Monday, August 05 | 6:00PM–7:00PM

State of the Field: Learning Analytics and Educational Data Mining

Date: August 5, 2013

Time: 1:00 p.m. ET (UTC-4) runs one hour; convert to your time zone

Special Guests

George SiemensGeorge Siemens

George Siemens is an educator and researcher on learning, technology, networks, analytics, and openness in education. He is the author of Knowing Knowledge, an exploration of how the context and characteristics of knowledge have changed and what it means to organizations today, and the Handbook of Emerging Technologies for Learning. Knowing Knowledge has been translated into Mandarin, Spanish, Italian, Persian, and Hungarian. Dr. Siemens is the Associate Director of the Technology Enhanced Knowledge Research Institute at Athabasca University, and a faculty member in the School of Computing and Information services and the Centre for Distance Education. Dr. Siemens is a founding member and President of the Society for Learning Analytics Research. In 2008, he pioneered massive open online courses (sometimes referred to as MOOCs) that have included more than 25,000 participants.

Ryan Shaun Joazeiro de BakerRyan Shaun Joazeiro de Baker

Ryan Shaun Joazeiro de Baker is the Julius and Rosa Sachs Distinguished Lecturer at Teachers College, Columbia University. He earned his PhD in human-computer interaction from Carnegie Mellon University. Baker is currently serving as the founding president of the International Educational Data Mining Society and as associate editor of the Journal of Educational Data Mining. His research combines educational data mining and quantitative field observation methods in order to better understand how students respond to educational software and how these responses impact their learning. He studies these issues within intelligent tutors, simulations, multiuser virtual environments, and educational games.



Join Malcolm Brown and Veronica Diaz as they moderate this webinar with George Siemens and Ryan Baker. The analysis of data generated through the learning process offers educators a new lens for assessing and supporting learners. Through analytics and data mining, researchers can discover which behaviors and decisions lead to learner success, identify learners who are at risk of dropping out or failing, personalize and adapt learning content and instruction to meet individual needs, and improve and optimize the use of institutional support structures to assist learners. This webinar offers a "state of the field" analysis of learning analytics and educational data mining. During this session, we’ll review

  • the current state of learning analytics,
  • the types of tools/software and methods useful for evaluating and understanding learner success,
  • the trends and future directions for the field, and
  • ways to get involved.

Additional Resources


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