Design Team Performance: Context, Measurement, and the Prospective Impact of Social Virtual Reality

2021 ◽  
pp. 177-201
Author(s):  
Ade Mabogunje ◽  
Neeraj Sonalkar ◽  
Mark Miller ◽  
Jeremy Bailenson
Keyword(s):  
Virtual Reality ◽  
Team Performance ◽  
Design Team ◽  
Performance Context

Prediction of Design Team Performance on a Conceptual Design Task Using an Automatable, Topic-Independent Analysis of Language Use

2019 ◽  
Author(s):  
David M. Cannon ◽  
Jonathan Edelman
Keyword(s):  
Conceptual Design ◽  
Team Performance ◽  
Language Use ◽  
Design Team ◽  
Interpersonal Dynamics ◽  
Design Task ◽  
Independent Analysis ◽  
Language Style Matching ◽  
Insight Into ◽  
Moving Pattern

Abstract In this research, starting with an established metric called the Language Style Matching (LSM) measure [1] we show that some new LSM-based measures can predict team performance on an open-ended design task. We call these Style Entrainment Signal (SES) measures. Using them, two conversational patterns are newly identified, which we call “dwelling” and “forward-moving.” We show that a forward-moving pattern is associated with better-rated results produced by teams in 30-minute long conceptual design meetings with significant brainstorming activity. Through this, we gain insight into some of the interpersonal dynamics that contribute to a design team’s success. These results are founded on previous work in psycholinguistics, where it has been shown that analysis of language use can be used in several ways to predict a team’s performance on short, well-defined tasks. By expanding the research to more open-ended design tasks, and identifying two newly-measurable conversational patterns, we contribute back to psycholinguistic theory. The analysis developed for this work is automatable and topic-independent, and so it has potential to be applied widely.

Only As Strong As the Strongest Link: The Impact of Individual Team Member Proficiency in Configuration Design

2020 ◽  
Author(s):  
Ethan Brownell ◽  
Jonathan Cagan ◽  
Kenneth Kotovsky
Keyword(s):  
Team Performance ◽  
Team Member ◽  
Positive Impact ◽  
Individual Characteristics ◽  
Configuration Design ◽  
Design Team ◽  
Markov Modeling ◽  
Team Members ◽  
Hidden Markov Modeling ◽  
The Impact

Abstract Prior research has demonstrated how the average characteristics of a team impact team performance. Individual characteristics of team members and individual team member behavior have been largely ignored, especially in the context of engineering design. In this work, a behavioral study was conducted to uncover whether the most or least proficient member of a configuration design team had a larger impact on overall performance. It was found that a configuration design team is most dependent on the proficiency of its most proficient member and results suggest that replacing the most proficient member with an even more proficient member can be expected to have a more positive impact than replacing any other member with a higher proficiency member of the same change in proficiency. The most proficient member had a significant positive effect on how quickly the team reached performance thresholds and that the other members of the team were not found to have the same positive impact throughout the design study. Behavioral heuristics were found using hidden Markov modeling to capture the differences in behavior and design strategy between different proficiency members. Results show that high proficiency and low proficiency team members exhibit different behavior, with the most proficient member’s behavior leading to topologically simpler designs and other members adopting their designs, leading to the most proficient member driving the team design and team performance.

scholarly journals Estimating Designers’ Performance considering Personal Characteristics and External Factors Together

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Stefano Filippi
Keyword(s):  
Performance Evaluation ◽  
Team Performance ◽  
Personal Characteristics ◽  
External Factors ◽  
Design Team ◽  
Team Members

Design team performance evaluation can occur in different ways, all of them requiring considerations on interactions among team members; in turn, these considerations should count on as many pieces of information as possible about individuals. The literature already explains how personal characteristics and/or external factors influence designers' performance; nevertheless, a way to evaluate performance considering several personal characteristics and external factors together is missing. This research tries to fill the gap by developing the Designer’s Performance Estimator (DPE), a ready-to-use tool for researchers and practitioners who need to make information about team members as richer as possible.

On the Motivational Basis of Cue Identification in Teams

2018 ◽  
Vol 49 (5) ◽  
pp. 519-544
Author(s):  
Michael J. Burtscher ◽  
John M. Levine ◽  
E. Tory Higgins
Keyword(s):  
Team Performance ◽  
Regulatory Focus ◽  
Status Quo ◽  
Detection Task ◽  
Interactive Effects ◽  
Team Members ◽  
Mixed Analysis ◽  
Team Adaptation ◽  
The Status ◽  
Performance Context

Although identifying cues indicating a problem represents a crucial aspect of team adaptation, little is known about the conditions under which team members do this correctly. To address this issue, the current study focused on the motivational basis of cue identification by investigating interactive effects of members’ regulatory focus, their contribution redundancy, and the team performance context. Participants working in 105 three-person teams were asked to identify problem cues in a signal detection task. Utilizing a 2 (regulatory focus: promotion vs. prevention) x 2 (performance context: status quo vs. loss) x 2 (contribution redundancy: low vs. high) mixed analysis of variance (ANOVA) design with contribution redundancy as a within-participants factor, we obtained the predicted three-way interaction: In the status quo condition, prevention-focused, but not promotion-focused, team members were less accurate in identifying problem cues when their contributions were redundant. Our findings contribute to a better understanding of the motivational basis of team adaptation.

scholarly journals Familiarity with teammate’s attitudes improves team performance in virtual reality

PLoS ONE ◽  
2020 ◽  
Vol 15 (10) ◽  
pp. e0241011
Author(s):  
Shannon M. Moore ◽  
Michael N. Geuss
Keyword(s):  
Virtual Reality ◽  
Team Performance

A Conceptual Framework and a Research Roadmap Towards Enhancing Team Working in Engineering Education

2019 ◽  
Author(s):  
Shun Takai ◽  
Marcos Esterman
Keyword(s):  
Engineering Education ◽  
Team Performance ◽  
Team Effectiveness ◽  
Team Member ◽  
Team Building ◽  
Building Design ◽  
Design Team ◽  
Design Teams ◽  
Effectiveness Model ◽  
Form Design

Abstract While design processes have been studied for many years, relationships among design team characteristics, teamwork, and team performance have not yet been fully understood. As such, there is no consensus on how to form design teams or enhance teamwork. In this paper, we propose a conceptual design-team effectiveness model based on team effectiveness theory in which we divide team process into two components: team member collaboration and design process. Built on this model, we then present a six-step research roadmap towards enhancing teamwork in engineering education by 1) improving methodology to form design teams and 2) finding a team-building design exercise to promote team member collaboration. We propose to improve team formation methodology by 1) comprehensively studying associations among team factors and team performance and 2) investigating how associations among team factors and team performance change with team-building design exercises. Together, we expect both team performance and team member collaboration to improve, which should lead to a better teamwork experience in engineering education.

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