Name
Title | ||
|---|---|---|
eRevise: Using Natural Language Processing to Provide Formative Feedback on Text Evidence Usage in Student Writing |
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. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1609/aaai.v33i01.33019619 | AAAI |
Field | DocType | Volume |
Software deployment,Computer science,Artificial intelligence,Natural language processing,Formative assessment | Conference | 33 |
Issue | ISSN | Citations |
01 | Proceedings of the AAAI Conference on Artificial Intelligence
(2019) vol. 33, 9619-9625 | 2 |
PageRank | References | Authors |
0.36 | 0 | 8 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Haoran Zhang | 1 | 3 | 2.07 |
| Magooda Ahmed | 2 | 13 | 3.71 |
| Diane J. Litman | 3 | 3542 | 484.90 |
| richard correnti | 4 | 11 | 2.27 |
| E. Wang | 5 | 16 | 2.60 |
| L. C. Matsmura | 6 | 2 | 0.36 |
| E. Howe | 7 | 2 | 0.36 |
| R. Quintana | 8 | 3 | 0.82 |