eRevise：使用自然语言处理为学生写作中的文本证据使用提供形成性反馈
eRevise: Using Natural Language Processing to Provide Formative Feedback on Text Evidence Usage in Student Writing
摘要：
写一篇好文章通常需要学生在收到反馈后修改最初的论文草稿。我们提出了eRevise，一个基于网络的写作和修改环境，使用自然语言处理功能生成的基于规则的论文评分，以触发形成反馈信息，学生的使用证据，在响应文本写作。通过帮助学生了解在写作过程中使用文本证据的标准，eRevise使学生能够更好地修改他们的论文草稿。在一个试点部署的eRevise在7个教室跨越5年级和6年级，在写作中的文本证据使用的质量提高后，学生收到形成性反馈，然后从事论文修订。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
