Computer programming skills are useful to chemists in academic research as well as in industrial careers. While I am not a computational chemist, I introduced chemistry and biochemistry majors at Santa Clara University, a mid-sized regional university located in Silicon Valley, to Python programming in two upper-division physical chemistry courses. I used computational-guided inquiry (CGI) exercises, written by my collaborators and co-authors, Dr. Steven Neshyba at University of Puget Sound and Dr. Tim Guasco at Millikin University, to make physical chemistry more accessible and relevant to “real world” research problems. CGIs helped students learn computer programming skills alongside chemical concepts. Python code in a Jupyter Notebook platform featured written documentation and detailed explanations in parallel with executable code. Students used Python to visualize equations and concepts that were otherwise abstract and difficult to grasp. Examples of a typical CGI assignment, graphical output generated by students, and student responses to “Pause for Analysis” questions and post-class activities will be presented. Since I did not have a dedicated lab section associated with my physical chemistry courses, I implemented CGIs by using flipped-classroom videos to supplement the lecture material that students “missed” when I incorporated active learning exercises. Educational outcomes of CGIs included improved quantitative skills, an introductory coding experience, and increased enthusiasm for "real world" problem solving.

Implementing python-based computational guided inquiry exercises in thermodynamics and quantum chemistry courses

2019 Fall National Meeting

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