Integrating generative AI (GenAI) into chemistry coursework is transforming how students approach scientific writing and evaluate information. In this activity, implemented in upper-level biochemistry and bioinorganic chemistry courses, 69 undergraduate and graduate students used chatbots like ChatGPT, U-M GPT, and Claude to create bibliographies for essays on chemistry research topics. Students then critically engaged with the chemical literature, systematically validating each AI-generated citation using scholarly tools. Our analysis of 456 GenAI-generated references revealed that on average a student essay contained 51.3% real and correctly cited references. These authentic citations were most frequently associated with multidisciplinary high-impact journals, particularly those in the Nature portfolio, and were linked to articles with high Altmetric Attention Scores. Through this process, students directly encountered the challenges and pitfalls of relying on AI-generated sources. Especially concerning was the observation that fabricated references were most frequently associated with disciplinary chemistry journals. Survey analysis and in-class discussions following the GenAI-assisted writing activity revealed that students developed a greater awareness of research integrity and gained practical skills for critically assessing scholarly sources. For example, when evaluating references from chemistry journals, students often identified inconsistencies and relied on their domain-specific knowledge to correct citations or locate original articles. Of the original 456 AI-generated citations, only 58% remained in students’ final essays, underscoring ongoing difficulties with both citation accuracy and relevance and highlighting the critical importance of source evaluation when working with AI. Overall, this activity underscores the importance of fostering both AI literacy and research integrity in chemistry education and offers actionable recommendations to help students use AI responsibly in academic writing.
Sevryugina et al. (2026) studied this question.