Leonardo Baptista Universidade do Estado do Rio de Janeiro, Departamento de Química e Ambiental.
The present manuscript intends to propose using the Google Colab platform to teach and solve physical chemistry problems using Python computational language. Seven Jupyter notebooks were written and made available for the students via Google Colab supplementary material of the physical chemistry course of the chemical engineering course of the Technological Faculty of the Rio de Janeiro State University. These notebooks include several problems extracted from the course bibliography and solved with the use of Python language. The scripts show how the students can perform linear and polynomial regressions, fit math models to given data, perform numerical integration and plot creation using Python and its standards libraries. The Colab platform was chosen because it is free to use, does not require the installation, setup, and configuration of Python packages and their libraries in the students’ personal computers. It is a multiuser and collaborative environment, ideal for remote classes. The notebooks can be shared between instructor and students or between the students, which easy the communication and track of students’ progress. Indeed, this resource can be useful even after the end of the pandemic. This manuscript describes the platform, its advantages, how it was applied in our physical chemistry course, and the students’ feedback at the end of the term. All notebooks are available as Supplementary Material of the manuscript, translated from Portuguese to English since our course is entirely in Portuguese. I hope the material and experience shared in this manuscript can be helpful to chemistry instructors who intend to abroad their pedagogical methods to engage more students in the undergraduate courses.
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