Ido seeks to understand how students become better learners and scientists and how this process can be supported. Towards that goal, Ido develops intelligent and adaptive learning environments that facilitate meaningful learning in which learners explore, err, and make sense of their learning. Developing learning analytics techniques allows him to assess learning processes, inform theories of learning, and provide tools for teachers. Ido is particularly interested in using large-scale fine-grain data across different time scales, from seconds (in problem solving environments and simulations) to months (in MOOCs and full courses).
Ido is a member of the Executive Committee of the International Artificial Intelligence in Education Society and the Steering Committee of Learning at Scale. He is also a member of the PISA Special Domains Expert Group. Ido received his PhD from Carnegie Mellon University, and later served as the Director of the Institute for Scholarship of Teaching and Learning at the University of British Columbia.
1995 B.Sc., The Hebrew University, Jerusalem. Math and Physics.
2007 M.Sc., Carnegie Mellon University. Human-Computer Interaction.
2009 Ph.D., Carnegie Mellon University. Human-Computer Interaction.
2009 Program for Interdisciplinary Education Research, Carnegie Mellon University.