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arXiv · 1908.01992

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

Haoran Zhang·Ahmed Magooda·Diane Litman·Richard Correnti·Elaine Wang·Lindsay Clare Matsumura·Emily Howe·Rafael Quintana
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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.

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Haoran Zhang, Ahmed Magooda, Diane Litman, Richard Correnti, Elaine Wang, Lindsay Clare Matsumura, Emily Howe, Rafael Quintana. 2019-08-06. eRevise: Using Natural Language Processing to Provide Formative Feedback on Text Evidence Usage in Student Writing. https://doi.org/10.1609/aaai.v33i01.33019619

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