A Document Analysis Method for Characterizing Design Team Performance

2003 ◽  
Vol 126 (3) ◽  
pp. 378-385 ◽  
Author(s):  
Andy Dong ◽  
Andrew W. Hill ◽  
Alice M. Agogino
Keyword(s):  
Engineering Design ◽  
Semantic Analysis ◽  
Design Teams ◽  
Team Members ◽  
Design Performance ◽  
Design Concepts ◽  
Semantic Coherence ◽  
Design Documentation ◽  
Design Documents ◽  
The Impact

The premise of this research is that the engineering design process is partially driven by achieving consensus and reconciling points of view among team members. Characterizing the quality of the design performance by measuring the coherence of the description of related design concepts and events in design documentation is examined. Latent Semantic Analysis (LSA) was used to analyze design documentation written by self-managing, cross-functional engineering design teams. Computational measurements of document variance and textual coherence were applied to the teams’ design documents, presentation materials and e-mail communication. The levels of semantic coherence were correlated to assessments by faculty and product designers and engineers from industry of the design teams’ process and outcome quality. The results indicated a statistically significant positive correlation between design document coherence and design performance, especially for poorly performing teams. The impact of this research is to provide team managers (people who create teams and manage teams) or self-organizing teams (teams that focus on self-reflection and peer evaluation) computational tools that could be integrated with design information management technologies to assist them in the management of engineering design teams.

The Impact of Team-Based Product Dissection on Design Novelty

2014 ◽  
Vol 136 (4) ◽  
Author(s):  
Christine A. Toh ◽  
Scarlett R. Miller ◽  
Gül E. Okudan Kremer
Keyword(s):  
Engineering Design ◽  
Design Education ◽  
Engineering Students ◽  
Design Method ◽  
Idea Generation ◽  
Team Members ◽  
Design Concepts ◽  
Engineering Design Education ◽  
Current Design ◽  
The Impact

Although design novelty is a critical area of research in engineering design, most research in this space has focused on understanding and developing formal idea generation methods instead of focusing on the impact of current design practices. This is problematic because formal techniques are often not adopted in industry due to the burdensome steps often included in these methods, which limit the practicality and adoption of these methods. This study seeks to understand the impact of product dissection, a design method widely utilized in academia and industry, on design novelty in order to produce recommendations for the use or alterations of this method for supporting novelty in design. To investigate the impact of dissection, a study was conducted with 76 engineering students who completed a team-based dissection of an electric toothbrush and then individually generated ideas. The relationships between involvement in the dissection activity, the product dissected, the novelty and quantity of the ideas developed were investigated. The results reveal that team members who were more involved in the dissection activity generated concepts that were more novel than those who did not. In addition, the type of the dissected product also had an influence on design novelty. Finally, a positive correlation between the number of ideas generated and the novelty of the design concepts was identified. The results from this study are used to provide recommendations for leveraging product dissection for enhancing novelty in engineering design education and practice.

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.

My Idea Is Best! Ownership Bias and its Influence on Engineering Concept Selection

2015 ◽  
Author(s):  
Christine A. Toh ◽  
Arti H. Patel ◽  
Andrew A. Strohmetz ◽  
Scarlett R. Miller
Keyword(s):  
Engineering Design ◽  
Design Education ◽  
Engineering Students ◽  
Selection Process ◽  
Concept Selection ◽  
Team Members ◽  
Design Concepts ◽  
Final Design ◽  
Process Factors ◽  
The Impact

Concept selection is considered one of the most crucial components of the engineering design process because the direction of the final design is largely determined at this stage. One of the most widely utilized techniques for filtering designs during this process involves informal review meetings where team members identify the designs that most closely satisfy the design goals. While this is often seen as an efficient process, factors such as ownership bias, or an unintentional preference for an individuals’ own ideas, and team member personality attributes may impact an individual’s decision-making process. However, few studies have explored the impact of these factors on concept selection. Therefore, an empirical study was conducted with 37 engineering students in order to investigate the effect of these attributes on the selection or filtering of design concepts in engineering education. The results from this study show that personality impacts the proportion of ideas selected, and that male students tend to select more of their own ideas (ownership bias) than their female counterparts who more often select their team member’s concepts. These results add to our understanding of the factors that impact the team concept selection process and provide empirical evidence of the occurrence of ownership bias in engineering design education.

Helping Teams Expand the Breadth of Their Solution Space Through Product Dissection: A Simulation Based Investigation

2018 ◽  
Author(s):  
Mohammad Alsager Alzayed ◽  
Christopher McComb ◽  
Samuel T. Hunter ◽  
Scarlett R. Miller
Keyword(s):  
Engineering Design ◽  
Design Education ◽  
Computational Simulation ◽  
Effective Means ◽  
Solution Space ◽  
First Year ◽  
Team Members ◽  
Engineering Design Education ◽  
Simulation Based ◽  
The Impact

Product dissection has been highlighted as an effective means of interacting with example products in order to produce creative outcomes. While product dissection is often conducted as a team in engineering design education as a component of larger engineering design projects, the research on the effectiveness of product dissection activities has been primarily limited to individuals. Thus, the goal of this study was to investigate the impact of the type(s) of product dissected in a team environment on the breadth of the design space explored and the underlying influence of educational level on these effects. This was accomplished through a computational simulation of 7,000 nominal brainstorming teams generated by a statistical bootstrapping technique that accounted for all possible team configurations. Specifically, each team was composed of four team members based on a design repository of 463 ideas generated by first-year and senior engineering design students after a product dissection activity. The results of the study highlight that simulated senior engineering design teams explored a larger solution space than simulated first-year teams and that dissecting different types of products allowed for the exploration of a larger solution space for all of the teams. The results also showed that dissecting two analogically far and two simple products was most effective in expanding the solution space for simulated senior teams. The findings presented in this study can lead to a better understanding of how to most effectively deploy product dissection modules in engineering design education in order to maximize the solution space explored.

scholarly journals Drawing Inspiration From Human Design Teams for Better Search and Optimization: The Heterogeneous Simulated Annealing Teams Algorithm

2016 ◽  
Vol 138 (4) ◽  
Author(s):  
Christopher McComb ◽  
Jonathan Cagan ◽  
Kenneth Kotovsky
Keyword(s):  
Simulated Annealing ◽  
Computational Model ◽  
Engineering Design ◽  
Search Strategies ◽  
Design Teams ◽  
Design Cognition ◽  
Team Members ◽  
Structure Interaction

Insights uncovered by research in design cognition are often utilized to develop methods used by human designers; in this work, such insights are used to inform and improve computational methodologies. This paper introduces the heterogeneous simulated annealing team (HSAT) algorithm, a multiagent simulated annealing (MSA) algorithm. HSAT is based on a validated computational model of human-based engineering design and retains characteristics of the model that structure interaction between team members and allow for heterogeneous search strategies to be employed within a team. The performance of this new algorithm is compared to several other simulated annealing (SA) based algorithms on three carefully selected benchmarking functions. The HSAT algorithm provides terminal solutions that are better on average than other algorithms explored in this work.

Application of a Protocol to Observe Leadership Behaviors in Engineering Design Teams

2019 ◽  
Author(s):  
James Righter ◽  
Chase Wentzky ◽  
Joshua D. Summers
Keyword(s):  
Engineering Design ◽  
Leadership Behaviors ◽  
Informal Leadership ◽  
Design Teams ◽  
Function Model ◽  
Team Members ◽  
Undergraduate Engineering ◽  
Protocol Study ◽  
Relational Behaviors ◽  
Functional Leadership

Abstract This protocol study was conducted to increase understanding of the emergence and distribution of functional leadership behaviors in undergraduate engineering design teams. This study applies the protocol presented at the 2018 IDETC to observe design teams consisting of novice engineers constructing a function model during a video recorded session. The videos were then coded for leadership functions and analyzed to determine the distribution of informal leadership functions between the team members and the temporal emergence of the informal leadership structures within the teams. Leadership behaviors were observed to be predominantly transition and action functions with relational behaviors occurring less frequently. The behaviors were quantified by number of occurrences per quintile. The leaders observed to perform the most leadership behaviors early in the sessions often remained consistent. However, leadership functions were shared between team members as demonstrated by the leadership network graphs.

Can Design Teams Be Empathically Creative? A Simulation-Based Investigation on the Role of Team Empathy on Concept Generation and Selection

2020 ◽  
Author(s):  
Mohammad Alsager Alzayed ◽  
Scarlett R. Miller ◽  
Jessica Menold ◽  
Jacquelyn Huff ◽  
Christopher McComb
Keyword(s):  
Engineering Design ◽  
Design Process ◽  
Engineering Students ◽  
Computational Simulation ◽  
Idea Generation ◽  
First Year ◽  
Concept Generation ◽  
Team Members ◽  
Design Activities ◽  
The Impact

Abstract Research on empathy has been surging in popularity in the engineering design community since empathy is known to help designers develop a deeper understanding of the users’ needs. Because of this, the design community has been invested in devising and assessing empathic design activities. However, research on empathy has been primarily limited to individuals, meaning we do not know how it impacts team performance, particularly in the concept generation and selection stages of the design process. Specifically, it is unknown how the empathic composition of teams, average (elevation) and standard deviation (diversity) of team members’ empathy, would impact design outcomes in the concept generation and selection stages of the design process. Therefore, the goal of the current study was to investigate the impact of team trait empathy on concept generation and selection in an engineering design student project. This was accomplished through a computational simulation of 13,482 teams of noninteracting brainstorming individuals generated by a statistical bootstrapping technique drawing upon a design repository of 806 ideas generated by first-year engineering students. The main findings from the study indicate that the elevation in team empathy positively impacted simulated teams’ unique idea generation and selection while the diversity in team empathy positively impacted teams’ generation of useful ideas. The results from this study can be used to guide team formation in engineering design.

scholarly journals BEHAVIOURAL DIFFERENCES OF HIGH AND LOW PERFORMING TEAMS: A MULTI-INSTITUTIONAL STUDY OF FIRST-YEAR ENGINEERING DESIGN TEAMS

2018 ◽  
Author(s):  
Patricia K. Sheridan ◽  
Adam Goodman ◽  
Todd Murphy ◽  
Doug Reeve ◽  
Greg Evans
Keyword(s):  
Engineering Design ◽  
First Year ◽  
Design Teams ◽  
Team Members ◽  
High Performing

 Abstract – This paper compares student intra-team feedback to identify behaviours that differentiate high and low performing teams. Data from two universities’ first-year engineering design courses was analysed and demonstrated that the ways in which students discussed high and low performing teams was similar. This paper discusses some of the issues with which low performing teams struggled. Both high and low performing teams experienced a lack of quality and quantity of communication, whereas low-performing teams struggled with hoarding work, leveraging team members and supporting others. High-performing teams may have a more collective team mindset that values the skills and perspectives of all team members more.

A Multimedia Concept Database for Improved Life Cycle Design

1991 ◽  
Author(s):  
Stephen R. Bradley ◽  
Alice M. Agogino
Keyword(s):  
Life Cycle ◽  
Engineering Design ◽  
Conceptual Design ◽  
Easy Access ◽  
Design Teams ◽  
Access To Information ◽  
Multimedia Design ◽  
Information Base ◽  
Design Concepts ◽  
Life Cycle Design

Abstract The architecture of a multimedia conceptual design aid, the Concept Database, is presented. The goal of the Concept Database is to provide design teams with easy access to information about life cycle design issues for competing design concepts and access to relevant past designs. The architecture builds on our previous experience in developing the multimedia design archival system called Design SCRIBE (Structured Capture and Retrieval Information Base for Engineering Design.) Approaches to selectively retrieving descriptions of design concepts and past designs are summarized.

Design Team Convergence: The Influence of Example Solution Quality

2010 ◽  
Vol 132 (11) ◽  
Author(s):  
Katherine Fu ◽  
Jonathan Cagan ◽  
Kenneth Kotovsky
Keyword(s):  
Problem Solving ◽  
Engineering Design ◽  
Semantic Analysis ◽  
Cognitive Engineering ◽  
Design Solution ◽  
Solution Quality ◽  
Team Members ◽  
Solution Approach ◽  
Over Time

This study examines how engineering design teams converge upon a solution to a design problem and how their solution is influenced by information given to them prior to problem solving. Specifically, the study considers the influence of the type of information received prior to problem solving on team convergence over time, as well as on the quality of produced solutions. To understand convergence, a model of the team members’ solution approach was developed through a cognitive engineering design study, specifically examining the effect of the introduction of a poor example solution or a good example solution prior to problem solving on the quality of the produced solutions. Latent semantic analysis was used to track the teams’ convergence, and the quality of design solutions was systematically assessed using pre-established criteria and multiple evaluators. Introducing a poor example solution was shown to decrease teams’ convergence over time, as well as the quality of their design solution; introducing a good example solution did not produce a statistically significant different effect on convergence compared with the control (with no prior example solution provided) but did lead to higher quality solutions.

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