eRevise: Using Natural Language Processing to Provide Formative Feedback on Text Evidence Usage in Student Writing

Authors

  • H. Zhang University of Pittsburgh
  • A. Magooda University of Pittsburgh
  • D. Litman University of Pittsburgh
  • R. Correnti University of Pittsburgh
  • E. Wang University of Pittsburgh
  • L.C. Matsmura University of Pittsburgh
  • E. Howe University of Pittsburgh
  • R. Quintana University of Pittsburgh

DOI:

https://doi.org/10.1609/aaai.v33i01.33019619

Abstract

Writing a good essay typically involves students revising an initial paper draft after receiving feedback. We present eRevise, a web-based writing and revising environment that uses natural language processing features generated for rubricbased essay scoring to trigger formative feedback messages regarding students’ use of evidence in response-to-text writing. By helping students understand the criteria for using text evidence during writing, eRevise empowers students to better revise their paper drafts. In a pilot deployment of eRevise in 7 classrooms spanning grades 5 and 6, the quality of text evidence usage in writing improved after students received formative feedback then engaged in paper revision.

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Published

2019-07-17

How to Cite

Zhang, H., Magooda, A., Litman, D., Correnti, R., Wang, E., Matsmura, L., Howe, E., & Quintana, R. (2019). eRevise: Using Natural Language Processing to Provide Formative Feedback on Text Evidence Usage in Student Writing. Proceedings of the AAAI Conference on Artificial Intelligence, 33(01), 9619-9625. https://doi.org/10.1609/aaai.v33i01.33019619

Issue

Section

IAAI Technical Track: Emerging Papers