Interactive Python Notebooks for Physical Chemistry

Chemistry simulations using interactive graphic user interfaces (GUIs) represent uniquely effective and safe tools to support multidimensional learning. Computer literacy and coding skills have become increasingly important in the chemical sciences. In response to both of these facts, a series of Ju...

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Bibliographic Details
Published in:Journal of chemical education 2023-02, Vol.100 (2), p.933-940
Main Authors: Bravenec, Ardith D., Ward, Karen D.
Format: Article
Language:English
Subjects:
Boltzmann distribution
Chemistry
College students
Colleges & universities
Computer graphics
Computer programming
Data analysis
Digital literacy
Exact solutions
Graphical user interface
Human-computer interaction
Laboratories
Modules
Pandemics
Physical chemistry
Programming languages
Python
Science activities
Simulation
Skills
Students
Undergraduate Students
Undergraduate study
User interface
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Description
Summary:Chemistry simulations using interactive graphic user interfaces (GUIs) represent uniquely effective and safe tools to support multidimensional learning. Computer literacy and coding skills have become increasingly important in the chemical sciences. In response to both of these facts, a series of Jupyter notebooks hosted on Google Colaboratory were developed for undergraduate students enrolled in physical chemistry. These modules were developed for use during the COVID-19 pandemic when Millsaps College courses were virtual and only virtual or online laboratories could be used. These interactive exercises employ the Python programming language to explore a variety of chemical problems related to kinetics, the Maxwell–Boltzmann distribution, numerical versus analytical solutions, and real-world application of concepts. All of the modules are available for download from GitHub (https://github.com/Abravene/Python-Notebooks-for-Physical-Chemistry). Accessibility was prioritized, and students were assumed to have no prior programming experience; the notebooks are cost-free and browser-based. Students were guided to use widgets to build interactive GUIs that provide dynamic representations, immediate access to multiple investigations, and interaction with key variables. To evaluate the perceived effectiveness of this introduction to Python programming, participants were surveyed at the beginning and end of the course to gauge their interest in pursuing programming and data analysis skills and how they viewed the importance of programming and data analysis for their future careers. Student reactions were generally positive and showed increased interest in programming and its importance in their futures, so these notebooks will be incorporated into the in-person laboratory in the future.
ISSN:0021-9584
1938-1328
DOI:10.1021/acs.jchemed.2c00665