大数据与仿真分析高等教育可持续发展

A. Kurkovsky
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引用次数: 0

摘要

高等教育机构已经积累了大量与学生成功、招生、教授、教育计划、教育计算机系统、经济学等相关的大数据,这些数据有可能用于可持续发展分析。然而,由于学科领域的复杂性和缺乏方法基础来重用一些有效的先前创建的模型,它们在高等教育机构中的实际应用仍然相对较少。本文介绍了一种将大数据纳入高等教育可持续性分析的方法,并通过使用一套形式化系统来降低学科领域基础设施的复杂性。在这种方法中,模拟伞被用作统一的方法基础,以结合大数据和可持续性分析实施。为了说明所提出的方法是如何工作的,本文中包括了一个与美国快速发展的年轻高等教育机构相关的模拟案例研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Big Data and Simulation to Analyze Higher Education Sustainable Development
Higher education institutions already accumulated enormous volumes of big data associated with student success, enrolment, professors, educational programs, educational computer systems, economics, etc., that potentially can be used for sustainable development analysis. However, their practical applications in higher education institutions are remained relatively rare because of complexity in the subject domain and lack of a methodological base to reuse some effective previously created models. This paper introduces an approach to incorporate big data into higher education sustainability analysis and reduce the complexity of the subject domain infrastructure by using a set of formalized systems. Within this approach, a simulation umbrella is used as a united methodological base to combine big data and sustainability analysis implementation. To illustrate how the proposed approach works, a simulation case-study associated with a USA young fast-growing higher education institution included in the paper.
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