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，但是许多大学生毕业，而没有证明改进或掌握学术写作。该项目通过修订环境探讨了改善学生的学术写作的可行性，该修订环境集成了自然语言处理方法，数据可视化和用户界面的最佳实践，以及库流的教学理论。环境将支持和鼓励学生发展为写作和修改所必需的自我调节技能，包括制定目标，编写策略的选择以及对进步的自我监控。作为一种学习技术，环境可以大规模应用，从而改善了包括英语学习者在内的不同学生人数的写作。此外，该项目对毕业生的多学科培训重点是增加网络学习研发的多样性。计划进行三个调查阶段。首先，为了分析学生的修订行为数据，进行了一系列实验，以研究学生与修订书写环境之间的互动。其次，收集到的数据构成了制定端到端系统的金色标准，该系统自动提取了调查的草稿之间的修订，并确定每个修订的目标。多种提取算法的思想，包括基于语义相似性指标和深度学习方法的短语对齐。为了确定修订的目标，监督分类器将从金标准进行训练。探索了一组各种特征和确定目标的表示（例如粒度，范围）。除了“提取到分类”管道之外，还开发了替代连接序列标记模型。序列的标记被使用，并将序列变为突变，以生成可能的纠正措施，以进行修订提取。写作环境是迭代精致的，通过频繁的用户研究来增强接口原型。第三，整合最成功的组件模型的完整到端系统是部署的Incollege级写作类。在多个任务中跟踪学生进度。

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

Semantic Pleonasm Detection

• DOI: 10.18653/v1/n18-2036
• 发表时间: 2018-06
• 作者: Omid Kashefi;A. Lucas;R. Hwa

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