Proceedings of the 9th International Conference on Educational Data Mining, EDM 2016, Raleigh, North Carolina, USA, June 29 - July 2, 2016

Data-Driven Education: Some opportunities and Challenges

A program of study can be viewed as a knowledge graph consisting of learning units and relationships between them. Such a knowledge graph provides the core data structure for organizing and navigating learning experiences. We address two issues in this talk. First, given a knowledge graph, how can we use data mining to identify and correct deficiencies in a knowledge graph. Second, how can we u...

WISE Ways to Strengthen Inquiry Science Learning

The Web-based Inquiry Science Environment (WISE) logs student and teacher interactions during classroom science inquiry instruction. Over the past 10 years we have used these logs for many purposes including: to analyze patterns of student interactions with dynamic, interactive scientific models and improve instruction; to determine when students revisit prior activities and assess whether the ...

Enabling people to harness and control EDM for lifelong, life-wide learning

There has been an explosion of digital learning sensors. Some are in bespoke learning applications. But many more are in the digital tools people use in every aspect of their lives. This paper introduces a user-centred view of EDM for lifelong, life-wide learning. That includes formal education, but goes beyond it to the complex, multi-faceted and ill-defined learning in our broader lives. This...

Impact of an improved neutrino energy estimate on outflows in neutron star merger simulations

Francois Foucart, Evan O’Connor, Luke Roberts, Lawrence E. Kidder, Harald P. Pfeiffer, and Mark A. Scheel Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, California 94720, USA Department of Physics, North Carolina State University, Raleigh, North Carolina 27695, USA TAPIR, Walter Burke Institute for Theoretical Physics, MC 350-17, California Institute of Technology, Pasadena,...

Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29 - July 2, 2000