Integrating Generative AI in Chemistry Education: Enhancing Career-Ready Writing Skills in Pharmaceutical Science

Abstract

Integrating generative AI (GenAI) into chemistry education offers opportunities to enhance student engagement and skill development, but its use raises questions about ensuring knowledge accuracy and fostering critical thinking. This study explored a context-based assignment in which undergraduate chemistry students analyzed a pharmaceutical formulation while collaborating with a GenAI tool to draft their reports. Students produced an initial GenAI-generated report, critically evaluated its content, and revised it extensively using authoritative sources. The assignment emphasized professional skills by encouraging students to co-create work that emulates tasks they might encounter in a pharmaceutical career. Analysis of student submissions revealed diverse engagement with GenAI tools. While a fraction of students overrelied on GenAI-generated content, resulting in factual inaccuracies, the majority demonstrated critical engagement by correcting errors, adding physicochemical justifications, and transforming GenAI-generated bullet points into professional, coherent paragraphs. Reflective evaluations further highlighted students’ awareness of GenAI’s strengths, such as efficiency and structure, as well as its limitations, including factual errors and lack of contextual depth. The findings suggest that GenAI can be a powerful tool for enhancing technical chemical writing and critical thinking when paired with structured guidance and iterative feedback. This study highlights the importance of teaching students to critically evaluate and refine GenAI outputs, preparing them for professional scenarios in which collaboration with GenAI will be increasingly common. The assignment provides a framework for integrating GenAI into chemistry and STEM education, balancing technological innovation with the need for scientific rigor and ethical awareness.