Integrating AI Literacy in Chemistry Graduate Education: Harnessing the Power of Transformer-Based Models

Abstract

Rapid adoption of general-purpose generative AI (GenAI) tools, such as ChatGPT, is reshaping teaching, learning, and assessment in chemical education. In this study, we expanded the implementation of GenAI tools within an upper-level undergraduate biochemistry course, providing students access to four distinct platforms: commercial chatbots (ChatGPT and LearningClues) and in-house tools developed at the University of Michigan (U-M GPT and U-M Maizey). We analyzed student learning outcomes from GenAI-enhanced writing assignments using pre- and post-surveys. Our results show that integrating GenAI into biochemistry coursework promoted effective and responsible usage, enhanced students’ prompt literacy, built ethical awareness, and increased confidence in utilizing these tools. The study specifically examined factors influencing GenAI acceptance: familiarity, perceived usefulness, ease of use, and trust. Trust emerged as the most significant criterion, with a majority of students recommending in-house chatbots for future cohorts due to strong privacy and ethical standards. Over the last year, we observed a shift in student sentiment from excitement about efficiency to emerging concerns about creativity silencing. This highlights the importance of addressing both capabilities and risks of using AI-tools through teaching AI literacy.

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