EXP: Development of Human Language Technologies to Improve Disciplinary Writing and Learning through Self-Regulated Revising

EXP：人类语言技术的发展，通过自我调节的修改来改善学科写作和学习

• 批准号: 1735752
• 负责人: Diane Litman
• 金额: $ 54.96万
• 依托单位: University of Pittsburgh
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-01 至 2022-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1735752&HistoricalAwards=false
• 关键词: EXP; Development; Human; Language; Technologies

Writing and revising are essential parts of learning, yet many college students graduate withoutdemonstrating improvement or mastery of academic writing. This project explores the feasibilityof improving students' academic writing through a revision environment that integrates naturallanguage processing methods, best practices in data visualization and user interfaces, andcurrent pedagogical theories. The environment will support and encourage students to developself-regulation skills that are necessary for writing and revising, including goal-setting, selectionof writing strategies, and self-monitoring of progress. As a learning technology, the environmentcan be applied on a large scale, thereby improving the writing of diverse student populations,including English learners. Additionally, the project's multidisciplinary training of graduatestudents is focused on increasing diversity in cyberlearning research and development. Three stages of investigation are planned. First, to analyze data on students' revision behaviors,a series of experiments are conducted to study interactions between studentsand variations of the revision writing environment. Second, the collected data forms the goldstandard for developing an end-to-end system that automatically extracts revisions betweenstudent drafts and identifies the goal for each revision. Multiple extraction algorithms areconsidered, including phrasal alignment based on semantic similarity metrics and deep learningapproaches. To identify the goal of a revision, a supervised classifier is trained from the goldstandard. A diverse set of features and the representations of the identified goals (e.g.,granularity, scope) are explored. In addition to the "extract-then-classify" pipeline, an alternativejoint sequence labeling model is also developed. The labeling of sequences is used torecognize revision goals and the sequences are mutated to generate possible corrections ofsentence alignments for revision extraction. The writing environment is iteratively refined,augmenting the interface prototyping through frequent user studies. Third, a completeend-to-end system that integrates the most successful component models is deployed incollege-level writing classes. Student progress is tracked across multiple assignments.

写作和修改是学习的重要组成部分，但许多大学生毕业时没有表现出学术写作的改进或掌握。该项目探讨了通过整合自然语言处理方法、数据可视化和用户界面的最佳实践以及当前教学理论的修订环境来提高学生学术写作的可行性。这种环境将支持和鼓励学生发展写作和修改所需的自我调节技能，包括目标设定，写作策略的选择和自我监控的进展。作为一种学习技术，环境可以大规模应用，从而改善包括英语学习者在内的各种学生群体的写作。此外，该项目对研究生的多学科培训侧重于增加网络学习研究和开发的多样性。计划进行三个阶段的调查。首先，为了分析学生修改行为的数据，作者进行了一系列的实验来研究学生之间的互动和修改写作环境的变化。其次，收集的数据形成了开发端到端系统的黄金标准，该系统可以自动提取学生草稿之间的修订，并确定每次修订的目标。考虑了多种提取算法，包括基于语义相似性度量的短语对齐和深度学习方法。为了识别修订的目标，从金标准训练监督分类器。一组不同的特征和所识别的目标的表示（例如，范围（scope）。除了“提取-然后-分类”流水线之外，还开发了交替联合序列标记模型。利用序列的标记来识别修改目标，并对序列进行变异以产生可能的句子对齐修正，从而进行修改提取。通过频繁的用户研究，不断地改进编写环境，增强界面原型。第三，一个完整的端到端系统，集成了最成功的组件模型，部署在学院级的写作课程中。学生的进步是通过多个作业跟踪。

项目成果

Quantifying the Evaluation of Heuristic Methods for Textual Data Augmentation

• DOI: 10.18653/v1/2020.wnut-1.26
• 发表时间: 2020-11
• 作者: Omid Kashefi;R. Hwa

Jointly Parse and Fragment Ungrammatical Sentences

联合分析和分割不合语法的句子

• 发表时间: 2018
• 期刊: Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence
• 作者: Hashemi, Homa B;Hwa, Rebecca
• 通讯作者: Hwa, Rebecca

ArgRewrite V.2: an annotated argumentative revisions corpus

ArgRewrite V.2：带注释的论证修订语料库

• DOI: 10.1007/s10579-021-09567-z
• 发表时间: 2022
• 期刊: Language Resources and Evaluation
• 影响因子: 2.7
• 作者: Kashefi, Omid;Afrin, Tazin;Dale, Meghan;Olshefski, Christopher;Godley, Amanda;Litman, Diane;Hwa, Rebecca
• 通讯作者: Hwa, Rebecca

Effective Interfaces for Student-Driven Revision Sessions for Argumentative Writing

学生主导的议论文复习课程的有效界面

• 发表时间: 2021
• 期刊: CHI '21: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
• 作者: Afrin, Tazin;Kashefi, Omid;Olshefski, Christopher;Litman, Diane;Hwa, Rebecca;Godley, Amanda
• 通讯作者: Godley, Amanda

An Automated Writing Evaluation System for Supporting Self-monitored Revising

支持自我监督修改的自动写作评估系统

• 发表时间: 2022
• 期刊: International Conference on Artificial Intelligence in Education
• 作者: Litman, D.;Afrin, T.;Kashefi, O.;Olshefski, C.;Godley, A.;Hwa, R.
• 通讯作者: Hwa, R.