Teaching and Learning about Artificial Intelligence (AI) in Secondary Education Chemistry Classes

Abstract

Artificial intelligence (AI) is increasingly transforming chemical research and practice, yet chemistry education has largely focused on students’ use of generative AI tools rather than on understanding AI as a driver of modern chemistry. This mixed-methods study examined the feasibility of teaching “AI in chemistry” in secondary chemistry education (grades 10–13) and developed a practice-oriented model for future implementation and research. To this end, a 3-h professional development (PD) program for chemistry teachers and two 90-min lessons addressing AI applications in chemistry research, as well as associated benefits and risks, were designed and evaluated. Qualitative teacher surveys explored relevance, feasibility, and implementation. Student questionnaires assessed perceived importance of the topic, expectations that teachers address it, interest, attitudes toward AI in chemistry, and science-related AI competencies. Across both samples, prior knowledge of AI applications in chemistry was low but increased following the interventions. Teachers considered “AI in chemistry” highly relevant to the curriculum and emphasized the importance of classroom-ready examples for successful implementation. Students reported higher perceived importance of the topic, stronger expectations that teachers address it, and increased interest after instruction. Attitudes toward AI use in chemistry showed minor changes. In addition, students demonstrated improved ability to identify specific application areas of AI in chemistry. Overall, the findings indicate that instruction on “AI in chemistry” is feasible and educationally valuable. Effective implementation appears to benefit from focusing on tangible, real-world applications of AI in chemistry and from structured discussion of ethical risks, limitations, and trade-offs associated with its use.