Strengthening the ecosystem for effective team science: A case study from University of California, Irvine, USA

Community member post by Dan Stokols, Judith S. Olson, Maritza Salazar and Gary M. Olson

Dan Stokols (biography)

How can an ecosystem approach help in understanding and improving team science? How can this work in practice?

An Ecosystem Approach

Collaborations among scholars from different fields and their community partners are embedded in a multi-layered ecosystem ranging from micro to macro scales, and from local to more remote regions. Ecosystem levels include:

Judith S. Olson (biography)
  • individual members of teams;
  • the teams to which they belong viewed as organizational units;
  • the broader institutional contexts (eg., universities, research institutes) that support multi-team systems; and,
  • their community and societal milieus (eg., science policies and priorities established by national and international agencies and foundations).
Maritza Salazar (biography)

The success of team-based scholarly and translational initiatives depends on circumstances and events at each of these ecosystem levels and the extent to which they are aligned. For instance, the capacity of a science team to create and apply new knowledge is dependent on the task-specific abilities, interpersonal skills, training, and diverse attributes that individuals bring to their teams. Similarly, the viability and productivity of the team is impacted by the support it receives from institutional leaders and research funding agencies.

Gary M. Olson (biography)

The Team Science Acceleration Lab at the University of California, Irvine

We focus especially on the university-institutional level of the ecosystem and describe an initiative at the University of California, Irvine, USA designed to promote successful cross-disciplinary collaboration on our campus.

We recognize the interdependencies that exist among initiatives undertaken at an institutional level and other facets of the ecosystem, including the importance of articulating university team science programs with the concerns and priorities of community partners and national organizations. The national level is illustrated by the fact that many funding agencies now require cross-disciplinary applicant teams to submit collaboration plans as part of their research proposals. These multiple facets of the team science ecosystem are shown in the figure below.

Key facets of the team science ecosystem, including individual core competencies (orange), a team and its immediate socio-spatial environment (yellow), the institutional contexts of spatially distributed multi-team systems (blue), and broader community and societal influences on team science (green). Links between institutional and societal levels of the ecosystem are denoted by the bi-directional green arrows connecting a particular team (Team 1 or T1) at the center of the diagram with its local environmental, institutional and societal contexts (the yellow, blue, and green circles, respectively). Interdependencies between the team and its immediate socio-spatial environment are shown by the bi-directional purple arrows connecting the orange and yellow circles. In some collaborations, a team must coordinate with spatially removed partners located either at the same institution or at others (eg., multi-team systems spanning two or more universities at the institutional level, and non-academic partners situated in the outermost green circle). These multi-team transactions are denoted in the diagram by the bi-directional pink arrows linking Teams 1, 2, 3, and 4 (T1, T2, T3, T4) (Copyright: Dan Stokols, Judith Olson, Maritza Salazar and Gary Olson).

Establishing a campus culture that supports cross-disciplinary team research requires a comprehensive approach—one that eliminates potential barriers to effective collaboration, and creates structural supports to incentivize inter-departmental, inter-school, and university-community partnerships. From an ecological systems perspective, there are several different “leverage points” within institutional settings that can be aligned so that, together, they exert a positive synergistic influence on faculty and administrators’ efforts to promote cross-disciplinary team science. Six facets of the university-institutional ecosystem that we are initially targeting are:

  1. Ensuring that campus-wide long-range plans emphasize excellence in team science as a strategic institutional goal;
  2. Implementing new promotion and tenure criteria that recognize and reward collaborative contributions to scholarship and translational research, and tools to assist faculty candidates in articulating their contributions to collaborative research as an integral part of personnel reviews;
  3. Establishing equitable criteria for sharing credit among multiple investigators on inter-departmental and inter-school extramural grants;
  4. Allocating seed funding to support the development of new team science initiatives and research centers;
  5. Consulting with facilities planners on the design of team research spaces; and,
  6. Designing and implementing team science workshops and certification courses for faculty and students.

Specific examples of our activities at the Team Science Acceleration Lab include:

  • Working with the university’s Task Force on Interdisciplinarity to ensure that excellence in team science is reflected in the allocation of graduate research and teaching stipends to doctoral candidates working with interdisciplinary research centers and training programs on campus;
  • Planning a campus-wide “Team Science Celebration” event to draw attention to the importance of collaborative scholarship and translational research;
  • Consulting with campus planners on the design of a collaborative research building for the Applied Innovation Institute, which promotes university-community partnerships;
  • Helping develop and implement equitable credit-sharing accounting strategies to incentivize faculty participation in the development of inter-departmental extramural grant proposals and research centers;
  • Developing a new website of team science resources for faculty, students, and administrators;
  • Creating and evaluating a Collaborative Contributions List to help faculty engaged in collaborative scholarship articulate the ways that they’ve contributed to team-based projects as they compile their dossiers for promotion and tenure reviews; and,
  • Presenting team science workshops and courses for departmental and school research directors, members of cross-disciplinary centers and teams (both existing and emerging), and other interested faculty, graduate students, and postdoctoral trainees.

Conclusion

By adopting an ecosystem model for advancing successful team science, we hope to achieve greater synergy toward establishing a campus culture that supports cross-disciplinary discovery, teaching, and translational research. Do you have relevant experience to share? Do you have suggestions for a longitudinal, multi-method study that we’re planning to assess our institution’s cumulative progress toward strengthening cross-disciplinary scholarship, training, and implementation research? We welcome your comments and suggestions.

Further reading:
Bennett, L. M., Gadlin, H. and Marchand, C. (2018). Collaboration and team science field guide. 2nd ed. National Cancer Institute, Bethesda, Maryland, United States of America. Online: https://www.cancer.gov/about-nci/organization/crs/research-initiatives/team-science-field-guide

Börner, K., Contractor, N., Falk-Krzesinski, H. F., Fiore, S. M., Hall, K. L., Keyton, J., Spring, B., Stokols, D., Trochim, W. and Uzzi, B. (2010). A multi-level perspective for the science of team science. Science Translational Medicine, 2, 45

Hall, K., Crowston, K. and Vogel, A. (2014). How to write a collaboration plan. Online: https://www.teamsciencetoolkit.cancer.gov/Public/TSResourceBiblio.aspx?tid=3&rid=3119

Klein, J. T. and Falk-Krzesinski, H. J. (2017). Interdisciplinary and collaborative work: Framing promotion and tenure practices and policies. Research Policy, 46, 6: 1055–61

Zaccaro, S. J., Marks, M. and DeChurch, L. (2012). Multi-team systems: An introduction. In, S. J. Zaccaro, L. DeChurch and M. Marks (Eds).  Multiteam systems: An organization form for dynamic and complex environments, Routledge-Taylor and Francis: London, United Kingdom: pp. 3-32

Acknowledgement:
We thank University of California, Irvine’s Office of Research, Office of Academic Affairs, and Institute for Clinical and Translational Science for their support of this initiative.

Biography: Dan Stokols is Chancellor’s Professor Emeritus at the University of California, Irvine, USA and served as founding Dean of the university’s School of Social Ecology. His research spans the fields of social ecology, environmental and ecological psychology, public health, and transdisciplinary team science. He is author of Social ecology in the digital age and co-author of Enhancing the effectiveness of team science.

Biography: Judith S. Olson is the Donald Bren Professor of Information and Computer Sciences Emerita in the Department of Informatics at the University of California, Irvine, USA. For over 20 years, she has researched teams whose members are not collocated. She co-authored (with Gary Olson) Working together apart: Collaboration over the internet.

Biography: Maritza Salazar is an assistant professor at the Paul Merage School of Business at the University of California, Irvine, USA. Her research focuses on learning and innovation in teams and organizations, especially enhancing the competitiveness of firms, the effectiveness of teams, and the quality of the work experience for individuals. She serves as President of the International Network for the Science of Team Science (INSciTS).

Biography: Gary M. Olson is Professor Emeritus and formerly Donald Bren Professor of Information and Computer Sciences at the University of California, Irvine, USA. The focus of his work has been on how to support small groups of people working on difficult intellectual tasks, particularly when the members of the group are geographically distributed. He co-edited (with Ann Zimmerman and Nathan Bos) Scientific collaboration on the internet.

 

Tracking stakeholder engagement and research impact

Community member post by Cathy Day

Cathy Day (biography)

Is there an easy and efficient way to keep track of stakeholder engagement and research impact?

My colleagues and I have developed a system with two components: (1) noting engagement and impact soon after they occur and (2) recording them in a way that enables the information to be extracted for whatever purpose is required. I describe the tracking spreadsheet, the recording process we use and then how the spreadsheet is used for reporting.

Tracking spreadsheet

The Microsoft Excel tracking spreadsheet has two parts: (1) the engagement or impact and (2) the research to which these are related. These are arranged in columns, which can be adapted for the needs of any particular group.

As shown in the extract from the spreadsheet below, the columns we use for engagement and impact are:

  • date of engagement/impact
  • activity
  • details
  • engagement (Yes/No)
  • impact (Yes/No)
  • lead researcher
  • other researchers.

For ‘activity’ we use a one- or two-word description selected from a dropdown list for the following activities:

  • media engagement (writing for or speaking about research)
  • media interest (report by the media on our research, without involving the researcher)
  • department contact (working with a national or state government body)
  • government contact (meeting or working with members of parliament)
  • stakeholder engagement
  • commissioned work
  • appointment (to a statutory or advisory body)
  • keynote address
  • conference presentation.

By minimising choice here, we can search and sort efficiently, depending on the particular purposes, such as university reporting requirements.

Extract from a tracking spreadsheet showing engagement (Eng) and impact (Imp) (supplied by Cathy Day)

As can be seen in the extract from the spreadsheet below, the columns we use for research are:

  • theme
  • project or sub-theme
  • paper/research/presentation
  • date of research
  • project identifier (not shown)
  • notes (not shown).

Our research group categorises all our investigations into broad, overarching themes such as ‘indigenous health’, ‘cardiovascular disease’ or ‘methods’, and these are provided in a drop-down list. The sub-theme or project column offers more detailed options such as ‘tobacco’, ‘social inequalities’, and ‘big data’.

Extract from a tracking spreadsheet showing research (supplied by Cathy Day)

Recording engagement and impact

Our entire research group meets fortnightly to keep each other informed of our work, to share ideas and to report to each other on all aspects of progress. These fortnightly group meetings include a standing agenda item on engagement and impact. At this point in the meeting, researchers inform each other of activity within the last fortnight including media coverage of their research, stakeholder engagement, advice provided to federal and state government agencies, collaborations with health-related non-government organisations and advocacy groups, changes in health practice based on their research and meetings with government ministers and members of parliament. This information is briefly noted in the meeting minutes.

A summary of this activity is then entered into the tracking spreadsheet by the research support team. Since this reporting happens on a fortnightly basis, the information is fresh in the researchers’ minds and detail is unlikely to be forgotten.

Reporting on engagement and impact

The columns were developed based on the variety of ways the group is required to report engagement and impact. It allows sorting by date of research or date of impact, as required, and can be filtered by the project identifier, in order to meet various reporting needs. For example, it can identify all activities for the group in a calendar year, or all activities led by a certain researcher, or all activities associated with a project or published paper.

The tracking spreadsheet allows for ambiguity (eg., imprecision in the date) and flexibility. For example, the two main Australian funding agencies categorise engagement and impact differently. The Australian Research Council defines ‘engagement’ as a subset of ‘impact’, while Australia’s National Health and Medical Research Council considers them to be separate outcomes. The tracking spreadsheet allows activity to be engagement or impact or both, and no column has to be filled in, to allow for engagement or impact that doesn’t fall neatly into the categories.

Conclusion

The use of a standardised, centralised repository for recording engagement and impact soon after it occurs has enabled the group to:

  • rapidly answer ad hoc queries about research, such as ‘what has been the impact of the group’s work on smoking by indigenous Australians?’
  • formally report to various funding agencies
  • help researchers frame their promotion applications.

Reflections on these reports have, in turn, enabled the group to identify the strategies for maximising stakeholder engagement and research impact.

What strategies have you found useful for keeping track of stakeholder engagement and/or research impact?

Biography: Cathy Day PhD is Research Manager of the Epidemiology for Policy and Practice Group in the National Centre for Epidemiology and Population Health, Research School of Population Health at The Australian National University.

Cathy Day is a member of blog partner PopulationHealthXchange, which is in the Research School of Population Health at The Australian National University.

Toolboxes as learning aids for dealing with complex problems

Community member post by Stefan Hilser

Stefan Hilser (biography)

How can toolboxes more effectively support those learning to deal with complex societal and environmental problems, especially novices such as PhD students and early career researchers?

In this blog post, I briefly describe four toolboxes and assess them for their potential to assist learning processes. My main aim is to open a discussion about the value of the four toolboxes and how they could better help novices.

Before describing the toolboxes, I outline the learning processes I have in mind, especially the perspective of legitimate peripheral participation. Continue reading

Metacognition as a prerequisite for interdisciplinary integration

Community member post by Machiel Keestra

Machiel Keestra (biography)

What’s needed to enable the integration of concepts, theories, methods, and results across disciplines? Why is communication among experts important, but not sufficient? Interdisciplinary experts must also meta-cognize: both individually and as a team they must monitor, evaluate and regulate their cognitive processes and mental representations. Without this, expertise will function suboptimally both for individuals and teams. Metacognition is not an easy task, though, and deserves more attention in both training and collaboration processes than it usually gets. Why is metacognition so challenging and how can it be facilitated? Continue reading

Trust and empowerment inventory for community groups

Community member post by Craig Dalton

Author - Craig Dalton
Craig Dalton (biography)

Community groups are often consulted by researchers, government agencies and industry. The issues may be contentious and the relationship vexed by distrust and poor communication. Could an inventory capture the fundamental sources of community frustration and highlight scope for improvement in respect, transparency, fairness, co-learning, and meeting effectiveness from a community perspective?

The trust and empowerment inventory presented below is based on the main sources of community frustration that I have witnessed over two decades as a public health physician and researcher liaising with communities about environmental health risks and it is likely to have broader relevance. Key issues include not being listened to; not being fully informed; Continue reading

Three “must have” steps to improve education for collaborative problem solving

Community member post by Stephen M. Fiore

stephen-fiore_aug-2017
Stephen M. Fiore (biography)

Many environmental, social, and public health problems require collaborative problem solving because they are too complex for an individual to work through alone. This requires a research and technical workforce that is better prepared for collaborative problem solving. How can this be supported by educational programs from kindergarten through college? How can we ensure that the next generation of researchers and engineers are able to effectively engage in team science?

Drawing from disciplines that study cognition, collaboration, and learning, colleagues and I (Graesser et al., 2018) make three key recommendations to improve research and education with a focus on instruction, opportunities to practice, and assessment. Across these is the need to attend to the core features of teamwork as identified in the broad research literature on groups and teams. Continue reading