scholarly journals Coordination in Design Teams as a Lens to Identifying Team Roles

2019 ◽  
Vol 1 (1) ◽  
pp. 79-88
Author(s):  
Arianne X. Collopy ◽  
Chengxi Li ◽  
Tianyi Liu ◽  
Eytan Adar ◽  
Panos Y. Papalambros
Keyword(s):  
System Design ◽  
Text Analysis ◽  
Team Member ◽  
Communication Patterns ◽  
Design Team ◽  
Design Teams ◽  
Communication Behaviors ◽  
Team Members ◽  
Roles And Responsibilities ◽  
Self Reports

AbstractCoordination in system design requires an interplay between different roles. In this work, we identify five design team roles that pertain to the partitioning and coordination of distributed design team tasks. The proposed characterization is based on self-reported responsibilities and communication behaviors from 109 student designers in 22 teams at the conclusion of a semester-long design project. The self-reports capture both how team members viewed their own work as well as communication patterns between team members. We leverage two representations of this data. Through text analysis, we identify keywords describing team member roles and responsibilities. Social network analysis can further distinguish roles based on team communication behaviors. Cluster analysis on both types of data identifies groups of individuals with similar characteristics. The resulting five clusters capture common roles in system design teams that simultaneously capture the diverse responsibilities and communication patterns.

The Influence of Team Goal Alignment and Awareness on Human-Centered Design Team Decision-Making Strategy

2021 ◽  
Author(s):  
Vivek Rao ◽  
Ananya Krishnan ◽  
Jieun Kwon ◽  
Euiyoung Kim ◽  
Alice Agogino ◽  
...  
Keyword(s):  
Decision Making ◽  
Personal Goals ◽  
Design Team ◽  
Design Teams ◽  
Goal Alignment ◽  
Team Members ◽  
Team Decision Making ◽  
Student Teams ◽  
Team Decision ◽  
Team Alignment

Abstract Design team decision-making underpins all activities in the design process. Simultaneously, goal alignment within design teams has been shown to be essential to the success of team activities, including engineering design. However, the relationship between goal alignment and design team decision-making remains unclear. In this exploratory work, we analyze six student design teams’ decision-making strategies underlying 90 selections of design methods over the course of a human-centered design project. We simultaneously examine how well each design team’s goals are aligned in terms of their perception of shared goals and their awareness of team members’ personal goals at the midpoint and end of the design process, along with three other factors underpinning team alignment at the midpoint. We report three preliminary findings about how team goal alignment and goal awareness influence team decision-making strategy that, while lacking consistent significance, invite further research. First, we observe that a decrease in awareness of team members’ personal goals may lead student teams to use a different distribution of decision-making strategies in design than teams whose awareness stays constant or increases. Second, we find that student teams exhibiting lower overall goal alignment scores appear to more frequently use agent-driven decision-making strategies, while student teams with higher overall goal alignment scores appear to more frequently use process-driven decision-making strategies. Third, we find that while student team alignment appears to influence agent- and process-driven strategy selection, its effect on outcome-driven selection is less conclusive. While grounded in student data, these findings provide a starting place for further inquiry into of designerly behavior at the nexus of teaming and design decision-making.

Integral Design: The Reflective Morphological Overview

2007 ◽  
Author(s):  
Wim Zeiler ◽  
Perica Savanovic ◽  
Emile Quanjel
Keyword(s):  
Design Process ◽  
Information Exchange ◽  
Building Design ◽  
Design Team ◽  
Design Teams ◽  
Design Decisions ◽  
Team Members ◽  
Complex Process ◽  
Dutch Association ◽  
Building Physics

Integral Building Design is done by multi disciplinary design teams and aims at integrating all aspects from the different disciplines involved in a design for a building such as; archtitecture, construction, building physics and building services. It involves information exchange between participants within the design process in amounts not yet known before. To support this highly complex process an Integral Building Design methods is developed based on the combination of a prescriptive approach, Methodical Design, and a descriptive approach, Reflective practice. Starting from the Methodical Design approach by van den Kroonenberg, a more reflective approach is developed. The use of Integral Design within the design process results in a transparency on the taken design steps and the design decisions. Within the design process, the extended prescriptive methodology is used as a framework for reflection on design process itself. To ensure a good information exchange between different disciplines during the conceptual phase of design a functional structuring technique can be used; Morphological Overviews (MO). Morphology provides a structure to give an overview of the consider functions and their solution alternatives. By using this method it is presumed that it helps to structure the communication between the design team members and a such forms a basis for reflection on the design results by the design team members. This method is used in the education program at the Technische Universiteit Eindhoven and was tested in workshops for students and for professionals from the Royal Institute of Dutch Architects (BNA) and the Dutch Association of Consulting Engineers (ONRI). Over 250 professionals participated in these workshops.

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 Comparing Team Interactions in Traditional and BIM-Lean Design Management

Buildings ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 447
Author(s):  
Rodrigo F. Herrera ◽  
Claudio Mourgues ◽  
Luis F. Alarcón ◽  
Eugenio Pellicer
Keyword(s):  
Empirical Evidence ◽  
Management Approach ◽  
Design Management ◽  
Design Team ◽  
Design Teams ◽  
Lean Management ◽  
Team Members ◽  
Team Interaction ◽  
Study Selection ◽  
Team Interactions

There is qualitative evidence showing that design teams that use BIM-lean management have a higher level of interaction than design teams that do not use this management approach. However, there is no quantitative empirical evidence of this higher level of interaction. Therefore, the objective of this paper is to present quantitative empirical evidence of the differences among the various types of interactions of a design team. Two case studies were analyzed, and their design management was assessed from a lean BIM perspective while their team interactions were assessed using social network analysis (SNA). To achieve the aim of this paper, four steps were performed: (1) case study selection; (2) description of the design management of the projects from the lean design management and BIM perspectives; (3) assessment of design team interaction; and (4) comparison using SNA. The results show that the project that applied BIM-lean management exhibited higher levels of interactions among its design team members than the traditional team; transparent, orderly, and standardized information flows; a collaborative, trusting, and learning environment; and commitment management. None of these interaction elements were visible in the project that did not apply BIM-lean management. It is suggested that an analysis be performed on a representative sample of projects in the future so that conclusive statistical inferences could be made.

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.

Understanding the Context of Multidisciplinary Design: Establishing Ecological Validity in the Study of Design Problem Solving

1993 ◽  
Vol 37 (16) ◽  
pp. 1082-1086 ◽  
Author(s):  
Michael D. McNeese ◽  
Brian S. Zaff ◽  
Clifford E. Brown ◽  
Maryalice Citera ◽  
Jonathan Selvaraj
Keyword(s):  
Problem Solving ◽  
Human Factors ◽  
Concept Mapping ◽  
Design Process ◽  
Collaborative Design ◽  
Design Problem ◽  
Design Team ◽  
Design Teams ◽  
Team Members ◽  
Design Activities

The need to understand the design process in all its complexity is motivated by an interest in the development of tools and technologies that would be capable of aiding collaborative design teams. This development effort depends upon an understanding of design activities as they occur within a real world context. Observations of design activities that are made without direct communication with the design team members may fail to capture many of the subtler aspects of the process - aspects that are best understood when described by the design team members themselves. In order to supplement observational studies, this paper presents a case study in which a dialog with members of a variety of collaborative design teams was established in order to elicit information about the nature of collaborative design. A knowledge acquisition technique, concept mapping, was used to achieve an understanding of the role of human factors specialists within the collaborative design process specific to the Air Force's system acquisition program. Results highlight various findings about the nature of design problem solving such as the way different organizational settings influence human factors input in the design process/product. The paper discusses the usefulness of concept mapping to capture in-depth design knowledge and how this type of knowledge complements other approaches to understanding design.

Effect of Team Size on Problem-Solving and Solution Quality: An Empirical Study

2019 ◽  
Author(s):  
Seth Jacobs ◽  
Matthew Pfarr ◽  
Mohammad Fazelpour ◽  
Abdul Koroma ◽  
Tseday Mesfin
Keyword(s):  
Problem Solving ◽  
Empirical Study ◽  
Design Solution ◽  
Design Team ◽  
Design Teams ◽  
Team Size ◽  
Solution Quality ◽  
Team Members ◽  
Protocol Study ◽  
The Impact

Abstract The size of a team can affect how they tackle a design problem and solution quality. This paper presents a protocol study of the impact of team size on problem-solving and design solution quality. The protocols are coded with micro-strategies, and macro-strategies, and final solutions are scored using a rubric of meeting constraints, manufacturability, feasibility, and cost. The results show that the larger design team sizes analyze design solutions more frequently and propose solutions less than the smaller design teams. Among the three team sizes of 1, 3, and 5, the teams of three designers scored the best on final designs. These teams used a fair amount of both proposing solutions and analyzing solutions of micro-strategies. The teams of 5 designers use backtracking macro-strategies more frequent than teams of 3 and one because as the team size increases, more time is spent among team members to discuss previous ideas.

Design Team Convergence: The Influence of Example Solution Quality

2009 ◽  
Author(s):  
Katherine Fu ◽  
Jonathan Cagan ◽  
Kenneth Kotovsky
Keyword(s):  
Problem Solving ◽  
Engineering Design ◽  
Semantic Analysis ◽  
Cognitive Engineering ◽  
Design Team ◽  
Design Teams ◽  
Solution Quality ◽  
Team Members ◽  
Common Understanding

This study examines how engineering design teams converge to a common understanding of a design problem and its solution, how that is influenced by the information given to them before problem solving and how it is correlated with quality of produced solutions. To understand convergence, a model of the team members’ representations was sought through a cognitive engineering design study, specifically examining the effect of the introduction of a poor example solution and a good example solution prior to problem solving. Latent Semantic Analysis (LSA) was used to track the teams’ convergence. Introducing a poor example solution was shown to have a slowing effect on teams’ convergence over time and quality of design, while the good example solution was not significantly different than the control (no example solution) in its effects on convergence, but did cause higher quality solutions. This may have implications for design team performance in practice.

An Ontology-Based Competence Model for Collaborative Design

2009 ◽  
pp. 188-202
Author(s):  
Vladimir Tarasov ◽  
Kurt Sandkuhl ◽  
Magnus Lundqvist
Keyword(s):  
Problem Solving ◽  
Collaborative Design ◽  
Ontology Matching ◽  
Design Team ◽  
Design Teams ◽  
Competence Model ◽  
Design Work ◽  
Team Members ◽  
Ontology Language ◽  
Competence Models

Collaborative design in dispersed groups of engineers creates various kinds of challenges to technology, organization and social environment. This paper presents an approach to description and representation of the competences needed for a planned collaborative design project. The most important competence areas are identified starting from the nature of design work, problem solving in design teams, and working in distributed groups. The competence model is built structuring these areas according to three perspectives: general, cultural, and occupational competences. An ontological representation is proposed to implement the described model for collaborative design competence. Using an ontology language for representation of collaborative design competence models makes it possible to identify those individuals who are best suited for the collaboration by ontology matching. Furthermore, a software design team consisting of two persons was interviewed and competence profiles were created using the developed ontological representation. Modeling of the team members has confirmed that the proposed approach can be applied to modeling competences needed for collaborative design in engineering fields.

Effective Design Team Composition Using Individual and Group Cognitive Attributes

2018 ◽  
Author(s):  
Kaitlyn Fritz ◽  
Line Deschenes ◽  
Vijitashwa Pandey
Keyword(s):  
Engineering Design ◽  
Brain Activity ◽  
Design Solution ◽  
Design Team ◽  
Design Teams ◽  
Team Members ◽  
Power Spectral ◽  
Team Interactions ◽  
Significant Area ◽  
Self Assessments

Engineering design is typically a team effort. Design teams frequently need to push technical boundaries to solve the most relevant challenges faced by our society. A significant area of research across multiple fields of investigation, including engineering, is the understanding and use of an individual’s cognitive attributes in the process of assembling productive teams. This research proposes an approach to assembling an engineering design team by first defining the desirable cognitive attributes in the team members. Subsequently, based on individual cognitive profile assessments along these attributes, an exhaustive list of possible design teams is investigated based on their cumulative attribute level. We compare the performance of two teams predicted to perform at different levels, and our results verify the differences between the observations of team interactions and the quality of designs produced. In addition to self-assessments, we also investigate the brain activity of the respondents using electroencephalography (EEG) to evaluate performance in an individual and a team setting. This analysis intends to highlight the characteristics of an individuals’ brain activity under different circumstances to reveal if these characteristics contribute to the success of a design team. EEG data revealed observations such as correlation between raw amplitude and level of team contribution, a higher variation in the channel power spectral density during individual versus team tasks, and a degradation of alpha activity moving from individual to group work. The results of this research can guide organizations to form teams with the necessary cognitive attributes to achieve the optimum design solution.

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