Text categorization for assessing multiple documents integration, or John Henry visits a data mine

  • Authors:
  • Peter Hastings;Simon Hughes;Joe Magliano;Susan Goldman;Kim Lawless

  • Affiliations:
  • DePaul University;DePaul University;Northern Illinois University;University of Illinois Chicago;University of Illinois Chicago

  • Venue:
  • AIED'11 Proceedings of the 15th international conference on Artificial intelligence in education
  • Year:
  • 2011

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Abstract

A critical need for students in the digital age is to learn how to gather, analyze, evaluate, and synthesize complex and sometimes contradictory information across multiple sources and contexts. Yet reading is most often taught with single sources. In this paper, we explore techniques for analyzing student essays to give feedback to teachers on how well their students deal with multiple texts. We compare the performance of a simple regular expression matcher to Latent Semantic Analysis and to Support Vector Machines, a machine learning approach.