Tutorial
Machine Learning for Student Learning
Emma Brunskill · Geoffrey Gordon

Mon Dec 3rd 01:00 -- 03:00 PM @ Emerald Bay B, Harveys Convention Center Floor (CC)

Intelligent tutoring systems and online classes have the potential to revolutionize education. Realizing this potential requires tackling a large number of challenges that can be framed as machine learning problems. We will first provide a survey of several machine learning problems in education, such as modeling a student's thought process as she solves a problem, constructing the atoms of knowledge, and automated problem design. We will then discuss cognitive modeling and instructional policy construction in more depth, and describe state-of-the-art methods as well as ongoing challenges. Throughout the tutorial we will highlight where student learning results in opportunities for new algorithmic and theoretical advances in machine learning.

Author Information

Emma Brunskill (Carnegie Mellon University)

Emma Brunskill is an Assistant Professor of Computer Science and an Affiliated Assistant Professor of Machine Learning at Carnegie Mellon University. Prior to this, she completed her PhD at the Massachusetts Institute of Technology and was a NSF Mathematical Sciences Postdoctoral Fellow at UC Berkeley. Her primary research is on sequential decision making under uncertainty, and she is particularly excited about applications of this work to intelligent tutoring systems and healthcare. Emma is also interested in how information technology can be used to help address challenges that arise in low resource areas. She is a Rhodes Scholar and was recently selected as a Microsoft Faculty Fellow.

Geoffrey Gordon (MSR Montréal & CMU)

Dr. Gordon is an Associate Research Professor in the Department of Machine Learning at Carnegie Mellon University, and co-director of the Department's Ph. D. program. He works on multi-robot systems, statistical machine learning, game theory, and planning in probabilistic, adversarial, and general-sum domains. His previous appointments include Visiting Professor at the Stanford Computer Science Department and Principal Scientist at Burning Glass Technologies in San Diego. Dr. Gordon received his B.A. in Computer Science from Cornell University in 1991, and his Ph.D. in Computer Science from Carnegie Mellon University in 1999.

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