Workshop on Computational Modeling for Individual and Organizational Science

意义和重要性的非技术性描述数学是科学的语言，但在社会科学中，假设解释现象的过程的计算表示是罕见的。其主要原因是缺乏对正式计算方法的价值的理解，以及缺乏计算建模策略的培训。在心理学和组织科学（包括工业组织心理学和组织行为学）的交叉学科中，这种缺乏欣赏和培训的情况尤其如此。俄亥俄州大学的研讨会汇集了来自心理学和组织科学几个子学科的国际学者，以突出计算建模方法的价值和培训一批新的学者。技术描述该项目的智力价值源于不同类型的计算建模者的一系列演示，这些演示将重点关注计算建模对于解决特定现象和促进构建专注于理解人类行为的累积科学的价值。工作。也就是说，计算建模为研究人员提供了在数学上和模拟上探索动态心理和情境概念的方法，包括关于什么样的研究设计可以用来正确研究因果理论的信息。此外，定量建模技术提供了一种工具，用于整合从神经到宏观过程（例如，经济活动）。通过培训一批新的计算建模人员和出版由已建立的建模人员和新培训的建模人员提交的论文汇编，将实现这一项目的更广泛影响。也就是说，作为讲习班培训内容的一部分，学员将开发和评估特定现象的新计算模型。这些模型中最好的将提交给期刊，供计算建模的特刊考虑。

Nontechnical Description of the Significance and ImportanceMathematics 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.