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

Community member post by Stephen M. Fiore

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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.

Systematic use of instructional strategies

First and foremost, researchers should collaborate with educators to make more systematic use of instructional strategies devised to teach components of collaboration. Research on groups and teams has produced methods that focus on team processes relevant to complex forms of work.

For example, knowledge building training emphasizes communicative processes that make explicit the structure of team member knowledge (eg., mental models), as well as assumptions and interpretations team members have about their knowledge. External representations make such knowledge explicit and concrete and build shared understanding.

Also relevant is training that draws attention to the team process following interactions. Team reflexivity training requires that members reflect on prior performance episodes by focusing on met or unmet objectives, strategies used to address task needs, and efficiency of collaborative interactions. Such training could be improved by further research both on effective interventions and on how students come to learn team processes that improve future interactions.

Opportunities for practice

Second, in addition to systematic implementation of instruction on team process, students need opportunities for practice. Collaboration in the classroom is common in science and engineering, and education level and nature of the content will dictate the team and task context.

For example, in introductory science classes, students may collaborate while learning about fundamental physics concepts, how they should be integrated, and applied, for particular problems. At these levels, knowledge is usually unevenly distributed across students such that they need to communicate what each knows as well as their interpretation of what needs to be applied. Teams need to discuss member contributions and evaluate their appropriateness while also using logical analyses to identify and evaluate solutions. In these stages of learning, basic interpersonal competencies associated with relationship management (eg., encourage participation) and communication (eg., listening to learn), are needed.

At more advanced levels, students address problems that require richer domain knowledge, as well as connection to more complicated scenarios. For example, upper level students might collaborate on complex socio-environmental problems such as overfishing wherein stakeholder factors necessitate consideration of species population dynamics and local economies. At these levels, collaboration requires sophisticated forms of perspective taking to consider alternative views of problem elements.

Considering the need to provide more structured practice opportunities, problem-based learning is a method tested in a variety of settings with meta-analytic support documenting effectiveness. Teams work on real-world problems, first discussing any lack of understanding and identifying gaps in knowledge. From this, they form explicit learning goals and collaborate to gather and integrate knowledge necessary to produce a solution. Research must thoroughly examine these in the classroom to understand how they can best provide the contextual grounding that fosters integration of collaboration skills.

Assessment to measure team work

Finally, more consistent assessments that measure teamwork to provide diagnostic feedback on collaboration are also necessary. To achieve this, there should be a more systematic integration of methods on team training with the educational programs devised for learning to work in teams. This includes consideration of self-ratings of soft skills as well as peer-ratings that assess categories of team involvement like contribution to the team’s work and keeping the team on track. Also needed are assessments of interpersonal competencies such as conflict resolution (eg., reactions to conflict) and assertive communication (eg., addressing differences without intimidation).

Critical to this assessment is ensuring students receive feedback regularly, can compare it to self-assessments, and have opportunities to calibrate it in future collaborations. Research must explore how to incentivize collaborative problem solving skills and integrate grades on collaboration into overall student assessment.

Concluding questions

Do you have successful experiences of teaching and assessing team work to share? What are the key concepts that you teach? Which pedagogical strategies have you found helpful? What questions must the burgeoning “Science of Team Science” pursue to ensure effectiveness in collaborative problem solving?

To find out more:
Graesser, A. C., Fiore, S. M., Greiff, S., Andrews-Todd, J., Foltz, P. W. and Hesse, F. W. (2018). Advancing the science of collaborative problem solving. Psychological Science in the Public Interest, 19, 2: 59-92. Online:  https://doi.org/10.1177/1529100618808244

Biography: Stephen M. Fiore PhD is Director, Cognitive Sciences Laboratory, and Professor with the University of Central Florida’s Cognitive Sciences Program in the Department of Philosophy and Institute for Simulation and Training. He is Past-President of the Interdisciplinary Network for Group Research, a founding committee member for the annual Science of Team Science Conference and founding board member for the International Network for the Science of Team Science. He maintains a multidisciplinary research interest that incorporates aspects of the cognitive, social, organizational, and computational sciences in the investigation of learning and performance in individuals and teams.

Grant proposal writing for teams: Avoiding Frankenstein’s monster

Community member post by Lauren Gee

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Lauren Gee (biography)

Writing a grant proposal as a team has many pluses—a plenitude of viewpoints, a wider wealth of knowledge to pull from, and a larger pool of resources to help edit and finalize the proposal. Too often, however, a team-written proposal turns out as “Frankenstein’s monster”: a mess of disparate parts, thrown onto the page. Agreement is missing throughout, with no consistency in terms of vocabulary, style, or even tense. So how can a team work together, from day one, to write a successful, cohesive proposal—how do we avoid Frankenstein’s monster? Continue reading

Building a global community to improve how complex real-world problems are tackled

Community member post by Gabriele Bammer

This is the third annual “state of the blog” review.

Gabriele Bammer (biography)

As the blog moves into its 4th year, how well is it achieving its goals? Is it succeeding in sharing concepts and methods across the multiple groups addressing complex real-world problems – groups including inter- and trans- disciplinarians, systems thinkers, action researchers and implementation scientists, as well as the myriad researchers working on complex environmental, health and other societal problems, who do not necessarily identify with these networks? Is it providing a forum to connect these disparate groups and individuals? Is it helping to build an international research community to improve how complex real-world problems are tackled? Continue reading

Collaboration and team science: Top ten take aways

Community member post by L. Michelle Bennett and Christophe Marchand

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L. Michelle Bennett (biography)

What are the key lessons for building a successful collaborative team? A new version of the Collaboration and Team Science Field Guide (Bennett et al., 2018) provides ten top take aways:

1. TRUST
It is almost impossible to imagine a successful collaboration without trust. Trust provides the foundation for a team. Trust is necessary for establishing other aspects of a successful collaboration such as psychological safety, candid conversation, a positive team dynamic, and successful conflict management. Continue reading

What can interdisciplinary collaborations learn from the science of team science?

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Suzi Spitzer (biography)

Community member post by Suzi Spitzer

How can we improve interdisciplinary collaborations? There are many lessons to be learned from the Science of Team Science. The following ten lessons summarize many of the ideas that were shared at the International Science of Team Science Conference in Galveston, Texas, in May 2018.

1. Team up with the right people
On the most basic level, scientists working on teams should be willing to integrate their thoughts with their teammates’ ideas. Participants should also possess a variety of social skills, such as negotiation and social perceptiveness. The most successful teams also encompass a moderate degree of deep-level diversity (values, perspectives, cognitive styles) and include women in leadership roles. Continue reading

Two types of interdisciplinary scholarship

Community member post by Andi Hess

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Andi Hess (biography)

Would it be helpful to identify two distinct forms of interdisciplinary scholarship ― 1) individual interdisciplinarity and 2) interdisciplinary dialogue and team science ― and to make this distinction explicit in the literature? What are the benefits and challenges of each? Are a different set of resources and methods required to achieve effective interdisciplinary scholarship?

As integration scientists are aware, there are many analyses of appropriate methods for conducting interdisciplinary work. Each has its own benefits and challenges, and each requires a different set of resources and methods for achieving effective interdisciplinary scholarship. Continue reading