Communication and Performance in Co-Located and Distributed Teams: An Issue of Shared Mental Models of Team Members?

2011 ◽  
Vol 23 (6) ◽  
pp. 616-638 ◽  
Author(s):  
Roar Espevik ◽  
Bjørn Helge Johnsen ◽  
Jarle Eid
Keyword(s):  
Mental Models ◽  
Shared Mental Models ◽  
Distributed Teams ◽  
Team Members ◽  
And Performance

The Role of Planning in Coordinated Team Decision Making: Implications for Training

1993 ◽  
Vol 37 (18) ◽  
pp. 1238-1242 ◽  
Author(s):  
Rene'e Stout ◽  
Eduardo Salas
Keyword(s):  
Decision Making ◽  
Mental Models ◽  
Shared Mental Models ◽  
Team Members ◽  
Team Decision Making ◽  
Team Planning ◽  
Team Decision ◽  
And Performance ◽  
The Relationship

Critical decisions are made every day by teams of individuals who must coordinate their activities to achieve effectiveness. Recently, researchers have suggested that shared mental models among team members may help them to make successful decisions. Several avenues for training shared mental models in teams exist, one of which is training in planning behaviors. The relationship between team planning, team shared mental models, and coordinated team decision making and performance is explored.

Do We Share the Same View? Validating the Shared Mental Models in Team Sports Questionnaire

2021 ◽  
Vol 128 (2) ◽  
pp. 831-850
Author(s):  
Charlotte Raue ◽  
Dennis Dreiskaemper ◽  
Bernd Strauss
Keyword(s):  
Mental Models ◽  
Team Sports ◽  
Positive Influence ◽  
Shared Mental Models ◽  
Model Fit ◽  
Sports Performance ◽  
Measurement Instruments ◽  
Team Members ◽  
Confirmatory Factor ◽  
Good Internal Consistency

Shared mental models (SMMs) can exert a positive influence on team sports performance because team members with SMMs share similar tasks and team-related knowledge. There is currently insufficient sports research on SMMs because the underlying theory has not been adapted adequately to the sports context, and different SMMs measurement instruments have been used in past studies. In the present study we aimed to externally validate and determine the construct validity of the “Shared Mental Models in Team Sports Questionnaire” (SMMTSQ). Moreover, we critically examined the theoretical foundation for this instrument. Participants were 476 active team athletes from various sports. While confirmatory factor analysis did not support the SMMTSQ’s hierarchical model, its 13 subfactors showed a good model fit in an explorative correlative approach, and the model showed good internal consistency and item–total correlations. Thus, the instrument’s subfactors can be applied individually, even while there are remaining questions as to whether other questionnaires of this kind are an appropriate means of measuring SMMs in sport.

Shared mental models—linking team cognition and performance

CoDesign ◽  
2007 ◽  
Vol 3 (1) ◽  
pp. 75-94 ◽  
Author(s):  
R. Bierhals ◽  
I. Schuster ◽  
P. Kohler ◽  
P. Badke-Schaub
Keyword(s):  
Mental Models ◽  
Shared Mental Models ◽  
Team Cognition ◽  
And Performance

Shared mental models as moderators of team process-performance relationships

2010 ◽  
Vol 38 (4) ◽  
pp. 433-444 ◽  
Author(s):  
Ying Zhou ◽  
Erping Wang
Keyword(s):  
Mental Models ◽  
Team Performance ◽  
Positive Impact ◽  
Project Planning ◽  
Shared Mental Models ◽  
Future Research ◽  
Team Process ◽  
Team Processes ◽  
And Performance ◽  
The Relationship

The effects of shared mental models on the relationship between episodic team behavioral processes and performance were investigated, while teams were using an experimentally stimulated construction project planning program. The results indicated that episodic team processes made positive contributions to the team performance. Furthermore, a hierarchical linear regression indicated that the convergence of shared teamwork mental models moderated the effects of team processes on team performance. Specifically, the positive impact of team processes on performance was found to be improved for those teams who shared more similar teamwork mental models than for teams who hold fewer similar teamwork mental models. Potential implications and relevant impacts on future research are discussed.

Distributed Teams and Distributed Memory

2002 ◽  
Vol 46 (3) ◽  
pp. 398-402
Author(s):  
Stephen M. Fiore ◽  
Haydee M. Cuevas ◽  
Eduardo Salas ◽  
Jonathan W. Schooler
Keyword(s):  
Mental Models ◽  
Team Performance ◽  
Cognitive Processes ◽  
Distributed Memory ◽  
Shared Mental Models ◽  
Distributed Teams ◽  
Team Cognition ◽  
Organizational Unit ◽  
Distributed Team

The nature of teams is changing in that the implementation of distributed teams as a definable organizational unit has substantially increased. In this paper we discuss a portion of the cognitive processes potentially impacting distributed team performance. We elaborate on how team opacity arising from distributed interaction can impact team cognition, with an emphasis on the critical memory components that are foundational to the development and implementation of shared mental models.

The influence of shared mental models on team process and performance.

2000 ◽  
Vol 85 (2) ◽  
pp. 273-283 ◽  
Author(s):  
John E. Mathieu ◽  
Tonia S. Heffner ◽  
Gerald F. Goodwin ◽  
Eduardo Salas ◽  
Janis A. Cannon-Bowers
Keyword(s):  
Mental Models ◽  
Shared Mental Models ◽  
Team Process ◽  
And Performance

scholarly journals Association of Social Network Analysis with Mental Models in Emergency Management Teams

2019 ◽  
Author(s):  
Bjørn Sætrevik ◽  
Line Solheim Kvamme
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Emergency Management ◽  
Mental Models ◽  
Shared Mental Models ◽  
Management Teams ◽  
Interaction Patterns ◽  
Team Members ◽  
The Impact

Social network analysis is a preferred approach to examine the impact of social processes and mechanisms on team performance, but it can be challenging to measure these dynamics in applied settings. Our aim was to test whether the understanding of the task at hand was more accurate and more shared for teams with more evenly distributed interaction patterns. We pre-registered a novel approach for measuring social networks from sparse reporting of ranked interactions. Our sample was eleven emergency management teams that performed a scenario training exercise, where we asked factual questions about the ongoing task during performance, and retrospective questions about who were the most important communication and collaboration partners. We quantified shared mental models as the extent to which a team member showed the same understanding as the rest of their team, and quantified situation awareness as the extent to which team members showed the same knowledge as their team leader. We calculated which team members where most central to the network, and which networks had more evenly distributed networks. Our findings support the pre-registered hypotheses that more interconnected teams are associated with more accurate and more shared mental models, while the individual’s position in the network was not associated with MM.

A Framework for Developing and Using Shared Mental Models in Human-Agent Teams

2017 ◽  
Vol 11 (3) ◽  
pp. 203-224 ◽  
Author(s):  
Matthias Scheutz ◽  
Scott A. DeLoach ◽  
Julie A. Adams
Keyword(s):  
Mental Models ◽  
Data Structures ◽  
Shared Mental Models ◽  
Related Factors ◽  
Computational Framework ◽  
Team Members ◽  
Human Agent ◽  
Pertinent Information ◽  
Organizational Science ◽  
Computational Processes

Converging evidence from psychology, human factors, management and organizational science, and other related fields suggests that humans working in teams employ shared mental models to represent and use pertinent information about the task, the equipment, the team members, and their roles. In particular, shared mental models are used to interact efficiently with other team members and to track progress in terms of goals, subgoals, achieved and planned states, as well as other team-related factors. Although much of the literature on shared mental models has focused on quantifying the success of teams that can use them effectively, there is little work on the types of data structures and processes that operate on them, which are required to operationalize shared mental models. This paper proposes the first comprehensive formal and computational framework based on results from human teams that can be used to implement shared mental models for artificial virtual and robotic agents. The formal portion of the framework specifies the necessary data structures and representations, whereas the computational framework specifies the necessary computational processes and their interactions to build, update, and maintain shared mental models.

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