CLIP Colloquium: Burr Settles (Duolingo)

Title: Duolingo: Improving Language Learning and Assessment with Data

Abstract: Student learning data can and should be analyzed to develop new instructional technologies, such as personalized practice schedules and data-driven proficiency assessments. I will describe several projects at Duolingo — the world's most popular language education platform with more than 200 million students worldwide — where we combine vast amounts of learner data with machine learning, computational linguistics, and psychometrics to improve learning, testing, and engagement.

Bio: Burr Settles leads the research group at Duolingo, an award-winning website and mobile app offering free language education for the world. He also runs FAWM.ORG, a global annual songwriting experiment. He is the author of Active Learning — an introductory text on machine learning algorithms that are adaptive, curious, and exploratory (if you will). His research has been published in NIPS, ICML, AAAI, ACL, EMNLP, NAACL-HLT, and CHI, and has been covered by The New York Times, Slate, Forbes, WIRED, and the BBC among others. In past lives, he was a postdoc at Carnegie Mellon and earned a PhD from UW-Madison. Burr currently lives in Pittsburgh, where he gets around by bike and plays guitar in the pop band "delicious pastries."