Hands-on VR Approach to Teach 3D Spatial Concepts of Molecular Reactions

Molecules require a certain relative orientation and proximity to react with each other, a concept that is often difficult for beginners to grasp. We present a virtual reality system designed to help users learn about chemistry reactions with hands-on manipulation and interaction with molecules in a simulated lab environment. Our system emphasizes intuitive molecular interactions over a full molecular dynamics simulation, minimizing erratic molecule motion and sensitivity, in order to help users better understand spatial requirements underlying chemistry reactions. The system uses a novel approach to mapping reagent and product molecules to facilitate reaction detection and animation. We propose to evaluate our system by training a machine learning classifier on motion features (head, hand, and eye) to estimate user understanding of chemistry reactions, thereby enabling adaptive system feedback, such as providing visual hints.

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Publication Details

Published
2024-09-13
DOI
https://doi.org/10.1145/3677386.3688904
Primary Topic
Various Chemistry Research Topics
Type
article
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article

Hands-on VR Approach to Teach 3D Spatial Concepts of Molecular Reactions

Christoph W. Borst, David M. Broussard, Adil Khokhar
Various Chemistry Research Topics
article

Hands-on VR Approach to Teach 3D Spatial Concepts of Molecular Reactions

Christoph W. Borst, David M. Broussard, Adil Khokhar
article en

Abstract

Molecules require a certain relative orientation and proximity to react with each other, a concept that is often difficult for beginners to grasp. We present a virtual reality system designed to help users learn about chemistry reactions with hands-on manipulation and interaction with molecules in a simulated lab environment. Our system emphasizes intuitive molecular interactions over a full molecular dynamics simulation, minimizing erratic molecule motion and sensitivity, in order to help users better understand spatial requirements underlying chemistry reactions. The system uses a novel approach to mapping reagent and product molecules to facilitate reaction detection and animation. We propose to evaluate our system by training a machine learning classifier on motion features (head, hand, and eye) to estimate user understanding of chemistry reactions, thereby enabling adaptive system feedback, such as providing visual hints.

University of Louisiana at Lafayette (US)
Openalex Percentile: Top 82%
Various Chemistry Research Topics
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Hands-on VR Approach to Teach 3D Spatial Concepts of Molecular Reactions — Christoph W. Borst, David M. Broussard, et al. · (2024) | TGRS Research Map | TGRS