Program

Schedules

Time Schedule
9:00 Opening …
9:10 – 10:00 Invited Talk by Konstantin Bauman
10:00 – 10:30 Break (Coffee available Outside Merchants)
10:30 – 10:55 “Collaborative Recommendation of Informal Learning Experiences”
Authors: Robin Burke and Farzad Eskandanian
10:55 – 11:20 “Recommender System to Support Brokering of Youth Learning Opportunities”
Authors: Taha Hamid, Denise Nacu, Jonathan Gemmell, Daniela Raicu, Michael Schutzenhofer, Taihua Li, Caitlin K. Martin, and Nichole Pinkard
11:20 – 11:45 “Educational Recommendation with Multiple Stakeholders”
Authors: Robin Burke and Himan Abdollahpouri
11:45 Closing remarks …

Invited Talk

Title: Recommending Remedial Learning Materials to the Students by Filling their Knowledge Gaps

Abstract: We study the problem of providing recommendations to the students that help them in their studies. To address this problem, we present an approach of providing recommendations of remedial learning materials to the students that fills the gaps in their knowledge of the subject in the courses that they take. According to this method, we first identify gaps in student’s mastery of various course topics. Then we identify those items from the library of assembled learning materials that help us to fill those gaps, and then we recommend these identified materials to the student. We show empirically through A/B testing that this approach leads to better performance results, as measured by student’s total score on the final exam across the Personalized, Non-personalized and the Control groups and by improvement of student’s average score on that exam in comparison to the previously taken courses. The proposed method is scalable since it can be applied to a large number of students across many courses.

Presenter: Konstantin Bauman. He is a Research Scientist in the Department of Information, Operations and Management Sciences at the Stern School of Business, NYU. His current research interests include machine learning, recommender systems, technology enhanced learning, and natural language processing. Konstantin received his M.S. in Mathematics from Moscow State Lomonosov University in 2008, his M.S. in Data Mining from Moscow Institute of Physics and Technology in 2009, and his Ph.D. in Geometry and Topology from Mathematical Institute of the Russian Academy of Science in 2012. Before joining NYU, Konstantin worked for five years at the research division of Yandex, working on data mining and machine learning problems.


List of Accepted Papers

  • Recommending Remedial Learning Materials to the Students by Filling their Knowledge Gaps 
    Authors: Konstantin Bauman and Alexander Tuzhilin [PDF]
  • Simulation of a Formal Apprentice with an Evolutionary Algorithm (withdrawn)
    Authors: Carlos Tobar Toledo, Juan Adán Coello, and Monise Costa

  • Educational Recommendation with Multiple Stakeholders
    Authors: Robin Burke and Himan Abdollahpouri [PDF]
  • Recommender System to Support Brokering of Youth Learning Opportunities
    Authors: Taha Hamid, Denise Nacu, Jonathan Gemmell, Daniela Raicu, Michael Schutzenhofer, Taihua Li, Caitlin K. Martin, and Nichole Pinkard [PDF]
  • Collaborative Recommendation of Informal Learning Experiences
    Authors: Robin Burke and Farzad Eskandanian  [PDF]
Advertisements