The Science and Practice of Team Science (2025) / Chapter Skim
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APPENDIX B 211 Wagner, C S., Roessner, J
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, 2015) , this appendix aims to equip readers with an understanding of the mechanisms that underpin successful team science by illuminating the processes that contribute to the evolution of high-functioning science teams.
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. Time not only influences the way teams operate but also provides valuable insights that can inform team science practices.
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By exploring both systems and temporal perspectives, we can gain insights into what makes these teams effective and how effective teams operate. Whether building, developing, or evaluating science teams, understanding the context in which they exist (i.e., a systems approach)
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Therefore, this section draws on both small-scale research from the science of team science to more extensive studies from organizational sciences to highlight the most important constructs and competencies of high-functioning science teams. FACTORS OF SUCCESSFUL SCIENCE TEAMS It is crucial to acknowledge that a wide array of factors contribute to team success across various contexts.
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. This shift is especially relevant for science teams, where different expertise and perspectives are essential.
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Shared leadership also has a demonstrated relationship with team performance. Faultlines One potential issue that can arise within science teams is the development of faultlines.
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Shared mental models can help science teams align on project goals, methodologies, and expected outcomes, ensuring that all members are working toward a unified vision. Meanwhile, transactive memory systems allow team members to efficiently leverage the expertise distributed across the team, enhancing problem-solving and innovation.
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Without effective team cognition, science teams may struggle with miscommunication, fragmented efforts, and missed opportunities for interdisciplinary collaboration. Therefore, fostering the development of shared mental models and transactive memory systems is essential to ensure that science teams can function cohesively and achieve their complex objectives.
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These go together with the emergent states, including trust, psychological safety, and shared mental models that evolve over time, creating an environment where team members feel safe to share ideas and collaborate effectively. The processes and emergent states mentioned here are particularly important for science teams given their interdisciplinary nature and the complexity of their goals.
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These characteristics are critical because they shape how teams within the system interact, coordinate, and ultimately achieve their shared objectives. In the context of science multiteam systems -- multiteam systems composed of science teams -- understanding these characteristics is important for ascertaining the most critical processes to focus on when developing and evaluating a science multiteam system.
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