Over the past 28 days, I have written about tools, techniques, and strategies for teaching programming using evidence-based information.
Today, I want to share what a course build using all these looks like. So here are 3 open teaching materials that I developed for you to check and use:
1. Introduction to interactive tutorials
A 3-hour course to learn how to use {learnr} and {gradethis} packages for building interactive tutorials using R. Explore the learner personas definition, the syllabus, and the content presentation.
2. Remote sensing with R applied to agriculture
An intensive 6-hour course on the R language and the spatial ecosystem focused on the rgee package and its agricultural applications. In Spanish. Explore how the exercises are authentic tasks. The slides show that there is not much content because most of the teaching uses live coding.
3. Mentorship Training and Orientation. rOpenSci Champions Program
Training about mentoring and how to mentor for the rOpenSci Champions Program. Explore the Instructor notes, where I developed a detailed script for the instructor of this material, with different options of exercises according to the time you have to teach the content. Authentic tasks, shared note-taking, and teamwork-to-solve exercises are used as strategies in this course.
My course web page has many more examples; you can find material in English and Spanish and training from one-hour sessions to one semester long.