TY - JOUR
T1 - Diverse teams build better forecasts
AU - Wilck, Joseph
AU - Lynch, Paul C.
N1 - Funding Information:
Dr. Joe Wilck is a Clinical Associate Professor in Business Analytics and Operations Management at the College of William & Mary. He is a registered Professional Engineer. He is a volunteer leader with the Institute of Industrial and Systems Engineers (IISE) and the American Society for Engineering Education (ASEE). He is also an active member of INFORMS, MORS, INCOSE, ASEM, and TRB. His research is in the areas of applied optimization and STEM education, and he has been funded by the National Science Foundation, the Department of Energy, DARPA, and the North Carolina Department of Transportation; among others. He primarily teaches courses in analytics, operations research, supply chain, operations management, and logistics.
Publisher Copyright:
© American Society for Engineering Education, 2018.
PY - 2018/6/23
Y1 - 2018/6/23
N2 - Is having a diverse team most useful for hard problems? This paper presents prior literature and results from a classroom activity that explores individuals versus homogeneous groups versus heterogeneous groups for solving complex problems. The forecasts from a classroom activity with 246 undergraduate and graduate students showed that the Random Groups (Heterogeneous Groups) forecasts were statistically better than Homogeneous Groups forecasts and Individual forecasts using the Mann-Whitney test. Combining this classroom exercise with a lecture focused on building diverse teams for forecasting (and other difficult problems), showed a statistically significant difference in pre-lesson perceptions versus post-lesson perceptions of the students using a test of marginal homogeneity.
AB - Is having a diverse team most useful for hard problems? This paper presents prior literature and results from a classroom activity that explores individuals versus homogeneous groups versus heterogeneous groups for solving complex problems. The forecasts from a classroom activity with 246 undergraduate and graduate students showed that the Random Groups (Heterogeneous Groups) forecasts were statistically better than Homogeneous Groups forecasts and Individual forecasts using the Mann-Whitney test. Combining this classroom exercise with a lecture focused on building diverse teams for forecasting (and other difficult problems), showed a statistically significant difference in pre-lesson perceptions versus post-lesson perceptions of the students using a test of marginal homogeneity.
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M3 - Conference article
AN - SCOPUS:85051173307
SN - 2153-5965
VL - 2018-June
JO - ASEE Annual Conference and Exposition, Conference Proceedings
JF - ASEE Annual Conference and Exposition, Conference Proceedings
T2 - 125th ASEE Annual Conference and Exposition
Y2 - 23 June 2018 through 27 December 2018
ER -