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

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.

preprint2019arXivOpen access
Haoran ZhangAhmed MagoodaDiane LitmanRichard CorrentiElaine WangLindsay Clare MatsumuraEmily HoweRafael Quintana
Computation and LanguageArtificial Intelligence
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Haoran ZhangAhmed MagoodaDiane LitmanRichard CorrentiElaine WangLindsay Clare MatsumuraEmily HoweRafael Quintana

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