Quadratic Model of Reciprocal Causation for Monitoring, Improving, and Reflecting on Design Team Performance

Author(s):  
Neeraj Sonalkar ◽  
Ade Mabogunje ◽  
Mark Cutkosky
Author(s):  
David M. Cannon ◽  
Jonathan Edelman

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.


Author(s):  
Ethan Brownell ◽  
Jonathan Cagan ◽  
Kenneth Kotovsky

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.


2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Stefano Filippi

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.


Author(s):  
Shun Takai ◽  
Marcos Esterman

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.


Author(s):  
Andrew D. Christian ◽  
Warren P. Seering

Abstract This paper describes a method of modeling the engineering design process and a simulation that implements the model. The model explicitly represents the communication requirements of interdependent design projects and the assigned roles of individuals. The simulation uses computer agents to represent individuals working within a design environment, exchanging information, and making decisions based on a limited rationality model of human behavior. This paper describes how the model and simulation can be used to make predictions about design team performance.


2020 ◽  
Vol 1 ◽  
pp. 2571-2580
Author(s):  
H. Singh ◽  
G. Cascini ◽  
C. McComb

AbstractSocial media influencers (SMI) are gaining interest and many are studying their influence on the online audience, little is known about the role played by them in offline teams. One such attempt to study the effect of influencers in co-design team is presented in this paper, where individuals who are confident in their abilities drive the team process. Thus, self-efficacy is considered for determining influencer behaviour. Results expose the relationship between self-efficacy and influencer status on the design process, besides briefly highlighting the effects on above-average teams.


Sign in / Sign up

Export Citation Format

Share Document