Artificial Intelligence in Chemistry Research : Implications for Teaching and Learning

Abstract

Artificial intelligence (AI) has become an important tool in modern scientific research, particularly in chemistry and related disciplines. Despite its growing relevance, the discussion of AI as a tool in research in (secondary) chemistry education remains limited. To address this gap, a review of AI applications in chemical and chemistry-related research was first carried out. According to this, AI is being used most frequently in the fields of pharmacology and biochemistry and is mainly used to make predictions and design molecules. Based on this review a workshop for pre- and in-service chemistry teachers was conducted to provide an initial overview of AI applications in scientific research. The workshop introduced key areas such as retrosynthesis, protein structure prediction, image processing, and autonomous laboratories, fostering awareness of AI’s role in scientific innovation. Participating secondary education science teachers reported an increased familiarity with AI applications and expressed intentions to incorporate these topics into their teaching. The findings highlight the importance of targeted teacher training programs to strengthen Technological Content Knowledge (TCK) in this emerging field. In addition, insights were gained into how such teacher training could be structured in the future to enable teachers to discuss “AI in science” in chemistry lessons. This research emphasizes the need to empower educators to bridge the gap between scientific advancements and chemistry education, preparing students for new career opportunities in AI-driven sciences. Although this work provides initial indications of possible approaches for the integration of AI applications in chemistry teacher education and chemistry lessons, further research is still needed in this area.