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ProWrite: Biometric technology for improving college students writing processes

ProWrite：生物识别技术改善大学生写作过程

基本信息

批准号：
2016868
负责人：
Evgeny Chukharev
金额：
$ 75万
依托单位：
Iowa State University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2020
资助国家：
美国
起止时间：
2020-10-01 至 2024-09-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2016868&HistoricalAwards=false
关键词：
ProWrite Biometric technology improving college

项目摘要

A staple of college-level writing instruction is individualized feedback that students receive about the texts that they write. This feedback is intended to help students understand what they could have done better in the current text, but also to help them learn how to be a more effective writer in the future. However, this feedback focuses on properties of written products (i.e., what a good text is supposed to look like) rather than on the process of writing (i.e., what to do while writing in order to produce a good text). This is because texts that students submit to instructors for feedback bear little (if any) evidence of the moment-by-moment actions taken by the writer in the process of composition. This Cyberlearning project will develop an intelligent tutoring system for writing, ProWrite, that will automatically capture such moment-by-moment actions using unobtrusive biometric technology, and then provide data-driven, personalized, actionable feedback about the composition process to the student. This feedback will take the form of focused strategy guidance: Instead of simply telling the student to try out a particular strategy, ProWrite will provide a coached writing session where the student will receive real-time, automatic scaffolding for the target strategy. This type of intelligent tutoring system in the context of writing instruction, if effective, has the potential for massive application and, therefore, economic and educational gain.Specifically, this project will utilize deployable, combined, time-aligned keystroke logging and eye tracking to (1) precisely diagnose issues with a student's writing process that may be preventing them from producing high-quality texts, (2) provide individualized writing-strategy advice for remediation, and (3) scaffold, automatically and in real time, the student applying these new strategies to their own writing. To this end, the researchers will develop an automated end-to-end pipeline for writing-process analysis that will include (1) pause detection based on statistical modeling of inter-key intervals, (2) classification of eye movement patterns, and (3) classification of within-draft revisions learned from an annotated corpus of writing processes. Research activities will be organized into four phases. In the first phase, the researchers will collect and annotate a dataset of writing-process data (keystroke logs, eye movement logs, and final texts), which will then be made publicly available. The second phase, focusing on the development of a first prototype of the full system, will follow the design-based research approach and consist of approximately six small-scale iterations of system development and evaluation. In Phase 3, system functionality will be expanded to include a larger set of diagnosable writing-process issues, with a new series of iterations involving more participants. Finally, Phase 4 will evaluate system efficacy in a randomized controlled study designed to provide a robust test of the benefits of process-focused feedback over currently-used instructional approaches.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

大学水平的写作教学的一个主要内容是学生收到的关于他们所写的文本的个性化反馈。这一反馈旨在帮助学生了解他们在当前课文中可以做得更好的地方，也帮助他们学习如何在未来成为一名更有效的作家。然而，这种反馈侧重于书面产品的属性(即，一个好的文本应该是什么样子的)，而不是写作的过程(即，为了产生一个好的文本，在写作时应该做什么)。这是因为学生提交给教师反馈的文本几乎没有(如果有的话)作者在写作过程中所采取的每一分钟行动的证据。这个网络学习项目将开发一个智能写作辅导系统ProWite，它将使用不引人注目的生物识别技术自动捕捉这些时刻的动作，然后向学生提供关于写作过程的数据驱动的、个性化的、可操作的反馈。这种反馈将采取有针对性的策略指导的形式：ProWite将提供一个有指导的写作课程，学生将在其中接受实时的、自动的目标策略支架，而不是简单地告诉学生尝试特定的策略。在写作教学中，这种类型的智能辅导系统如果有效，将具有大规模应用的潜力，从而获得经济和教育收益。具体地说，该项目将利用可部署的、组合的、时间一致的击键记录和眼球跟踪来(1)准确地诊断学生写作过程中可能阻碍他们产生高质量文本的问题，(2)为补救提供个性化的写作策略建议，以及(3)脚手架，学生自动和实时地将这些新策略应用到他们自己的写作中。为此，研究人员将开发一种自动化的端到端写作过程分析管道，其中将包括(1)基于键间间隔统计建模的停顿检测，(2)眼动模式的分类，以及(3)从带注释的写作过程语料库学习的草稿内修改的分类。研究活动将分四个阶段进行。在第一阶段，研究人员将收集和注释书写过程数据(击键日志、眼球运动日志和最终文本)的数据集，然后将其公开。第二阶段侧重于开发整个系统的第一个原型，将遵循以设计为基础的研究方法，包括大约六次系统开发和评价的小规模迭代。在第三阶段，系统功能将扩展到包括更多可诊断的书写过程问题，以及涉及更多参与者的一系列新的迭代。最后，第四阶段将在随机对照研究中评估系统效能，旨在对以过程为中心的反馈相对于当前使用的教学方法的好处进行稳健的测试。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。