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Computer Tutors and Educational Data Mining


The expanding role of computers in education and in educational research will be addressed by two back-to-back research conferences hosted by Carnegie Mellon University that will draw several hundred researchers to Pittsburgh this month from more than 20 countries.

About 100 participants are expected for the Third International Conference on Educational Data Mining (EDM2010), which will be held June 11-13, and more than 250 people are registered for the 10th International Conference on Intelligent Tutoring Systems (ITS2010), June 14-18. Both conferences will be on the Carnegie Mellon campus.

"These are independent, but mutually supportive conferences," said ITS2010 conference chair Jack Mostow, research professor of robotics, machine learning, language technologies and human-computer interaction in CMU's School of Computer Science. "Students are learning more and more from intelligent tutors; tutors are collecting more and more data from their students; and educational data mining is learning more and more from this data."

Educational data mining, the focus of EDM2010, is an emerging discipline that is developing methods for exploring data gathered from educational settings, and using those methods to identify the best ways for students to learn.

Intelligent tutoring systems, the focus of ITS2010, are interactive computer systems that can present lessons and problem sets to students, provide step-by-step guidance with complex problem solving, analyze the students' performance and adjust accordingly. One example is the Reading Tutor developed by Mostow's Project LISTEN, which displays stories to a student and then listens and analyzes as the student reads the stories aloud. Another example are the Cognitive Tutors for middle-school and high-school mathematics originally developed at Carnegie Mellon and now marketed by spin-off firm Carnegie Learning, which are being used by more than half a million students nationwide.

The six-year-old Pittsburgh Science of Learning Center (PSLC), a National Science Foundation-sponsored project at Carnegie Mellon and the University of Pittsburgh, is heavily invested in both intelligent tutoring systems and educational data mining. With the goal of identifying robust learning methods, the PSLC uses computer tutors to teach such subjects as algebra, geometry, physics, chemistry, Chinese, and English as a second language in 40 schools and colleges across the country. In addition to evaluating the effectiveness of the computer tutors, the computers gather information about the learning process itself. That information is stored in the Data Shop, already one of the world's largest public repositories of empirical educational data, where it is available for data mining and analysis.


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