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

EAGER：讨论跟踪器：人类语言技术的发展，以改善高中英语课堂协作论证的教学

• 批准号: 1842334
• 负责人: Amanda Godley
• 金额: $ 14.98万
• 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: 2018
• 资助国家: 美国
• 起止时间: 2018-09-01 至 2019-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1842334&HistoricalAwards=false
• 关键词: EAGER; Discussion; Tracker; Development; Human

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.

协作论证——通过对话建立基于证据的、理性的知识和解决方案——对于STEM和其他学科的个人学习和群体解决问题至关重要，也是21世纪工作场所的一个决定性特征。然而，合作论证教学是许多高中教师努力发展的一项高级技能。这项探索性研究的早期拨款探索了通过一个名为讨论跟踪器的计算机系统提高高中教师对协作论证和教学理解的可行性。原型系统借鉴了人类语言技术（HLT）的最新进展，为教师提供有关学生讨论的特征和质量的自动生成数据。该系统还就如何促进此类讨论为教师提供个性化指导。该项目有潜力培养新一代的教师和学生，使他们能够在未来的教育和工作环境中进行富有成效的合作论证。本研究的结果和成果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。调查计划分为三个阶段：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特征的图式，以确定最关键的话语特征。其次，开发了系统界面的原型，提供不同数量和类型的数据可视化以及对教师学习的明确指导。第三，为了分析教师学习的数据，进行了一系列实验，研究教师如何与系统的各种原型进行交互。为了测试最佳的教师学习，教师将被分配到两个条件中的一个：(1)使用该系统与一个简短的反思指南，旨在记录教师的观察和提示教师的教学变化；(2)使用该系统与一个专业的教学教练。教师学习将通过反思性、定性的大声思考协议、前后问卷调查和教学观察来研究。两种实验条件的结果将使用标准统计方法进行比较。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。