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: 09 Oct 2025 02:14
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Author:
Derri J. Hughes
Author:
Sam C. Perry
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