Who should be my teammates: using a conversational agent to understand individuals and help teaming

Ziang Xiao, Michelle X. Zhou, W. Fu
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引用次数: 41

Abstract

We are building an intelligent agent to help teaming efforts. In this paper, we investigate the real-world use of such an agent to understand students deeply and help student team formation in a large university class involving about 200 students and 40 teams. Specifically, the agent interacted with each student in a text-based conversation at the beginning and end of the class. We show how the intelligent agent was able to elicit in-depth information from the students, infer the students' personality traits, and reveal the complex relationships between team personality compositions and team results. We also report on the students' behavior with and impression of the agent. We discuss the benefits and limitations of such an intelligent agent in helping team formation, and the design considerations for creating intelligent agents for aiding in teaming efforts.
谁应该成为我的队友:使用会话代理来理解个人并帮助团队合作
我们正在构建一个智能代理来帮助团队合作。在本文中,我们研究了这种智能体在现实世界中的应用,以深入了解学生,并帮助一个涉及约200名学生和40个团队的大型大学班级的学生团队组建。具体来说,代理在课程开始和结束时与每个学生进行基于文本的对话。我们展示了智能代理如何能够从学生那里获得深入的信息,推断学生的人格特征,并揭示了团队人格构成与团队结果之间的复杂关系。我们还报告了学生对中介的行为和印象。我们讨论了这种智能代理在帮助团队形成方面的优点和局限性,以及创建智能代理以帮助团队工作的设计考虑。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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