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Analysis and Modeling of Academia's Collaborative Decision Support System Based on Key Performance Indicators and Degree of Certainty

机译:基于关键绩效指标和确定性学术界协作决策支持系统的分析与建模

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Increasingly, academia is relying on a novel concept of virtual teams for Collaborative Decision Making (CDM) processes amongst the students across the globe (different cultures). To facilitate collaboration in international virtual teams there is a need to support cross-cultural decision making through a series of steps required to improve problem solving and decision making. In this paper we analyze the CDM processes in international virtual environment and discuss the opportunity to support CDM through the use of a Computer-Aided Collaborative Decision Making (CA-CDM). In CA-CDM students declare their knowledge in terms of the Degree of Certainty (DC) during the collaboration process. In this research, a process model based on various Key Performance Indicators (KPI) designed to figure out the key challenges, performance and differences in CDM. Based on these KPI variables and their scores, two different models are suggested to calculate the difference and similarity in CDM. The designed computer-supported environment supports CDM processes to address critical thinking, deep learning and knowledge transformation. In this computer program model, based on Degree of Certainty of each peer student, each student declares their communication certainty before starting a virtual interaction to support a CDM process. Incorporation of the suggested KPIs modeling; this learning environment will optimize the output of virtual team decision support collaboration.
机译:越来越多的学术界依靠全球学生中的协作决策(CDM)流程的虚拟团队的新颖概念(不同的文化)。为了促进国际虚拟团队中的合作,需要通过改善问题解决和决策所需的一系列步骤来支持跨文化决策。在本文中,我们将CDM流程分析在国际虚拟环境中,并通过使用计算机辅助协作决策(CA-CDM)来讨论支持CDM的机会。在CA-CDM中,学生在协作过程中,学生在确定性(DC)方面宣布他们的知识。在本研究中,基于各种关键性能指标(KPI)的过程模型旨在弄清楚CDM的关键挑战,性能和差异。基于这些KPI变量及其分数,建议两个不同的模型来计算CDM中的差异和相似性。设计的计算机支持的环境支持CDM流程来解决关键思维,深度学习和知识转型。在此计算机程序模型中,根据每个同行学生的确定性,每个学生在开始虚拟交互之前宣布他们的沟通确定,以支持CD​​M过程。纳入建议的KPIS建模;此学习环境将优化虚拟团队决策支持协作的输出。

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