6

Forward-Looking Research Recommendations and Infrastructure Needs

This report has discussed the existing research on science teams, as well as research on teams more generally, with particular attention to best practices, external support, and evaluation. Team science has already demonstrated benefits in innovation and problem-solving, and there is reason to believe that strengthening both the way team science is performed and the way it is researched and supported would strengthen these benefits and lead to more effective teams. This final chapter reviews the subjects discussed in the previous chapters and assesses needs for additional research specific to the science of team science.

BEST PRACTICES

The current literature on science teams indicates a pressing need for systematic empirical research to evaluate interventions in real-world team settings. While numerous best practices and interventions have been identified, much of the supporting evidence remains anecdotal or correlational. Chapter 3 highlights how most studies are primarily case based or correlation driven, leaving a gap in experimentally validated best practices that can be applied widely across various team science contexts. By funding real-time studies, research sponsors can facilitate rigorous experimental research that could lead to more generalizable and reliable data, fostering the development of evidence-based guidelines that directly improve team science processes and outcomes. Table 3-1 in Chapter 3 details possible future research questions to address that would strengthen the evidence for best practices.

Science teams often encounter a variety of challenges, ranging from interdisciplinary differences to unique project requirements and team compositions. Thus, interventions need to be tailored to each team’s specific circumstances to enhance effectiveness. Chapter 3 notes the diversity of team needs and configurations, which affect the efficacy of interventions labeled as “best practices.” For example, research shows that establishing norms around tool use needs to account for individual team characteristics, such as team composition and the cultural or linguistic backgrounds of team members, to promote efficient collaboration. Consequently, a reflexive approach that adapts practices based on each team’s requirements and experiences can lead to more effective team functioning. This tailored approach not only respects the unique nature of each science team but also encourages team members to critically evaluate and refine their workflows, fostering adaptability and resilience.

Virtual collaboration tools, if thoughtfully selected and integrated, can address geographic and temporal challenges that often arise in hybrid or distributed teams. Chapter 3 emphasizes that these tools need to be evaluated based on their alignment with team configuration, accessibility needs, and the skills of team members. For example, ensuring that tools include features such as screen sharing, closed captioning, and language translation can help accommodate team needs, increasing participation and improving communication. However, improper or inconsistent use of these tools can hinder trust and create conflict, particularly if team members feel that tools lack transparency or do not provide a secure environment for open communication.

Moreover, periodic reassessment of tool efficacy is recommended as team compositions and technological options evolve. Regularly revisiting tool usage norms can help avoid potential misalignments between team needs and available functionalities, ensuring that the technology remains a facilitator rather than a barrier to effective collaboration. The evolving nature of team science necessitates a flexible approach to tool integration, underscoring the importance of establishing clear norms and ensuring that all members are adequately trained to use these tools effectively.

In summary, supporting science teams through tailored approaches, well-integrated virtual tools, and robust research funding are essential for enabling effective and adaptable team science practices. These recommendations reflect the heterogenous configurations and complex dynamics of science teams, underscoring the importance of real-time research, a flexible methodology, and carefully chosen virtual collaboration tools to foster productive and resilient scientific collaboration.

INSTITUTIONAL AND EXTERNAL SUPPORT

As discussed in Chapter 4, a comprehensive institutional approach is critical to support successful team science outcomes. This includes considering team science in decisions regarding personnel, funding, incentives, technology, and policy. However, many institutions lack clear practices or infrastructure for facilitating such a holistic approach, and limited research exists to identify which specific supports are most effective in fostering successful team science environments. Institutional challenges, such as inadequate incentives for teamwork in promotion and tenure criteria, limited access to collaborative technologies, and lack of administrative support, can all hinder team performance. To optimize team science, more research is needed to understand how institutional practices influence collaboration outcomes, allowing for the development of informed strategies for supporting effective teamwork.

To advance team science, funders and institutions need to encourage best practices by recognizing team science contributions in hiring, tenure, promotion, and awards. Traditional evaluation methods, such as publication count and grant funding, often overlook collaborative efforts and are disadvantageous to scientists involved in cross-disciplinary projects. Revising these criteria to value team science roles—such as leadership in large projects and contributions to shared research outcomes, as well as additional contributions that may include mentoring, community-based research, and other work—would incentivize engagement and address current disincentives. Additionally, simplifying data sharing, open-science practices, and ethical review processes can alleviate administrative burdens on science teams, thereby enhancing collaboration. For instance, open-science frameworks that support sharing data and research products streamline workflows and promote transparency, benefiting both individual scientists and their teams.

Active support from funders for research on team science effectiveness is also crucial. Investing in studies on team science competencies, the impact of professional development (e.g., workshops, courses), and metrics to evaluate development of these competencies will provide insights into optimizing team dynamics. This includes research on how incentives affect team science prevalence and success across institutions, helping funders understand and refine policies that foster collaboration. Furthermore, studies examining institutional support structures—like research development professionals and team facilitators—can reveal their contributions to project efficiency and success. For a sustained impact, funders and institutions need to ensure accountability in adapting policies to support team-based science effectively. Addressing these areas comprehensively will not only support team science but also contribute to high-quality, impactful scientific outcomes across disciplines.

EVALUATION

To effectively evaluate science team outcomes, funders, institutions, and researchers need to prioritize three core questions that capture the essential aspects of team effectiveness: the social processes within the team, the tangible outputs produced, and the positive impact on individual members. Evaluating team dynamics, including social processes such as communication, cohesion, and psychological safety, is fundamental, as these factors directly influence a team’s ability to collaborate and achieve high performance. Research suggests that well-functioning social processes foster trust, reduce conflict, and enable teams to address complex tasks more efficiently.

Evaluating outputs—such as publications, patents, and other research deliverables—enables a direct assessment of the team’s productivity and contributions to scientific knowledge. By measuring both quantity and quality of these outputs, evaluators can gain insights into the team’s innovative capacity and impact within the broader scientific community. That said, evaluation needs to move beyond that which is easily counted. This can include the study of how scientific collaborations adapt scientific concepts, how they change professional networks and societies, as well as the nature and form of material artifacts produced. Additionally, understanding the broader impact of these outputs, including societal or policy contributions, provides a comprehensive view of the team’s success.

Finally, assessing the team’s impact on individual members is crucial, as participation in team science can significantly affect career development, professional satisfaction, and future collaborative opportunities. Positive experiences within science teams can lead to personal growth, expanded professional networks, and improved career trajectories. Emphasizing individual well-being and professional development aligns with the evolving goals of modern scientific research, which increasingly prioritizes inclusivity and career sustainability for team members. For a comprehensive evaluation, funding agencies and institutions can consider multiple evaluation criteria tailored to specific team goals, resources, and evaluation purposes. A multidimensional evaluation approach that captures short- and long-term outcomes enables a nuanced understanding of team performance, guiding future investments and fostering a supportive environment for team science initiatives to thrive.

IDENTIFICATION OF RESEARCH GAPS

While there has been substantial application of team science principles derived from the social and organizational sciences (e.g., social and organizational psychology, organizational behavior, cognitive science), the

empirical basis for applying these insights to science teams is still limited. This gap is crucial to address, as science teams are distinct from the types of teams typically studied outside of science, raising concerns about the generalizability of these findings. The committee suggests that a better understanding of these distinctions requires context-specific research focused on the unique structures and dynamics of science teams.

Funders need to provide more funding mechanisms for the scientific study of science teams. Indeed, major funding bodies such as the National Science Foundation and National Institutes of Health emphasize the critical importance of team science in solving complex global problems, but the support needed to fund the study of science teams is lacking. This disparity is problematic given the complexity of studying science teams, which requires both significant financial resources and specialized methodological approaches tailored to scientific collaboration contexts.

CONCLUSION AND RECOMMENDATION

Conclusion 6-1: The research translating findings on the functioning of teams general to the functioning of science teams is incomplete for reasons that include insufficient funding and a lack of professional recognition and reward for the study of science teams. Specifically needed are:

• Studies focused on the science team context that explore the application of existing theories to the unique processes and dynamics that distinguish science teams from traditional organizational teams.
• Studies of team science competencies and interventions that allow for robust statistical analyses or pre- and post-testing to build the empirical evidence base for team science learning, training, and professional development in real time.
• Data-driven research, including longitudinal studies, to better understand team science outcomes.
• Research to identify and investigate institutional policies and practices that reinforce or serve as barriers to team science, such as the support structures universities can provide (e.g., research development professionals, team facilitators), how these affect team science processes and outcomes, and other incentives that influence the conduct of team science.
• Research into the effectiveness of virtual collaboration tools and how these relate to the specific configuration of hybrid and virtual teams, including factors such as geographic distribution, temporal dynamics, and communication needs.

Recommendation 6-1: Funders interested in supporting the conduct of science should prioritize research on, and provide sufficient funding for, the application of findings from the broader study of teams to the science context. Areas of prioritization may include but are not limited to studies that incorporate both qualitative and quantitative data to build empirical evidence about the science context and research evaluating institutional policies and supports for science teams.