Towards a Conceptual Framework for Predicting Engineering Design Team Performance Based on Question Asking Activity Simulation

2003 ◽  
pp. 154-163
Author(s):  
Ade Mabogunje
Keyword(s):  
Conceptual Framework ◽  
Engineering Design ◽  
Team Performance ◽  
Design Team ◽  
Question Asking

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.

Effects of Locus of Control Personality Trait on Team Performance in Cooperative Engineering Design Tasks

2020 ◽  
Author(s):  
Alkım Z. Avşar ◽  
Paul T. Grogan
Keyword(s):  
Locus Of Control ◽  
Engineering Design ◽  
Team Performance ◽  
Personality Trait ◽  
Performance Outcomes ◽  
Design Teams ◽  
Support Design ◽  
Explanatory Hypothesis ◽  
Total Data ◽  
Data Points

Abstract Teams in engineering design tackle problems that exceed the abilities of individuals. Improved understanding of how personality traits influence human behaviors and interaction may help create new methods and tools to support design teams. This paper seeks to understand how the Locus of Control (LOC) personality trait influences designer behaviors and team performance. A designer experiment studies 12 participant pairs controlled for categorical LOC pairing factors (internal-internal, external-external, and internal-external). Each design team completes six simplified cooperative parameter design tasks to minimize completion time, yielding 72 total data points. Regression analysis shows LOC pairing affects team efficiency in agreement with literature outside engineering design: diverse LOC traits reduce design efficiency while similarity increases team effectiveness. Results contribute to an explanatory hypothesis that LOC pairing influences designer behaviors related to action effectiveness which, subsequently, affects team performance outcomes.

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.

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