The SpinDrops Didactics Framework: A Modular Toolbox for Creating Educational Content in Magnetic Resonance

The SpinDrops Didactics Framework (SDDF) is a built-in framework for the development of educational contents in the free software SpinDrops. SpinDrops was specifically designed for dynamically simulating and visualizing systems of coupled spins-1/2 in the context of nuclear magnetic resonance (NMR), yet it provides a vast range of tools and applications in an unguided manner, potentially overloading users who are to learn NMR spectroscopy. Previously, we introduced the digital SpinDrops Learning Environment (SDLE), engineered with the SDDF. This learning environment targeted the most relevant topics in liquid state 1H NMR spectroscopy, that is, precession, chemical shift, and scalar coupling. These are relevant concepts for chemists and other scientists when interpreting NMR spectra which were addressed by offering carefully designed interactive SDDF exercises. In the following, the SDDF is introduced from a detailed technological point of view. We show that the SDDF offers a fully modular toolbox which can be used to create highly interactive multifaceted exercises and learning units in a simple and easy-to-understand way. Our software particularly aims to enable teachers to design custom educational content which can be tailored to the teaching of magnetic resonance from school to expert level and can cover topics ranging from experimental applications of NMR in organic chemistry to quantum mechanical theory of magnetic resonance. The obtained exercises can be distributed to students and directly imported into SpinDrops.

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Publication Details

Journal
Journal of Chemical Education
Published
2025-06-11
DOI
https://doi.org/10.1021/acs.jchemed.5c00115
Citations
1
Primary Topic
Experimental Learning in Engineering
Type
article
Field-Weighted Citation Impact
1.14

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article

The SpinDrops Didactics Framework: A Modular Toolbox for Creating Educational Content in Magnetic Resonance

Steffen J. Glaser, Jenna Koenen, Dennis Huber, Dominik Diermann
1 citations
Journal of Chemical Education
Experimental Learning in Engineering
1.14
article

The SpinDrops Didactics Framework: A Modular Toolbox for Creating Educational Content in Magnetic Resonance

Steffen J. Glaser, Jenna Koenen, Dennis Huber, Dominik Diermann
article en
1 citations

Abstract

The SpinDrops Didactics Framework (SDDF) is a built-in framework for the development of educational contents in the free software SpinDrops. SpinDrops was specifically designed for dynamically simulating and visualizing systems of coupled spins-1/2 in the context of nuclear magnetic resonance (NMR), yet it provides a vast range of tools and applications in an unguided manner, potentially overloading users who are to learn NMR spectroscopy. Previously, we introduced the digital SpinDrops Learning Environment (SDLE), engineered with the SDDF. This learning environment targeted the most relevant topics in liquid state 1H NMR spectroscopy, that is, precession, chemical shift, and scalar coupling. These are relevant concepts for chemists and other scientists when interpreting NMR spectra which were addressed by offering carefully designed interactive SDDF exercises. In the following, the SDDF is introduced from a detailed technological point of view. We show that the SDDF offers a fully modular toolbox which can be used to create highly interactive multifaceted exercises and learning units in a simple and easy-to-understand way. Our software particularly aims to enable teachers to design custom educational content which can be tailored to the teaching of magnetic resonance from school to expert level and can cover topics ranging from experimental applications of NMR in organic chemistry to quantum mechanical theory of magnetic resonance. The obtained exercises can be distributed to students and directly imported into SpinDrops.

Journal of Chemical EducationVol. 102(7)
Munich Center for Quantum Science and Technology (DE), Technical University of Munich (DE)
Verband der Chemischen Industrie, Technische Universität München
Quality Education
Openalex Percentile: Top 19%
Experimental Learning in Engineering
1.14
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