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

协作辩论--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和集体问题解决至关重要，也是21世纪工作场所的一个显著特征。然而，协作议论教学是许多高中教师努力培养的一项高级技能。这项早期的探索性研究补助金探索了通过一个名为讨论追踪器的基于计算机的系统来提高高中教师对协作辩论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，为教师提供关于学生讨论的特征和质量的自动生成数据。该系统还为教师提供个性化的指导，指导他们如何改进这种讨论的便利性。该项目有可能为新一代教师和学生做好准备，以便他们在未来的教育和工作场所环境中进行富有成效的协作辩论。这项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、年级水平和学习平台中的教师学习和学生讨论。此外，该项目对研究生和本科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。计划了三个阶段的调查，首先，创建并测试高中英语语言艺术(ELA)讨论中高质量协作论证的特征，以确定最关键的语篇特征。其次，开发了系统界面的原型，为教师的学习提供了不同数量和类型的数据可视化和明确的指导。第三，为了分析教师学习的数据，进行了一系列实验来研究教师如何与系统的不同原型进行交互。为了测试最佳的教师学习，教师将被分配到两种情况之一：(1)使用带有简短反思指南的系统，旨在记录教师的观察并促使教师进行教学更改；(2)使用系统和专家教学教练。教师的学习将通过反思性的、定性的有声思考方案、事后问卷调查和教学观察来研究。这两个实验条件的结果将使用标准的统计方法进行比较。这一奖项反映了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。

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.