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UEC Int’l Mini-Conference No.54 81

Exploring Effective AI Applications in Teaching Molecular Structures for

Secondary Chemistry Education

Jordão MANUEL* and Kayoko YAMAMOTO
Joint Doctoral Program for Sustainability Research
The University of Electro-Communications, Tokyo University of Foreign Studies, Tokyo University of Agriculture and
Technology.
Tokyo, Japan

Keywords: Artificial Intelligence, Molecular Structures, Chemistry Education.

Abstract

The rapid evolution of artificial intelligence (AI) has opened new opportunities in education, particularly in enhancing
the teaching and learning of complex scientific concepts, such as molecular structures, in secondary chemistry
education. This study presents a scoping review of AI applications in this field, aiming to identify effective tools and
highlight current gaps. Through the analysis of 23 selected studies from databases such as Google Scholar and ERIC,
several trends were observed, including the use of virtual laboratories, molecular modelling, chatbots, and
personalized learning systems. While the benefits of AI integration are notable—such as improved visualization,
adaptive learning, and continuous student support—challenges remain, especially regarding ethical concerns, teacher
training, and regional adaptation. The review also identified a lack of studies focused on AI-generated feedback for
teachers and the development of chemistry-specific algorithms. The findings support the development of a
responsive, personalized AI chatbot to enhance students' understanding of molecular structures. This study aligns
with SDG 4 (Quality Education), emphasizing the importance of empowering teachers with innovative tools to
improve educational outcomes.

*The author is supported by SESS MEXT Scholarship