From invisible to visible: tracking the learning process in student work to make AI use visible for automated reliable assessment
Thematic Area: Teaching and Learning
Faculty Advisor: One-U Responsible AI Initiative faculty fellow Vineet Pandey, Kahlert School of Computing
Current approaches to student AI attribution—self-reported citations and disclosures—are often inaccurate, require additional work, and reveal surface-level details, making it impossible for instructors to distinguish genuine intellectual growth from mindless delegation to AI. Sujit Kumar Kamaraj proposes ProcessGit, a framework that tracks the learning process passively—without interrupting students’ workflow—while giving instructors direct, observable evidence of AI use. His research platform will instantiate the ProcessGit framework and deploy these ideas across large classrooms to help improve learning, assessment, and pedagogy.
Sujit started studying computer science at the University of Utah in 2023 and earned a master’s before continuing toward his Ph.D. He holds a bachelor’s in the same field from the Vellore Institute of Technology in Tamil Nadu, India.
