Modular integration of Python programming in undergraduate physical chemistry experiments
Modular integration of Python programming in undergraduate physical chemistry experiments
Programming is a key transferable skill within the chemical sciences with applications supporting data acquisition, as a tool for chemical and spectroscopic analysis and as an environment for theoretical modeling. Of the many available programming languages, Python stands out due to its broad functionality and open-source structure. However, introducing any programming training to an undergraduate chemistry curriculum can be challenging due to students’ lack of previous experience and limited time in pre-existing curricula for dedicated training. Here, we present a modular approach to introducing undergraduate students to Python programming through a series of taught undergraduate physical chemistry laboratory experiments. Students are first provided with a carefully scaffolded approach to basic Python syntax before enhancing the student skill set through context-based learning integrated with practical chemistry challenges. In this way, we demonstrate how a modularly integrated approach can provide a complete introduction to Python programming regardless of previous experience and without needing dedicated training time.
Python programming, Curriculum design, Scaffolded learning, Active learning, Undergraduate experiments, Physical chemistry
4005-4016
Hughes, Derri J.
d6bbf37e-8579-4382-8215-59b64ce00fc7
Perry, Sam C.
8e204d86-4a9c-4a5d-9932-cf470174648e
19 August 2025
Hughes, Derri J.
d6bbf37e-8579-4382-8215-59b64ce00fc7
Perry, Sam C.
8e204d86-4a9c-4a5d-9932-cf470174648e
Hughes, Derri J. and Perry, Sam C.
(2025)
Modular integration of Python programming in undergraduate physical chemistry experiments.
Journal of Chemical Education, 102 (9), .
(doi:10.1021/acs.jchemed.5c00677).
Abstract
Programming is a key transferable skill within the chemical sciences with applications supporting data acquisition, as a tool for chemical and spectroscopic analysis and as an environment for theoretical modeling. Of the many available programming languages, Python stands out due to its broad functionality and open-source structure. However, introducing any programming training to an undergraduate chemistry curriculum can be challenging due to students’ lack of previous experience and limited time in pre-existing curricula for dedicated training. Here, we present a modular approach to introducing undergraduate students to Python programming through a series of taught undergraduate physical chemistry laboratory experiments. Students are first provided with a carefully scaffolded approach to basic Python syntax before enhancing the student skill set through context-based learning integrated with practical chemistry challenges. In this way, we demonstrate how a modularly integrated approach can provide a complete introduction to Python programming regardless of previous experience and without needing dedicated training time.
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modular-integration-of-python-programming-in-undergraduate-physical-chemistry-experiments
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Python in Chemistry Labs SI
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e-pub ahead of print date: 19 August 2025
Published date: 19 August 2025
Keywords:
Python programming, Curriculum design, Scaffolded learning, Active learning, Undergraduate experiments, Physical chemistry
Identifiers
Local EPrints ID: 505447
URI: http://eprints.soton.ac.uk/id/eprint/505447
ISSN: 0021-9584
PURE UUID: eb627824-4cb4-495e-b27b-b59f8d1ae001
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Date deposited: 08 Oct 2025 16:55
Last modified: 11 Feb 2026 03:06
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Author:
Derri J. Hughes
Author:
Sam C. Perry
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