Physical chemistry challenges students to translate concepts among various representations. For example, the harmonic oscillator may be described simultaneously using text, symbols, numbers, and graphs. Here we present one tool, Jupyter notebooks, to enhance students’ math literacy and their ability to switch among representations. Each notebook includes conceptual, mathematical, and programming learning objectives; embedded in the notebook are guided inquiry questions supporting pre-written Python code cells. Students solve equations, calculate solutions, and predict the appearance of graphs before running a specified Python code cell to get immediate feedback on their prediction. Students complete these notebooks while working in teams in a classroom with an instructor facilitating their work. Initially, we ask students to interpret and alter rather than write original code so that they focus on connecting the meaning of constants and variables in a formula to the graphical or diagrammatic output. As student confidence with coding improves, we provide structured opportunities for students to generate their own code. We discuss our choice of Python, Jupyter notebooks, and the Google Colaboratory environment. We will describe examples of how the notebooks can help students prepare for and practice content across the physical chemistry curriculum, and we will present student responses to these notebooks. Some examples of students’ adaptation of Jupyter notebook codes for final project assignments will also be shared.

Enhancing student engagement with mathematical concepts in physical chemistry using Python and Jupyter notebooks

ACS Fall 2021

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