Zachary Pardos

Assistant Professor (I School and Graduate School of Education)

Focus

Learning Analytics, Digital Learning Environments, Machine Learning

Research areas

Biography

Dr. Pardos is an Assistant Professor at UC Berkeley in a joint position between the Information School and the School of Education. His focal areas of study are knowledge representation and personalized supports leveraging big data in education. He earned his PhD in Computer Science at WPI and comes to UC Berkeley after a post-doc at MIT CSAIL studying Massive Open 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.

Most recent work:

Pardos, Z.A., Dadu, A. (2017) Imputing KCs with Representations of Problem Content and Context. In Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization (UMAP'17). Bratislava, Slovakia. ACM. Pages 148-155. [pdf] [slides]

Pardos, Z.A., Tang, S., Davis, D., Le. C.V. (2017) Enabling Real-Time Adaptivity in MOOCs with a Personalized Next-Step Recommendation Framework. In Proceedings of the Fourth (2017) ACM Conference on Learning @ Scale (L@S '17). ACM. Pages 23-32. [pdf] [slides]

Pardos, Z.A. & Nam, A. (2017) The School of Information and its Relationship to Computer Science at UC Berkeley. In Proceedings of the 2017 iConference. Wuhan, China. [pdf - forthcoming] [slides - forthcoming]

Current Research

(NSF IIS) Deep Learning in Higher Education Big Data to Explore Latent Student Archetypes and Knowledge Profiles.

(NSF DRK-12) Personalizing Recommendations in a Large-Scale Education Analytics Pipeline.

(BMGF) Next Generation Courseware Challenge: Inspark Science Network for Postsecondary Success in Entry Level Science for Disadvantaged Students. 

(Google) Scaling Cognitive Modeling to Massive Open Environments. 

General areas:

- Personalized educational supports leveraging learner process data
- Distributed representation of knowledge from behavioral data
- Digital Learning Environments (online courses and Intelligent Tutoring Systems)

I am currently accepting students. Consult tiny.cc/zpUCB to schedule a meeting. 

Select Service / Professional Activities

  • Director of Computational Approaches to Human Learning (CAHL) Research Lab: https://github.com/CAHLR
  • Artificial Intelligence in Education Executive committee
  • Editorial Board – Journal of Educational Data Mining & Int. Journal of AI in Education
  • Panelist/speaker - National Academy of Education: Big Data and Privacy (2016): http://naeducation.org/bigdata
  • Program co-chair of the 2014 Educational Data Mining Conference
  • Program committee for the 2014,2016 Learning @ Scale Conference
  • Program committee EDM and LAK 2009-2016
  • Community Liaison for the International Educational Data Mining Society
  • Panelist - White House/OSTP: Big Data and Privacy Workshop, Berkeley (2014)
  • Joint Campus Committee on Information Technology (JCCIT)
  • Asiomar Highered Convention: http://asilomar-highered.info/

Teaching

INFO 254: Data Mining and Analytics (every Spring)
INFO/EDU C290F: Machine Learning in Education (every Fall)
WEDUC 161: Digital Learning Environments (every Fall - online, UC wide - website)

Education

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

Last updated:

September 20, 2017