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A Mobile App for Exploring Chemical Molecules: Machine Learning-Powered Handwritten Compound Identification and 3D Visualization

Authors:
Luiza Souza
Pedro Ceccon
Silvana Alves
Raphael Kitahara

Keywords: Chemistry; education; machine learning; mobile app; CoreML.

Abstract:
The study of Chemistry is part of the mandatory school curriculum in Brazilian basic education and is considered by students to be a difficult subject to understand and abstract, generating resistance in learning, assimilation of concepts, and applicability in everyday life. As an experimental science, laboratory practice has contributed to students' learning. However, it is not always possible to carry out experiments, as many schools do not have the necessary physical requirements or for classes that are taught online. This article presents the development of a mobile application that uses machine learning to improve the process of teaching chemistry, making it possible to identify hand-drawn molecules and display 3D virtual correspondents, showing the structure of the element as well as information that relates it to everyday life.

Pages: 31 to 34

Copyright: Copyright (c) IARIA, 2024

Publication date: March 10, 2024

Published in: conference

ISSN: 2308-3913

ISBN: 978-1-68558-140-4

Location: Athens, Greece

Dates: from March 10, 2024 to March 14, 2024