Artificial intelligence in chemistry teaching-learning: trends, challenges, and educational opportunities. A narrative review
Keywords:
generative artificial intelligence; chemical education; virtual laboratory; educational simulationAbstract
Introduction: There is a growing incorporation of tools based on artificial intelligence (AI) in the educational field; however, in the specific field of Chemistry teaching, this continues to be an emerging and little-explored space. Materials and methods: This narrative review aims to identify the trends, challenges, and pedagogical opportunities associated with the use of AI in the teaching and learning of Chemistry, based on the critical analysis of selected studies between 2020 and 2025, compiled from the Scopus database. The methodology used is based on the QR (Question and Reproducibility) approach, aimed at ensuring rigor and transparency in narrative reviews. Results: The findings emphasize that chemistry teaching with AI incorporates platforms for remote practices, simulations, and automated assessment, consolidating a teacher-technology symbiosis. However, challenges persist in infrastructure, digital literacy, and model accuracy, in addition to ethical considerations in data management. Discussion: Despite this, AI offers content personalization, the development of critical thinking, and democratized access to virtual laboratories, fostering collaboration and real-time feedback. These innovations redefine the role of the teacher as a mediator and promote autonomous, ethical, and participatory learning. Conclusions: It is concluded that artificial intelligence represents a transformative opportunity to renew teaching and learning practices in chemistry. However, its implementation requires a critical, ethical, and contextualized approach that considers both technological advances and the training needs and potential of educational stakeholders.
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