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

  • 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


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.

IAAI Technical Track: Emerging Papers