Argument Mining from Text and its Application in Education | College of Information Sciences and Technology
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Argument Mining from Text and its Application in Education

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The Department of Computer Science and Engineering and the College of Information Sciences and Technology present

Diane Litman
Professor, Computer Science, University of Pittsburgh

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 language 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.


BIO: Diane Litman is a Professor of Computer Science, and a Senior Scientist with the Learning Research and Development Center (LRDC), at the University of Pittsburgh. She received her Ph.D. and M.S. in Computer Science from the University of Rochester, and A.B. in Mathematics and Computer Science from the College of William and Mary in Virginia. Her research interests are in the areas of artificial intelligence and education, computational linguistics, knowledge representation and reasoning, natural language learning, spoken language, and user modeling.

Friday, November 3, 2017, 2:00 PM to 3:00 PM

W201 Westgate Building