EAGER: Comprehension Assessment via Spoken Dialog

EAGER：通过口语对话进行理解评估

• 批准号: 1938024
• 负责人: Wayne Ward
• 金额: $ 15万
• 依托单位: University of Colorado at Boulder
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-08-01 至 2021-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1938024&HistoricalAwards=false
• 关键词: EAGER; Comprehension; Assessment; via; Spoken

My Science Tutor (MyST) is an intelligent virtual tutor for elementary school students that has been developed over the last 10 years, with over 13,000 spoken dialog sessions in 8 areas of science. Its goal is to assess student understanding of concepts rather than facts, which is very important to prepare students and the future workforce in STEM. This early-stage, exploratory EAGER project seeks to determine whether the analysis of a new corpora of data could advance the development and use of MyST so that teachers, curriculum developers and researchers could more easily develop automated assessments for new science topics. The approach will apply recent advances in deep learning techniques to assess students' conceptual understanding of science during spoken dialogs with the virtual tutor. The project is motivated by the recent availability of a corpus of examples suitable for training and testing the proposed system. Successful outcomes of the proposed research will result in a novel, robust and portable method for extracting semantic representations from student responses and comparing these to reference statements to determine if conceptual relationships are correctly expressed. The approach has the potential to remove the primary impediments to developing dialog-based assessments: grammar development or topic-specific training. This novel and untested approach is high-risk, but if successful, would have high-payoff, by allowing tutorial developers to only need to provide one example statement for each concept being discussed rather than having to explicitly specify all allowable ways that it could be expressed through development of grammars. This in turn could remove barriers to widespread development of spoken dialog systems and develop automated assessments for new topics using little or no training data.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.

My Science Tutor（MyST）是一个面向小学生的智能虚拟导师，在过去的10年里一直在开发，在8个科学领域拥有超过13，000个口语对话会话。它的目标是评估学生对概念的理解，而不是事实，这对学生和未来的STEM劳动力做好准备非常重要。 这个早期阶段的探索性EAGER项目旨在确定对新数据语料库的分析是否可以促进MyST的开发和使用，以便教师，课程开发人员和研究人员可以更容易地为新的科学主题开发自动化评估。该方法将应用深度学习技术的最新进展，以评估学生在与虚拟导师进行口头对话时对科学的概念理解。该项目的动机是最近可用的一个语料库的例子适合训练和测试拟议的系统。所提出的研究的成功结果将导致一种新颖的，强大的和便携式的方法，从学生的反应中提取语义表示，并将这些参考语句，以确定是否正确表达概念关系。这种方法有可能消除发展基于对话的评估的主要障碍：语法发展或特定主题的培训。 这种新颖且未经测试的方法是高风险的，但如果成功的话，将有很高的回报，因为它允许教程开发人员只需要为正在讨论的每个概念提供一个示例语句，而不必显式指定所有允许的方式，通过语法的开发来表达。这反过来又可以消除口语对话系统广泛发展的障碍，并使用很少或没有训练数据为新主题开发自动评估。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。