Abstract

The use of dispersed (virtual) teams is growing rapidly in the engineering profession. To help prepare students for work in this type of industry, university engineering courses are requiring students to work in teams. Industry leaders and university faculty are interested in improving and measuring the performance of these distributed teams. Surveys, interviews, and observations from the AerosPACE Partners for the Advancement of Collaborative Engineering (AerosPACE) capstone design course are examined to demonstrate how different collaboration tools can be used to best enhance a distributed design team's effectiveness. Collaboration tools to which distributed design teams should give extra consideration at different stages of the product development process are identified and presented in a model. Teams that follow this model will be more effective in their communication patterns. This study also consists of examining whether peer ratings can accurately predict team effectiveness (as defined by task and relational effectiveness) within a dispersed multidisciplinary, design team. The hypotheses predict that peer ratings will not be unidimensional over time, and will have a positive, significant relationship with team effectiveness. A longitudinal study was conducted on data gathered form the same capstone design course. Confirmatory factor analysis (CFA) was first used to test unidimensionality of peer ratings and structural equation modeling (SEM) was used to model the data and determine any predictive relationships. Model fit statistics are reported to confirm adequate fit for each model. Results showed that while peer ratings are unidimensional at individual time points, they don't behave equally over time and should be considered separately. The structural equation models yielded mixed results, with some parts of peer ratings significantly predicting relational effectiveness and with yet failing to predict task effectiveness. As such, by examining peer assessments, supervisors and faculty will be able to determine and predict relational effectiveness of teams working at different locations, but should use other methods to predict task effectiveness.

Degree

College and Department

Ira A. Fulton College of Engineering and Technology; Mechanical Engineering

Rights

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