Language Technologies Institute Colloquium
- Porter Hall
- KEVYN COLLINS-THOMPSON
- Associate Professor
- School of Information and Department of Electrical Engineering and Computer Science
- University of Michigan, Ann Arbor
Connecting Searching with Learning
While search engines are widely used to find educational material, current search technology is optimized to provide information of generic relevance, not results that are oriented toward a specific user's background and learning goals. As a result, users often do not get effective access to the materials best suited for their learning needs. Moreover, little is known about the relationship between search interaction over time and actual learning outcomes. With collaborators, I have been exploring new content representations and interaction features, implicit assessment methods, and retrieval algorithms for search engines for better understanding and support of human learning, broadly defined. This talk will summarize progress from recent projects toward that goal, including new types of retrieval models that try to directly optimize expected learning gains, and user studies exploring the relationship between search quality, interaction patterns, and learning outcomes.
Kevyn Collins-Thompson is an Associate Professor of Information and Computer Science at the University of Michigan. His research explores theoretical models, algorithms, and software systems for optimally connecting people with information, especially toward educational goals. His research on personalization has been applied to real-world systems ranging from intelligent tutoring systems to commercial Web search engines. Kevyn has also pioneered techniques for modeling the reading difficulty of text, creating risk-averse search engines that maximize effectiveness while minimizing worst-case errors, and understanding and supporting how people learn language. He received his Ph.D. from the Language Technologies Institute at Carnegie Mellon University, where his advisor was Jamie Callan. Before joining the University of Michigan in 2013, he was a researcher for five years in the Context, Learning, and User Experience for Search (CLUES) group at Microsoft Research.
Instructor: Graham Neubig