ProWrite: Biometric technology for improving college students writing processes

大学水平写作教学的一个主要内容是学生收到的关于他们所写文章的个性化反馈。这种反馈的目的是帮助学生理解他们在当前的文本中可以做得更好，但也帮助他们学习如何在未来成为一个更有效的作家。然而，这种反馈集中在书面产品的属性上（即，好的文本应该是什么样的）而不是基于写作的过程（即，如何写一篇好的文章（）。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时每刻的行动的证据。这个Cyberlearning项目将开发一个智能写作辅导系统ProWrite，该系统将使用不显眼的生物识别技术自动捕捉这种时刻的动作，然后向学生提供关于写作过程的数据驱动，个性化，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：而不是简单地告诉学生尝试一个特定的策略，ProWrite将提供一个指导写作会议，学生将收到实时，自动脚手架的目标策略。这种类型的智能辅导系统在写作教学的背景下，如果有效，具有大规模应用的潜力，因此，经济和教育收益。具体来说，该项目将利用可部署的，组合的，时间对齐的日志记录和眼动跟踪（1）精确诊断学生的写作过程中可能会阻止他们产生高质量文本的问题，（2）提供个性化的写作策略建议，用于补救，（3）自动地和真实的地为学生将这些新策略应用于他们自己的写作搭建支架。为此，研究人员将开发一个用于写作过程分析的自动化端到端管道，其中包括（1）基于键间间隔统计建模的停顿检测，（2）眼动模式分类，以及（3）从注释的写作过程语料库中学习的草稿内修订分类。研究活动将分为四个阶段。在第一阶段，研究人员将收集和注释书写过程数据集（书写日志、眼动日志和最终文本），然后将其公开。第二阶段的重点是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，包括大约六个小规模的系统开发和评价迭代。在第三阶段，系统功能将被扩展，以包括更大的一组可诊断的写作过程问题，一系列新的迭代涉及更多的参与者。最后，第四阶段将在一项随机对照研究中评估系统的有效性，该研究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益处进行强有力的测试。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估来支持。

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.