Experience from running R workshops in developing countries

Having run a couple of workshops introducing R in developing countries, I offer four pieces of advice:

1. Don’t rely on the internet. The internet reaches everywhere but what may be adequate for light use by a single user quickly crumbles when large numbers try to make downloads simultaneously. We anticipated this would be a problem and came equipped with R and Rstudio on many cheap memory sticks but this is not sufficient. For example, try installing the Tidyverse and knitting an R markdown document. You will find this requires installing several packages with multiple dependencies. You’ve probably forgotten the multiple packages, pieces of software and configurations you did to make things work on your own machine. It was all so easy when you had a good internet connection. Find an old laptop with a fresh OS install and disconnect it from the internet. Discover what it takes to get it running on your R teaching materials and then you’ll be prepared. Purchase a local data SIM for that country so you can create a local WiFi hotspot. At least you’ll have a chance to access the internet in case of need (quite likely!). Also plan on a period of chaos at the beginning of the workshop to take care of the many install problems.
2. Tidyverse. R is difficult, particularly for users only familiar with GUI-based statistics software. A tidyverse-only approach greatly simplifies the range of syntax and commands that the workshop participants will need to understand. You can create exercises that they can successfully complete. The tidyverse is sufficiently powerful that you can perform a wide range of practically useful tasks. The participants will gain a feeling of accomplishment and some ability to use R for their own work. Soon enough they will also need to learn to use base R. But if you start with base R, the entry cost is much higher and some of your students will not make it.
3. Simplicity. This comes in two forms. Firstly, in countries where English is not the native language, you will find that most professional people (who are attending your workshop) know at least some English but that does not mean all of them are entirely fluent. In your presentation, speak slowly and enunciate your words clearly. Avoid colloquial expressions and figures of speech. Do not use complex words. As a native speaker of English, you will find this difficult. Use written documentation to supplement your spoken presentation. Consider using a translator. Secondly, consider simplicity in your R presentation. It is tempting to include some cool R tricks but beginners won’t enjoy this. Stick to the basics and reduce complexity where possible.
4. Local Data. All too many expositions of R use overworn example datasets such as mtcars. Find some datasets from the country of the workshop. The participants will find this far more interesting and will suggest different ways to analyze the data. This will demonstrate how R can be used to turn data into knowledge.