Linking Research and Education

I am enthusiastic about the open-source, reproducible science movement. The ideal tool currently available for scientists is Jupyter, among a few others. Jupyter is also an excellent teaching tool. From this common ground, I want to connect research and education. Research results written in Jupyter can be easily converted into educational notebooks. These notebooks will include data, code, figures, and tables, allowing students to understand the content much more efficiently. Furthermore, because students can modify the code, they can experiment with their own ideas, creating a natural link to inquiry-based learning.

Many research areas in Earth and planetary sciences are intrinsically data-driven. We often handle very large datasets. Can we train our undergraduates and graduates to be fluent in handling large data? This will be an important educational contribution we can make.

(Photo below) 2019 AGU session on Linking Research and Education through Jupyter (from left to right: Fernando Perez, Rebecca Farrington, and Dan Shim)

Jupyter notebooks for PeakPo

github repo

Peakpo is a GUI application that can analyze large X-ray diffraction data sets. Like other GUI applications, it has a rigid structure and workflow. By examining the code used by PeakPo and the output files from PeakPo in a Jupyter notebook, you can customize the workflow and visualization of data files for a more personalized approach. The notebooks can also be used for teaching basic X-ray diffraction data processing in a classroom or tutorial setting.

Jupyter notebooks for Pytheos

github repo

In a series of notebooks, I demonstrate how Pytheos can be used for datasets related to equations of state. I found that it is much easier to start new modules with example notebooks rather than with a manual.

Jupyter notebooks for Planetary Materials Education

github repo

Earth scientists and planetary scientists have built large databases for research. Here, we demonstrate that such databases can also be a very powerful tool to teach not only planetary science but also coding and data science skills simultaneously. This initiative is still under development. The goal is to provide open-source teaching modules.