Improving Team Performance: The Cognitive Style Factor
- Conference
- Location
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Louisville, Kentucky
- Publication Date
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June 20, 2010
- Start Date
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June 20, 2010
- End Date
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June 23, 2010
- ISSN
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2153-5965
- Conference Session
- Tagged Division
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Educational Research and Methods
- Page Count
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14
- Page Numbers
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15.701.1 - 15.701.14
- DOI
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10.18260/1-2--15646
- Permanent URL
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https://sftp.asee.org/15646
- Download Count
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408
Paper Authors
Joanna DeFranco Pennsylvania State University
Joanna F. DeFranco is an Engineering faculty member at Penn State University. She earned her B.S. in Electrical Engineering and Math from Penn State, M.S. in Computer Engineering from Villanova, and earned her Ph.D. in Computer and Information science from New Jersey Institute of Technology. Previous to entering academia, Dr. DeFranco held a number of positions in industry and government, including software engineer for Motorola in Horsham, PA and an Electronics Engineer for the Naval Air Development Center in Warminster, PA. She has published a number of articles in journals and conference proceedings in the area of collaborative problem solving, group cognition, global engineering, and computer forensics.
Colin Neill Pennsylvania State University
Colin J. Neill, associate professor of software and systems engineering and associate division head of engineering and information science, earned his Ph.D. in software and systems engineering, M.Sc. in communication systems, and B.Eng. in electrical and electronic engineering from the University of Wales, Swansea, United Kingdom. He teaches in the graduate systems engineering, software engineering, and engineering management programs. Prior to joining Penn State, Dr. Neill worked on manufacturing and enterprise systems with Oxford University, the Rover Car Company, and British Aerospace. His research has been funded by the Ben Franklin Technology Partners and the Department of Defense. He has written more than sixty articles on software design, architecture, process, and management, and serves as associate editor-in-chief of Innovations in Software and Systems Engineering.
Abstract
NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract
Improving Team Performance: The Cognitive Style Factor
Abstract
It is widely considered that success in the design and development of an engineering system is contingent upon the team having a shared vision of the problem they are solving. The goal of this research is to determine which factors improve the performance of an engineering team. One of the aspects explored is the effectiveness of arranging teams based upon each team member’s cognitive problem solving style preference using the Adaption-Innovation framework1. This paper presents a complete experiment evaluating concept map data from the design stage of engineering, graduate student, teams.
Introduction
In previous research we showed that the Cognitive Collaborative Model (CCM) can improve team performance in systems design2 and may also be effective in facilitating a shared vision, or mental model of the problem being solved by a team3. Research indicates, however, that working within a team actually generates its own set of problems: the difficulties associated with managing the diversity of those within a team, referred to as Problem B (in contrast to Problem A: solving the actual problem on which the team is working)4.
Diversity here refers to the difference in problem solving style preferences of the individuals comprising the team. In the A-I framework, one’s problem-solving preference reveals how one visualizes, conceptualizes, and communicates about the problem the team is attempting to solve. An individual’s preference is at a point along a continuum from more adaptive to more innovative. A more adaptive problem solver seeks to refine or improve upon existing solutions whereas more innovative problem solvers propose to alter solutions outside those already proposed, and possibly outside the existing paradigm. In a randomly assigned team we could reasonably expect dispersion across that continuum and the theory implies that the dissonance between individuals distant along the continuum will lead to Problem B.
To investigate the impact of problem-solving diversity we used the A-I cognitive style inventory to determine the problem solving styles of individuals working in a team and measured the degree of convergence of the team’s mental model. Concept maps were used to elicit and represent team member mental models and an application called Pathfinder Network analysis along with a descriptive evaluation were used to determine the degree of commonality and similarity within each team.
Background
Cooke et al. [2001] investigated the factors that influence team performance and found that both taskwork knowledge (i.e., understanding of the task at hand) and team situational awareness (i.e., understanding of a complex and dynamic situation at any one point in time) were good predictors of team performance. This implies that team cognition is an important factor in the success of a
DeFranco, J., & Neill, C. (2010, June), Improving Team Performance: The Cognitive Style Factor Paper presented at 2010 Annual Conference & Exposition, Louisville, Kentucky. 10.18260/1-2--15646
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