Maybe we don’t all have to reinvent the wheel…
There is a huge number of open education / online tutorials that teach earth and environmental data science skills. However, these lessons will quickly become obsolete as tools evolve. This blog is about why simply publishing a lesson online is not enough.
The idea of Open Education Resources (OER) and the field of earth and environmental sciences are not new. But the terms have become popular in recent years. While I only recently identified with these terms, i've been working in this space for years. Here I talk about how I discovered open education in the context of building online resources.
Open Education Resources (OER) referred to lessons and materials that are published online for anyone to use. Here I present a few lessons learned from my experiences.
Working in the diversity, equity, inclusion and accessibility space (DEIA) requires time, patience and lifelong learning. Here I present a few lessons learned from working with students & faculty at tribal & hispanic serving schools to support learning earth and environmental data science.
Undergraduate students at colleges serving underrepresented communities often don't have access to earth and environmental science data skills. Learn about a NSF award that built capacity to teach and learn data skills at hispanic and tribal serving colleges.
In this post I will discuss how to setup a build using GitHub actions that was created to test the earth-analytics-python conda environment on different operating systems. Testing supports building open science workflows as it ensures that the environment will run on Windows, Mac and Linux.
Teaching earth and environmental data science can be time consuming. Learn about what I learned when I tried to create an consistent Python environment that was easy for students to install. (and how this could help your science as well.
