English

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

Computation and Language 2020-02-26 v1 Artificial Intelligence

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 rubric-based 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.

Keywords

Cite

@article{arxiv.1908.01992,
  title  = {eRevise: Using Natural Language Processing to Provide Formative Feedback on Text Evidence Usage in Student Writing},
  author = {Haoran Zhang and Ahmed Magooda and Diane Litman and Richard Correnti and Elaine Wang and Lindsay Clare Matsumura and Emily Howe and Rafael Quintana},
  journal= {arXiv preprint arXiv:1908.01992},
  year   = {2020}
}

Comments

Published in IAAI 19

R2 v1 2026-06-23T10:40:37.835Z