Mónica Muñoz Torres - University of Colorado Anschutz Medical Campus
Colleen Cuddy, Stanford University, School of Medicine
Jake Y. Chen, University of Alabama at Birmingham
Sean Davis, University of Colorado Anschutz Medical Campus
Pamela Foster, University of Alabama at Birmingham
Grace Gonzalez, University of Colorado, Denver
Goldie Komaie, University of Colorado, Denver
Janai Ravi, University of Colorado Anschutz Medical Campus
Sara J. Singer, Stanford University
Jamie Toghranegar, University of South Florida
Christine Velez, University of Colorado, Denver
Toyin Ajisaf, National Institutes of Health
Vikram Adithya Ganesh, University of Colorado Anschutz Medical Campus
Monica Munoz-Torres, University of Colorado Anschutz Medical Campus
While the Science of Team Science has produced robust theoretical frameworks for effective collaboration, a persistent implementation gap remains. Research teams often struggle to translate scholarly insights into sustainable daily routines, particularly in high-stakes, multi-institutional environments where time is scarce and data integration is complex. This poster presents the Bridge2AI Team Science Training Workshop, a five-hour, modular intervention specifically designed to move teams from conceptual understanding to immediate practical application.
The workshop's design addresses a critical necessity: while technical mastery is standard in scientific training, the formal social infrastructure required for high-stakes, transdisciplinary collaboration is often absent. By prioritizing the development of tangible artifacts, the curriculum moves beyond team dynamics theory to guide participants through six critical modules: Foundations, Communication Architecture, Governance, Data Sharing and Resource Management, Interdisciplinary Navigation, and Sustainability. Utilizing a variety of tools, such as the exploration of governance models and Hackman's and Edmondson's frameworks for leading teams, the training transforms abstract concepts into concrete outputs, such as the development of a Team Communication Charter, a Team Data Agreement for interoperability, privacy, and access, and a diagnostic Team Science Assessment.
A central innovation of this model is the “Monday Morning Protocol,†a suite of micro-pilots and implementation routines that team members can initiate immediately following the training. This approach directly addresses the knowing-doing gap by embedding team science practices into the existing workflow of complex research initiatives. In a post-workshop survey, participants said they appreciated concrete strategies, such as this protocol, and the knowledge that they could implement processes and structures to foster successful collaboration.
We include initial and anticipated outcomes, including enhanced understanding of team dynamics and best practices, and present a scalable, adaptable training model. By operationalizing team science theory into a scalable training model, the workshop supports faster, more trustworthy interdisciplinary collaboration in complex, multi-institutional research initiatives. The workshop content is available for attendees to reuse and adapt as appropriate: https://bridge2ai.github.io/teaming-training-workshop.