Ziang Xiao 1, Michelle X. Zhou2, Wai-Tat Fu1

1University of Illinois at Urbana-Champaign,2Juji. Inc.


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.


        author = {Xiao, Ziang and Zhou, Michelle X. and Fu, Wat-Tat},
        title = {Who Should Be My Teammates: Using a Conversational Agent to Understand Individuals and Help Teaming},
        booktitle = {Proceedings of the 24th International Conference on Intelligent User Interfaces},
        series = {IUI '19},
        year = {2019},
        isbn = {978-1-4503-6272-6},
        location = {Marina del Ray, California},
        pages = {437--447},
        numpages = {11},
        url = {http://doi.acm.org/10.1145/3301275.3302264},
        doi = {10.1145/3301275.3302264},
        acmid = {3302264},
        publisher = {ACM},
        address = {New York, NY, USA},
        keywords = {chatbot, conversational agent, personality inference, team companion, team formation, teaming},