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Zachary A Pardos

Assistant Professor *
Postdoctoral Associate, Physics & CSAIL - Massachusetts Institute of Technology
Doctor of Philosophy, Computer Science - Worcester Polytechnic Institute
Bachelors of Science, Computer Science - Worcester Polytechnic Institute

Dr. Pardos is an assistant professor in the Graduate School of Education and School of Information at UC Berkeley. His work focuses on knowledge representation and engineering personalized supports leveraging big data from educational contexts. His current projects focus on increasing upward mobility in the California postsecondary system and using behavioral and semantic data to map out paths to cognitive and career achievement in K-16. He earned his PhD in Computer Science from Worcester Polytechnic Institute funded by an NSF Graduates in K-12 Fellowship (GK12), during which he spent extensive time with K-12 educators and students working to integrate educational technology into the curriculum as a formative assessment tool. He holds several academic leadership positions in the learning analytics community, including posts as an editorial board member for two of its journals (JEDM and IJAIED), executive committee member for the Artificial Intelligence in Education Society, and program committee member of the 2018 education conferences; ICLS, ITS, LAK, EDM, AIED and L@S. Dr. Pardos came to UC Berkeley in 2013 after a post-doc at MIT’s Computer Science Artificial Intelligence Lab (CSAIL), exploring models of cognitive mastery applied to learner process data from, then nascent, large scale online courses. At UC Berkeley, he directs the Computational Approaches to Human Learning (CAHL) research lab and teaches courses on data mining and analytics, digital learning environments, and machine learning in education. 


INFO 254: Data Mining and Analytics (every Spring) [syllabus]
INFO/EDU C290F: Machine Learning in Education (every Fall) [page]
EDUC W161: Digital Learning Environments (every Fall - online, UC wide - website) [syllabus]
EDUC 290A/003: Computational Approaches to Human Learning (CAHL) research group (website)
Research group class info: This group will be run as a platform for discussions on topics ranging from analysis of equity, diversity, and inclusion on campus to the role of AI in K-16 education. Each session will involve a workshoping aspect, such as designing taxonomies or running analyses with new learning analytics tools shared by classmates and the facilitator (me). While this class can be a segue to research in my lab, it is primarily meant to be a thinktank, of sorts, of its own. The group will meet Wednesdays 11:30-1pm in Tolman Hall 4529 (CCN is 15555).

Please see the CV pdf for an updated list of my publications and my iSchool web page.

Contact Info
Tolman Hall 4641
(321) 219-9224
Staff Contact: