Research Papers

A Multi-User Computer-Aided Design Competition: Experimental Findings and Analysis of Team-Member Dynamics

[+] Author and Article Information
Brett Stone, Keenan Eves, Matthew Killian, Landon Wright, Jordan Oldroyd

Department of Mechanical Engineering,
Brigham Young University,
Provo, UT 84602

John Salmon

Assistant Professor
Department of Mechanical Engineering,
Brigham Young University,
Provo, UT 84602
e-mail: johnsalmon@byu.edu

Steve Gorrell

Associate Professor
Department of Mechanical Engineering,
Brigham Young University,
Provo, UT 84602

Michael C. Richey

Learning, Training, and Development,
Seattle, WA 98108

1Corresponding author.

Contributed by the Design Engineering Division of ASME for publication in the JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN ENGINEERING. Manuscript received January 13, 2016; final manuscript received December 16, 2016; published online February 16, 2017. Assoc. Editor: Yong Chen.

J. Comput. Inf. Sci. Eng 17(3), 031003 (Feb 16, 2017) (10 pages) Paper No: JCISE-16-1020; doi: 10.1115/1.4035674 History: Received January 13, 2016; Revised December 16, 2016

A competition for teams of three students using a prototype multi-user computer-aided design (MUCAD) tool was held to investigate various hypotheses regarding the performance of teams in such a setting. By comparing models from the competition to the same model in a single-user CAD environment, it is seen that use of a MUCAD system can significantly increase the value-added per unit of calendar time for a modeling effort. An investigation was also made into the causes of the performance differences among the various MUCAD teams which participated in the competition. Analysis of the results shows that teams that encouraged effective forms of communication and teams whose members scored similarly on the Purdue Spatial Visualization Test: Visualization of Rotations (PSVT:R) performed better than other teams. Areas of future research in analyzing teams in MUCAD environments are suggested.

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Fig. 1

Example of a problem from the PSVT:R test

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Fig. 2

Cutting guard which served as the basis for the competition

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Fig. 3

Two teams competing simultaneously at different stations with proctors monitoring and taking notes

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Fig. 4

Graphic given to competitors at start of 25 min of competition

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Fig. 5

Team score adjustment. Scores before and after adjustment versus average error severity.

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Fig. 6

Points per minute per team. A comparison of the effectiveness of single-user and MUCAD teams based on calendar time.

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Fig. 7

Points per minute per person. A comparison of the effectiveness of single-user and MUCAD individuals (man hours).

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Fig. 8

High-performing team audio. Graph showing communication frequency for a high-performing team.

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Fig. 9

Low-performing team audio. Graph showing communication frequency for a low-performing team.

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Fig. 10

Adjusted scores versus PSVT:R standard deviation. A linear regression of team score versus a team's standard deviation of PSVT:R test scores shows a negative correlation.

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Fig. 11

Adjusted score versus PSVT:R. Individual (hollow points) and team average (filled points) PSVT:R scores versus competition score. Note the general trend of less variation between team member PSVT:R scores as competition score increases.

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Fig. 12

Adjusted score by relationship rating. Each point represents one relationship rating. A rating of four reflects a very strong relationship, with a zero being very weak.



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