Case study development with AI: prompt design as a training strategy for Chemistry teachers

Authors

DOI:

https://doi.org/10.56117/resbenq.2026.v7.e072615

Keywords:

Prompt Design, Artificial Intelligence, Chemistry Education

Abstract

This study aims to present and discuss a teacher education experience designed to improve the formulation of prompts by preservice teachers for the production of Case Studies for Chemistry Teaching (CSCT) mediated by Artificial Intelligence (AI) systems. Methodologically, a pedagogical intervention (PI) study was conducted in five stages with sixth-semester students enrolled in a Chemistry Teacher Education program at a federal educational institution. The analytical corpus consisted of the prompts formulated by the preservice teachers and the corresponding responses generated by the AI systems. The results indicated that, initially, the students had limited mastery of the elements required to construct appropriate prompts, relying on generic commands that were poorly aligned with the proposed demands. This resulted in CSCT presenting significant limitations for the chemistry teaching and learning process. Following the PI, improvements were observed in the formulation of the prompts, particularly in the description of the teaching context, the clarity of the requests submitted to the AI systems, and the definition of the expected output criteria. Nevertheless, the CSCT produced still exhibited excessive simplification, fragmented content, the absence of relevant chemical concepts, the omission of scientific terminology, and limited alignment with the previously established pedagogical objectives. The PI made it possible to identify both the potential and the challenges associated with using AI as a methodological resource in teacher education. At the same time, it contributed to the development of prompt literacy among the students, the adoption of a critical, continuous, and evaluative stance during interactions with AI systems, and the expansion of the future teachers’ pedagogical repertoire. It is concluded that initial teacher education should provide further opportunities for the critical use of emerging technologies in authentic classroom situations, integrating technological, pedagogical, and content knowledge in the development of professional knowledge for chemistry teaching.

Author Biographies

Thiago, IFSP

Bachelor’s degree in Chemistry from the Institute of Chemistry of Araraquara, São Paulo State University “Júlio de Mesquita Filho” (IQ-UNESP Araraquara), and a teaching degree in Chemistry from the Faculty of Philosophy, Sciences and Letters of Ribeirão Preto, University of São Paulo (FFCLRP-USP). Holds a specialization in Planning, Implementation, and Management of Distance Education from the Fluminense Federal University / UAB (2013). Master’s degree in Chemistry (IQ-UNESP Araraquara), subfield of Analytical Chemistry (2010), and PhD in Chemistry (Federal University of São Carlos – UFSCar), subfield of Chemistry Education/Teacher Education (2021). Currently, he is a professor at the Federal Institute of São Paulo, Catanduva campus

Joana, FFCLRP-USP

Licenciada em Ciências Naturais e em Biologia (Unicentro, 1999), possui Especialização em Instrumentação para o Ensino de Ciências (Unicentro, 2000), Mestre em Educação nas Ciências (Unijuí, 2003), Doutora em Educação (FE-UNICAMP, 2008) e Pós-doutor em Educação (FE UN CAMP, 2011). Atualmente é professora do Departamento de Química da Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto da Universidade de São Paulo (FFCLRP-USP).

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Published

2026-09-25

How to Cite

Bernardo Cavassani, T., & de Jesus de Andrade, J. (2026). Case study development with AI: prompt design as a training strategy for Chemistry teachers. Revista Da Sociedade Brasileira De Ensino De Química, 7(1), e072615. https://doi.org/10.56117/resbenq.2026.v7.e072615