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

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Bibliographic Details
Title: eRevise: Using Natural Language Processing to Provide Formative Feedback on Text Evidence Usage in Student Writing
Language: English
Authors: Zhang, H., Magooda, A., Litman, D., Correnti, R., Wang, E., Matsumura, L. C., Howe, E., Quintana, R.
Source: Grantee Submission. 2019Paper presented at the Annual Meeting of the Association for the Advancement of Artificial Intelligence (AAAI) (31st, 2019).
Peer Reviewed: Y
Page Count: 7
Publication Date: 2019
Sponsoring Agency: Institute of Education Sciences (ED)
Contract Number: R305A160245
Document Type: Speeches/Meeting Papers
Reports - Research
Education Level: Elementary Education
Grade 5
Intermediate Grades
Middle Schools
Grade 6
Descriptors: Formative Evaluation, Essays, Writing (Composition), Revision (Written Composition), Scoring, Computer Software, Web Based Instruction, Teaching Methods, Feedback (Response), Grade 5, Grade 6, Elementary School Students, Pilot Projects, Writing Instruction, Natural Language Processing, Rural Schools
Geographic Terms: Louisiana
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. [This paper was published in: "The Thirty-First AAAI Conference on Innovative Applications of Artificial Intelligence (IAAI-19)" (p. 9619-9625). Association for the Advancement of Artificial Intelligence.]
Abstractor: As Provided
IES Funded: Yes
Entry Date: 2019
Accession Number: ED598633
Database: ERIC
Description
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. [This paper was published in: "The Thirty-First AAAI Conference on Innovative Applications of Artificial Intelligence (IAAI-19)" (p. 9619-9625). Association for the Advancement of Artificial Intelligence.]