Automatically Extracting Topical Components for a Response-to-Text Writing Assessment

نویسندگان

  • Zahra Rahimi
  • Diane J. Litman
چکیده

We investigate automatically extracting multiword topical components to replace information currently provided by experts that is used to score the Evidence dimension of a writing in response to text assessment. Our goal is to reduce the amount of expert effort and improve the scalability of an automatic scoring system. Experimental results show that scoring performance using automatically extracted data-driven topical components is promising.

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تاریخ انتشار 2016