Members of the Texas A&M Institute of Data Science (TAMIDS) recently received a grant from the National Science Foundation for their ongoing project, “Empowering STEM Education by Creating Benchmarking Models for Generative Artificial Intelligence Learning Assistants.” This project is led by Dr. Namgyun Kim from Texas A&M’s Department of Construction Science, with several Texas A&M faculty serving as Co-PIs, including Dr. Nick Duffield (TAMIDS), Dr. Yalong Pi (TAMIDS), Dr. Kunhee Choi (Department of Construction Science), and Dr. Daseok Chai (Department of Education & Human Development). Drs. Duffield and Pi are part of the TAMIDS Operational Data Science Lab, which recently welcomed Rohit Venkata Sai Dulam as a Postdoctoral Research Associate to assist in studying the university’s infrastructure data to improve campus operations. This collaboration between Texas A&M and the University of Arizona received $400,000 to support this interdisciplinary project.
Generative AI (GenAI) has the potential to greatly enhance student learning as a cutting-edge resource in research and education. However, when integrated into undergraduate STEM courses, certain characteristics and requirements of each academic discipline need to be considered. Architecture, engineering, and construction are particularly complex fields, pulling together elements of social sciences, liberal arts, and visual design. The goal of this project is to develop GenAI learning assistant models tailored to key courses in these three disciplines and study their effects on student learning across different academic levels. With combined expertise in construction, architecture, computer vision, and AI, this project will advance our understanding of strategies for GenAI adoption in education.
Welcome, Dr. Dulam!
Dr. Rohit Venkata Sai Dulam joined the TAMIDS Operational Data Science Lab in July of this year as a postdoctoral research associate under Dr. Yalong Pi. His research interests include designing and building novel deep learning architectures for computer vision applications in agriculture and disaster management.