Workshop on Computational Modeling for Individual and Organizational Science
Ohio University, Athens OH
Investigators
Abstract
Nontechnical Description of the Significance and Importance Mathematics is the language of science, yet in the social sciences computational representations of the processes hypothesized to explain phenomena are rare. A primary reason for this is a lack of understanding of the value of formal, computational approaches and a lack of training in computational modeling strategies. This lack of appreciation and training is particularly true at the intersection of psychology and organizational science, which includes the disciplines of industrial-organizational psychology and organizational behavior. The workshop at the Ohio University brings together an international group of scholars from several sub-disciplines of psychology and organizational science to highlight the value and training a new set of scholars in computational modeling methodology. Technical Description The intellectual merit of the project arises from a series of presentations by computational modelers of difference types that will focus on the value of computational modeling for addressing specific phenomena and for facilitating the construction of a cumulative science focused on understanding human behavior at work. That is, computational modeling provides researchers with the means to explore dynamic psychological and contextual concepts mathematically and with simulations, including information regarding what study designs can be used to investigate the causal theories properly. Moreover, quantitative modeling techniques provide a vehicle for integrating levels of theory ranging from neurological to macro processes (e.g., economic activity). The broader impact of this project will be achieved via training of a cadre of new computational modelers and the publication of an edited collection of the papers presented by the established modelers and newly trained modelers. That is, as part of the training element of the workshop the trainees will develop and evaluate new computational models of specific phenomena. The best of these models will be submitted to journals for special issue consideration on computational modeling.
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