Beyond Team Makeup: Diversity in Teams Predicts Valued Outcomes in Computer-Mediated Collaborations

Collaborative Learning & Peer TeachingComputational Methods in HCIUniversity Professors & ResearchersHCI Researchers

In an increasingly globalized and service-oriented economy, people need to engage in computer-mediated collaborative problem solving (CPS) with diverse teams. However, teams routinely fail to live up to expectations, showcasing the need for technologies that help develop effective collaboration skills. We take a step in this direction by investigating how different dimensions of team diversity (demographic, personality, attitudes towards teamwork, prior domain experience) predict objective (e.g. effective solutions) and subjective (e.g. positive perceptions) collaborative outcomes. We collected data from 96 triads who engaged in a 30-minute CPS task via videoconferencing. We found that demographic diversity and differing attitudes towards teamwork predicted impressions of positive engagement, while personality diversity predicted learning outcomes. Importantly, these relationships were maintained after accounting for team makeup. None of the diversity measures predicted task performance. We discuss how our findings can be incorporated into technologies that aim to help diverse teams develop CPS skills.

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https://hci.top/en/papers/chi/32142/2020

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DOI: https://doi.org/10.1145/3313831.3376279
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CHI
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Year
2020
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4 authors
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Subtopics
Collaborative Learning & Peer Teaching, Computational Methods in HCI
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University Professors & Researchers, HCI Researchers
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Abstract only
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