Research Expertise and Interest

knowledge representation, Adaptive Learning, artificial intelligence, Learning Analytics, Recommender Systems, higher education, data science, Digital Learning Environments, Cognitive Modeling, Big Data in Education, Knowledge Tracing, Formative Assessment, intelligent tutoring systems, Online Learning, psychometrics, Educational Data Mining

Research Description

Dr. Pardos is an Associate Professor of Education at UC Berkeley studying adaptive learning and AI. His current research focuses on knowledge representation and recommender systems approaches to increasing upward mobility in postsecondary education.

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. At Cal, he directs the Computational Approaches to Human Learning research lab, teaches in the data science undergraduate program, and is an affiliated faculty in Cognitive Science.

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