外语教学与研究

自动写作评阅反馈系统研究述评与展望

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  • 上海交通大学,上海,200240;
    University of California, Irvine, CA 92697;
    上海工程技术大学,上海,201620
张荔,博士,上海交通大学外国语学院副教授。主要研究方向为计算机辅助语言教学、学术英语写作。电子邮箱:zhangli@sjtu.edu.cn。MarkWarschauer,加利福尼亚大学欧文分校教育学院教授。主要研究方向为CALL、Cloud-BasedWriting、VirtualLearning。电子邮箱:markw@uci.edu。盛越,上海工程技术大学外国语学院副教授。主要研究方向为计算机辅助语言教学。电子邮箱:sheng.yue@163.com

网络出版日期: 2020-07-25

基金资助

*本研究受国家社科基金项目“基于语料库和云技术的网络自动作文评阅系统信效度及其辅助教学研究”(编号13BYY081)资助

Automated Essay Evaluation: Past, Present and Prospect

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Online published: 2020-07-25

摘要

文章论述了PEG、IEA、IntelliMetric、e-rater、BETSY这五种具有代表性的自动作文评阅(AES)系统的原理、特征、功能、优缺点,分析比较其共性和差异,论证其发展过程,总结和展望未来发展的若干特点:设计有助于提高学习者认知能力和辩证性思维能力的AES系统;评判重点从语言和结构转向论点思辨和修辞效果;能够对各种文体类型的作文进行评定;开发对写作过程提供形成性评估的AES系统;利用机器学习技术,设计开放式AES系统平台;开发和利用可进行人机对话的反馈模式;交叉学科的合作在系统发展中的作用将更为突出;逐步建立对多种语言的评分反馈功能。

本文引用格式

张荔, Mark Warschauer, 盛越 . 自动写作评阅反馈系统研究述评与展望[J]. 当代外语研究, 2016 , 16(06) : 54 -61 . DOI: 10.3969/j.issn.1674-8921.2016.06.009

Abstract

This paper gives an overview of the principles, features and functions of the most well known automated essay scoring systems, including PEG, IEA, e rater and Criterion, IntelliMetric and MY Access!, and BETSY. Reliabilities of these systems are analyzed, and strengths and weaknesses of each of the systems are compared and contrasted. The paper analyzes the future development of AES systems on the basis of the discussion of former researches and the model of cognitively based assessment of writing competency. It summarize the orientation of development in seven aspects: design of AES systems on cognitively based assessment model of writing competence; shift of emphasis from surface features of grammar and structure to underlying features of critical thinking and rhetorical effect; expansion of subject areas, with focus on both English language arts and scientific reasoning; development of a new genre of AES software that can provide meaningful and effective formative feedback to assist writing process; use of machine learning technology to develop an open AES system that can address new problems automatically; enhancement of feedback effect via machine student dialogue; integration and cooperation of various disciplines of studies in the field of AES.

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