Zachary Pardos

Associate Professor
Graduate School of Education
School of Information
(321) 219-9224
Research Expertise and Interest
knowledge representation, Adaptive Learning, Learning Analytics, Recommender Systems, Education Data Mining, data science, higher education, Digital Learning Environments, Cognitive Modeling, Big Data in Education, Knowledge Tracing, Formative Assessment, intelligent tutoring systems, Massive Open Online Courses, machine learning, Online Learning, psychometrics
Research Description

Dr. Pardos is an Associate Professor at UC Berkeley studying adaptive learning and AI. His current research focuses on knowledge representation and recommender systems approaches to increasing credit mobility and degree attainment in postsecondary education using behavioral and semantic data.

He earned his PhD in Computer Science at Worcester Polytechnic Institute with a dissertation on computational models of cognitive mastery. Funded by a National Science Foundation Fellowship (GK-12), he spent extensive time with K-12 educators and students working to integrate educational technology into the curriculum as a formative assessment tool. After completing his PhD in 2012, he spent one year as a Postdoctoral Associate at the Massachusetts Institute of Technology applying adaptive learning paradigms to Massive Open Online Courses. At Cal, he directs the Computational Approaches to Human Learning research lab, teaches in the Graduate School of Education and the Division of Computing, Data Science, and Society, and is an affiliated faculty in Cognitive Science.

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