ADMU: Education Data Mining

Educational Data Mining

26 May 2014, 8:30 to 12:00

Room Faura 227

Ateneo de Manila University

Hosted by

Ateneo Laboratory for the Learning Sciences

Department of Information Systems and Computer Science

Ateneo de Manila University, Loyola Heights, Quezon City

In cooperation with

The Educational Data Mining Laboratory

Teachers College, Columbia University

New York, New York

Resource Speakers

The Ateneo Laboratory for the Learning Sciences (ALLS) is a research office that lies at the intersection of computer science and education.  The Educational Data Mining Laboratory of Teachers College, Columbia University is headed by Dr. Ryan Baker, President of the International Educational Data Mining Society and Associate Editor of the Journal of Educational Data Mining. Both laboratories make use of statistical and data mining techniques to investigate behavioral and affective phenomena that mediate learning. These include in depth examinations of learning outcomes, prediction of STEM career choice, student help-seeking, carelessness, and conscientiousness as well as patterns of student confusion, frustration, and boredom.

Educational Data Mining is concerned with the quantitative analysis of student interactions with computer-based learning environments to derive insights about how students learn best.  The half-day session gives participants an overview of data gathering, analysis, and validation techniques.

ERDT scholars are strongly encouraged to attend the talk.  To register, prospective participants should send their names, email addresses, cel numbers, and institutional affiliations to Ma. Mercedes T. Rodrigo ( This email address is being protected from spambots. You need JavaScript enabled to view it. ) by 20 May 2014.

About the speakers:

Joseph Beck, assistant professor of Computer Science, has been at WPI since 2007. His research focuses on educational data mining, a new discipline that develops techniques for analyzing large educational data sets to make discoveries that will improve teaching and learning. His work centers on estimating how computer tutors impact learning. He established the first workshop in the field and in 2008 was program co-chair of the first International Conference on Educational Data Mining. He holds a BS in mathematics, computer science, and cognitive science from Carnegie Mellon University, and a PhD in computer science from the University of Massachusetts, Amherst.

Jaclyn Ocumpaugh is a post-doctoral fellow at Teachers College, Columbia University. As a member of the Educational Data Mining Laboratory, she specializes in the learning sciences and learning technologies.  Since 2012, she has been extensively publishing in the area of Educational Data Mining (EDM), winning a best paper award at the 11^th International Conference on Intelligent Tutoring Systems.

Ma. Mercedes T. Rodrigo is a full professor of Computer Science at the Ateneo de Manila University.  She is the head of the Ateneo Laboratory for the Learning Sciences.  She has published actively in the areas of intelligent tutoring systems, artificial intelligence in education, and educational technology.