STEM Learning and Learning Environments  

Generative AI as a STEM Learning Partner: Supporting Deep and Self-Regulated Learning in Chemistry

Effective Years: 2025-2028

The NSF ECR Building Capacity of STEM Education Research (BCSER) program contributes to the NSF mission 42 U.S. Code Chapter 16 by building the US workforce undertaking STEM education research. The BCSER Individual Investigator Development in STEM Education Research (IID) track supports individual investigators who are new to STEM education research to develop foundational skills and gain practical experience to advance STEM education knowledge through mentored professional development and pilot research activities. STEM education research generates the knowledge, theories, and understandings on which viable strategies for improving STEM education and workforce outcomes are based. This project will teach students to use generative artificial intelligence (AI) tools in STEM as learning partners aimed at facilitating deep, self-regulated learning in organic chemistry courses. The study will compare GAI-enhanced instruction to traditional learning environments to understand student mastery of a STEM learning in undergraduate organic chemistry courses. This BCSER IID project will allow the PI to develop foundational skills and gain practical experience in designing and implementing cutting edge STEM education research using innovative methods and tools. The PI will develop new expertise in implementing cutting edge STEM education research using modern methods and tools, as wells as using generative AI tools and statistical analyses in STEM education research. The PI will work with experts in evidence-based STEM teaching methods and interdisciplinary quantitative methodologies. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.