eRevise

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

Published in: Proceedings of the AAAI Conference on Artificial Intelligence (2019). doi: 10.1609/aaai.v33i01.33019619

Posted on RAND.org on February 26, 2020

by Haoran Zhang, Ahmed Magooda, Diane Litman, Richard Correnti, Elaine Lin Wang, Lindsay Clare Matsumura, Emily Howe, Rafael Quintana

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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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