This initiative builds upon the foundations of OATutor, the first open-source adaptive tutoring system grounded in Intelligent Tutoring Systems principles. Our project is dedicated to developing a technology that autonomously generates a computer tutor capable of covering any lower-division college STEM subject. Utilizing large language models (LLMs), our approach aims to rapidly produce content that not only meets the specific needs of educators but also appeals to the unique experiences and career goals of adult learners.
Zach Pardos
Associate Professor of Education
Zachary Pardos is an Associate Professor of Education at UC Berkeley studying adaptive learning and AI. He has 17 years of research experience with intelligent tutoring systems and leads the Computational Approaches to Human Learning research lab, developing tools like OATutor and AskOski, a course recommendation and multi-institution student success initiative. His work designing Human-AI collaborations to pave pathways to and within systems of higher education has been published in venues such as SIGCHI, NeurIPS, Computers & Education, and Science. At Berkeley, he teaches in the data science undergraduate program and is an affiliated faculty member in Cognitive Science.