Advancing the Use of Automated Dialogue Systems for Teaching Communication and Interpersonal Skills

该项目促进了技术的使用，以提高工人的沟通和人际交往能力。该项目追求的是一个短期愿景，即学生和工作人员将很快能够通过自动化教学代理接收会话练习和个性化教程反馈来增强他们的人际交往能力。通过实践有效的策略来处理常见的人际挑战，例如涉及沟通，团队合作，解决冲突，谈判或处理工作场所的偏见的挑战，学员将能够提高他们的就业能力，工作效率和职业机会。特别是，该项目直接支持妇女和代表性不足的少数民族在科学，技术，工程和数学（STEM）方面的教育和充分参与，解决他们在STEM职业中晋升的障碍。鉴于人际交往技能发展的广泛重要性，该项目的成果预计将产生广泛的影响，超出其核心研究学科，还包括法律和政治学，以及对工作技能培训和人力资源管理等应用的实际影响。该项目通过解决几个基本的科学和技术挑战，了解其有效性并实现这些系统的广泛部署。它通过使用最先进的口语对话系统技术来提供基于对话的培训，增强体验式学习的现实性，从而提高了以前基于菜单的培训方法的生态有效性。它通过开发新技术来解决将口语对话系统技术应用于人际技能培训的高开发成本，这些新技术降低了教授特定学习目标所需的劳动力和知识成本。最后，该项目设计和评估自动化系统可用于向受训者提供个性化评估和反馈的创新方法。该项目的目标是展示自动化，智能会话代理的潜力，以加强人际交往技能的体验式学习，并提高使用自动导师教授复杂的交际技能背后的科学。该项目计划包括对话代理的设计和实施，自动评估和反馈的新方法的开发，数据收集，以及该方法的培训效益的实证验证。预期的结果是提高对技术如何有效地应用于沟通和人际交往技能领域的一系列培训需求的理解。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。

This project advances the use of technology to improve worker communication and interpersonal skills. The project pursues a near-term vision that students and workers will soon be able to augment their interpersonal skills by receiving conversational practice and personalized tutorial feedback with automated teaching agents. By practicing effective strategies for handling common interpersonal challenges, such as challenges involving communication, working in teams, resolving conflicts, negotiation, or dealing with bias in the workplace, trainees will be able to enhance their employability, their on-the-job effectiveness, and their career opportunities. In particular, the project directly supports the education and full participation of women and underrepresented minorities in science, technology, engineering, and mathematics (STEM) by addressing identified obstacles to their advancement in STEM careers. Given the broad importance of interpersonal skills development, the project's results are expected to have wide-ranging impact extending beyond its core research disciplines to include also law and political science as well as practical impact for applications such as job skills training and human-machine teaming.This project advances the application of technology to interpersonal skills training by addressing several fundamental scientific and technical challenges in understanding their effectiveness and achieving broad deployment of these systems. It improves the ecological validity of previous menu-based training methods by using state-of-the-art spoken dialogue system technology to provide conversation-based training that enhances the realism of experiential learning. It addresses the high development costs of applying spoken dialogue system technology to interpersonal skills training by developing new techniques that reduce the costs in labor and knowledge required to teach specific learning objectives. Finally, the project designs and evaluates innovative methods that automated systems can use to provide individualized assessment and feedback to trainees. The objective of the project is to demonstrate the potential of automated, intelligent conversational agents to enhance the experiential learning of interpersonal skills, and enhance the science behind the use of automated tutors for teaching complex communicative skills. The project plan includes the design and implementation of a conversational agent, development of new approaches to automated assessment and feedback, data collection, and empirical validation of the training benefits of the approach. An expected outcome is an improved understanding of how technology can be effectively applied to a range of training needs in the areas of communication and interpersonal skills.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.