Abstract

The written arguments of students are educational data that can be automatically mined for purposes of student instruction and assessment.  This talk will illustrate some of the opportunities and challenges in educationally-oriented argument mining from text. I will first describe how we are using natural processing to develop argument mining systems that are being embedded in educational technologies for essay grading, peer review, and writing revision analysis. I will then present the results of empirical evaluations of these technologies, using argumentative writing data obtained from elementary, high school, and university students.

Biography

Diane Litman is Professor of Computer Science, Senior Scientist with the Learning Research and Development Center, and Faculty Co-Director of the Graduate Program in Intelligent Systems, all at the University of Pittsburgh.  Previously she was a member of the Artificial Intelligence Principles Research Department, AT&T Labs – Research (formerly Bell Laboratories).  Dr. Litman’s current research focuses on enhancing the effectiveness of educational technology through the use of spoken and natural language processing techniques such as argument mining, summarization, and dialogue systems.  Dr. Litman has been Chair of the North American Chapter of the Association for Computational Linguistics, has co-authored multiples papers winning best paper awards, and has been awarded Senior Member status by the Association for the Advancement of Artificial Intelligence.

http://people.cs.pitt.edu/~litman/