from the strictures imposed by propriety websites and software served up by textbook publishers and various other academic hangers-on. Here some key points militating in favor of doing so:

(1) The ‘pro’ version of the R Shiny server is available to academic institutions at no to very low cost.

(2) The learning curve involved in writing and deploying R Shiny apps is not steep. For people who already have experience writing R scripts it can be fairly characterized as easy. Even for people who have limited programming background, it is a manageable task, particularly if given institutional guidance in the form of workshops or training materials.

(3) Web activities can be created which are tuned to the very specific needs of one’s own curriculum, institution and even classroom. In particular, R’s extensive graphics capabilities in its base graphics package can be leveraged to create learning tools which integrate numerical, symbolically and graphical approaches to the demonstration of and interaction with key concepts.

(4) Developing and deploying R Shiny apps gives faculty and staff a constructive outlet for creativity which provides opportunities for collaboration within and across disciplines and results in a tangible (OK, internet ‘tangible’) product which can be used by students and faculty throughout the world.

I would be happy to share my experiences in this realm to help anyone or any institution pursue this path. I think the possibilies in this direction are almost without limit. Feel free to email me at [email protected].

Published by

Richard Gayle

Teaching of math and statistics for many years. PhD mathematics, Oregon, 1993. NSF-sponsored post-doc biostatistics, Minnesota, 2002-3. 18 year R user, 3 year R Shiny app developer

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