EAGER: Discussion Tracker: Development of Human Language Technologies to Improve the Teaching of Collaborative Argumentation in High School English Classrooms

协作论证-通过对话建立基于证据的推理知识和解决方案-对于STEM和其他学科的个人学习以及小组解决问题至关重要，也是21世纪世纪工作场所的定义特征。然而，教学合作论证是一个先进的技能，许多高中教师的斗争发展。EARLY探索性研究补助金旨在探索通过一个名为“讨论跟踪器”的基于计算机的系统来提高高中教师对协作论证和教学的理解的可行性。该原型系统利用人类语言技术（HLT）的最新进展，为教师提供自动生成的数据，他们的学生的讨论的特点和质量。该系统还就如何更好地促进这种讨论向教师提供个性化指导。该项目有可能为新一代的教师和学生做好准备，为他们未来的教育和工作场所环境进行富有成效的协作论证。本研究的结果和产品也有助于研究和技术创新，旨在改善高中英语课堂和其他内容领域，年级和学习平台的教师学习和学生讨论。此外，该项目的研究生和本科生的多学科培训的重点是增加多样性的网络学习的研究和development.Three阶段的调查计划，首先，高质量的合作论证在高中英语语言艺术（ELA）的讨论的功能模式创建和测试，以确定最关键的话语功能。其次，原型系统的界面开发，提供不同数量和类型的数据可视化和明确的指导教师学习。第三，为了分析教师学习的数据，进行了一系列的实验，研究教师如何与系统的各种原型的互动。为了测试最佳的教师学习，教师将被分配到两个条件之一：（1）使用该系统与简短的反思指南，旨在记录教师的意见，并提示教师的教学变化，（2）使用该系统与专家教学教练。教师的学习将通过反思，定性的思考出声协议，前后问卷调查，并观察教学。两个实验条件的结果将使用标准的统计方法进行比较。该奖项反映了NSF的法定使命，并已被认为是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的支持。

Collaborative argumentation - the building of evidence-based, reasoned knowledge and solutions through dialogue - is essential to individual learning as well as group problem-solving in STEM and other disciplines and a defining characteristic of 21st century workplaces. However, teaching collaborative argumentation is an advanced skill that many high school teachers struggle to develop. This EArly Grant for Exploratory Research explores the feasibility of improving high school teachers' understanding of collaborative argumentation and instruction through a computer-based system called Discussion Tracker. The prototype system draws upon recent advances in human language technologies (HLT) to provide teachers with automatically generated data about the characteristics and quality of their students' discussions. The system also provides individualized guidance for teachers on how to improve the facilitation of such discussions. The project has the potential to prepare a new generation of teachers and students for the productive collaborative argumentation they will need for future educational and workplace settings. Findings and products resulting from this study also contribute to research and technological innovations aimed at improving teacher learning and student discussions in high school English classrooms and other content areas, grade levels, and learning platforms. Additionally, the project's multidisciplinary training of graduate and undergraduate students is focused on increasing diversity in cyberlearning research and development.Three stages of investigation are planned, First, a schema of the features of high-quality collaborative argumentation in high school English language arts (ELA) discussions is created and tested in order to identify the most critical discourse features. Second, prototypes of the system's interface is developed that provide varied amounts and types of data visualizations and explicit guidance for teacher learning. Third, in order to analyze data on teacher learning, a series of experiments are conducted to study how teachers interact with various prototypes of the system. In order to test optimal teacher learning, teachers will be assigned to one of two conditions: (1) Use of the system with a brief reflection guide, designed to document teachers' observations and prompt teachers' instructional changes, (2) Use of the system with an expert instructional coach. Teacher learning will be studied through reflective, qualitative think aloud protocols, pre-post questionnaires, and observations of instruction. Outcomes of the two experimental conditions will be compared using standard statistical methods.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.